Methods and materials for assessing and treating cancer

Abstract

Provided herein are methods and materials for detecting and / or treating a subject (e.g., a human) having cancer. In some embodiments, methods and materials are provided for identifying a subject has cancer (e.g., local cancer) in which the presence of one or more members of two or more categories of biomarkers is detected. In some embodiments, methods and materials are provided for identifying a subject has cancer (e.g., local cancer) in which the presence of one or more members of at least one category of biomarkers and the presence of aneuploidy are detected. In some embodiments, the methods described herein provide for increased sensitivity and / or specificity in detecting cancer in a subject (e.g., a human).

Description

[0001] This application is a divisional application of PCT application PCT / US2018 / 045669, filed on August 7, 2018, with the invention name “Methods and Materials for Assessing and Treating Cancer”. The date on which the PCT application entered the Chinese national phase is April 7, 2020, and the application number is 201880066039.X.

[0002] Statement Regarding Federal Funding

[0003] This invention was made with U.S. government support under Grant Nos. CA062924 and HG007804 from the National Institutes of Health. The U.S. government has certain rights in this invention.

[0004] Sequence Listing

[0005] This application includes a sequence listing in electronic format submitted to the U.S. Patent and Trademark Office through the electronic filing system and is incorporated herein by reference in its entirety. The sequence listing was created on August 6, 2018, is named 448070306WO1SL.txt, and is 208,305 bytes in size.

[0006] Electronic application form

[0007] This application includes tables in electronic format submitted to the United States Patent and Trademark Office through the electronic filing system. ASCII text files, each of which is incorporated herein by reference in its entirety, include a text file named Table1.txt, created on August 7, 2018, of 152,000 bytes; a text file named Table2.txt, created on August 7, 2018, of 351,000 bytes; a text file named Table3.txt, created on August 7, 2018, of 438,000 bytes; a text file named Table4.txt, created on August 7, 2018, of 1,081,000 bytes; a text file named Table5.txt, created on August 7, 2018, of 3 1,000 bytes; a text file named Table6.txt, created on August 7, 2018, with a size of 103,000 bytes; a text file named Table7.txt, created on August 7, 2018, with a size of 25,000 bytes; a text file named Table8.txt, created on August 7, 2018, with a size of 59,000 bytes; a text file named Table9.txt, created on August 7, 2018, with a size of 38,000 bytes; a text file named Table10.txt, created on August 7, 2018, with a size of 22,000 bytes; a text file named Table11.txt This file, created on August 7, 2018, is 17,000 bytes in size; a text file named Table12.txt, created on August 7, 2018, is 14,000 bytes in size; a text file named Table13.txt, created on August 7, 2018, is 104,000 bytes in size; a text file named Table14.txt, created on August 7, 2018, is 106,000 bytes in size; a text file named Table15.txt, created on August 7, 2018, is 370,000 bytes in size; a text file named Table16.txt, created on August 7, 2018, is The following are the following: a text file named Table17.txt, created on August 7, 2018, with a size of 8,000 bytes; a text file named Table18.txt, created on August 7, 2018, with a size of 52,000 bytes; a text file named Table19.txt, created on August 7, 2018, with a size of 41,000 bytes; a text file named Table20.txt, created on August 7, 2018, with a size of 14,000 bytes; a text file named Table21.txt, created on August 7, 2018, with a size of 6,000 bytes; and a text file named Table22.txt.txt, created on August 7, 2018, with a size of 19,000 bytes; a text file named Table23.txt, created on August 7, 2018, with a size of 6,000 bytes; a text file named Table24.txt, created on August 7, 2018, with a size of 42,000 bytes; a text file named Table25.txt, created on August 7, 2018, with a size of 25,000 bytes; a text file named Table26.txt, created on August 7, 2018, with a size of 14,000 bytes; a text file named Table27.txt, created on August 7, 2018 , 5,000 bytes in size; a text file named Table28.txt, created on August 7, 2018, 10,000 bytes in size; a text file named Table29.txt, created on August 7, 2018, 9,000 bytes in size; a text file named Table30.txt, created on August 7, 2018, 3,000 bytes in size; a text file named Table31.txt, created on August 7, 2018, 2,000 bytes in size; a text file named Table32.txt, created on August 7, 2018, 9,000 bytes in size; a text file named Table33.txt The following are text files: Table34.txt, created on August 7, 2018, with a size of 22,000 bytes; Table35.txt, created on August 7, 2018, with a size of 1,536,000 bytes; Table36.txt, created on August 7, 2018, with a size of 1,591,000 bytes; Table37.txt, created on August 7, 2018, with a size of 13,000 bytes; Table38.txt, created on August 7, 2018 7, 2018, with a size of 5,000 bytes; a text file named Table39.txt, created on August 7, 2018, with a size of 30,000 bytes; a text file named Table40.txt, created on August 7, 2018, with a size of 9,000 bytes; a text file named Table41.txt, created on August 7, 2018, with a size of 4,000 bytes; a text file named Table42.txt, created on August 7, 2018, with a size of 8,000 bytes; a text file named Table43.txt, created on August 7, 2018, with a size of 25,000 bytes; a text file named Table44.txt, created on August 7, 2018, with a size of 25,000 bytes.txt, created on August 7, 2018, with a size of 11,000 bytes; a text file named Table45.txt, created on August 7, 2018, with a size of 11,000 bytes; a text file named Table46.txt, created on August 7, 2018, with a size of 18,000 bytes; a text file named Table47.txt, created on August 7, 2018, with a size of 18,000 bytes; a text file named Table The text file named Table48.txt was created on August 7, 2018 and is 8,000 bytes in size. The text file named Table49.txt was created on August 7, 2018 and is 167,000 bytes in size. The text file named Table50.txt was created on August 7, 2018 and is 312,000 bytes in size. The text file named Table51.txt was created on August 7, 2018 and is 20,000 bytes in size. The text file named able52.txt was created on August 7, 2018 and is 1,000 bytes in size. The text file named Table53.txt was created on August 7, 2018 and is 3,000 bytes in size. The text file named Table54.txt was created on August 7, 2018 and is 3,000 bytes in size. The text file named Table55.txt was created on August 7, 2018 and is 8,000 bytes in size. A text file named ble56.txt, created on August 7, 2018, and 1,000 bytes in size; a text file named Table57.txt, created on August 7, 2018, and 14,000 bytes in size; a text file named Table58.txt, created on August 7, 2018, and 3,000 bytes in size; and a text file named Table59.txt, created on August 7, 2018, and 309,000 bytes in size. Background of the Invention 1. Technical Field

[0009] Provided herein are methods and materials for detecting and / or treating subjects (e.g., people) with cancer. In some embodiments, methods and materials for identifying subjects with cancer (e.g., localized cancer) are provided, wherein the presence of two or more members of two or more categories of biomarkers are detected. In some embodiments, methods and materials for identifying subjects with cancer (e.g., localized cancer) are provided, wherein the presence of two or more members of at least one category of biomarkers and the presence of aneuploidy are detected. In some embodiments, the methods described herein provide increased sensitivity and / or specificity for detecting cancer in subjects (e.g., people). 2. Background Technology

[0010] Cancer will kill 592,000 Americans this year, and according to the Centers for Disease Control, it will soon become the leading cause of death in the United States. How can this dire situation be avoided? Today, the vast majority of translational cancer research focuses on extending survival in patients with advanced disease. Our research perspective is different: in the long run, prevention is always better than cure. Examples of the value of this perspective abound, from infectious diseases to cardiovascular disease. Cardiovascular disease is particularly important, as a combination of primary and secondary preventive measures has reduced deaths from this disease by 75% over the past 60 years. In contrast, over the same period, overall cancer deaths have remained virtually unchanged.

[0011] Early detection through blood tests for cancer can be considered a form of secondary prevention. The word "earlier" is particularly important. Across all cancers studied, the probability of cure is much higher with early, localized disease than with advanced disease. The earlier the disease is detected, the greater the likelihood that the tumor can be cured with surgery alone. Furthermore, cancers do not necessarily need to be detected in their earliest stages to be cured. Theoretically, response to treatment depends on the total number of cancer cells and the mutation rate in a person's cells before treatment. The more cancer cells there are, the greater the likelihood that at least one of them will contain or develop a mutation that confers resistance to any form of treatment, whether conventional chemotherapy, radiation, targeted therapy, or immunotherapy. Clinically, numerous studies have shown that drugs can be curative in the adjuvant setting, but not in patients with advanced disease. For example, nearly half of patients with stage III colorectal cancer who would otherwise die from their disease can be cured with adjuvant therapy, but almost no patients with stage IV colorectal cancer can be cured with the same regimen.

[0012] In many cancers, there is a strong correlation between tumor stage and prognosis (Ansari D, et al. (2017) Relationship between tumor size and outcome in pancreatic ductal adenocarcinoma. Br J Surg 104(5): 600-607). Very few patients with lung, colon, esophageal, or gastric cancer who have distant metastases at diagnosis survive for more than five years (Howlader N et al. (2016) SEER Cancer Statistics Review, 1975-2013, National Cancer Institute. Bethesda, MD, http: / / seer.cancer.gov / csr / 1975_2013 / , based on SEER data submission in November 2015, posted to the SEER website in April 2016). Broadly speaking, the size of the cancer is also important because smaller tumors at diagnosis tend to have fewer metastases than larger tumors and are therefore more likely to be cured by surgery alone. Even when cancer has metastasized to distant sites, a smaller disease burden is more manageable than bulky lesions (Bozic I et al. (2013) Evolutionary dynamics of cancer in response to targeted combination therapy. Elife 2: e00747).Thus, administration of adjuvant chemotherapy to patients with micrometastases arising from colorectal cancer can cure nearly 50% of cases (Semrad TJ, Fahrni AR, Gong IY, and Khatri VP (2015) Integrating Chemotherapy into the Management of Oligometastatic Colorectal Cancer: Evidence-Based Approach Using Clinical Trial Findings. Ann Surg Oncol Suppl 223:S855-862; Moertel CG et al. (1995) Fluorouracil plus levamisole as effective adjuvant therapy after resection of stage III colon carcinoma: a final report. Ann Intern Med 122(5):321-326; Andre T et al. (2009) Improved overall survival with oxaliplatin, fluorouracil, and leucovorin as adjuvant treatment in stage II or III colon cancer in the MOSAIC trial. J Clin Oncol 27(19):3109-3116). Delivery of the same chemotherapy agents to patients with radiovisible metastatic lesions rarely results in cure (Dy GK et al. (2009) Long-term survivors of metastatic colorectal cancer treated with systemic chemotherapy alone: a North Central Cancer Treatment Group review of 3811 patients, N0144. Clin Colorectal Cancer 8(2):88-93).

[0013] Therefore, it is clear that early detection of cancer is a key to reducing deaths caused by these diseases, including pancreatic cancer. In addition to providing the possibility of surgical resection, there is no doubt that newly developed adjuvant chemotherapy and emerging immunotherapy regimens have proven to be more effective in patients with minimal disease than in patients who are surgically curable (Huang AC et al. (2017) T-cell invigoration to tumor burden ratio associated with anti-PD-1response. Nature 545(7652): 60-65). Circulating biomarkers provide one of the best ways to detect early cancer in principle. Historically, the type of biomarker used to monitor cancer is protein (Liotta LA & Petricoin EF, 3rd (2003) The promise of proteomics. Clin Adv Hematol Oncol 1(8): 460-462), and include carcinoembryonic antigen (CEA), carbohydrate antigen 19-9 (CA19-9) and cancer antigen 125 (CA125). These biomarkers have proven useful for tracking patients with known disease but have not been approved for screening purposes, in part because of their low sensitivity or specificity (Lennon AM & Goggins M (2010) Diagnostic and Therapeutic Response Markers. Pancreatic Cancer, (Springer New York, New York, NY), pp. 675-701; Clarke-Pearson DL (2009) Clinical practice. Screening forovarian cancer. N Engl J Med 361(2): 170-177; Locker GY et al. (2006) ASCO 2006 update of recommendations for the use of tumor markers in gastrointestinal cancer.J Clin Oncol 24(33):5313-5327). Recently, mutant DNA has been investigated as a biomarker. The basic concept of this approach (often referred to as "liquid biopsy") is that cancer cells, like normal self-renewing cells, frequently turn over. DNA released from dying cells can escape into body fluids such as urine, feces, and plasma (Haber DA & Velculescu VE (2014) Blood-based analyses of cancer: circulating tumor cells and circulating tumor DNA. Cancer Discov 4(6): 650-661; Dawson SJ et al. (2013) Analysis of circulating tumor DNA to monitor metastatic breast cancer. N Engl J Med 368(13): 1199-1209; Bettegowda C et al. (2014) Detection of circulating tumor DNA in early- and late-stage human malignancies. Science translational medicine 6(224): 224ra224; Kinde I et al. (2013) Evaluation of DNA from the Papanicolaou test to detect ovarian and endometrial cancers. Science translational medicine 5(167): 167ra164; Wang Y et al. (2015) Detection of somatic mutations and HPV in thesaliva and plasma of patients with head and neck squamous cellcarcinomas. Science translational medicine 7(293): 293ra104; Wang Y et al. (2015) Detection of tumor-derived DNA in cerebrospinal fluid of patients with primary tumors of the brain and spinal cord.Proe Natl Acad Sci USA 112(31):9704-9709; Wang Y et al. (2016) Diagnostic potential of tumor DNA from ovarian cystfluid. Elife 5; Springer S et al. (2015) A Combination of Molecular Markers and Clinical Features Improve the Classification of PancreaticCysts. Gastroenterology 149(6):1501-1510; Forshew T et al (2012) Noninvasive identification and monitoring of cancer mutations by targeted deep sequencing of plasma DNA. Science translational medicine 4(136): 136ra168; Vogelstein B and Kinzler KW (1999) Digital PCR. Proe Natl Acad Sci USA 96(16):9236-9241; Dressman D, Yan H, Traverso G, Kinzler KW and Vogelstein B (2003) Transforming single DNA molecules into fluorescent magnetic particles for detection and enumeration of genetic variations. Proe Natl Acad Sci USA 100(15):8817-8822). The advantage of using mutant DNA in the circulation as a biomarker is its excellent specificity. Every cell in cancer has a core set of somatic mutations in the driver genes responsible for its clonal growth (Vogelstein B et al. (2013) Cancer genome landscapes. Science 339(6127):1546-1558). In contrast, normal cells do not undergo clonal expansion in adulthood, and the proportion of normal cells with any particular somatic mutation is extremely low.

[0014] Most studies of circulating tumor DNA (ctDNA) have focused on tracking cancer patients rather than evaluating its use in a screening setting. Existing data suggest that ctDNA is elevated in >85% of patients with advanced forms of many cancer types (Bettegowda C et al. (2014) Detection of circulating tumor DNA in early-and late-stage human malignancies. Science translational medicine 6(224): 224ra224; Wang Y et al. (2015) Detection of somatic mutations and HPV in the saliva and plasma of patients with head and neck squamous cell carcinomas. Science translational medicine 7(293): 293ra104). However, a substantial proportion of patients with early-stage cancer have detectable levels of ctDNA in their plasma (Bettegowda C et al. (2014) Detection of circulating tumor DNA in early- and late-stage human malignancies. Science translational medicine 6(224): 224ra224; Wang Y et al. (2015) Detection of somatic mutations and HPV in the saliva and plasma of patients with head and neck squamous cell carcinomas. Science translational medicine 7(293): 293ra104).

[0015] Most localized cancers can be cured by surgery alone, without any systemic therapy (Siegel et al., 2017 CA Cancer J Clin 67:7-30). However, once distant metastases occur, surgical resection is rarely curative. Therefore, a major goal of cancer research is to detect cancers before they metastasize to distant sites. Depending on the type of cancer, typical cancers in adults appear to take 20 to 30 years to progress from early neoplastic lesions to advanced cancers (Vogelstein et al., 2013 Science 339:1546-1558; Jones et al., 2008 Proc Natl Acad Sci USA 105:4283-4288; and Yachida et al., 2012 Clin Cancer Res 18:6339-6347). Only in the last few years of this long process do neoplastic cells appear to successfully seed and give rise to metastatic lesions (Vogelstein et al., 2013 Science 339:1546-1558; Jones et al., 2008 Proc Natl Acad Sci USA 105:4283-4288; Yachida et al., 2012 Clin Cancer Res 18:6339-6347; and Vogelstein et al., 2015 N Engl J Med 373:1895-1898). Therefore, there is a great opportunity to detect cancer before the onset of metastasis. However, once large metastatic tumors are established, current therapies are ineffective (Bozic et al., 2013 Elife 2:e00747; Semrad et al., 2015 Ann Surg Oncol 22(Suppl 3):S855-862; Moertel et al., 1995 Ann Intern Med 122:321-326; Huang et al., 2017 Nature 545:60-65).

[0016] Pancreatic ductal adenocarcinoma (hereinafter referred to as "pancreatic cancer") is the third leading cause of cancer death and is expected to become the second most common cause in the United States by 2030 (Rahib L, et al. (2014) Projecting cancer incidence and deaths to 2030: the unexpected burden of thyroid, liver, and pancreas cancers in the United States. Cancer Res 74(11): 2913-2921). Pancreatic cancer is known to be fatal, with less than 9% of patients surviving five years after diagnosis (Siegel RL, Miller KD, & Jemal A (2016) Cancer statistics, 2016. CA Cancer J Clin 66(1): 7-30). The poor prognosis for pancreatic cancer patients is partly due to the fact that 80% to 85% of patients are diagnosed at an advanced stage, when radiological studies have found that the tumor has invaded surrounding major blood vessels or has metastasized to distant sites (Ryan DP, Hong TS, & Bardeesy N (2014) Pancreatic adenocarcinoma. NEngl J Med 371(22):2140-2141). In this advanced stage of the disease, pancreatic cancer is not suitable for surgical resection, and the 3-year survival rate is less than 5%.In contrast, for very small localized tumors, the five-year survival rate is reported to be close to 60%; in resectable cancers, the smaller the tumor, the better the prognosis (Ansari D, et al. (2017) Relationship between tumour size and outcome in pancreatic ductal adenocarcinoma. Br J Surg 104(5): 600-607; Jung KW, et al. (2007) Clinicopathological aspects of 542 cases of pancreatic cancer: a special emphasis on small pancreatic cancer. J Korean Med Sci 22 Suppl: S79-85; Egawa S, et al. (2004) Clinicopathological aspects of small pancreatic cancer. Pancreas 28(3): 235-240; Ishikawa O, et al. (1999) Minute carcinoma of the pancreas measuring 1 cm or less in diameter--collective review of Japanese case reports. Hepatogastroenterology 46(25):8-15; Tsuchiya R, et al. (1986) Collective review of small carcinomas of the pancreas. Ann Surg 203(1):77-81).

[0017] Pancreatic cancer is no different from other cancers, with a strong correlation between tumor stage and prognosis (Ansari D, et al. (2017) Relationship between tumor size and outcome in pancreatic ductal adenocarcinoma. Br J Surg 104(5): 600-607). Very few patients with lung, colon, esophageal, or gastric cancer who have distant metastases at diagnosis survive for more than five years (Howlader N et al. (2016) SEER Cancer Statistics Review, 1975-2013, National Cancer Institute. Bethesda, MD, http: / / seer.cancer.gov / csr / 1975_2013 / , based on SEER data submission in November 2015, posted to the SEER website in April 2016). Broadly speaking, the size of the cancer is also important because smaller tumors at diagnosis tend to have fewer metastases than larger tumors and are therefore more likely to be cured by surgery alone. Even when cancer has metastasized to distant sites, a smaller disease burden is more manageable than bulky lesions (Bozic I et al. (2013) Evolutionary dynamics of cancer in response to targeted combination therapy. Elife 2: e00747).Thus, administration of adjuvant chemotherapy to patients with micrometastases arising from colorectal cancer can cure nearly 50% of cases (Semrad TJ, Fahrni AR, Gong IY, and Khatri VP (2015) Integrating Chemotherapy into the Management of Oligometastatic Colorectal Cancer: Evidence-Based Approach Using Clinical Trial Findings. Ann Surg Oncol Suppl 22 3:S855-862; Moertel CG et al. (1995) Fluorouracil plus levamisole as effective adjuvant therapy after resection of stage III colon carcinoma: a final report. Ann Intern Med 122(5):321-326; Andre T et al. (2009) Improved overall survival with oxaliplatin, fluorouracil, and leucovorin as adjuvant treatment in stage II or III colon cancer in the MOSAIC trial. J Clin Oncol 27(19):3109-3116). Delivery of the same chemotherapy agents to patients with radiovisible metastatic lesions rarely results in cure (Dy GK et al. (2009) Long-term survivors of metastatic colorectal cancer treated with systemic chemotherapy alone: a North Central Cancer Treatment Group review of 3811 patients, N0144. Clin Colorectal Cancer 8(2):88-93).

[0018] Therefore, it is clear that early detection of cancer is a key to reducing deaths caused by these diseases, including pancreatic cancer. In addition to providing the possibility of surgical resection, there is no doubt that newly developed adjuvant chemotherapy and emerging immunotherapy regimens have proven to be more effective in patients with minimal disease than in patients who are surgically curable (Huang AC et al. (2017) T-cell invigoration to tumor burden ratio associated with anti-PD-1response. Nature 545(7652): 60-65). Circulating biomarkers provide one of the best ways to detect early cancer in principle. Historically, the type of biomarker used to monitor cancer is protein (Liotta LA & Petricoin EF, 3rd (2003) The promise of proteomics. Clin Adv Hematol Oncol 1(8): 460-462), and include carcinoembryonic antigen (CEA), carbohydrate antigen 19-9 (CA19-9) and cancer antigen 125 (CA125). These biomarkers have proven useful for tracking patients with known disease but have not been approved for screening purposes, in part because of their low sensitivity or specificity (Lennon AM & Goggins M (2010) Diagnostic and Therapeutic Response Markers. Pancreatic Cancer, (Springer New York, New York, NY), pp. 675-701; Clarke-Pearson DL (2009) Clinical practice. Screening forovarian cancer. N Engl J Med 361(2): 170-177; Locker GY et al. (2006) ASCO 2006 update of recommendations for the use of tumor markers in gastrointestinal cancer.J Clin Oncol 24(33):5313-5327). Recently, mutant DNA has been investigated as a biomarker. The basic concept of this approach (often referred to as "liquid biopsy") is that cancer cells, like normal self-renewing cells, frequently turn over. DNA released from dying cells can escape into body fluids such as urine, feces, and plasma (Haber DA & Velculescu VE (2014) Blood-based analyses of cancer: circulating tumor cells and circulating tumor DNA. Cancer Discov 4(6): 650-661; Dawson SJ et al. (2013) Analysis of circulating tumor DNA to monitor metastatic breast cancer. N Engl J Med 368(13): 1199-1209; Bettegowda C et al. (2014) Detection of circulating tumor DNA in early- and late-stage human malignancies. Science translational medicine 6(224): 224ra224; Kinde I et al. (2013) Evaluation of DNA from the Papanicolaou test to detect ovarian and endometrial cancers. Science translational medicine 5(167): 167ra164; Wang Y et al. (2015) Detection of somatic mutations and HPV in thesaliva and plasma of patients with head and neck squamous cellcarcinomas. Science translational medicine 7(293): 293ra104; Wang Y et al. (2015) Detection of tumor-derived DNA in cerebrospinal fluid of patients with primary tumors of the brain and spinal cord.Proc Natl Acad Sci USA 112(31):9704-9709; Wang Y et al. (2016) Diagnostic potential of tumor DNA from ovarian cystfluid. Elife 5; Springer S et al. (2015) A Combination of Molecular Markers and Clinical Features Improve the Classification of PancreaticCysts. Gastroenterology 149(6):1501-1510; Forshew T et al (2012) Noninvasive identification and monitoring of cancer mutations by targeted deep sequencing of plasma DNA. Science translational medicine 4(136): 136ra168; Vogelstein B and Kinzler KW (1999) Digital PCR. Proc Natl Acad Sci USA 96(16):9236-9241; Dressman D, Yan H, Traverso G, Kinzler KW and Vogelstein B (2003) Transforming single DNA molecules into fluorescent magnetic particles for detection and enumeration of genetic variations. Proc Natl Acad Sci USA 100(15):8817-882). The advantage of using circulating mutant DNA as a biomarker is its excellent specificity. Every cell in cancer harbors a core set of somatic mutations in driver genes responsible for its clonal growth (Vogelstein B et al. (2013) Cancer genome landscapes. Science 339(6127):1546-1558). In contrast, normal cells do not undergo clonal expansion in adulthood, and the proportion of normal cells harboring any particular somatic mutation is extremely low.

[0019] Most studies of circulating tumor DNA (ctDNA) have focused on tracking cancer patients rather than evaluating its use in a screening setting. Existing data suggest that ctDNA is elevated in >85% of patients with advanced forms of many cancer types (Bettegowda C et al. (2014) Detection of circulating tumor DNA in early-and late-stage human malignancies. Science translational medicine 6(224): 224ra224; Wang Y et al. (2015) Detection of somatic mutations and HPV in the saliva and plasma of patients with head and neck squamous cell carcinomas. Science translational medicine 7(293): 293ra104). However, a substantial proportion of patients with early-stage cancer have detectable levels of ctDNA in their plasma (Bettegowda C et al. (2014) Detection of circulating tumor DNA in early- and late-stage human malignancies. Science translational medicine 6(224): 224ra224; Wang Y et al. (2015) Detection of somatic mutations and HPV in the saliva and plasma of patients with head and neck squamous cell carcinomas. Science translational medicine 7(293): 293ral04).

[0020] There is a continuing need in the art to increase the sensitivity of detection of resectable or otherwise treatable cancers while maintaining high specificity.

[0021] The Papanicolaou (Pap) test has significantly reduced the incidence and mortality of cervical cancer in screened populations. Unfortunately, the Pap test generally cannot detect endometrial or ovarian cancer (L. Geldenhuys, ML Murray, Sensitivity and specificity of the Pap smear for glandular lesions of the cervix and endometrium. Acta cytologica 51, 47-50 (2007); AB Ng, JW Reagan, S. Hawliczek, BW Wentz, Significance of endometrial cells in the detection of endometrial carcinoma and its precursors. Acta cytologica 18, 356-361 (1974); PF Schnatz, M. Guile, DMO'Sullivan, JI Sorosky, Clinical significance of atypical glandular cells on cervical cytology. Obstetrics and gynecology 107, 701-708 (2006); C. Zhao, A. Florea, A. Onisko, RM Austin, Histologic follow-up results in 662 patients with Pap test findings of atypical glandular cells: results from a large academic women's hospital laboratory employing sensitive screening methods. Gynecologic oncology 114, 383-389 (2009)). Given the success of the Pap test in detecting early, curable cervical cancer, ovarian cancer and endometrial cancer are currently the most deadly and most common gynecologic malignancies, respectively, in countries where Pap tests are routinely performed (N. Howlader et al., SEER Cancer Statistics Review, 1975-2014, National Cancer Institute. (2017)).Endometrial and ovarian cancers together account for approximately 25,000 deaths each year and are the third leading cause of cancer-related mortality among women in the United States (N. Howlader et al., SEER Cancer Statistics Review, 1975-2014, National Cancer Institute. (2017)). Most of these deaths are caused by high-grade tumor subtypes that tend to metastasize before the onset of symptoms (RJ Kurman, M. Shih Ie, The origin and pathogenesis of epithelial ovarian cancer: a proposed unifying theory. The American journal of surgical pathology 34, 433-443 (2010); KN Moore, AN Fader, Uterine papillary serous carcinoma. Clin Obstet Gynecol 54, 278-291 (2011)).

[0022] Endometrial cancer is the most common gynecological malignancy, with an estimated 61,380 new cases in the United States in 2017 (N. Howlader et al., SEER Cancer Statistics Review, 1975-2014, National Cancer Institute. (2017)). The incidence of endometrial cancer has increased with increasing obesity and life expectancy (M. Arnold et al., Global burden of cancer attributable to high body-mass index in 2012: a population-based study. The Lancet. Oncology 16, 36-46 (2015)). At the same time, relative survival rates have not improved over the past few decades (N. Howlader et al., SEER Cancer Statistics Review, 1975-2014, National Cancer Institute. (2017); L. Rahib et al., Projecting cancer incidence and deaths to 2030: the unexpected burden of thyroid, liver, and pancreas cancers in the United States. Cancer research 74, 2913-2921 (2014)). Many efforts have been directed to developing screening tests for this type of cancer. The most common diagnostic test is transvaginal ultrasound (TVUS), which measures the thickness of the endometrium. The potential of TVUS as a screening test has been diminished by the inability of TVUS to reliably distinguish between benign and malignant lesions, thereby subjecting women without cancer to unnecessary invasive procedures and their associated complications. The high false-positive rate is demonstrated by the fact that only one of 50 women with a positive TVUS test was confirmed to have endometrial cancer after undergoing additional diagnostic procedures (Jacobs et al., Sensitivity of transvaginal ultrasound screening for endometrial cancer in postmenopausal women: a case-control study within the UKCTOCS cohort. The Lancet. Oncology 12, 38-48 (2011)).

[0023] Ovarian cancer is the second most common gynecological malignancy in the United States and Europe. It is usually diagnosed in the late stage, when the 5-year survival rate is less than 30% (N. Howlader et al., SEER Cancer Statistics Review, 1975-2014, National Cancer Institute. (2017)). The high mortality rate has made the development of an effective screening test a top priority. Large randomized trials have evaluated the use of CA-125 and TVUS as potential screening tests for ovarian cancer (Buys et al., Effect of screening on ovarian cancer mortality: the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Randomized Controlled Trial. JAMA 305, 2295-2303 (2011); Kobayashi et al., A randomized study of screening for ovarian cancer: a multicenter study in Japan. Int J Gynecol Cancer 18, 414-420 (2008); Jacobs et al., Ovarian cancer screening and mortality in the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS): a randomized controlled trial. Lancet 387, 945-956 (2016); Menon et al., Risk Algorithm Using Serial Biomarker Measurements Doubles the Number of Screen-Detected Cancers Compared with a Single-Threshold Rule in the United Kingdom Collaborative Trial of Ovarian Cancer Screening. J Clin Oncol 33, 2062-2071 (2015)).However, screening of the general population using current diagnostic methods is not recommended because it can lead to "significant harms, including major surgical intervention in women without cancer" (VA Moyer, USPST Force, Screening for ovarian cancer: US Preventive Services Task Force reaffirmation recommendation statement. Annals of internal medicine 157, 900-904 (2012)). Therefore, new diagnostic methods are urgently needed.

[0024] Among ovarian cancers, high-grade serous carcinoma (HGSC) accounts for 90% of all ovarian cancer deaths. There is increasing evidence that most HGSCs arise in the fallopian tube and subsequently migrate to the ovarian surface (16-21R.J.Kurman, M.Shih Ie, Molecular pathogenesis and extraovarian origin of epithelial ovarian cancer--shifting the paradigm.Human pathology 42, 918-931 (2011); Lee et al., A candidate precursor to serous careinoma that originates in the distal fallopian tube.The Journal of pathology 211, 26-35 (2007); Eckert et al., Genomics of Ovarian Cancer Progression Reveals Diverse Metastatic Trajectories Including Intraepithelial Metastasis to the Fallopian Tube.Cancer Discov 6, 1342-1351 (2016); AM Karst, K. Levanon, R. Drapkin, Modeling high-grade serous ovarian careinogenesis from the fallopian tube. Proe Natl Acad Sci USA 108, 7547-7552 (2011); Zhai et al., High-grade serous careinomas arise in the mouse oviduct via defects linked to the human disease. The Journal of pathology 243, 16-25(2017); RJKurman, M.ShihIe, The Dualistic Model of Ovarian Carcinogenesis: Revisited, Revised, and Expanded. Am J Pathol 186, 733-747 (2016)). A recent prospective study of symptomatic women reported that the majority of early-diagnosed HGSCs had extraovarian origins (Gilbert et al. Assessment of symptomatic women for early diagnosis of ovarian cancer: results from the prospective DOvE pilot project. The Lancet. Oncology 13, 285-291 (2012)). This may explain the low sensitivity of TVUS for early-stage disease when no ovarian abnormalities are detected. Multimodal screening of serum CA-125 levels has improved sensitivity, however CA-125 lacks specificity and is elevated in a variety of common benign conditions (H. Meden, A. Fattahi-Meibodi, CA 125 in benign gynecological conditions. Int J Biol Markers 13, 231-237 (1998)).

[0025] Unlike markers associated with neoplasia, cancer driver gene mutations are causative agents of neoplasia and are absent in non-neoplastic conditions. Tumor DNA has been shown to be detectable in the vagina of women with ovarian cancer (Erickson et al., Detection of somatic TP53 mutations in tampons of patients with high-grade serous ovarian cancer. Obstetrics and gynecology 124, 881-885 (2014)). In addition, a recent proof-of-principle study showed that cells shed by endometrial and ovarian cancers accumulate in the cervix, allowing detectable levels of tumor DNA to be found in fluid obtained during a routine Pap test (Kinde et al., Evaluation of DNA from the Papanicolaou test to detect ovarian and endometrial cancers. Sci Transl Med 5, 167ra164 (2013)). These cells are sampled with a brush inserted into the cervical canal (a "Pap brush"). The brush is then immersed in an antiseptic fluid. To detect cervical cancer, cells in the fluid are applied to a slide for cytology (the classic Pap smear). Additionally, DNA is typically purified from the fluid to look for HPV sequences.

[0026] Bladder cancer (BC) is the most common urinary tract malignancy. According to the American Cancer Society, in 2017, an estimated 79,030 new cases of bladder cancer and 18,540 deaths were reported in the United States alone [Siegel RL, Miller KD, Jemal A (2017) Cancer Statistics, 2017. CA Cancer J Clin 67: 7-30]. Based primarily on urothelial histology, invasive BC originates from non-invasive papillary or flat precursors. Many BC patients experience multiple recurrences before progression, providing ample preparation time for early detection and treatment before metastasis [Netto GJ (2013) Clinical applications of recent molecular advances in urologic malignancies: no longer chasing a "mirage"? Adv Anat Pathol 20: 175-203]. Urine cytology and cystoscopy performed with transurethral biopsy (TURB) are the current gold standards for diagnosing and following up bladder cancer. Although urine cytology has value in detecting high-grade neoplasms, it fails to detect the vast majority of low-grade tumors [Netto GJ, Tafe LJ (2016) Emerging Bladder Cancer Biomarkers and Targets of Therapy. Urol Clin North Am 43:63–76; Lotan Y, Roehrborn CG (2003) Sensitivity and specificity of commonly available bladder tumor markers versus cytology: results of a comprehensive literature review and meta-analyses. Urology 61:109–18; discussion 118; Zhang ML, Rosenthal DL, VandenBussche CJ (2016) The cytomorphological features of low-grade urothelial neoplasms vary by specimen type.Cancer Cytopathol 124:552-564]. This fact, coupled with the high cost and invasiveness of repeated cystoscopies and TURB procedures, has led to numerous attempts to develop novel noninvasive strategies. These include urine- or serum-based genetic and protein assays for screening and surveillance [Kawauchi et al. (2009) 9p21 Index as Estimated by Dual-Color Fluorescence in Situ Hybridization is Useful to Predict Urothelial Carcinoma Recurrence in Bladder Washing Cytology. Hum Pathol 40: 1783-1789; Kruger S, Mess F, Bohle A, Feller AC (2003) Numerical aberrations of chromosome 17 and the 9p21 locus are independent predictors of tumor recurrence in non-invasive transitional cell carcinoma of the urinary bladder. Int J Oncol 23: 41-48; Skacel et al. (2003) Multitarget fluorescence in situ hybridization assay detects transitional cell carcinoma in the majority of patients with bladder cancer and atypical or negative urine cytology. J Urol 169: 2101-2105; Sarosdy et al., (2006) Use of a multitarget fluorescence in situ hybridization assay to diagnose bladder cancer in patients with hematuria.J Urol 176: 44 - 47; Moonen et al., (2007) UroVysion compared with cytology and quantitative cytology in the surveillance of non - muscle - invasive bladder cancer. Eur Urol 51: 1275 - 80; discussion 1280; Fradet Y, Lockhard C (1997) Performance characteristics of a new monoclonal antibody test for bladder cancer: ImmunoCyt trade mark. Can J Urol 4: 400 - 405; Yafi et al., (2015) Prospective analysis of sensitivity and specificity of urinary cytology and other urinary biomarkers for bladder cancer. Urol Oncol 33: 66.e25 - 66.e31; Serizawa et al., (2010) Integrated genetic and epigenetic analysis of bladder cancer reveals an additive diagnostic value of FGFR3 mutations and hypermethylation events. Int J Cancer; Kinde et al., (2013) TERT promoter mutations occur early in urothelial neoplasia and are biomarkers of early disease and disease recurrence in urine. Cancer Res 73: 7162 - 7167; Hurst CD, Platt FM, Knowles MA (2014) Comprehensive mutation analysis of the TERT promoter in bladder cancer and detection of mutations in voided urine.Eur Urol 65: 367 - 369; Wang et al., (2014) TERT promoter mutations are associated with distant metastases in upper tract urothelial carcinomas and serve as urinary biomarkers detected by a sensitive castPCR. Oncotarget 5: 12428 - 12439; Ralla et al., (2014) Nucleic acid-based biomarkers in body fluids of patients with urologic malignancies. Crit Rev Clin Lab Sci 51: 200 - 231; Ellinger J, Muller SC, Dietrich D (2015) Epigenetic biomarkers in the blood of patients with urological malignancies. Expert Rev Mol Diagn 15: 505 - 516; Bansal N, Gupta A, Sankhwar SN, Mahdi AA (2014) Low- and high-grade bladder cancer appraisal via serum-based proteomics approach. Clin Chim Acta 436: 97 - 103; Goodison S, Chang M, Dai Y, Urquidi V, Rosser CJ (2012) A multi-analyte assay for the non-invasive detection of bladder cancer. PLoS One 7: e47469; Allory et al., (2014) Telomerase reverse transcriptase promoter mutations in bladder cancer: high frequency across stages, detection in urine, and lack of association with outcome.Eur Urol 65:360–366]. Currently available U.S. Food and Drug Administration (FDA)-approved assays include the ImmunoCyt test (Scimedx Corp), the nuclear matrix protein 22 (NMP22) immunoassay (Matritech), and multitarget FISH (UroVysion) [Kawauchi et al. (2009) 9p21 Index as Estimated by Dual-Color Fluorescence in Situ Hybridization is Useful to Predict Urothelial Carcinoma Recurrence in Bladder Washing Cytology. Hum Pathol 40:1783-1789; Kruger S, Mess F, Bohle A, Feller AC (2003) Numerical aberrations of chromosome 17 and the 9p21 locus are independent predictors of tumor recurrence in non-invasive transitional cell carcinoma of the urinary bladder. Int J Oncol 23:41-48; Skacel et al. (2003) Multitarget fluorescence insitu hybridization assay detects transitional cell carcinoma in the majority of patients with bladder cancer and atypical or negative urine cytology. JUrol 169: 2101-2105; Sarosdy et al., (2006) Use of a multitarget fluorescence insitu hybridization assay to diagnose bladder cancer in patients with hematuria.J Urol 176:44-47; Moonen et al. (2007) UroVysion compared with cytology and quantitative cytology in the surveillance of non-muscle-invasive bladder cancer. Eur Urol 51:1275-80; discussion 1280; Fradet Y, Lockhard C (1997) Performance characteristics of a new monoclonal antibody test for bladder cancer: ImmunoCyt trademark. Can J Urol 4:400-405; Yafi et al. (2015) Prospective analysis of sensitivity and specificity of urinary cytology and other urinary biomarkers for bladder cancer. Urol Oncol 33:66.e25-66.e31]. Some of these tests have been reported to have sensitivities between 62% and 69% and specificities between 79% and 89%. However, such assays have not been integrated into routine clinical practice due to inconsistent assay performance, cost, or required technical expertise.

[0027] Bladder cancer is generally divided into three types, which begin in the cells of the bladder's lining. In some embodiments, bladder cancer is named after the cell type that becomes malignant (cancerous), including transitional cell carcinoma, squamous cell carcinoma, and adenocarcinoma. Transitional cell carcinoma begins in the cells of the innermost tissue layer of the bladder. Transitional cell carcinoma can be low-grade or high-grade. Low-grade transitional cell carcinoma can recur after treatment, but rarely spread to the muscle layer of the bladder or other parts of the body. High-grade transitional cell carcinoma can recur after treatment and often spreads into the muscle layer of the bladder, to other parts of the body, and to the lymph nodes. Almost all deaths caused by bladder cancer are due to high-grade disease. Squamous cell carcinoma begins in squamous cells, which are thin, flat cells that may form in the bladder after long-term infection or irritation. Adenocarcinoma begins in glandular (secretory) cells present in the lining of the bladder and is a very rare type of bladder cancer.

[0028] It was found that the rate of activating mutations in the upstream promoter of the TERT gene was high in most BC and other cancer types [Huang Fw, Hodis E, Xu MJ, Kryukov GV, Chin L, Garraway LA (2013) Highly recurrent TERT promoter mutations in human melanoma. Science 339: 957-959; Killela et al. (2013) TERT promoter mutations occur frequently in gliomas and a subset of tumors derived from cells with low rates of self-renewal. Proc Natl Acad Sci USA 110: 6021-6026; Scott GA, Laughlin TS, Rothberg PG (2014) Mutations of the TERT promoter are common in basal cell carcinoma and squamous cell carcinoma. Mod Pathol 27: 516-523]. TERT promoter mutations primarily affect two hotspots, g.1295228 C>T and g.1295250C>T, which result in the generation of CCGGAA / T or GGAA / T motifs, thereby altering the binding sites of ETS transcription factors and subsequently increasing TERT promoter activity [Huang Fw, Hodis E, Xu MJ, Kryukov GV, Chin L, Garraway LA (2013) Highly recurrent TERT promoter mutations in human melanoma. Science 339: 957-959; Horn et al. (2013) TERT promoter mutations in familial and sporadic melanoma. Science 339: 959-961].TERT promoter mutations occur in up to 80% of invasive urothelial carcinomas of the bladder and upper urinary tract and several of their histologic variants [Kinde et al. (2013) TERT promoter mutations occur early in urothelial neoplasia and are biomarkers of early disease and disease recurrence in urine. Cancer Res 73:7162-7167; Killela et al. (2013) TERT promoter mutations occur frequently in gliomas and a subset of tumors derived from cells with low rates of self-renewal. Proc Natl Acad Sci USA 110:6021-6026; Allory et al. (2014) Telomerase reverse transcriptase promoter mutations in bladder cancer: high frequency across stages, detection in urine, and lack of association with outcome. Eur Urol 65:360-366; Cowan et al. (2016) Detection of TERT promoter mutations in primary adenocarcinoma of the urinary bladder. Hum Pathol 53: 8-13; Nguyen et al., (2016) High prevalence of TERT promoter mutations in micropapillary urothelial carcinoma. Virchows Arch 469: 427-434].Furthermore, TERT promoter mutations occur in 60%-80% of BC precursors (including papillary urothelial neoplasia of low malignant potential [Rodriguez et al., (2017) Spectrum of genetic mutations in de novo PUNLMP of the urinary bladder. Virchows Arch], non-invasive low-grade papillary urothelial carcinoma, non-invasive high-grade papillary urothelial carcinoma, and “flat” carcinoma in situ (CIS)), as well as in urine cells of a subset of these patients [Kinde et al., (2013) TERT promoter mutations occur early in urothelial neoplasia and are biomarkers of early disease and disease recurrence in urine. Cancer Res 73:7162-7167]. Thus, TERT promoter mutations have been identified as the most common genetic alterations in BC [Kinde et al. (2013) TERT promoter mutations occur early in urothelial neoplasia and are biomarkers of early disease and disease recurrence in urine. Cancer Res 73: 7162-7167; Cheng L, Montironi R, Lopez-Beltran A (2017) TERT Promoter Mutations Occur Frequently in Urothelial Papilloma and Papillary Urothelial Neoplasm of Low Malignant Potential. Eur Urol 71: 497-498].Other oncogene-activating mutations include those in FGFR3, RAS, and PIK3CA, which have been shown to occur in a significant proportion of non-muscle invasive bladder cancers [International Agency for Research on Cancer. (2016) WHO Classification of Tumors of the Urinary System and Male Genital Organs. World Health Organization; 4th ed.; Netto GJ (2011) Molecular biomarkers in urothelial carcinoma of the bladder: are we there yet? . Nat Rev Urol 9:41-51].In muscle-invasive bladder cancer, mutations in TP53, CDKN2A, MLL, and ERBB2 are also frequently found [Netto GJ (2011) Molecular biomarkers in urothelial carcinoma of the bladder: are we there yet?. Nat Rev Urol 9:41-51; Mo et al., (2007) Hyperactivation of Ha-ras oncogene, but not Ink4a / Arf deficiency, triggers bladder tumorigenesis. J Clin Invest 117:314-325; Sarkis et al., (1993) Nuclear overexpression of p53 protein in transitional cell bladder carcinoma: a marker for disease progression. J Natl Cancer Inst 85:53-59; Lin et al., (2010) Increase sensitivity in detecting superficial, low grade bladder cancer by combination analysis of hypermethylation of E-cadherin, p16, p14, RASSF1A genes in urine. Urol Oncol 28:597-602; Sarkis et al., (1994) Association of P53 nuclear overexpression and tumor progression in carcinoma in situ of the bladder. J Urol 152:388-392; Wu XR (2005) Urothelial tumorigenesis: a tale of divergent pathways. Nat Rev Cancer 5:713-725; Cancer Genome Atlas Research Network (2014) Comprehensive molecular characterization of urothelial bladder carcinoma. Nature 507:315-322].

[0029] Because urine cytology is relatively insensitive for detecting recurrence, cystoscopy is performed every three months in such patients in the United States whenever possible. In fact, the cost of managing these patients is higher than that of managing any other type of cancer, totaling $3 billion annually [Netto GJ, Epstein JI (2010) Theranostic and prognostic biomarkers: genomic applications in urological malignancies. Pathology 42: 384-394]. Therefore, a non-invasive test that can predict which of these patients is most likely to develop recurrent BC is of great medical and economic importance.

[0030] More than 400,000 new cases of urinary transitional cell carcinoma are diagnosed worldwide each year (Antoni, S., Ferlay, J., Soerjomataram, I., Znaor, A., Jemal, A., & Bray, F. (2017). Bladder Cancer Incidence and Mortality: A Global Overview and Recent Trends. Eur Urol, 71(1), 96-108. doi: 10.1016 / j.eururo.2016.06.010). Although most of these urothelial carcinomas arise in the bladder of the lower urinary tract, 5%–10% arise in the upper urinary tract of the renal pelvis and / or ureters (Roupret, M., Babjuk, M., Comperat, E., Zigeuner, R., Sylvester, R.J., Burger, M., Cowan, N.C., Bohle, A., Van Rhijn, B.W., Kaasinen, E., Palou, J., & Shariat, S.F. (2015). European Association of Urology Guidelines on Upper Urinary Tract Urothelial Cell Carcinoma: 2015 Update. European Association of Urology. Urol, 68(5), 868-879. doi: 10.1016 / j.eururo.2015.06.044; Soria, F., Shariat, SF, Lerner, SP, Fritsche, HM, Rink, M., Kassouf, W., Spiess, PE, Lotan, Y., Ye, D., Fernandez, MI, Kikuchi, E., Chade, DC, Babjuk, M., Grollman, AP, and Thalmann, GN (2017). Epidemiology, diagnosis, preoperative evaluation and prognostic assessment of upper-tract urothelial carcinoma (UTUC). World J Urol, 35(3), 379-387. doi: 10.1007 / s00345-016-1928-x).The annual incidence of these upper tract urothelial cancers (UTUCs) is 1–2 per 100,000 people in Western countries, but is much higher in populations exposed to aristolochic acid (AA) (Chen, CH, Dickman, KG, Moriya, M., Zavadil, J., Sidorenko, VS, Edwards, KL, Gnatenko, DV, Wu, L., Turesky, RJ, Wu, XR, Pu, YS, & Grollman, AP (2012). Proc Natl Acad Sci USA, 109(21), 8241–8246. doi: 10.1073 / pnas.1119920109; Grollman, AP (2013). Aristolochic acid nephropathy: Harbinger of a global iatrogenic disease. Environ Mol. Mutagen, 54(1), 1-7. doi: 10.1002 / em.21756; Lai, MN, Wang, SM, Chen, PC, Chen, YY, & Wang, JD (2010). Population-based case-control study of Chinese herbal products containing aristolochic acid and urinary tract cancer risk. J Natl Cancer Inst, 102(3), 179-186. doi: 10.1093 / jnci / djp467. AA is a carcinogenic and nephrotoxic nitrophenanthrene carboxylic acid produced by Aristolochia plants (Hsieh, SC, Lin, IH, Tseng, WL, Lee, CH, & Wang, JD (2008). Chin Med, 3, 13. doi: 10.1186 / 1749-8546-3-13; National Toxicology Program. (2011). Aristolochic acids. Rep Carcinog, 12, 45-49). An etiological link between AA exposure and UTUC has been established in two different populations.The first group lives in the Balkans, where Aristolochia plants grow naturally in wheat fields (Jelakovic, B., Karanovic, S., Vukovic-Lela, I., Miller, F., Edwards, KL, Nikolic, J., Tomic, K., Slade, N., Brdar, B., Turesky, RJ, Stipancic, Z., Dittrich, D., Grollman, AP, & Dickman, KG (2012). Aristolactam-DNA adducts are a biomarker of environmental exposure to aristolochiacid. Kidney Int, 81(6), 559-567. doi: 10.1038 / ki.2011.371). The second group is in Asia, where Aristolochia herbs are widely used in traditional Chinese medicine practices (Grollman, 2013; National Toxicology Program, 2011). Taking the public health threat posed by the medicinal use of Aristolochia herbs in Taiwan, China as an example, Taiwan has the highest incidence of UTUC in the world (Chen, CH, Dickman, KG, Moriya, M., Zavadil, J., Sidorenko, VS, Edwards, KL, Gnatenko, DV, Wu, L., Turesky, RJ, Wu, XR, Pu, YS, & Grollman, AP (2012). Proc Natl Acad Sci USA, 109(21), 8241-8246. doi: 10.1073 / pnas.1119920109; Yang, MH, Chen, KK, Yen, CC, Wang, WS, Chang, YH, Huang, WJ, Fan, FS, Chiou, TJ, Liu, JH, & Chen, PM (2002). Urology, 59(5), 681-687). More than one-third of the adult population in Taiwan is prescribed herbal medicines containing AA (Hsieh, SC, Lin, IH, Tseng, WL, Lee, CH, & Wang, JD (2008). Chin Med, 3, 13. doi: 10.1186 / 1749-8546-3-13), resulting in an unusually high proportion of UTUC cases relative to all urothelial cancers (37%).

[0031] Nephroureterectomy can cure patients with UTUC detected at an early stage (Li, CC, Chang, TH, Wu, WJ, Ke, HL, Huang, SP, Tsai, PC, Chang, SJ, Shen, JT, Chou, YH, & Huang, CH (2008). Eur Urol, 54(5), 1127-1134. doi: 10.1016 / j.eururo.2008.01.054). However, most of these cancers are silent until overt clinical symptoms (usually hematuria) develop, and therefore, most patients are diagnosed only at an advanced stage (Roupret, M., Babjuk, M., Comperat, E., Zigeuner, R., Sylvester, RJ, Burger, M., Cowan, NC, Bohle, A., Van Rhijn, BW, Kaasinen, E., Palou, J., & Shariat, SF (2015). European Association of Urology Guidelines on Upper Urinary Tract Urothelial Cell Carcinoma: 2015 Update. Eur Urol, 68(5), 868-879. doi: 10.1016 / j.eururo.2015.06.044). Currently, diagnostic tests for detecting early UTUC are not available. Therefore, there is a need for clinical tools that can be used to identify early UTUC in populations at risk for developing this type of malignancy.Recurrence after surgery is also a problem, as UTUC can recur in the contralateral upper urinary tract and / or bladder (Roupret, M., Babjuk, M., Comperat, E., Zigeuner, R., Sylvester, RJ, Burger, M., Cowan, N.C., Bohle, A., Van Rhijn, B.W., Kaasinen, E., Palou, J., & Shariat, S.F. (2015). European Association of Urology Guidelines on Upper Urinary Tract Urothelial Cell Carcinoma: 2015 Update. European Association of Urology. Urol, 68(5), 868-879. doi: 10.1016 / j.eururo.2015.06.044; Soria, F., Shariat, SF, Lerner, SP, Fritsche, HM, Rink, M., Kassouf, W., Spiess, PE, Lotan, Y., Ye, D., Fernandez, MI, Kikuchi, E., Chade, DC, Babjuk, M., Grollman, AP, and Thalmann, GN (2017). Epidemiology, diagnosis, preoperative evaluation and prognostic assessment of upper-tract urothelialcarcinoma (UTUC). World J Urol, 35(3), 379-387. doi: 10.1007 / s00345-016-1928-x). Therefore, vigilant surveillance for signs of malignancy is an essential part of follow-up care for patients with UTUC, and non-invasive testing for recurrent disease could significantly improve postoperative management, particularly because urine cytology fails to detect most UTUC (Baara, J., de Bruin, DM, Zondervan, PJ, Kamphuis, G., de la Rosette, J., & Laguna, MP (2017). Diagnostic dilemmas in patients with upper tract urothelial carcinoma. Nat Rev Urol, 14(3), 181-191. doi: 10.1038 / nrurol.2016.252). Summary of the Invention

[0032] Generally speaking, provided herein is the method and material for the existence of cancer in subject compared with the conventional method for identifying the existence of cancer in subject with the sensitivity and specificity of increase.In some embodiments, provided herein is for the method for the existence of cancer in subject with the sensitivity and specificity of increase to perform to the liquid sample (such as blood, blood plasma or serum) obtained from subject, and the conventional method for identifying the existence of cancer in subject can not reach sensitivity level, specificity level or both when performing detection to the liquid sample obtained from subject.In some embodiments, provided herein is for the method for the existence of cancer in subject with the sensitivity and specificity of increase to determine that subject has suffered from cancer before, before determining that subject carries cancer cell and / or before subject shows the symptom associated with cancer and performs.In some embodiments, provided herein is for the method for the existence of cancer in subject with the sensitivity and specificity of increase to be used as first line detection method, rather than simply being used as the confirmation (for example, " overestimation (overcall)") of another detection method that subject suffers from cancer.

[0033] In some embodiments, provided herein are methods for identifying the presence of pancreatic cancer in a subject, comprising: detecting the presence of one or more genetic biomarkers in one or more of the following genes: KRAS, TP53, CDKN2A, or SMAD4 in a first biological sample obtained from the subject; detecting the level of one or more of the following protein biomarkers: carbohydrate antigen 19-9 (CA19-9), carcinoembryonic antigen (CEA), hepatocyte growth factor (HGF), or osteopontin (OPN) in a second biological sample obtained from the subject; comparing the detected levels of the one or more protein biomarkers to a reference level of the one or more protein biomarkers; and identifying the presence of pancreatic cancer in the subject upon detecting the presence of the one or more genetic biomarkers, the detected levels of the one or more protein biomarkers being higher than the reference level of the one or more protein biomarkers, or both. In some of the methods for identifying the presence of pancreatic cancer in a subject, the first biological sample, the second biological sample, or both comprise plasma. In some of the methods for identifying the presence of pancreatic cancer in a subject, the first biological sample and the second biological sample are the same. In some of the methods for identifying the presence of pancreatic cancer in a subject, the presence of one or more of the following genetic biomarkers is detected: KRAS, TP53, CDKN2A, and SMAD4. In some of the methods for identifying the presence of pancreatic cancer in a subject, the levels of the following are detected: carbohydrate antigen 19-9 (CA19-9), carcinoembryonic antigen (CEA), hepatocyte growth factor (HGF), and osteopontin (OPN). In some of the methods for identifying the presence of pancreatic cancer in a subject, the presence of one or more of the following genetic biomarkers is detected using a PCR-based multiplex sequencing assay, the PCR-based multiplex sequencing assay comprising: a. assigning a unique identifier (UID) to each of a plurality of template molecules present in the sample; b. amplifying each uniquely tagged template molecule to generate a UID family; and c. redundantly sequencing the amplified products. In some of the methods for identifying the presence of pancreatic cancer in a subject, detecting the presence of one or more genetic biomarkers, detecting the level of one or more protein biomarkers, or both is performed without knowing that the subject carries cancer cells. In some of the methods for identifying the presence of pancreatic cancer in a subject, one or more therapeutic interventions (e.g., surgery, adjuvant chemotherapy, neoadjuvant chemotherapy, radiation therapy, immunotherapy, targeted therapy, and / or immune checkpoint inhibitors) are administered to the subject.

[0034] In some embodiments, provided herein are methods for identifying the presence of cancer in a subject, comprising: detecting the presence of one or more genetic biomarkers in one or more of the following genes: NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A, or GNAS in a first biological sample obtained from the subject; detecting the level of one or more protein biomarkers in a second biological sample obtained from the subject: CA19-9, CEA, HGF, OPN, CA125, prolactin, TIMP-1, or MPO; comparing the detected levels of the one or more protein biomarkers to a reference level of the one or more protein biomarkers; and identifying the presence of cancer in the subject upon detecting the presence of the one or more genetic biomarkers, the detected levels of the one or more protein biomarkers being above the reference level of the one or more protein biomarkers, or both. In some embodiments of the method for identifying the presence of cancer in a subject, the first biological sample, the second biological sample, or both comprise plasma. In some embodiments of the method for identifying the presence of cancer in a subject, the first biological sample and the second biological sample are the same. In some embodiments of the method for identifying the presence of cancer in a subject, the presence of one or more genetic biomarkers of the following is detected: NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A, and GNAS. In some embodiments of the method for identifying the presence of cancer in a subject, the levels of the following are detected: CA19-9, CEA, HGF, OPN, CA125, prolactin, TIMP-1, and MPO. In some embodiments of the method for identifying the presence of cancer in a subject, the presence of one or more genetic biomarkers of one or more of the following is detected using a PCR-based multiplex sequencing assay comprising: a. assigning a unique identifier (UID) to each of a plurality of template molecules present in the sample; b. amplifying each uniquely tagged template molecule to generate a family of UIDs; and c. redundantly sequencing the amplified products. In some embodiments of the method for identifying the presence of cancer in a subject, the cancer is liver cancer, ovarian cancer, esophageal cancer, gastric cancer, pancreatic cancer, colorectal cancer, lung cancer, breast cancer, or prostate cancer.In some embodiments of the method for identifying the presence of cancer in a subject, detecting the presence of one or more genetic biomarkers, detecting the level of one or more protein biomarkers, or both are performed without knowing that the subject carries cancer cells. In some embodiments of the method for identifying the presence of cancer in a subject, one or more therapeutic interventions (e.g., surgery, adjuvant chemotherapy, neoadjuvant chemotherapy, radiotherapy, immunotherapy, targeted therapy, and / or immune checkpoint inhibitors) are administered to the subject.

[0035] In some embodiments, provided herein are methods for identifying the presence of cancer in a subject, comprising: detecting the presence of one or more genetic biomarkers in one or more of the following genes: NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A, or GNAS in a first biological sample obtained from the subject; detecting the level of one or more protein biomarkers in a second biological sample obtained from the subject: CA19-9, CEA, HGF, OPN, CA125, AFP, prolactin, TIMP-1, follistatin, G-CSF, or CA15-3; comparing the detected levels of the one or more protein biomarkers to a reference level of the one or more protein biomarkers; and identifying the presence of cancer in the subject upon detecting the presence of the one or more genetic biomarkers, the detected levels of the one or more protein biomarkers being above the reference level of the one or more protein biomarkers, or both. In some embodiments of the method for identifying the presence of cancer in a subject, the first biological sample, the second biological sample, or both comprise plasma. In some embodiments of the method for identifying the presence of cancer in a subject, the first biological sample and the second biological sample are the same. In some embodiments of the method for identifying the presence of cancer in a subject, the presence of one or more genetic biomarkers of the following is detected: NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A, and GNAS. In some embodiments of the method for identifying the presence of cancer in a subject, the levels of the following are detected: CA19-9, CEA, HGF, OPN, CA125, AFP, prolactin, TIMP-1, follistatin, G-CSF, and CA15-3. In some embodiments of the method for identifying the presence of cancer in a subject, a PCR-based multiplex sequencing assay is used to detect the presence of one or more genetic biomarkers of one or more of the following: NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A or GNAS, wherein the PCR-based multiplex sequencing assay comprises: a. assigning a unique identifier (UID) to each of a plurality of template molecules present in the sample; b. amplifying each uniquely tagged template molecule to generate a family of UIDs; and c. redundantly sequencing the amplified products.In some embodiments of the method for identifying the presence of cancer in a subject, cancer is liver cancer, ovarian cancer, esophageal cancer, gastric cancer, pancreatic cancer, colorectal cancer, lung cancer, breast cancer or prostate cancer. In some embodiments of the method for identifying the presence of cancer in a subject, without knowing that the subject carries cancer cells, the presence of one or more genetic biomarkers, the level of one or more protein biomarkers or both are detected. In some embodiments of the method for identifying the presence of cancer in a subject, one or more therapeutic interventions (for example, surgery, adjuvant chemotherapy, neoadjuvant chemotherapy, radiotherapy, immunotherapy, targeted therapy and / or immune checkpoint inhibitors) are administered to the subject.

[0036] In some embodiments, provided herein are methods for identifying the presence of cancer in a subject, comprising: detecting the presence of one or more genetic biomarkers in one or more of the following genes: NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A, or GNAS in a first biological sample obtained from the subject; detecting the level of one or more protein biomarkers: CA19-9, CEA, HGF, OPN, CA125, AFP, prolactin, TIMP-1, or CA15-3 in a second biological sample obtained from the subject; comparing the detected level of the one or more protein biomarkers to a reference level of the one or more protein biomarkers; and identifying the presence of cancer in the subject upon detecting the presence of the one or more genetic biomarkers, the detected level of the one or more protein biomarkers being higher than the reference level of the one or more protein biomarkers, or both. In some embodiments of the method for identifying the presence of cancer in a subject, the first biological sample, the second biological sample, or both comprise plasma. In some embodiments of the method for identifying the presence of cancer in a subject, the first biological sample and the second biological sample are the same. In some embodiments of the method for identifying the presence of cancer in a subject, the presence of one or more genetic biomarkers of the following is detected: NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A, and GNAS. In some embodiments of the method for identifying the presence of cancer in a subject, the levels of the following are detected: CA19-9, CEA, HGF, OPN, CA125, AFP, prolactin, TIMP-1, and CA15-3. In some embodiments of the method for identifying the presence of cancer in a subject, the presence of one or more genetic biomarkers of one or more of the following is detected using a PCR-based multiplex sequencing assay comprising: a. assigning a unique identifier (UID) to each of a plurality of template molecules present in the sample; b. amplifying each uniquely tagged template molecule to generate a family of UIDs; and c. redundantly sequencing the amplified products. In some embodiments of the method for identifying the presence of cancer in a subject, the cancer is liver cancer, ovarian cancer, esophageal cancer, gastric cancer, pancreatic cancer, colorectal cancer, lung cancer, breast cancer, or prostate cancer.In some embodiments of the method for identifying the presence of cancer in a subject, detecting the presence of one or more genetic biomarkers, detecting the level of one or more protein biomarkers, or both are performed without knowing that the subject carries cancer cells. In some embodiments of the method for identifying the presence of cancer in a subject, one or more therapeutic interventions (e.g., surgery, adjuvant chemotherapy, neoadjuvant chemotherapy, radiotherapy, immunotherapy, targeted therapy, and / or immune checkpoint inhibitors) are administered to the subject.

[0037] In some embodiments, provided herein are methods for identifying the presence of bladder cancer or upper tract urothelial cancer in a subject, comprising: detecting the presence of one or more genetic biomarkers in one or more of the following genes: TP53, PIK3CA, FGFR3, KRAS, ERBB2, CDKN2A, MLL, HRAS, MET, or VHL in a first biological sample obtained from the subject; detecting the presence of at least one mutation in the TERT promoter in a second biological sample obtained from the subject; and detecting the presence of aneuploidy in a third biological sample obtained from the subject; and upon detecting the presence of the one or more genetic biomarkers, the presence of at least one mutation in the TERT promoter, the presence of aneuploidy, or a combination thereof, identifying the presence of bladder cancer or upper tract urothelial cancer in the subject. In some embodiments of the method for identifying the presence of bladder cancer or upper tract urothelial cancer in a subject, the first biological sample and the second biological sample are the same; the first biological sample and the third biological sample are the same; the second biological sample and the third biological sample are the same; or the first biological sample, the second biological sample, and the third biological sample are the same. In some embodiments of the method for identifying the presence of bladder cancer or upper tract urothelial carcinoma in a subject, the first biological sample, the second biological sample, or the third biological sample is a urine sample. In some embodiments of the method for identifying the presence of bladder cancer or upper tract urothelial carcinoma in a subject, the presence of aneuploidy is detected on one or more of chromosome arms 5q, 8q, or 9p. In some embodiments of the method for identifying the presence of bladder cancer or upper tract urothelial carcinoma in a subject, the presence of one or more genetic biomarkers of the following is detected: TP53, PIK3CA, FGFR3, KRAS, ERBB2, CDKN2A, MLL, HRAS, MET, and VHL. In some embodiments of the method for identifying the presence of bladder cancer or upper tract urothelial carcinoma in a subject, the presence of one or more genetic biomarkers of one or more of the following is detected using a PCR-based multiplex sequencing assay, the PCR-based multiplex sequencing assay comprising: a. assigning a unique identifier (UID) to each of a plurality of template molecules present in the sample; b. amplifying each uniquely tagged template molecule to generate a family of UIDs; and c. redundantly sequencing the amplified products. In some embodiments of the method for identifying the presence of bladder cancer or upper tract urothelial carcinoma in a subject, detecting the presence of one or more genetic biomarkers, detecting the presence of at least one mutation in the TERT promoter, or detecting the presence of aneuploidy is performed without knowing that the subject carries cancer cells.In some embodiments of the methods for identifying the presence of bladder cancer or upper tract urothelial carcinoma in a subject, one or more therapeutic interventions (e.g., surgery, adjuvant chemotherapy, neoadjuvant chemotherapy, radiation therapy, immunotherapy, targeted therapy, and / or immune checkpoint inhibitors) are administered to the subject.

[0038] In some embodiments, provided herein are methods for identifying the presence of ovarian or endometrial cancer in a subject, comprising: detecting the presence of one or more genetic biomarkers in one or more of the following genes: NRAS, PTEN, FGFR2, KRAS, POLE, AKT1, TP53, RNF43, PPP2R1A, MAPK1, CTNNB1, PIK3CA, FBXW7, PIK3R1, APC, EGFR, BRAF, or CDKN2A in a first biological sample obtained from the subject; detecting the presence of aneuploidy in a second biological sample obtained from the subject; and upon detecting the presence of one or more genetic biomarkers, detecting the presence of aneuploidy, or both, identifying the presence of ovarian or endometrial cancer in the subject. In some embodiments of the method for identifying the presence of ovarian or endometrial cancer in a subject, the first biological sample and the second biological sample are the same. In some embodiments of the method for identifying the presence of ovarian or endometrial cancer in a subject, the first biological sample or the second biological sample is a cervical sample or an endometrial sample. In some embodiments of the method for identifying the presence of ovarian cancer or endometrial cancer in a subject, the presence of aneuploidy is detected on one or more of chromosome arms 4p, 7q, 8q, or 9q. In some embodiments of the method for identifying the presence of ovarian cancer or endometrial cancer in a subject, the presence of one or more genetic biomarkers is detected: NRAS, PTEN, FGFR2, KRAS, POLE, AKT1, TP53, RNF43, PPP2R1A, MAPK1, CTNNB1, PIK3CA, FBXW7, PIK3R1, APC, EGFR, BRAF, and CDKN2A. In some embodiments of the method for identifying the presence of ovarian cancer or endometrial cancer in a subject, a PCR-based multiplex sequencing assay is used to detect the presence of one or more genetic biomarkers of one or more of the following: NRAS, PTEN, FGFR2, KRAS, POLE, AKT1, TP53, RNF43, PPP2R1A, MAPK1, CTNNB1, PIK3CA, FBXW7, PIK3R1, APC, EGFR, BRAF or CDKN2A, wherein the PCR-based multiplex sequencing assay comprises: a. assigning a unique identifier (UID) to each of a plurality of template molecules present in the sample; b. amplifying each uniquely tagged template molecule to generate a family of UIDs; and c. redundantly sequencing the amplified products.In some embodiments of the method for identifying the presence of ovarian cancer or endometrial cancer in a subject, the method further comprises: detecting the presence of at least one genetic biomarker in one or more of the following genes in a circulating tumor DNA (ctDNA) sample obtained from the subject: AKT1, APC, BRAF, CDKN2A, CTNNB1, EGFR, FBXW7, FGFR2, GNAS, HRAS, KRAS, NRAS, PIK3CA, PPP2R1A, PTEN, or TP53. In some embodiments of the method for identifying the presence of ovarian cancer or endometrial cancer in a subject, detecting the presence of one or more genetic biomarkers or detecting the presence of aneuploidy is performed without knowing that the subject carries cancer cells. In some embodiments of the method for identifying the presence of ovarian cancer or endometrial cancer in a subject, one or more therapeutic interventions (e.g., surgery, adjuvant chemotherapy, neoadjuvant chemotherapy, radiotherapy, immunotherapy, targeted therapy, and / or immune checkpoint inhibitors) are administered to the subject.

[0039] The present disclosure also provides the following specific implementation schemes:

[0040] 1. A method for identifying the presence of pancreatic cancer in a subject, comprising:

[0041] detecting the presence of one or more genetic biomarkers in one or more of the following genes: KRAS, TP53, CDKN2A, or SMAD4 in a first biological sample obtained from the subject;

[0042] detecting the level of one or more of the following protein biomarkers: carbohydrate antigen 19-9 (CA19-9), carcinoembryonic antigen (CEA), hepatocyte growth factor (HGF), or osteopontin (OPN) in a second biological sample obtained from the subject;

[0043] comparing the detected levels of the one or more protein biomarkers to one or more reference levels of the protein biomarkers; and

[0044] The presence of pancreatic cancer in the subject is identified when the presence of one or more genetic biomarkers is detected, the detected level of the one or more protein biomarkers is above the reference level of the one or more protein biomarkers, or both.

[0045] 2. The method of embodiment 1, wherein the first biological sample, the second biological sample, or both comprise plasma.

[0046] 3. The method of embodiment 1, wherein the first biological sample and the second biological sample are the same.

[0047] 4. The method of embodiment 1, wherein the presence of one or more genetic biomarkers of: KRAS, TP53, CDKN2A, and SMAD4 is detected.

[0048] 5. The method of embodiment 1, wherein the levels of carbohydrate antigen 19-9 (CA19-9), carcinoembryonic antigen (CEA), hepatocyte growth factor (HGF), and osteopontin (OPN) are detected.

[0049] 6. The method of embodiment 1, wherein the presence of one or more genetic biomarkers in one or more of KRAS, TP53, CDKN2A, or SMAD4 is detected using a PCR-based multiplex sequencing assay comprising:

[0050] a. assigning a unique identifier (UID) to each of the plurality of template molecules present in the sample;

[0051] b. Amplifying each uniquely tagged template molecule to generate a UID family; and

[0052] c. performing redundant sequencing on the amplified products.

[0053] 7. The method of embodiment 1, wherein detecting the presence of one or more genetic biomarkers, detecting the level of one or more protein biomarkers, or both is performed without knowing that the subject carries cancer cells.

[0054] 8. The method of embodiment 1, wherein the subject is administered one or more of the following therapeutic interventions: surgery, adjuvant chemotherapy, neoadjuvant chemotherapy, radiotherapy, immunotherapy, targeted therapy, or an immune checkpoint inhibitor.

[0055] 9. A method for identifying the presence of cancer in a subject, comprising:

[0056] detecting the presence of one or more genetic biomarkers in one or more of the following genes: NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A, or GNAS in a first biological sample obtained from the subject;

[0057] detecting the level of one or more of the following protein biomarkers: CA19-9, CEA, HGF, OPN, CA125, prolactin, TIMP-1, or MPO in a second biological sample obtained from the subject;

[0058] comparing the detected levels of the one or more protein biomarkers to one or more reference levels of the protein biomarkers; and

[0059] The presence of cancer in the subject is identified when the presence of one or more genetic biomarkers is detected, the detected level of the one or more protein biomarkers is above the reference level of the one or more protein biomarkers, or both.

[0060] 10. The method of embodiment 9, wherein the first biological sample, the second biological sample, or both comprise plasma.

[0061] 11. The method of embodiment 9, wherein the first biological sample and the second biological sample are the same.

[0062] 12. The method of embodiment 9, wherein the presence of one or more genetic biomarkers selected from the group consisting of NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A, and GNAS is detected.

[0063] 13. The method of embodiment 9, wherein the levels of CA19-9, CEA, HGF, OPN, CA125, prolactin, TIMP-1, and MPO are detected.

[0064] 14. The method of embodiment 9, wherein the presence of one or more genetic biomarkers of one or more of NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A, or GNAS is detected using a PCR-based multiplex sequencing assay comprising:

[0065] a. assigning a unique identifier (UID) to each of the plurality of template molecules present in the sample;

[0066] b. Amplifying each uniquely tagged template molecule to generate a UID family; and

[0067] c. performing redundant sequencing on the amplified products.

[0068] 15. The method of embodiment 9, wherein the cancer is liver cancer, ovarian cancer, esophageal cancer, gastric cancer, pancreatic cancer, colorectal cancer, lung cancer, breast cancer, or prostate cancer.

[0069] 16. The method of embodiment 9, wherein detecting the presence of one or more genetic biomarkers, detecting the level of one or more protein biomarkers, or both is performed without knowing that the subject carries cancer cells.

[0070] 17. The method of embodiment 9, wherein the subject is administered one or more of the following therapeutic interventions: surgery, adjuvant chemotherapy, neoadjuvant chemotherapy, radiotherapy, immunotherapy, targeted therapy, or an immune checkpoint inhibitor.

[0071] 18. A method for identifying the presence of cancer in a subject, comprising:

[0072] detecting the presence of one or more genetic biomarkers in one or more of the following genes: NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A, or GNAS in a first biological sample obtained from the subject;

[0073] detecting the level of one or more of the following protein biomarkers in a second biological sample obtained from the subject: CA19-9, CEA, HGF, OPN, CA125, AFP, prolactin, TIMP-1, follistatin, G-CSF, or CA15-3;

[0074] comparing the detected levels of the one or more protein biomarkers to one or more reference levels of the protein biomarkers; and

[0075] The presence of cancer in the subject is identified when the presence of one or more genetic biomarkers is detected, the detected level of the one or more protein biomarkers is above the reference level of the one or more protein biomarkers, or both.

[0076] 19. The method of embodiment 18, wherein the first biological sample, the second biological sample, or both comprise plasma.

[0077] 20. The method of embodiment 18, wherein the first biological sample and the second biological sample are the same.

[0078] 21. The method of embodiment 18, wherein the presence of one or more genetic biomarkers selected from the group consisting of NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A, and GNAS is detected.

[0079] 22. The method of embodiment 18, wherein the levels of CA19-9, CEA, HGF, OPN, CA125, AFP, prolactin, the TIMP follistatin, G-CSF, and CA15-3 are detected.

[0080] 23. The method of embodiment 18, wherein the presence of one or more genetic biomarkers of one or more of NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A, or GNAS is detected using a PCR-based multiplex sequencing assay comprising:

[0081] a. assigning a unique identifier (UID) to each of the plurality of template molecules present in the sample;

[0082] b. Amplifying each uniquely tagged template molecule to generate a UID family; and

[0083] c. performing redundant sequencing on the amplified products.

[0084] 24. The method of embodiment 18, wherein the cancer is liver cancer, ovarian cancer, esophageal cancer, gastric cancer, pancreatic cancer, colorectal cancer, lung cancer, breast cancer, or prostate cancer.

[0085] 25. The method of embodiment 18, wherein detecting the presence of one or more genetic biomarkers, detecting the level of one or more protein biomarkers, or both is performed without knowing that the subject carries cancer cells.

[0086] 26. The method of embodiment 18, wherein the subject is administered one or more of the following therapeutic interventions: surgery, adjuvant chemotherapy, neoadjuvant chemotherapy, radiotherapy, immunotherapy, targeted therapy, or an immune checkpoint inhibitor.

[0087] 27. A method for identifying the presence of cancer in a subject, comprising:

[0088] detecting the presence of one or more genetic biomarkers in one or more of the following genes: NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A, or GNAS in a first biological sample obtained from the subject;

[0089] detecting the level of one or more of the following protein biomarkers in a second biological sample obtained from the subject: CA19-9, CEA, HGF, OPN, CA125, AFP, prolactin, TIMP-1, or CA15-3;

[0090] comparing the detected levels of the one or more protein biomarkers to one or more reference levels of the protein biomarkers; and

[0091] The presence of cancer in the subject is identified when the presence of one or more genetic biomarkers is detected, the detected level of the one or more protein biomarkers is above the reference level of the one or more protein biomarkers, or both.

[0092] 28. The method of embodiment 27, wherein the first biological sample, the second biological sample, or both comprise plasma.

[0093] 29. The method of embodiment 27, wherein the first biological sample and the second biological sample are the same.

[0094] 30. The method of embodiment 27, wherein the presence of one or more genetic biomarkers selected from the group consisting of NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A, and GNAS is detected.

[0095] 31. The method of embodiment 27, wherein the levels of CA19-9, CEA, HGF, OPN, CA125, AFP, prolactin, TIMP-1, and CA15-3 are detected.

[0096] 32. The method of embodiment 27, wherein the presence of one or more genetic biomarkers of one or more of NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A, or GNAS is detected using a PCR-based multiplex sequencing assay comprising:

[0097] a. assigning a unique identifier (UID) to each of the plurality of template molecules present in the sample;

[0098] b. Amplifying each uniquely tagged template molecule to generate a UID family; and

[0099] c. performing redundant sequencing on the amplified products.

[0100] 33. The method of embodiment 27, wherein the cancer is liver cancer, ovarian cancer, esophageal cancer, gastric cancer, pancreatic cancer, colorectal cancer, lung cancer, breast cancer, or prostate cancer.

[0101] 34. The method of embodiment 27, wherein detecting the presence of one or more genetic biomarkers, detecting the level of one or more protein biomarkers, or both is performed without knowing that the subject carries cancer cells.

[0102] 35. The method of embodiment 27, wherein the subject is administered one or more of the following therapeutic interventions: surgery, adjuvant chemotherapy, neoadjuvant chemotherapy, radiotherapy, immunotherapy, targeted therapy, or an immune checkpoint inhibitor.

[0103] 36. A method for identifying bladder cancer or upper tract urothelial carcinoma in a subject, comprising:

[0104] detecting the presence of one or more genetic biomarkers in one or more of the following genes: TP53, PIK3CA, FGFR3, KRAS, ERBB2, CDKN2A, MLL, HRAS, MET, or VHL in a first biological sample obtained from the subject;

[0105] detecting the presence of at least one mutation in the TERT promoter in a second biological sample obtained from the subject; and

[0106] detecting the presence of aneuploidy in a third biological sample obtained from the subject; and

[0107] The presence of bladder cancer or upper tract urothelial cancer in the subject is identified when the presence of one or more genetic biomarkers is detected, the presence of the at least one mutation in the TERT promoter is detected, the presence of euploidy is detected, or a combination thereof.

[0108] 37. The method of embodiment 36, wherein:

[0109] The first biological sample and the second biological sample are identical;

[0110] The first biological sample and the third biological sample are identical;

[0111] The second biological sample and the third biological sample are the same; or

[0112] The first biological sample, the second biological sample, and the third biological sample are identical.

[0113] 38. The method of embodiment 37, wherein the first biological sample, the second biological sample, or the third biological sample is a urine sample.

[0114] 39. The method of embodiment 36, wherein the presence of aneuploidy is detected on one or more of chromosome arms 5q, 8q, or 9p.

[0115] 40. The method of embodiment 36, wherein the presence of one or more genetic biomarkers of: TP53, PIK3CA, FGFR3, KRAS, ERBB2, CDKN2A, MLL, HRAS, MET, and VHL is detected.

[0116] 41. The method of embodiment 36, wherein the presence of one or more genetic biomarkers of one or more of TP53, PIK3CA, FGFR3, KRAS, ERBB2, CDKN2A, MLL, HRAS, MET, or VHL is detected using a PCR-based multiplex sequencing assay comprising:

[0117] a. assigning a unique identifier (UID) to each of the plurality of template molecules present in the sample;

[0118] b. Amplifying each uniquely tagged template molecule to generate a UID family; and

[0119] c. performing redundant sequencing on the amplified products.

[0120] 42. The method of embodiment 36, wherein detecting the presence of one or more genetic biomarkers, detecting the presence of the at least one mutation in the TERT promoter, or detecting the presence of aneuploidy is performed without knowing that the subject carries cancer cells.

[0121] 43. The method of embodiment 36, wherein the subject is administered one or more of the following therapeutic interventions: surgery, adjuvant chemotherapy, neoadjuvant chemotherapy, radiotherapy, immunotherapy, targeted therapy, or an immune checkpoint inhibitor.

[0122] 44. A method for identifying the presence of ovarian cancer or endometrial cancer in a subject, comprising:

[0123] detecting the presence of one or more genetic biomarkers in one or more of the following genes: NRAS, PTEN, FGFR2, KRAS, POLE, AKT1, TP53, RNF43, PPP2R1A, MAPK1, CTNNB1, PIK3CA, FBXW7, PIK3R1, APC, EGFR, BRAF, or CDKN2A in a first biological sample obtained from the subject;

[0124] detecting the presence of aneuploidy in a second biological sample obtained from the subject; and

[0125] The presence of ovarian cancer or endometrial cancer in the subject is identified when the presence of one or more genetic biomarkers is detected, the presence of aneuploidy is detected, or both.

[0126] 45. The method of embodiment 44, wherein the first biological sample and the second biological sample are the same.

[0127] 46. The method of embodiment 45, wherein the first biological sample or the second biological sample is a cervical sample or an endometrial sample.

[0128] 47. The method of embodiment 44, wherein the presence of aneuploidy is detected on one or more of chromosome arms 4p, 7q, 8q, or 9q.

[0129] 48. The method of embodiment 44, wherein the presence of one or more genetic biomarkers selected from the group consisting of NRAS, PTEN, FGFR2, KRAS, POLE, AKT1, TP53, RNF43, PPP2R1A, MAPK1, CTNNB1, PIK3CA, FBXW7, PIK3R1, APC, EGFR, BRAF, and CDKN2A is detected.

[0130] 49. The method of embodiment 44, wherein the presence of one or more genetic biomarkers of one or more of: NRAS, PTEN, FGFR2, KRAS, POLE, AKT1, TP53, RNF43, PPP2R1A, MAPK1, CTNNB1, PIK3CA, FBXW7, PIK3R1, APC, EGFR, BRAF, or CDKN2A is detected using a PCR-based multiplex sequencing assay comprising:

[0131] a. assigning a unique identifier (UID) to each of the plurality of template molecules present in the sample;

[0132] b. Amplifying each uniquely tagged template molecule to generate a UID family; and

[0133] c. performing redundant sequencing on the amplified products.

[0134] 50. The method of embodiment 44, further comprising detecting the presence of at least one genetic biomarker in a circulating tumor DNA (ctDNA) sample obtained from the subject: AKT1, APC, BRAF, CDKN2A, CTNNB1, EGFR, FBXW7, FGFR2, GNAS, HRAS, KRAS, NRAS, PIK3CA, PPP2R1A, PTEN, or TP53.

[0135] 51. The method of embodiment 44, wherein detecting the presence of one or more genetic biomarkers or detecting the presence of aneuploidy is performed without knowing that the subject carries cancer cells.

[0136] 52. The method of embodiment 44, wherein the subject is administered one or more of the following therapeutic interventions: surgery, adjuvant chemotherapy, neoadjuvant chemotherapy, radiotherapy, immunotherapy, targeted therapy, or an immune checkpoint inhibitor.

[0137] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the invention belongs. Methods and materials for use in the present invention are described herein; other suitable methods and materials known in the art may also be used. The materials, methods, and examples are illustrative only and are not intended to be limiting. All publications, patent applications, patents, sequences, database entries, and other references mentioned herein are incorporated herein by reference in their entirety. In the event of a conflict, the present specification (including definitions) shall prevail. The titles used in the various sections of this article should not be construed as limiting the disclosure of the section to the subject matter of the title, nor should they be construed as limiting the disclosure of other sections to the subject matter outside the title. Such titles are exemplary and are included simply for ease of reading. Such titles are also not intended to limit the applicability or generality of the section to other parts of the disclosure.

[0138] Other features and advantages of the invention will be apparent from the following detailed description and drawings, and from the claims. BRIEF DESCRIPTION OF THE DRAWINGS

[0139] Figure 1 A schematic diagram is included showing the CancerSEEK test for detecting and localizing cancer.

[0140] Figure 2Contains a graph showing the development of a PCR-based assay for identifying tumor-specific mutations in plasma samples. The colored curves represent the proportion of eight types of cancer evaluated in this study that can be detected as the number of short (<40 bp) amplicons increases. The sensitivity of the assay increases with the number of amplicons but reaches a plateau at approximately 60 amplicons. The colored dots represent the fraction of cancers detected using the 61-amplicon panel in 805 cancers evaluated in our study, with an average of 82% (see text). Publicly available sequencing data were obtained from the Catalogue of Somatic Mutations in Cancer (COSMIC) database.

[0141] Figure 3 Included is a graph showing the distribution of the number of detectable mutations in the 805 primary tumors evaluated.

[0142] Figure 4 Included are graphs showing the performance of CancerSEEK. (A) Receiver Operating Characteristic (ROC) curve for CancerSEEK. The red dot on the curve represents the average performance (61%) tested at a specificity of >99%. The error bars represent the 95% confidence interval for the sensitivity and specificity at this particular point. As described in the text, the median performance was 70% across the 8 cancer types evaluated. (B) Sensitivity of CancerSEEK by stage. Error bars represent the standard error of the median. (C) Sensitivity of CancerSEEK by tumor type. Error bars represent the 95% confidence interval.

[0143] Figure 5 A waterfall plot of ctDNA and eight protein features used in CancerSEEK, illustrating the separation between healthy donors and healthy patients. Values are sorted from high (left) to low (right). Each column represents an individual patient sample (red, cancer patients; blue, healthy controls).

[0144] Figure 6 Contains a graph showing principal component analysis of ctDNA and eight protein features used in CancerSEEK. Each point represents an individual patient sample (red, cancer patients; blue, healthy controls).

[0145] Figure 7 Contains graphs showing the impact of individual CancerSEEK features on sensitivity. (A) Sensitivity of CancerSEEK by tumor type, as Figure 4 Same as in C. (BJ) Each panel shows the sensitivity achieved when a specific CancerSEEK feature is excluded from the logistic regression. The difference in sensitivity relative to the sensitivity achieved by CancerSEEK reflects the relative contribution of each biomarker to the performance of the CancerSEEK test.

[0146] Figure 8 Contains a graph showing the cancer type identification performed by supervised machine learning for patients classified as positive by CancerSEEK. The percentage corresponds to the proportion of patients correctly classified as one of the two most likely types (the sum of the light blue and dark blue bars) or the most likely type (the light blue bar). Table 6 provides predictions for all cancer types for all patients. Error bars represent 95% confidence intervals.

[0147] Figure 9 Figures are included showing that combining ctDNA KRAS mutations with protein biomarkers increases the sensitivity of early detection of PDAC. (A) Sensitivity of ctDNA KRAS mutations alone, ctDNA KRAS mutations plus CA19-9, and ctDNA KRAS mutations with CA19-9 and other proteins (combined assay) for AJCC stage. (B) Sensitivity of ctDNA KRAS mutations alone, ctDNA KRAS mutations plus CA19-9, and ctDNA KRAS mutations with CA19-9 and other proteins (combined assay) for tumor size. Error bars represent 95% confidence intervals.

[0148] Figure 10 Included is a graph showing the increased sensitivity of combining ctDNA and protein markers, as most patients were detected by only one marker. Number of patients detected by ctDNA KRAS mutations (red circles), CA19-9 (green circles), and three other protein biomarkers (blue circles), and their combination (overlapping area). Eighty patients (36% of the total) could not be detected by any of the three markers.

[0149] Figure 11 Contains a graph showing that the mutant allele frequencies (MAF) of KRAS and TP53 mutations are strongly correlated (Pearson r=0.885) in the plasma of 12 patients who contained detectable amounts of both mutations, providing validation of the reliability of the ctDNA assay and its quantitative properties. The shaded area represents the 95% confidence interval.

[0150] Figure 12 Included are Kaplan-Meier survival curves of the 221 PDAC patients included in this study stratified by AJCC stage (stage IA or IB: blue curve, stage IIA or IIB: red curve).

[0151] Figure 13Contains a graph showing the correlation between triple assay markers and tumor size. (A) The frequency of KRAS mutations was found to be higher in larger tumors than in smaller tumors, but the mutant allele frequency was not correlated with tumor size (Pearson r = 0.039). (B) In patients with elevated CA19-9, there was a weak correlation between CA19-9 plasma concentration and tumor size (Pearson r = 0.287). (CE) Plasma levels of CEA, HGF, and OPN were less dependent on tumor size than KRAS mutations or CA19-9 (CEA Pearson r = 0.153; HGF Pearson r = 0.037; OPN Pearson r = 0.018). The shaded area represents the 95% confidence interval.

[0152] Figure 14 Contains a graph showing that prolactin (G) and midkine (E) levels were significantly elevated in samples collected after anesthesia but before surgical resection. In contrast, no differences were observed in the proportion of samples with mutant KRAS ctDNA (A), CA19-9 plasma concentrations (B), CEA plasma concentrations (C), HGF plasma concentrations (D), and OPN plasma concentrations between samples collected before or after anesthesia. NS not significant, P>0.05 (exact permutation t-test).

[0153] Figure 15 Included is a graph showing the fold change in protein biomarker levels in 29 pairs of plasma samples collected before and immediately after the administration of anesthesia. Of the six markers evaluated, only prolactin and midkine were found to be elevated by anesthesia, fully consistent with the correlation between collection site and protein levels.

[0154] Figure 16 Kaplan-Meier survival curves stratified by independent predictors of overall survival identified by multivariate analysis: (A) combined assay status (HR = 1.76, 95% CI, 1.10-2.84, p = 0.018); (B) grade of differentiation (poorly differentiated, HR = 1.72, 95% CI 1.11-2.66, p = 0.015); (C) lymphovascular invasion (present, HR = 1.81, 95% CI 1.06-3.09, p = 0.028); (D) nodal disease (present, HR = 2.35, 95% CI 1.20-4.61, p = 0.013); (E) margin status (HR = 1.59, 95% CI 1.01-2.55, p = 0.050)

[0155] Figure 17Receiver operating characteristic (ROC) curves for (A) KRAS mutation, (B) CA19-9, (C) CEA, (D) HGF, (E) OPN, and (F) combined assays. (AE) ROC curves show the performance of each combined assay biomarker independently. The red dots on the curves represent the marker performance at the threshold used in the combined assay. Error bars represent the 95% confidence intervals for sensitivity and specificity at a specific threshold (red font). (D) ROC curves showing the performance of the combined assay when the KRAS threshold was varied and the CA19-9, CEA, HGF, and OPN thresholds were fixed at the levels used in the combined assay (black curve), the CA19-9 threshold was varied and the KRAS, CEA, HGF, and OPN thresholds were fixed at the levels used in the combined assay (red curve), the CEA threshold was varied and the KRAS, CA19-9, HGF, and OPN thresholds were fixed at the levels used in the combined assay (blue curve), the HGF threshold was varied and the KRAS, CA19-9, CEA, and OPN thresholds were fixed at the levels used in the combined assay (green curve), and the OPN threshold was varied and the KRAS, CA19-9, CEA, and HGF thresholds were fixed at the levels used in the combined assay (orange curve). The intersection of these three curves specifies the overall performance of the triple assay (64% sensitivity, 99.5% sensitivity).

[0156] Figure 18 The performance of the marker panel for identifying cancer in 8 cancer types is shown. (A) Numerical data. (B) Graphical data.

[0157] Figure 19 Schematic diagram of an exemplary PapSEEK test for detecting tumor DNA in a Pap brush, a Dow brush, and a plasma sample from a patient with endometrial or ovarian cancer. Tumor cells shed from ovarian or endometrial cancer are carried into the uterine cavity, where they can be collected by a Dow brush. Tumor cells that descend into the cervical canal can be captured by the Pap brush used in conventional Pap tests. These brushes are immersed in a liquid fixative, from which DNA is isolated and sequenced. The sequences are analyzed for somatic mutations and aneuploidy. In addition, tumor DNA shed into the bloodstream can be detected by ctDNA analysis.

[0158] Figure 20 Contains graphs showing detection of aneuploidy and somatic mutations (PapSEEK) in Pap brush (A) and Dow brush (B) samples from healthy controls and endometrial and ovarian cancer patients. Error bars represent 95% confidence intervals.

[0159] Figure 21Included are Venn diagrams showing that combined testing for somatic mutations and aneuploidy in Pap brush (A) and Dow brush (B) samples increases sensitivity for both ovarian and endometrial cancers. For ovarian cancer, combined testing of Pap brush and plasma samples also increases sensitivity compared to testing either sample type alone (C).

[0160] Figure 22 Contains graphs showing the detection of endometrial cancer (A) or ovarian cancer (B) by stage in Pap or Dow brush samples using PapSEEK. Error bars represent 95% confidence intervals.

[0161] Figure 23 Contains a graph showing the detection of ovarian cancer in Pap brush and plasma samples. Error bars represent 95% confidence intervals.

[0162] Figure 24 Contains graphs showing detection of endometrial and ovarian cancer using PapSEEK in Pap brushes, Dow brushes, and plasma samples. Error bars represent 95% confidence intervals.

[0163] Figure 25 Included is a schematic diagram of an exemplary method used to evaluate urine cells in this study.

[0164] Figure 26 A flow chart showing the number of patients in the early detection cohort and the surveillance cohort and data summary is included. Cytology was performed on a subset of patients.

[0165] Figure 27 Contains graphs showing the fraction of mutations found in a ten-gene panel of 231 urine cell samples evaluated in the early detection cohort (A) and 132 urine cell samples evaluated in the surveillance cohort (B).

[0166] Figure 28 Venn diagram containing the distribution of samples positive for each of the three assays according to the early detection cohort (A) and the surveillance cohort (B). URO = deca-genomic set, TERT = TERT promoter region, ANEU = aneuploidy test.

[0167] Figure 29 Bar graphs containing the lead time between a positive UroSEEK test and clinical-level disease detection in the early detection cohort (A) and the surveillance cohort (B).

[0168] Figure 30 Included are bar graphs showing the performance of cytology compared to UroSEEK in diagnosing low-grade and high-grade urothelial tumors in the early detection cohort and the surveillance cohort.

[0169] Figure 31Schematic diagram of an exemplary non-invasive test for upper tract urothelial carcinoma (UTUC) performed by genetic analysis of urine cell DNA. Upper tract tumors arise in the renal pelvis and / or ureters and come into direct contact with urine. Urine contains a mixture of normal cells constitutively shed from various parts of the urinary system, along with malignant cells (when present) (blue). The UroSEEK assay relies on mutational analysis of genes frequently mutated in urinary cancer and determination of chromosome loss and gain.

[0170] Figure 32 Included is a Venn diagram showing the distribution of positive results for each of the three UroSEEK assays.

[0171] Figure 33 Contains a graph showing a comparison of copy number changes in matched tumor and urine cell DNA samples from a UTUC cohort. The primary tumor is shown in the upper portion of each section, while the urine cell DNA is shown in the lower portion. Chromosome gains are blue, while losses are red. The significance level for gains and losses was set at a Z score of >3 and <-3, respectively. The x-axis is the chromosome arm. The y-axis is the Z score.

[0172] Figure 34 Contains a graph showing the fraction of total mutations in each gene in a 10-gene panel used to analyze urine cell DNA from UTUC patients.

[0173] Figure 35 Contains a graph showing comparison of copy number changes in matched tumor and urine cell DNA samples from four individual UTUC patients ( Figure 35 A-35D). Z scores >3 or <-3 were considered significant for chromosome gain or loss, respectively. NS indicates not significant. Data for all 56 patients are provided in Table 28.

[0174] Figure 36Contains a schematic diagram illustrating an overview of an exemplary WALDO method. (A) A single primer pair amplifies approximately 38,000 long interspersed nucleotide elements (LINEs). (B) The test sample is matched to seven euploid samples of genomic DNA of similar size. (C) The genome is divided into 4361 intervals, each 500-kb in size. (D) The reads within these 500-kb genomic intervals in the euploid sample are grouped into 4361 clusters. All 500-kb genomic intervals in the cluster have similar read depths. (E) The reads of each 500-kb genomic interval in the test sample are placed in a predefined cluster. (F) Statistical tests (including algorithms based on support vector machines (SVMs)) are used to determine whether the total reads of all 500-kb genomic intervals on each chromosome arm are distributed as expected when the sample is euploid. Statistical tests are based on the distribution of observed reads in the clusters of the test sample, rather than on comparisons with the reads in the euploid sample. (G) Germline sequence variants at sites with known common polymorphisms in LINEs provide information about arm-level allelic imbalance, which can also be used to assess aneuploidy in individual chromosome arms. These same polymorphisms can be used to determine whether any two samples originate from the same individual. (H) When a matched normal sample from the same individual is available, WALDO can detect the number and nature of single-base substitutions, as well as insertions and deletions, in LINEs.

[0175] Figure 37 Contains a graph showing gains and losses of individual chromosome arms identified in nine cancer types. The figure depicts the average fraction of tumors with gains or losses in each chromosome arm. The same nine tumor types were analyzed in both cohorts, but there was no overlap between the samples evaluated by WALDO (red) or GISTIC (blue). WALDO uses data from LINE sequencing of the tumors reported here, while GISTIC uses data from the Affymetrix SNP6.0 array provided by TCGA.

[0176] Figure 38 Figure 2 shows aneuploidy detected in cancer patient plasma samples. Receiver operating characteristics (ROC) and area under the curve (AUC) for three ranges of neoplastic cell fractions are shown. True positives are defined as those samples from cancer patients that scored positive, while false positives are defined as those samples from normal individuals that scored positive. As described in the text, the neoplastic cell fraction of each plasma sample was estimated based on driver gene sequencing data. (A) Samples with a neoplastic cell fraction <0.5%. (B) Samples with a neoplastic cell fraction of 0.5%-1%. (C) Samples with a neoplastic cell fraction >1%.

[0177] Figure 39 Contains graphs showing a comparison of aneuploidy correlations in cancers detected using FAST-SeqS and WALDO compared to The Cancer Genome Atlas (TCGA) using Affymetrix SNP 6.0 and GISTIC in nine different cancer types. (A) Correlation of the fraction of chromosome arms gained. (B) Correlation of the fraction of chromosome arms lost.

[0178] Figure 40 Contains a graph showing a comparison of aneuploidy for individual cancer types detected using the WALDO framework compared to The Cancer Genome Atlas (TCGA). For each cancer type, the fraction of gains and losses for each chromosome arm was compared. The correlation of these gains and losses from WALDO and TCGA was compared. Each subgraph represents a different cancer type. (A) Breast invasive carcinoma (BRCA). (B) Colon and rectal adenocarcinoma (COAD; COADREAD). (C) Esophageal cancer (ESCA). (D) Head and neck squamous cell carcinoma (HNSC). (E) Hepatocellular carcinoma (LIHC). (F) Pancreatic cancer (PAAD). (G) Ovarian serous cystadenocarcinoma (OV). (H) Gastric adenocarcinoma (STAD). (I) Uterine corpus endometrial carcinoma (UCEC).

[0179] Figure 41 Contains a graph showing trisomy 21 performance as a function of read depth. DNA samples from trisomy individuals were physically mixed with normal peripheral white blood cell (WBC) samples at a ratio of 2ng normal DNA and approximately 0.2ng trisomy 21 DNA. The mixture was generated to replicate the typical fetal fraction (approximately 10%) in noninvasive prenatal testing. Using polymorphisms in LINE-amplicons, the trisomy incorporation rate of the samples was estimated to be 7.7% to 10.4%. Using a z-threshold of 2.5, sensitivity (A) and specificity (B) were calculated for a range of read depths.

[0180] Figure 42 Included is a graph showing a comparison of the total number of somatic single base substitutions (SBS) detected in exome sequencing relative to WALDO.

[0181] Figure 43 Included is a graph showing a comparison of the percentage of single base substitution mutations detected as A:T>T:A mutations by exome sequencing relative to WALDO.

[0182] Figure 44Contains graphs showing the spectrum of single base substitution (SBS) mutations. (A) SBS identified by WALDO. (B) SBS identified by exome sequencing.

[0183] Figure 45 Contains a graph showing the distribution of the number of genomic intervals included in the clusters of representative normal WBC samples.

[0184] Figure 46 Contains graphs showing the distribution of scaled read lengths. (A) Distribution of scaled read lengths, showing that read lengths in FAST-SeqS amplicon sequencing are not randomly distributed. (B) Clusters of representative normal WBC samples, showing the normality of scaled read lengths within the cluster. (C) Clusters of representative aneuploid primary tumor samples, showing the normality of scaled read lengths within the cluster.

[0185] Figure 47 Contains a figure showing an example of a statistical procedure for identifying chromosome arm gains or losses.

[0186] Figure 48 Contains a plot showing the empirical estimate of the variance of the B allele frequency for heterozygous SNPs as a function of read depth. Increasing UID depth improves the estimate of the B allele frequency for heterozygous SNPs.

[0187] Figure 49 Example pseudo code for generating a composite with one arm change is shown.

[0188] Figure 50 Example pseudocode for generating a composite with multiple arm changes is shown.

[0189] Figure 5 l contains a plot showing the distribution of genome-wide aneuploidy scores (SVM scores) as a function of read depth. Lower read depths are more likely to produce higher scores, and failure to correct for UID depth can result in false positives.

[0190] Figure 52Contains a diagram showing an exemplary overview of the bottleneck sequencing method. Each color in the upper portion of the figure represents the double-stranded DNA of the genome of one cell in the population. Random non-clonal point mutations (red) are exclusive to individual cells. In contrast, clonal reference changes (black A) are present in all genomes within the cell population. (Step 1) Random shearing produces DNA molecules of variable size. (Step 2) The non-complementary single-stranded regions of the Illumina Y adapter (gray P5 and black P7) are represented as fork-like structures connected to both ends of each DNA molecule. (Step 3) Dilution reduces the number of DNA molecules in the original population in a random manner (shown as five). The ends of the DNA molecules are uniquely aligned with the reference genome. During data processing, the mapping coordinates are used as unique molecular "barcodes". (Step 4) PCR primers (black arrows) anneal and the primers independently extend (dashed line) the Watson and Crick templates of the original DNA molecules. Red asterisks represent errors generated during PCR of the library. (Step 5) The Watson and Crick templates generate two families of PCR replicas. The orientation of the adapter-containing P5 (grey) and P7 (black) relative to the DNA molecule (insert) distinguishes the two families. The P5 and P7 sequences determine which end is sequenced on the Illumina flow cell with read length 1 and read length 2, respectively. Red asterisks represent PCR errors that propagate in members of the Watson but not Crick family. True mutations (red C:G mutations) will be present in both Watson and Crick family members, compared to artifacts. (Step 6) The BotSeqS pipeline identifies and quantifies the number of unique DNA molecules and point mutations (red C:G) in the sequencing data by eliminating artifacts and clonal variations (black A:T).

[0191] Figure 53 Contains graphs showing increased nuclear point mutations in normal tissues from individuals with DNA repair defects or exposed to environmental carcinogens compared to controls. (A) In individuals with different DNA mismatch repair genotypes (PMS2 + / + or PMS2 - / -Comparison of the prevalence of point mutations in the nuclear genome (left) and mitochondrial genome (right) in age-matched normal colon epithelium (filled circles) or in age-matched normal renal cortex (filled squares) without (none) or with (aristolochic acid or smoking) carcinogen exposure. Red lines represent the mean. *P < 0.05, t-test; **P < 0.001 and ***P < 0.0001, one-way ANOVA with Bonferroni multiple comparison post-test; ns, not significant, indicating P > 0.05. (B) Stacked columns representing the substitution frequency (y-axis) of each of the six possible types (see legend). Cohort labels are shown in A directly above each column. The number of substitutions (N) that generated each mutation spectrum is shown on the x-axis. nd, not determined due to insufficient number of mutations for mutation spectrum analysis (N = 7). *P = 0.04, Fisher's exact test; **P = 2.6 × 10 -8 And ***P=1.5×10 -16 , Fisher's exact test with Bonferroni correction for multiple comparisons; ns, not significant, indicates P > 0.05. All statistical tests in this figure were two-tailed.

[0192] Figure 54 Contains a diagram showing that normal human tissue accumulates point mutations in genome-specific and tissue-specific mutation patterns throughout life. The point mutation prevalence in the nuclear genome (top) and mitochondrial genome (bottom) was measured in four normal tissue types (9 individual frontal cortexes, 5 individual renal cortexes, 11 individual colon epithelium, and 1 individual duodenum). A total of 26 individuals were assessed, each contributing a normal tissue type. The pie chart illustration shows the prevalence of each substitution among six possible substitution types (see the pie chart legend on the right). Each pie chart is compiled based on the individual represented in its respective scatter plot, but the duodenum is omitted. The number of substitutions that generated the pie chart, for the nuclear genome, n=31 for the brain, n=73 for the kidney, and n=94 for the colon, and for the mitochondrial genome, n=181 for the brain, n=299 for the kidney, and n=116 for the colon.

[0193] Figure 55 Includes MiSeq TM Evaluation of replicate counts performed in a pre-run. A histogram showing the distribution of family members (PCR replicates from individual template molecules, shown on the x-axis). TMTwo or three serial dilutions (103, 104, 105, or 106) were evaluated for six samples (COL373, SA_117, KID038, BRA01, BRA04, BRA07) to generate approximately 5M correctly paired reads per library. Family member counts were determined here using Picard's Estimate Library Complexity program. The library generated from the 105 dilution (blue) was then used for the final HiSeq sequence reported in this study. TM It should be noted that with MiSeq TM Compared to the distribution, HiSeq TM The distribution is expected to be shifted to the right. For example, the BotSeqS library from the 106 dilution (red) was not used because the members of each family are TM The number of different families that can be assessed in a given run will be too high, thus limiting the number of different families that can be assessed with a given amount of sequencing.

[0194] Figure 56 Contains a graph showing family member counts for the 44 BotSeqS libraries reported in this study. Horizontal box and whisker plot of the 44 BotSeqS libraries (y-axis) versus the number of members per family (replicate count, x-axis). The white boxes represent the first to third interquartile range, with the hash mark indicating the median. The whiskers represent 1.5*IQR (interquartile range), and data points outside the whiskers are shown as outliers. The average of 3.97M (range 0.38 to 10.91M) unfiltered families was assessed for each library. Families were identified using the BotSeqS pipeline using genomic mapping coordinates as unique molecular identifiers. Blue names indicate technical replicates. It should be noted that Bot01-Bot06 and Bot23-28 were performed on the same sample with a 100-fold difference in dilution (see Table 43).

[0195] Figure 57Included are graphs illustrating the reduction of artifacts, particularly G>T transversions, by considering both Watson and Crick family members. (A) Nuclear point mutation frequency (y-axis), considering mutations observed in "Watson and / or Crick" (black circles) or "Watson and Crick" families (black squares) in normal tissue derived from the frontal cortex of the brain (left), renal cortex (center, shaded), or colon epithelium (right). Specifically, "OR" mutations represent a mutation fraction ≥90% in Watson families with at least two Watson reads, or a mutation fraction ≥90% in Crick families with at least two Crick reads. Note that "OR" mutations only have either Watson or Crick families represented in the data, but not both. "AND" mutations represent a mutation fraction ≥90% in Watson families with at least two Watson reads, and a mutation fraction ≥90% in Crick families with at least two Crick reads. "AND" mutations are an internal subset of the "AND / OR" dataset, which is a modified version of the BotSeqS pipeline. 25 individuals were organized by increasing age within each tissue. (B) Pie charts showing the frequency of each nuclear substitution from (a) among the six possible substitution types (see legend) for Watson and / or Crick (upper pie chart) or Watson and Crick (lower pie chart) in each normal tissue type. The number of nuclear mutations that generated the mutation spectrum was n = 616 for brain, n = 1,257 for kidney, and n = 2,542 for colon for Watson and / or Crick, and n = 33 for brain, n = 74 for kidney, and n = 99 for colon for Watson and Crick.

[0196] Figure 58 Contains a graph showing that rare point mutations accumulate more in normal tissues of the colon than in the brain. Frequency of point mutations (y-axis) in the nuclear genome (top) and mitochondrial genome (bottom) in normal brain frontal cortex (left) and normal colon epithelium (right) grouped by age (infants are green, young adults are purple, and elderly are blue). Mean values for each age cohort are shown, with error bars representing standard deviations. GraphPad Prism was used. TMTwo-way ANOVA with Bonferroni's multiple comparison post-hoc test was performed using 5.0f software, with P values reported above the bars. ns (not significant) indicates P > 0.05. For the brain, the number of subjects and mean age of the groups were as follows: infants: n = 3 subjects, 3.5 years (y / o) (BRA01, BRA02, BRA03); young adults: n = 3 subjects, 22 y / o (BRA04, BRA05, BRA06); and elderly adults: n = 3 subjects, 93 y / o (BRA07, BRA08, BRA09). For colon, infants: n=2 individuals, 5.5 y / o (COL229, COL231); young adults: n=6 individuals, 28 (COL235, COL236, COL237, COL373, COL374, COL375); elderly: n=3 individuals, 96 y / o (COL232, COL233, COL234).

[0197] Figure 59 Figure 50 shows the frequency of mitochondrial point mutations and nuclear point mutations in the normal tissue of the same individual. The data points represent the ratio (y-axis) between the frequency of mitochondrial point mutations and nuclear point mutations in the normal tissue of the same individual. The individuals are grouped into four queues (x-axis), wherein n=24 individuals are used for control (see Table 51), n=2 individuals (COL238, COL239) are used for DNA repair defect PMS2- / -, n=3 individuals (AA_105, AA_124, AA_126) are used for aristolochic acid exposure, and n=3 individuals (SA_117, SA_118, SA_119) are used for smoking exposure. A ratio (COL229) in the control queue is zero and is omitted from this analysis. The average (red line) ratio of each queue is 24.5 for control, 0.5 for DNA repair defect PMS2- / -, 1.1 for aristolochic acid exposure, and 2.0 for smoking exposure. *P<0.05, **P<0.01, one-way ANOVA with Bonferroni multiple comparison post-test.

[0198] Figure 60 Contains graphs showing that normal tissues and tumors derived from the same tissue type have similar mutational profiles. (A) Pie chart comparing the nuclear and mitochondrial frequencies of each of the six possible substitution types (see legend) in normal tissue (left) and tumors (right) derived from colon (top) and kidney (bottom). "Normal" represents normal tissue derived from Figure 54Rare mutation profile data for normal tissues are shown. "Nuclear tumor mutations" represent clonal mutation data from colorectal cancer (COAD / READ) or clear cell renal carcinoma (KIRC) from the TCGA dataset #!Synapse:syn1729383 on the synapse.org website. "mtDNA tumor mutations" from colon and kidney were obtained from the "colorectal" and "kidney" tumor types in Supplementary File 2 of Ju et al. (2014 eLife 3). For normal tissues, the number of substitutions assessed was as follows: colon nuclear n = 94, from 13 individuals; colon mtDNA n = 116, from 12 individuals; kidney nuclear n = 73, from 7 individuals; and kidney mtDNA n = 299, from 5 individuals. For tumor tissues, the number of substitutions assessed was as follows: colorectal cancer nuclei n = 18,538, from 193 individuals; colorectal cancer mtDNA n = 64, from 76 individuals; clear cell renal cell carcinoma nuclei n = 24,559, from 417 individuals; and renal cancer mtDNA n = 16, from 23 individuals. (B) Principal component analysis (PCA) of the mutational profiles from the cohort shown in (A). PCA was performed and plotted using R software.

[0199] Figure 61 Included is a schematic diagram showing the elements of Safe-SeqS. In the first step, each fragment to be analyzed is assigned a unique identifier (UID) sequence (a bar with metallic shading or dots). In the second step, the uniquely tagged fragments are amplified, thereby generating UID families, each member of which has the same UID. A supermutant is defined as a UID family in which >95% of the family members have the same mutation.

[0200] Figure 62 Contains a schematic diagram showing an exemplary Safe-SeqS with endogenous UID plus capture. The sequence at the end of each fragment generated by random shearing (bars with different shading) serves as a unique identifier (UID). The fragments are ligated to adapters (bars with earth-shaded and cross-hatched lines) so that they can then be amplified by PCR. One uniquely identifiable fragment is generated from each strand of the double-stranded template; only one strand is shown. The fragment of interest is captured on a solid phase containing oligonucleotides complementary to the sequence of interest. After PCR amplification with primers containing 5' "graft" sequences (bars filled with adhesive and with light dots) to generate UID families, sequencing is performed, and super mutants such as Figure 61 defined.

[0201] Figure 63A schematic diagram of an exemplary Safe-SeqS using exogenous UIDs is included. DNA (clipped or unclipped) is amplified using a set of gene-specific primers. One of the primers has a random DNA sequence (e.g., a set of 14N sequences) located 5' to its gene-specific sequence that forms a unique identifier (UID; bars with different shading), and both primers have sequences that allow for universal amplification in the next step (bars with earth-tone shading and cross-hatching). As shown, two UID assignment cycles produce two fragments from each double-stranded template molecule, each with a different UID. PCR is then performed with universal primers (bars filled with adhesive and with light dots) that also contain the "graft" sequence to generate families of UIDs that are directly sequenced. Super mutants such as Figure 61 As defined in the legend.

[0202] Figure 64 Contains figures showing single-base substitutions identified by conventional and Safe-SeqS analysis. Figure 63 The exogenous UID strategy depicted in was used to generate PCR fragments from the CTNNB1 gene of three normal, unrelated individuals. Each position represents one of 87 possible single-base substitutions (3 possible substitutions / base x 29 bases analyzed). These fragments were sequenced on an Illumina GA IIx instrument and analyzed in a conventional manner (A) or using Safe-SeqS (B). Safe-SeqS results are shown on the same scale as conventional analysis for direct comparison; the inset is an enlarged view. It should be noted that most variants identified by conventional analysis are likely to represent sequencing errors, as shown by their high frequency relative to Safe-SeqS and their consistency in unrelated samples.

[0203] Figure 65 Included is a schematic diagram showing an exemplary Safe-SeqS with endogenous UIDs plus inverse PCR. The sequence at the end of each fragment generated by random shearing serves as a unique identifier (UID; bars with different shading). The fragments are ligated to adapters (bars with earth-shaded and cross-hatched lines) as in standard Illumina library preparation. A uniquely tagged fragment is generated from each strand of the double-stranded template; only one strand is shown. After circularization with ligase, inverse PCR is performed with gene-specific primers that also contain a 5′ “graft” sequence (bars filled with adhesive and with light dots). This PCR generates families of UIDs that are directly sequenced. Supermutants such as Figure 61 defined.

[0204] Figure 66Contains a graph showing the position of single base substitutions relative to the frequency of errors in oligonucleotides synthesized with phosphoramidites and Phusion. Representative portions of the same 31-base DNA fragment synthesized by phosphoramidite (A) or Phusion polymerase (B) were analyzed by Safe-SeqS. The mean and standard deviation of seven independent experiments of each type are plotted. An average of 1,721 ± 383 and 196 ± 143 SBS supermutants were identified in the phosphoramidite-synthesized fragments and Phusion-generated fragments, respectively. The y-axis represents the proportion of total errors at the indicated position. It should be noted that the errors in the phosphoramidite-synthesized DNA fragments were consistent between the seven replicates, as would be expected if errors were systematically introduced during the synthesis itself. In contrast, the errors in the Phusion-generated fragments appeared to be heterogeneous between samples, as would be expected from a random process (Luria and Delbruck, 1943 Genetics 28: 491-511).

[0205] Figure 67 Contains a plot showing the distribution of UID family members. Figure 63 The exogenous UID strategy depicted was used to generate PCR fragments from the CTNNB1 region of three normal, unrelated individuals (Table 53); a representative example of a UID family with ≤300 members (99% of the total UID family) generated from one individual is shown. The y-axis represents the number of different UID families containing the number of family members shown on the x-axis.

[0206] Figure 68 contains an exemplary random forest model tree for tumor location classification. (A) shows the complete tree, and (B)-(K) contain magnified images of portions of the complete tree shown in (A).

[0207] Figure 69Comprise the exemplary rule of tissue identification extracted from random forest model.The randomForest function from randomForest software package (v4.6-14) is applied to the protein data from CancerSEEK project.Protein data has 33 kinds of proteins and is correctly predicted as 626 tumor samples of cancer by CancerSEEK.If the value of every kind of protein is less than the value of the 25th quantile in normal sample, then they are set to zero.In order to obtain specific decision rule (table 58), all 500 trees that inTrees software package (v1.2) is used to extract all rules that are less than or equal to 6 in length from randomForest creation.Use the function (selectRuleRRF, buildLearner, applyLearner) in inTrees software package to select relevant and non-redundant rule from this group of rules, create classifier, apply it to data, and extract final rule list.The execution of this final rule list is similar to complete random forest, and represents the good approximation with complete forest. DETAILED DESCRIPTION

[0208] definition

[0209] As used herein, the word "a" preceding a noun represents one or more of the particular noun. For example, the phrase "a genetic alteration" encompasses "one or more genetic alterations."

[0210] As used herein, the term "about" means approximately, within the range of, roughly, or around. When used in conjunction with a numerical range, the term "about" modifies the range by extending the boundaries above and below the listed values. Generally speaking, the term "about" is used herein to modify a numerical value to a deviation of 10% above and below the stated value.

[0211] As used herein, the term "aneuploidy" refers to the condition of having less than or more than the natural diploid number of chromosomes or any deviation from euploidy.

[0212] As used herein in the context of circulating tumor DNA or cell-free DNA, the phrase "derived from a gene" means that the circulating tumor DNA is shed from tumor cells (e.g., tumor cells that have lysed or otherwise died). For example, circulating tumor DNA "derived from the KRAS gene" means that the circulating tumor DNA was originally present in tumor cells. When detecting mutations present in circulating tumor DNA derived from a gene, it is not necessary to first identify the mutations in the tumor cells themselves.

[0213] As used herein, the phrases "genetic biomarker" and "genetic marker" refer to nucleic acids that are characteristic of a subject's cancer, alone or in combination with other genetic markers or other biomarkers. Genetic biomarkers can include modifications (e.g., mutations) in a gene. Examples of modifications include, but are not limited to, single base substitutions, insertions, deletions, insertions / deletions, translocations, and copy number variations. In some embodiments, genetic biomarkers include modifications (e.g., inactivating modifications) in tumor suppressor genes. In some embodiments, genetic biomarkers include modifications (e.g., activating modifications) in oncogenes. Individual genetic biomarkers and sets of genetic biomarkers are described in more detail herein.

[0214] As used herein, the terms "mutation," "genetic modification," and "genetic alteration" are used interchangeably to indicate a change in a wild-type nucleic acid sequence. For example, in some embodiments, methods are described herein for detecting mutations in cell-free DNA (e.g., ctDNA). It should be understood that such methods can be interchangeably described as detecting mutations, genetic modifications, or genetic alterations.

[0215] As used herein, the phrases "protein biomarker," "protein marker," "peptide biomarker," and "peptide marker" refer to proteins that are characteristic of a subject's cancer, alone or in combination with other proteins or other biomarkers. In some embodiments, a protein biomarker comprises elevated levels of a protein in a subject (e.g., a subject with cancer, regardless of whether the subject is known to have cancer) compared to a reference subject without cancer. In some embodiments, a protein biomarker comprises decreased levels of a protein in a subject (e.g., a subject with cancer, regardless of whether the subject is known to have cancer) compared to a reference subject without cancer. As used herein, the phrase "detecting a protein biomarker" can refer to detecting the level (e.g., increased level or decreased level) of a protein biomarker. Individual protein biomarkers and protein biomarker panels are described in more detail herein. In some embodiments, peptides other than protein biomarkers are used in the methods provided herein.

[0216] As used herein with respect to protein biomarkers, the phrase "elevated level" refers to a level of a protein biomarker that is greater than a reference level of a protein biomarker typically observed in a sample (e.g., a reference sample) from a healthy subject (e.g., a subject that does not exhibit a particular disease or condition). In some embodiments, the reference sample can be a sample obtained from a subject without cancer (e.g., a different subject or a reference subject). For example, for a protein biomarker associated with colorectal cancer, the reference sample can be a sample obtained from a different subject or a reference subject without colorectal cancer. In some embodiments, the reference sample can be a sample obtained from the same subject in which an elevated level of the protein biomarker is observed, wherein the reference sample is obtained before the onset of cancer. In some embodiments, such a reference sample obtained from the same subject is frozen or otherwise preserved for future use as a reference sample. In some embodiments, when a reference sample has an undetectable level of a protein biomarker, the elevated level can be any detectable level of the protein biomarker. It should be understood that when determining whether a particular level is an elevated level, the level from a comparable sample can be used.

[0217] As used herein with respect to protein biomarkers, the phrase "reference level" refers to the level of a protein biomarker that is typically present in a healthy subject (e.g., a subject that does not exhibit a particular disease or condition). The reference level of a protein biomarker can be the level present in a reference subject that does not exhibit a disease or condition (e.g., cancer). For example, for a protein biomarker associated with colorectal cancer, the reference sample can be a sample obtained from a subject that does not have colorectal cancer. As another example, the reference level of a protein biomarker can be the level present in the subject before the onset of the disease or condition (e.g., cancer) in the subject. In some embodiments, a disease or condition can be identified in a subject when the measured or detected level of one or more protein biomarkers is higher than the reference level of the one or more protein biomarkers.

[0218] As used herein, the term "sensitivity" refers to the ability of a method to correctly identify or diagnose the presence of a disease in a subject (e.g., the sensitivity of a method can be described as the ability of the method to identify a true positive rate or the probability of detecting a condition in a subject). For example, when used with respect to any of the various methods described herein that can detect the presence of cancer in a subject, high sensitivity means that the method correctly identifies the presence of cancer in the subject most of the time. For example, a method described herein that correctly detects the presence of cancer in a subject 95% of the time when the method is performed is said to have a sensitivity of 95%. In some embodiments, the method described herein that can detect the presence of cancer in a subject provides a sensitivity of at least 80% (e.g., at least 80%, 85%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%, 99.5% or more). In some embodiments, the methods provided herein that include detecting the presence of one or more members of two or more classes of biomarkers (e.g., genetic biomarkers and / or protein biomarkers) provide greater sensitivity compared to methods that include detecting one or more members of only one class of biomarkers.

[0219] As used herein, the term "specificity" refers to the ability of a method to correctly refute the presence of a disease in a subject (e.g., the specificity of a method can be described as the method's ability to identify a true negative rate or the probability of correctly determining the absence of a condition in a subject. For example, when used with respect to any of the various methods described herein that can detect the presence of cancer in a subject, high specificity means that the method correctly identifies the absence of cancer in the subject most of the time (e.g., the method does not falsely identify the absence of cancer in the subject most of the time). For example, a method described herein that correctly detects the absence of cancer in a subject 95% of the time is referred to as With 95% specificity. In some embodiments, the methods described herein that can detect the absence of cancer in a subject provide a specificity of at least 80% (e.g., at least 80%, 85%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%, 99.5% or more). In some embodiments, the methods provided herein that include detecting the presence of one or more members of two or more classes of biomarkers (e.g., genetic biomarkers and / or protein biomarkers) provide greater specificity than methods that include detecting one or more members of only one class of biomarkers.

[0220] As used herein, the term "subject" is used interchangeably with the term "patient" and refers to vertebrates including any member of the class Mammalian, including humans, domestic and farm animals, and zoo, competitive, or pet animals, such as mice, rabbits, pigs, sheep, goats, cattle, horses (e.g., racehorses), and higher primates. In some embodiments, the subject is a human. In some embodiments, the subject suffers from a disease. In some embodiments, the subject suffers from cancer. In some embodiments, the subject is a person carrying cancer cells. In some embodiments, the subject is a person carrying cancer cells but not knowing that they carry cancer cells. In some embodiments, the subject suffers from a viral disease. In some embodiments, the subject suffers from a bacterial disease. In some embodiments, the subject suffers from a fungal disease. In some embodiments, the subject suffers from a parasitic disease. In some embodiments, the subject suffers from asthma. In some embodiments, the subject suffers from an autoimmune disease. In some embodiments, the subject suffers from graft-versus-host disease.

[0221] As used herein, the term "treatment" is used interchangeably with the phrase "therapeutic intervention."

[0222] Methods of testing DNA isolated or obtained from leukocytes (e.g., leukocyte clones arising during age-associated clonal hematopoiesis (e.g., clonal hematopoiesis of indeterminate potential or CHIP) or myelodysplasia) for the presence of genetic mutations associated with cancer in order to determine whether the genetic alterations originated from cancer cells in a subject are collectively referred to herein as "validating genetic alterations on leukocytes," "validating genetic alterations on DNA from leukocytes," "leukocyte validation," and similar phrases.

[0223] Overview

[0224] Generally speaking, provided herein is the method and material for detecting or identifying the existence of cancer in a subject with high sensitivity and specificity compared to the conventional method for identifying the existence of cancer in a subject. In some embodiments, the liquid sample (such as blood, blood plasma or serum) obtained from the subject is performed provided herein for the method for identifying the existence of cancer in the subject with high sensitivity and specificity, and the conventional method for identifying the existence of cancer in the subject can not reach sensitivity level, specificity level or both when the liquid sample obtained from the subject is performed. In some embodiments, provided herein is the method for identifying the existence of cancer in a subject with high sensitivity and specificity before determining that the subject has suffered from cancer, before determining that the subject carries cancer cells and / or before the subject shows the symptom associated with cancer. Therefore, in some embodiments, provided herein is the method for identifying the existence of cancer in a subject with high sensitivity and specificity and is used as a first line detection method, rather than simply being used as the confirmation (for example, " overestimation ") of another detection method that the subject suffers from cancer.

[0225] In some embodiments, provided herein are methods and materials that provide high sensitivity (e.g., correctly identifying a subject with a high frequency or incidence of cancer) in the detection or diagnosis of cancer. In some embodiments, provided herein are methods and materials that provide at least about 10%, at least about 15%, at least about 20%, at least about 25%, at least about 30%, at least about 35%, at least about 40%, at least about 45%, at least about 50%, at least about 55%, at least about 60%, at least about 65%, at least about 70%, at least about 75%, at least about 80%, at least about 85%, at least about 90%, at least about 91%, at least about 92%, at least about 93%, at least about 94%, at least about 95%, at least about 96%, at least about 97%, at least about 98%, at least about 99% or higher sensitivity. In some embodiments, provided herein are methods and materials that provide high sensitivity when detecting a single type of cancer. In some embodiments, provided herein are methods and materials that provide high sensitivity when detecting two or more types of cancer. Any of the various cancer types can be detected using the methods and materials provided herein (see, for example, the section entitled "Cancer"). In some embodiments, the cancer that can be detected using the methods and materials provided herein includes pancreatic cancer. In some embodiments, the cancer that can be detected using the methods and materials provided herein includes liver cancer, ovarian cancer, esophageal cancer, gastric cancer, pancreatic cancer, colorectal cancer, lung cancer, or breast cancer. In some embodiments, the cancer that can be detected using the methods and materials provided herein includes cancer of the female reproductive tract (e.g., cervical cancer, endometrial cancer, ovarian cancer, or fallopian tube cancer). In some embodiments, the cancer that can be detected using the methods and materials provided herein includes bladder cancer or upper urinary tract urothelial carcinoma.

[0226] In some embodiments, provided herein are methods and materials that provide high specificity (for example, when a subject does not have cancer, mistakenly identify that the subject suffers from a low frequency or incidence of cancer) in the detection or diagnosis of cancer. In some embodiments, provided herein are methods and materials that provide at least about 10%, at least about 15%, at least about 20%, at least about 25%, at least about 30%, at least about 35%, at least about 40%, at least about 45%, at least about 50%, at least about 55%, at least about 60%, at least about 65%, at least about 70%, at least about 75%, at least about 80%, at least about 85%, at least about 90%, at least about 91%, at least about 92%, at least about 93%, at least about 94%, at least about 95%, at least about 96%, at least about 97%, at least about 98%, at least about 99% or higher specificity. As will be understood by those of ordinary skill in the art, 99% specificity means that only 1% of subjects without cancer are mistakenly identified as suffering from cancer. In some embodiments, the methods and materials provided herein provide high specificity when detecting a single cancer (e.g., a very low probability of falsely identifying that the subject has the single cancer type). In some embodiments, the methods and materials provided herein provide high specificity when detecting two or more cancers (e.g., a very low probability of falsely identifying that the subject has the two or more cancer types).

[0227] As will be understood by those of ordinary skill in the art, it is possible to select suitable sensitivity or specificity in the detection or diagnosis of cancer based on various factors.As a non-limiting example, the method designed to provide lower specificity in the detection or diagnosis of cancer can be designed to have increased sensitivity.As another non-limiting example, the method designed to provide higher specificity in the detection or diagnosis of cancer can be designed to have lower sensitivity.In some embodiments, even low sensitivity can also be advantageous (for example, when screening a normally unscreened colony).In some embodiments, in the popular colony of cancer (for example, a particular type of cancer), even at the expense of the specificity of reduction, the method for detecting or diagnosing the existence of cancer can also be designed to have relatively high sensitivity.In some embodiments, the sensitivity and specificity of the various detection methods provided herein are determined based on the morbidity of the disease in a particular patient colony.For example, for not knowing that the screening test for the general patient colony suffering from cancer can be selected to have high specificity (to eliminate false positive diagnosis and unnecessary further diagnostic tests and / or monitoring). As another example, a cancer screening test for a high-risk population (e.g., a population in which the risk of developing or developing cancer is higher than the overall general population, for example because the population engages in or has engaged in risky behaviors, has a family history of risk, experiences or has been in a risky environment, etc.) can be selected to have a high sensitivity (in order to increase the certainty of detecting the presence of cancer, even at the expense of additional further diagnostic testing and / or monitoring, which may not be appropriate for the general population). As a non-limiting example, in a population with a prevalence of 0.01%, a test with 90% sensitivity and 95% specificity will have a positive predictive value (PPV) of 15% and a negative predictive value (NPV) of >99%, while if the prevalence is 40% (a high-risk population), both predictive values can be greater than 99%. PPV can be calculated as follows: # true positives (TP) / (# true positives + # false positives). PPV can also be calculated as follows: (sensitivity X prevalence) / (sensitivity X prevalence) + ((1-specificity) x (1-prevalence)). NPV can be calculated as follows: # true negatives / # number of negative identifications. PPV can also be calculated as follows: Specificity X (1-Prevalence) / ((1-Sensitivity) x Prevalence) + (Specificity X (1-Prevalence). See, e.g., Lalkhen and McCluskey, Clinical tests: sensitivity and specificity, Continuing Education in Anaesthesia, Critical Care & Pain, Vol. 8, 2008, which is herein incorporated by reference in its entirety.

[0228] Detection method

[0229] Provided herein are methods and materials for detecting the presence of one or more members (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 or more members) of one or more classes of biomarkers in a sample obtained from a subject and / or the presence of aneuploidy. In some embodiments, the presence of one or more members of one or more classes of biomarkers and / or the presence of aneuploidy are tested simultaneously (e.g., in a testing procedure, including embodiments in which the testing procedure itself may include multiple discrete testing methods or systems). In some embodiments, the presence of one or more members of one or more classes of biomarkers and / or the presence of aneuploidy are tested sequentially (e.g., in two or more different testing procedures performed at two or more different time points, including embodiments in which the testing procedure itself may include multiple discrete testing methods or systems). In some embodiments of simultaneously testing and sequentially testing for the presence of one or more members of one or more classes of biomarkers and / or the presence of aneuploidy, the testing can be performed on a single sample, or can be performed on two or more different samples (e.g., two or more different samples obtained from the same subject).

[0230] Any of the various detection methods described herein (see, for example, the sections entitled “Detection of Genetic Biomarkers,” “Detection of Protein Biomarkers,” and “Detection of Aneuploidy”) can be used to detect the presence of one or more members of one or more classes of biomarkers and / or the presence of aneuploidy in a sample obtained from a subject. In some embodiments, one or more members of one or more classes of biomarkers and / or one or more classes of biomarkers are associated with a disease in a subject. In some embodiments, aneuploidy is associated with a disease in a subject. In some embodiments, the disease is cancer (e.g., any of the various types of cancer described herein). In some embodiments, the one or more members are members of a class of genetic biomarkers. In some embodiments, the one or more members are members of a class of protein biomarkers. In some embodiments, a method comprising detecting the presence of one or more members of one or more classes of biomarkers in a sample obtained from a subject further comprises detecting the presence of aneuploidy in a sample obtained from the subject. For example, a method comprising detecting the presence of one or more members of a class of genetic biomarkers in a sample obtained from a subject may also comprise detecting the presence of aneuploidy in a sample obtained from a subject (e.g., the same sample or two different samples from a subject). As another example, a method comprising detecting the presence of one or more members of a class of protein biomarkers in a sample obtained from a subject can further comprise detecting the presence of aneuploidy in a sample obtained from the subject (e.g., the same sample or two different samples from the subject). In some embodiments, a method comprising detecting the presence of both one or more members of a class of genetic biomarkers and one or more members of a class of protein biomarkers in a sample obtained from a subject can further comprise detecting the presence of aneuploidy in a sample obtained from the subject (e.g., the same sample or two or more different samples from the subject).

[0231] In some embodiments, provided herein are methods included in detecting the presence of one or more members of a single class of biomarkers (e.g., genetic biomarkers or protein biomarkers) in one or more samples obtained from a subject. In some embodiments, provided herein are methods included in detecting the presence of aneuploidy (e.g., genetic biomarkers or protein biomarkers) in one or more samples obtained from a subject. In some embodiments, provided herein are methods included in detecting the presence of one or more members of a single class of biomarkers (e.g., genetic biomarkers or protein biomarkers) in one or more samples obtained from a subject and detecting the presence of aneuploidy in one or more samples obtained from a subject. In some embodiments, provided herein are methods included in detecting the presence of one or more members of two or more classes of biomarkers (e.g., genetic biomarkers and protein biomarkers) in one or more samples obtained from a subject. In some embodiments, provided herein are methods included in detecting the presence of one or more members of two or more classes of biomarkers (e.g., genetic biomarkers and protein biomarkers) in one or more samples obtained from a subject and detecting the presence of aneuploidy in one or more samples obtained from a subject.

[0232] In some embodiments, a single sample obtained from a subject can be tested to detect the presence of one or more members of one or more classes of biomarkers and / or the presence of aneuploidy. Alternatively, two or more samples can be obtained from a subject, and each of the two or more samples can be tested separately to detect the presence of one or more members of one or more classes of biomarkers and / or the presence of aneuploidy. As a non-limiting example, a first sample obtained from a subject can be tested to detect the presence of one or more members of a first class of biomarkers (e.g., genetic biomarkers), and a second sample obtained from a subject can be tested to detect the presence of one or more members of a second class of biomarkers (e.g., protein biomarkers). As another non-limiting example, a first sample obtained from a subject can be tested to detect the presence of one or more members of a class of biomarkers (e.g., genetic biomarkers or protein biomarkers), and a second sample obtained from a subject can be tested to detect the presence of aneuploidy. As another non-limiting example, a first sample obtained from a subject can be tested to detect the presence of one or more members of a first category of biomarkers (e.g., genetic biomarkers) and to detect the presence of one or more members of a second category of biomarkers (e.g., protein biomarkers), while a second sample obtained from the subject can be tested to detect the presence of an aneuploidy. As another non-limiting example, a first sample obtained from a subject can be tested to detect the presence of one or more members of a first category of biomarkers (e.g., genetic or protein biomarkers) and to detect the presence of an aneuploidy, while a second sample obtained from the subject can be tested to detect the presence of one or more members of a second category of biomarkers (e.g., a class of biomarkers different from the first category of biomarkers tested in the first sample).

[0233] In some embodiments, the presence of one or more members of the biomarkers of one or more categories in the sample obtained from the subject and / or the presence of aneuploidy (for example, detected by any of the various methods disclosed herein) is associated with the disease, and the subject is instructed to suffer from the disease. In some embodiments, when the presence of one or more members of the biomarkers of one or more categories and / or the presence of aneuploidy (the biomarkers and / or aneuploidy are associated with the disease) is detected in the sample obtained from the subject, the subject is diagnosed to have a disease. In some embodiments, the disease is cancer (for example, any of the various cancers described herein). In some embodiments, before detecting the presence of one or more members of the biomarkers of one or more categories and / or the presence of aneuploidy, it is not known that the subject has a disease (for example, cancer). In some embodiments, before detecting the presence of one or more members of the biomarkers of one or more categories and / or the presence of aneuploidy, it is not known that the subject carries cancer cells. In some embodiments, before detecting the presence of one or more members of the biomarkers of one or more categories and / or the presence of aneuploidy, the subject does not show symptoms associated with cancer.

[0234] Diagnostic methods

[0235] Also provided herein are methods and materials for diagnosing or identifying the presence of a disease in a subject (e.g., identifying that the subject has cancer) by detecting one or more members (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 or more members) of one or more classes of biomarkers and / or the presence of aneuploidy in a sample obtained from the subject. In some embodiments of diagnosing or identifying the presence of a disease in a subject (e.g., identifying that the subject has cancer), the presence of one or more members of one or more classes of biomarkers and / or the presence of aneuploidy are tested simultaneously (e.g., in a testing procedure, including embodiments in which the testing procedure itself may include multiple discrete testing methods or systems). In some embodiments of diagnosing or identifying the presence of a disease in a subject (e.g., identifying that the subject has cancer), the presence of one or more members of one or more classes of biomarkers and / or the presence of aneuploidy are tested sequentially (e.g., in two or more different testing procedures performed at two or more different time points, including embodiments in which the testing procedure itself may include multiple discrete testing methods or systems). In some embodiments of diagnosing or identifying the presence of a disease in a subject (e.g., identifying a subject as having cancer) that include simultaneously testing or sequentially testing (or both) for the presence of one or more members of one or more classes of biomarkers and / or the presence of aneuploidy, the testing can be performed on a single sample, or can be performed on two or more different samples (e.g., two or more different samples obtained from the same subject).

[0236] Any of the various detection methods described herein (see, for example, the sections entitled “Detection of Genetic Biomarkers,” “Detection of Protein Biomarkers,” and “Detection of Aneuploidy”) can be used to detect the presence of one or more members of one or more classes of biomarkers and / or the presence of aneuploidy in a sample obtained from a subject. In some embodiments, one or more members of one or more classes of biomarkers and / or one or more classes of biomarkers are associated with a disease in a subject. In some embodiments, aneuploidy is associated with a disease in a subject. In some embodiments, the disease is cancer (e.g., any of the various types of cancer described herein). In some embodiments, the one or more members are members of a class of genetic biomarkers. In some embodiments, the one or more members are members of a class of protein biomarkers. In some embodiments, a method comprising diagnosing the presence of cancer in a subject (e.g., identifying a subject as having cancer) by detecting the presence of one or more members of one or more classes of biomarkers in a sample obtained from a subject also comprises detecting the presence of aneuploidy in a sample obtained from the subject. For example, a method comprising diagnosing the presence of cancer in a subject (e.g., identifying a subject as having cancer) by detecting the presence of one or more members of a class of genetic biomarkers in a sample obtained from the subject may also include detecting the presence of aneuploidy in a sample obtained from the subject (e.g., the same sample or two different samples from the subject). As another example, a method comprising diagnosing the presence of cancer in a subject (e.g., identifying a subject as having cancer) by detecting the presence of one or more members of a class of protein biomarkers in a sample obtained from the subject may also include detecting the presence of aneuploidy in a sample obtained from the subject (e.g., the same sample or two different samples from the subject). In some embodiments, a method comprising diagnosing the presence of cancer in a subject (e.g., identifying a subject as having cancer) by detecting the presence of one or more members of a class of genetic biomarkers and detecting the presence of one or more members of a class of protein biomarkers in a sample obtained from the subject may also include detecting the presence of aneuploidy in a sample obtained from the subject (e.g., the same sample or two or more different samples from the subject).

[0237] In some embodiments, the methods provided herein include diagnosing the presence of cancer in a subject (e.g., identifying that the subject has cancer) by detecting the presence of one or more members of a single class of biomarkers (e.g., genetic biomarkers or protein biomarkers) in one or more samples obtained from the subject. In some embodiments, the methods provided herein include diagnosing the presence of cancer in a subject (e.g., identifying that the subject has cancer) by detecting the presence of aneuploidy (e.g., genetic biomarkers or protein biomarkers) in one or more samples obtained from the subject. In some embodiments, the methods provided herein include diagnosing the presence of cancer in a subject (e.g., identifying that the subject has cancer) by detecting the presence of one or more members of a single class of biomarkers (e.g., genetic biomarkers or protein biomarkers) in one or more samples obtained from the subject and detecting the presence of aneuploidy in one or more samples obtained from the subject. In some embodiments, the methods provided herein include diagnosing the presence of cancer in a subject (e.g., identifying that the subject has cancer) by detecting the presence of one or more members of two or more classes of biomarkers (e.g., genetic biomarkers and protein biomarkers) in one or more samples obtained from the subject. In some embodiments, the methods provided herein comprise diagnosing the presence of cancer in a subject (e.g., identifying the subject as having cancer) by detecting the presence of one or more members of two or more classes of biomarkers (e.g., genetic biomarkers and protein biomarkers) in one or more samples obtained from the subject and detecting the presence of aneuploidy in one or more samples obtained from the subject.

[0238] In some embodiments, a single sample obtained from a subject can be tested to detect the presence of one or more members of one or more classes of biomarkers and / or the presence of aneuploidy, and when the presence of one or more members of one or more classes of biomarkers and / or the presence of aneuploidy is detected, the subject can be diagnosed with cancer (e.g., identifying the subject as having cancer). Alternatively, two or more samples can be obtained from a subject, and each of the two or more samples can be tested separately to detect the presence of one or more members of one or more classes of biomarkers and / or the presence of aneuploidy, and when the presence of one or more members of one or more classes of biomarkers and / or the presence of aneuploidy is detected, the subject can be diagnosed with cancer (e.g., identifying the subject as having cancer). As a non-limiting example, a first sample obtained from a subject can be tested to detect the presence of one or more members of a first category of biomarkers (e.g., genetic biomarkers), and a second sample obtained from the subject can be tested to detect the presence of one or more members of a second category of biomarkers (e.g., protein biomarkers), wherein when the presence of one or more members of the first category of biomarkers is detected and / or the presence of one or more members of the second category of biomarkers is detected (e.g., when the presence of one or more members of the category of biomarkers is detected and the presence of one or more members of the second category of biomarkers is detected), the subject is diagnosed with cancer (e.g., the subject is identified as having cancer). As another non-limiting example, a first sample obtained from a subject can be tested to detect the presence of one or more members of a class of biomarkers (e.g., genetic biomarkers or protein biomarkers), and a second sample obtained from the subject can be tested to detect the presence of an aneuploidy, wherein when the presence of one or more members of the category of biomarkers is detected and / or the presence of an aneuploidy is detected (e.g., when the presence of one or more members of the category of biomarkers is detected and the presence of an aneuploidy is detected), the subject is diagnosed with cancer (e.g., the subject is identified as having cancer).As another non-limiting example, a first sample obtained from the subject can be tested to detect the presence of one or more members of a first category of biomarkers (e.g., genetic biomarkers) and to detect the presence of one or more members of a second category of biomarkers (e.g., protein biomarkers), while a second sample obtained from the subject can be tested to detect the presence of an aneuploidy, wherein the subject is diagnosed with cancer (e.g., identified as having cancer) when the presence of one or more members of the first category of biomarkers is detected, the presence of one or more members of the second category of biomarkers is detected, and / or the presence of an aneuploidy is detected (e.g., when the presence of one or more members of the first category of biomarkers is detected, the presence of one or more members of the second category of biomarkers is detected, and the presence of an aneuploidy is detected). As another non-limiting example, a first sample obtained from the subject can be tested to detect the presence of one or more members of a first category of biomarkers (e.g., genetic biomarkers or protein biomarkers) and to detect the presence of an aneuploidy, while a second sample obtained from the subject can be tested to detect the presence of one or more members of a second category of biomarkers (e.g., a different category of biomarkers than the first category of biomarkers tested in the first sample), wherein the subject is diagnosed with cancer (e.g., identified as having cancer) when the presence of one or more members of the first category of biomarkers is detected, the presence of one or more members of the second category of biomarkers is detected, and / or the presence of an aneuploidy is detected (e.g., when the presence of one or more members of the first category of biomarkers is detected, the presence of one or more members of the second category of biomarkers is detected, and the presence of an aneuploidy is detected).

[0239] In some embodiments (for example, using any of various methods as described herein) of the existence of disease (for example, cancer) in diagnosis or identification subject, subject is also accredited as a candidate for further diagnostic test. In some embodiments (for example, using any of various methods as described herein) of the existence of disease (for example, cancer) in diagnosis or identification subject, subject is also accredited as a candidate for increasing monitoring. In some embodiments (for example, using any of various methods as described herein) of the existence of disease (for example, cancer) in diagnosis or identification subject, subject is also accredited as a candidate for responding to or possibly to treatment (for example, any of various therapeutic interventions as described herein). In some embodiments (for example, using any of various methods as described herein) of the existence of disease (for example, cancer) in diagnosis or identification subject, treatment (for example, any of various therapeutic interventions as described herein) is also applied to subject.

[0240] Methods for identifying a subject at risk for having or developing a disease

[0241] Provided herein are methods and materials for identifying a subject as having a risk (e.g., an increased risk) for having or developing a disease (e.g., cancer) by detecting the presence of one or more members (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 or more members) of one or more classes of biomarkers in a sample obtained from the subject and / or the presence of aneuploidy. In some embodiments of identifying a subject as having a risk (e.g., an increased risk) for having or developing a disease (e.g., cancer), the presence of one or more members of one or more classes of biomarkers and / or the presence of aneuploidy are tested simultaneously (e.g., in a testing procedure, including embodiments in which the testing procedure itself may include multiple discrete testing methods or systems). In some embodiments of identifying a subject as having a risk (e.g., an increased risk) of having or developing a disease (e.g., cancer), one or more members of one or more classes of biomarkers are tested sequentially for the presence of aneuploidy (e.g., in two or more different testing procedures performed at two or more different time points, including embodiments in which the testing procedures themselves may include multiple discrete testing methods or systems). In some embodiments of identifying a subject as having a risk (e.g., an increased risk) of having or developing a disease (e.g., cancer) that include simultaneously testing or sequentially testing (or both) for the presence of one or more members of one or more classes of biomarkers and / or the presence of aneuploidy, the testing can be performed on a single sample, or can be performed on two or more different samples (e.g., two or more different samples obtained from the same subject).

[0242] Any of the various detection methods described herein (see, for example, the sections entitled “Detection of Genetic Biomarkers,” “Detection of Protein Biomarkers,” and “Detection of Aneuploidy”) can be used to detect the presence of one or more members of one or more classes of biomarkers and / or the presence of aneuploidy in a sample obtained from a subject. In some embodiments, one or more members of one or more classes of biomarkers and / or one or more classes of biomarkers are associated with a disease in a subject. In some embodiments, aneuploidy is associated with a disease in a subject. In some embodiments, the disease is cancer (e.g., any of the various types of cancer described herein). In some embodiments, the one or more members are members of a class of genetic biomarkers. In some embodiments, the one or more members are members of a class of protein biomarkers. In some embodiments, a method comprising identifying a subject as having a risk (e.g., an increased risk) of having or developing a disease (e.g., cancer) by detecting the presence of one or more members of one or more classes of biomarkers in a sample obtained from a subject also comprises detecting the presence of aneuploidy in a sample obtained from the subject. For example, a method comprising identifying a subject as having a risk (e.g., an increased risk) for having or developing a disease (e.g., cancer) by detecting the presence of one or more members of a class of genetic biomarkers in a sample obtained from the subject can also include detecting the presence of aneuploidy in a sample obtained from the subject (e.g., the same sample or two different samples from the subject). As another example, a method comprising identifying a subject as having a risk (e.g., an increased risk) for having or developing a disease (e.g., cancer) by detecting the presence of one or more members of a class of protein biomarkers in a sample obtained from the subject can also include detecting the presence of aneuploidy in a sample obtained from the subject (e.g., the same sample or two different samples from the subject). In some embodiments, a method comprising identifying a subject as having a risk (e.g., an increased risk) for having or developing a disease (e.g., cancer) by detecting the presence of one or more members of a class of genetic biomarkers and detecting the presence of one or more members of a class of protein biomarkers in a sample obtained from the subject can also include detecting the presence of aneuploidy in a sample obtained from the subject (e.g., the same sample or two or more different samples from the subject).

[0243] In some embodiments, provided herein are methods for identifying that a subject has a risk (e.g., an increased risk) of having or developing a disease (e.g., cancer) including detecting the presence of one or more members of a single class of biomarkers (e.g., genetic biomarkers or protein biomarkers) in one or more samples obtained from a subject. In some embodiments, provided herein are methods for identifying that a subject has a risk (e.g., an increased risk) of having or developing a disease (e.g., cancer) including detecting the presence of one or more members of a single class of biomarkers (e.g., genetic biomarkers or protein biomarkers) in one or more samples obtained from a subject. In some embodiments, provided herein are methods for identifying that a subject has a risk (e.g., an increased risk) of having or developing a disease (e.g., cancer) including detecting the presence of one or more members of a single class of biomarkers (e.g., genetic biomarkers or protein biomarkers) in one or more samples obtained from a subject and detecting the presence of aneuploidy in one or more samples obtained from a subject. In some embodiments, methods provided herein for identifying that a subject has a risk (e.g., an increased risk) of having or developing a disease (e.g., cancer) include detecting the presence of one or more members of two or more classes of biomarkers (e.g., genetic biomarkers and protein biomarkers) in one or more samples obtained from the subject. In some embodiments, methods provided herein for identifying that a subject has a risk (e.g., an increased risk) of having or developing a disease (e.g., cancer) include detecting the presence of one or more members of two or more classes of biomarkers (e.g., genetic biomarkers and protein biomarkers) in one or more samples obtained from the subject and detecting the presence of aneuploidy in one or more samples obtained from the subject.

[0244] In some embodiments, a single sample obtained from a subject can be tested to detect the presence of one or more members of one or more classes of biomarkers and / or the presence of aneuploidy, and when the presence of one or more members of one or more classes of biomarkers and / or the presence of aneuploidy is detected, the subject can be identified as having a risk (e.g., an increased risk) of having or developing a disease (e.g., cancer). Alternatively, two or more samples can be obtained from a subject, and each of the two or more samples can be tested separately to detect the presence of one or more members of one or more classes of biomarkers and / or the presence of aneuploidy, and when the presence of one or more members of one or more classes of biomarkers and / or the presence of aneuploidy is detected, the subject can be identified as having a risk (e.g., an increased risk) of having or developing a disease (e.g., cancer). As a non-limiting example, a first sample obtained from a subject can be tested to detect the presence of one or more members of a first category of biomarkers (e.g., genetic biomarkers), and a second sample obtained from the subject can be tested to detect the presence of one or more members of a second category of biomarkers (e.g., protein biomarkers), wherein when the presence of one or more members of the first category of biomarkers is detected and / or the presence of one or more members of the second category of biomarkers is detected (e.g., when the presence of one or more members of the category of biomarkers is detected and the presence of one or more members of the second category of biomarkers is detected), the subject is identified as having a risk (e.g., an increased risk) of having or developing a disease (e.g., cancer). As another non-limiting example, a first sample obtained from a subject can be tested to detect the presence of one or more members of a class of biomarkers (e.g., genetic biomarkers or protein biomarkers), and a second sample obtained from the subject can be tested to detect the presence of an aneuploidy, wherein when the presence of one or more members of the class of biomarkers is detected and / or the presence of an aneuploidy is detected (e.g., when the presence of one or more members of the class of biomarkers is detected and the presence of an aneuploidy is detected), the subject is identified as having a risk (e.g., an increased risk) of having or developing a disease (e.g., cancer).As another non-limiting example, a first sample obtained from a subject can be tested to detect the presence of one or more members of a first category of biomarkers (e.g., genetic biomarkers) and to detect the presence of one or more members of a second category of biomarkers (e.g., protein biomarkers), while a second sample obtained from the subject can be tested to detect the presence of an aneuploidy, wherein when the presence of one or more members of the first category of biomarkers is detected, the presence of one or more members of the second category of biomarkers is detected, and / or the presence of an aneuploidy is detected (e.g., when the presence of one or more members of the first category of biomarkers is detected, the presence of one or more members of the second category of biomarkers is detected, and the presence of an aneuploidy is detected), the subject is identified as having a risk (e.g., an increased risk) of having or developing a disease (e.g., cancer). As another non-limiting example, a first sample obtained from a subject can be tested to detect the presence of one or more members of a first category of biomarkers (e.g., genetic biomarkers or protein biomarkers) and to detect the presence of an aneuploidy, while a second sample obtained from the subject can be tested to detect the presence of one or more members of a second category of biomarkers (e.g., a different category of biomarkers than the first category of biomarkers tested in the first sample), wherein when the presence of one or more members of the first category of biomarkers is detected, the presence of one or more members of the second category of biomarkers is detected, and / or the presence of an aneuploidy is detected (e.g., when the presence of one or more members of the first category of biomarkers is detected, the presence of one or more members of the second category of biomarkers is detected, and the presence of an aneuploidy is detected), the subject is identified as having a risk (e.g., an increased risk) of having or developing a disease (e.g., cancer).

[0245] In identifying that the experimenter has the risk (for example, the risk of increase) (for example, using any of the various approaches as herein described) of suffering from or developing disease in some embodiments, the experimenter is also accredited as the candidate for carrying out further diagnostic test. In identifying that the experimenter has the risk (for example, the risk of increase) (for example, using any of the various approaches as herein described) of suffering from or developing disease in some embodiments, the experimenter is also accredited as the candidate for carrying out increased monitoring. In identifying that the experimenter has the risk (for example, the risk of increase) (for example, using any of the various approaches as herein described) of suffering from or developing disease in some embodiments, the experimenter is also accredited as will or may be to treatment (for example, any of various therapeutic interventions as herein described, including but not limited to chemoprevention) reacted candidate. In identifying that the experimenter has the risk (for example, the risk of increase) (for example, using any of the various approaches as herein described) of suffering from or developing disease in some embodiments, treatment (for example, any of various therapeutic interventions as herein described, including but not limited to chemoprevention) is also applied to the experimenter.

[0246] Treatment

[0247] Also provided herein are methods and materials for treating a subject who has been diagnosed or identified as having a disease (e.g., cancer) or has been identified as having a risk (e.g., increased risk) of having or developing a disease (e.g., cancer) by detecting one or more members (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 or more members) of one or more classes of biomarkers and / or the presence of aneuploidy in a sample obtained from the subject. In some embodiments of treating a subject who has been diagnosed or identified as having a disease (e.g., cancer) or has been identified as having a risk (e.g., increased risk) of having or developing a disease (e.g., cancer), the presence of one or more members of one or more classes of biomarkers and / or the presence of aneuploidy are tested simultaneously (e.g., in a testing procedure, including embodiments in which the testing procedure itself may include multiple discrete testing methods or systems). In some embodiments of treating a subject who has been diagnosed or identified as having a disease (e.g., cancer) or has been identified as having a risk (e.g., increased risk) of having or developing a disease (e.g., cancer), one or more members of one or more classes of biomarkers are tested sequentially for the presence of aneuploidy (e.g., in two or more different testing procedures performed at two or more different time points, including embodiments in which the testing procedures themselves may include multiple discrete testing methods or systems). In some embodiments of treating a subject who has been diagnosed or identified as having a disease (e.g., cancer) or has been identified as having a risk (e.g., increased risk) of having or developing a disease (e.g., cancer) that includes testing simultaneously or sequentially (or both) for the presence of one or more members of one or more classes of biomarkers and / or the presence of aneuploidy, the testing can be performed on a single sample, or can be performed on two or more different samples (e.g., two or more different samples obtained from the same subject).

[0248] Any of the various detection methods described herein (see, for example, the sections entitled “Detection of Genetic Biomarkers,” “Detection of Protein Biomarkers,” and “Detection of Aneuploidy”) can be used to detect the presence of one or more members of one or more classes of biomarkers and / or the presence of aneuploidy in a sample obtained from a subject. In some embodiments, one or more members of one or more classes of biomarkers and / or one or more classes of biomarkers are associated with a disease in a subject. In some embodiments, aneuploidy is associated with a disease in a subject. In some embodiments, the disease is cancer (e.g., any of the various types of cancer described herein). In some embodiments, the one or more members are members of a class of genetic biomarkers. In some embodiments, the one or more members are members of a class of protein biomarkers. In some embodiments, a method comprising treating a subject who has been diagnosed or identified as having a disease (e.g., cancer) or has been identified as having a risk (e.g., an increased risk) of having or developing a disease (e.g., cancer) by detecting the presence of one or more members of one or more classes of biomarkers in a sample obtained from a subject also includes detecting the presence of aneuploidy in a sample obtained from the subject. For example, a method comprising treating a subject that has been diagnosed or identified as having a disease (e.g., cancer) or has been identified as having a risk (e.g., increased risk) of having or developing a disease (e.g., cancer) by detecting the presence of one or more members of a class of genetic biomarkers in a sample obtained from the subject can also include detecting the presence of aneuploidy in a sample obtained from the subject (e.g., the same sample or two different samples from the subject). As another example, a method comprising treating a subject that has been diagnosed or identified as having a disease (e.g., cancer) or has been identified as having a risk (e.g., increased risk) of having or developing a disease (e.g., cancer) by detecting the presence of one or more members of a class of protein biomarkers in a sample obtained from the subject can also include detecting the presence of aneuploidy in a sample obtained from the subject (e.g., the same sample or two different samples from the subject). In some embodiments, a method comprising treating a subject who has been diagnosed or identified as having a disease (e.g., cancer) or has been identified as having a risk (e.g., increased risk) of having or developing a disease (e.g., cancer) by detecting the presence of one or more members of a class of genetic biomarkers and detecting the presence of one or more members of a class of protein biomarkers in a sample obtained from the subject may also comprise detecting the presence of aneuploidy in a sample obtained from the subject (e.g., the same sample or two or more different samples from the subject).

[0249] In some embodiments, provided herein are methods for treating a subject that has been diagnosed or identified as having a disease (e.g., cancer) or has been identified as having a risk (e.g., increased risk) of having or developing a disease (e.g., cancer) comprising detecting the presence of one or more members of a single class of biomarkers (e.g., genetic biomarkers or protein biomarkers) in one or more samples obtained from the subject. In some embodiments, provided herein are methods for treating a subject that has been diagnosed or identified as having a disease (e.g., cancer) or has been identified as having a risk (e.g., increased risk) of having or developing a disease (e.g., cancer) comprising detecting the presence of one or more members of a single class of biomarkers (e.g., genetic biomarkers or protein biomarkers) in one or more samples obtained from the subject and detecting the presence of aneuploidy in one or more samples obtained from the subject. In some embodiments, provided herein are methods for treating a subject that has been diagnosed or identified as having a disease (e.g., cancer) or has been identified as having a risk (e.g., increased risk) of having or developing a disease (e.g., cancer) comprising detecting the presence of one or more members of a single class of biomarkers (e.g., genetic biomarkers or protein biomarkers) in one or more samples obtained from the subject and detecting the presence of aneuploidy in one or more samples obtained from the subject. In some embodiments, the methods provided herein for treating a subject that has been diagnosed or identified as having a disease (e.g., cancer) or has been identified as having a risk (e.g., increased risk) of having or developing a disease (e.g., cancer) include detecting the presence of one or more members of two or more classes of biomarkers (e.g., genetic biomarkers and protein biomarkers) in one or more samples obtained from the subject. In some embodiments, the methods provided herein for treating a subject that has been diagnosed or identified as having a disease (e.g., cancer) or has been identified as having a risk (e.g., increased risk) of having or developing a disease (e.g., cancer) include detecting the presence of one or more members of two or more classes of biomarkers (e.g., genetic biomarkers and protein biomarkers) in one or more samples obtained from the subject and detecting the presence of aneuploidy in one or more samples obtained from the subject.

[0250] In some embodiments, a single sample obtained from a subject can be tested to detect the presence of one or more members of one or more classes of biomarkers and / or the presence of an aneuploidy, and when the presence of one or more members of one or more classes of biomarkers and / or the presence of an aneuploidy is detected, the subject can be diagnosed or identified as having a disease (e.g., cancer) or as having a risk (e.g., an increased risk) of having or developing a disease (e.g., cancer) and / or the subject can be treated. Alternatively, two or more samples can be obtained from a subject, and each of the two or more samples can be tested separately to detect the presence of one or more members of one or more classes of biomarkers and / or the presence of an aneuploidy, and when the presence of one or more members of one or more classes of biomarkers and / or the presence of an aneuploidy is detected, the subject can be diagnosed or identified as having a risk (e.g., an increased risk) of having or developing a disease (e.g., cancer) and / or the subject can be treated. As a non-limiting example, a first sample obtained from a subject can be tested to detect the presence of one or more members of a first category of biomarkers (e.g., genetic biomarkers), and a second sample obtained from the subject can be tested to detect the presence of one or more members of a second category of biomarkers (e.g., protein biomarkers), wherein when the presence of one or more members of the first category of biomarkers is detected and / or the presence of one or more members of the second category of biomarkers is detected (e.g., when the presence of one or more members of the category of biomarkers is detected and the presence of one or more members of the second category of biomarkers is detected), the subject is diagnosed or identified as having a disease (e.g., cancer) or as having a risk (e.g., an increased risk) of having or developing a disease (e.g., cancer) and / or the subject can be treated. As another non-limiting example, a first sample obtained from a subject can be tested to detect the presence of one or more members of a class of biomarkers (e.g., genetic biomarkers or protein biomarkers), and a second sample obtained from the subject can be tested to detect the presence of an aneuploidy, wherein when the presence of one or more members of the class of biomarkers is detected and / or the presence of an aneuploidy is detected (e.g., when the presence of one or more members of the class of biomarkers is detected and the presence of an aneuploidy is detected), the subject is diagnosed or identified as having a disease (e.g., cancer) or as having a risk (e.g., increased risk) of having or developing a disease (e.g., cancer) and / or the subject is treated.As another non-limiting example, a first sample obtained from a subject can be tested to detect the presence of one or more members of a first category of biomarkers (e.g., genetic biomarkers) and to detect the presence of one or more members of a second category of biomarkers (e.g., protein biomarkers), while a second sample obtained from the subject can be tested to detect the presence of an aneuploidy, wherein when the presence of one or more members of the first category of biomarkers is detected, the presence of one or more members of the second category of biomarkers is detected, and / or the presence of an aneuploidy is detected (e.g., when the presence of one or more members of the first category of biomarkers is detected, the presence of one or more members of the second category of biomarkers is detected, and the presence of an aneuploidy is detected), the subject is diagnosed or identified as having a disease (e.g., cancer) or as having a risk (e.g., an increased risk) of having or developing a disease (e.g., cancer) and / or the subject is treated. As another non-limiting example, a first sample obtained from a subject can be tested to detect the presence of one or more members of a first class of biomarkers (e.g., genetic biomarkers or protein biomarkers) and to detect the presence of an aneuploidy, while a second sample obtained from the subject can be tested to detect the presence of one or more members of a second class of biomarkers (e.g., a class of biomarkers that is different from the first class of biomarkers tested in the first sample), wherein when the presence of one or more members of the first class of biomarkers is detected, the presence of one or more members of the second class of biomarkers is detected, and / or the presence of an aneuploidy is detected (e.g., when the presence of one or more members of the first class of biomarkers is detected, the presence of one or more members of the second class of biomarkers is detected, and the presence of an aneuploidy is detected), the subject is diagnosed or identified as having a disease (e.g., cancer) or as having a risk (e.g., an increased risk) of having or developing a disease (e.g., cancer) and / or the subject is treated.

[0251] In some embodiments of treating a subject who has been diagnosed or identified as having a disease, or who has been identified as having a risk (e.g., increased risk) of having or developing a disease, by detecting the presence of one or more members (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 or more members) of one or more classes of biomarkers and / or aneuploidy in a sample obtained from the subject, the treatment is any of the various therapeutic interventions disclosed herein, including but not limited to Chemotherapy, neoadjuvant chemotherapy, radiotherapy, hormone therapy, cytotoxic therapy, immunotherapy, adoptive T cell therapy (e.g., chimeric antigen receptors and / or T cells with wild-type or modified T cell receptors), targeted therapy such as administration of kinase inhibitors (e.g., kinase inhibitors targeting specific genetic lesions (such as translocations or mutations)), (e.g., kinase inhibitors, antibodies, bispecific antibodies), signal transduction inhibitors, bispecific antibodies or antibody fragments (e.g., BiTEs), monoclonal antibodies, immune checkpoint inhibitors, surgery (e.g., surgical resection), or any combination thereof. In some embodiments where the disease is cancer, the therapeutic intervention reduces the severity of the cancer, alleviates the symptoms of the cancer, and / or reduces the number of cancer cells present in the subject.

[0252] In some embodiments of treating a subject who has been diagnosed or identified as having a disease or has been identified as having a risk (e.g., an increased risk) of having or developing a disease (e.g., by any of the various methods described herein), the subject is also identified as a subject who will or may respond to the treatment. In some embodiments of treating a subject who has been diagnosed or identified as having a disease or has been identified as having a risk (e.g., an increased risk) of having or developing a disease (e.g., by any of the various methods described herein), the subject is also identified as a candidate for further diagnostic testing (e.g., before and / or after administering the treatment, to determine the effect of the treatment and / or whether the subject is a candidate for additional administration of the same treatment or a different treatment). In some embodiments of treating a subject who has been diagnosed or identified as having a disease or has been identified as having a risk (e.g., an increased risk) of having or developing a disease (e.g., by any of the various methods described herein), the subject is also identified as a candidate for increased monitoring (e.g., before and / or after administering the treatment, to determine the effect of the treatment and / or whether the subject is a candidate for additional administration of the same treatment or a different treatment).

[0253] Identify treatment methods

[0254] Also provided herein are methods and materials for identifying treatments for a subject who has been diagnosed or identified as having a disease (e.g., cancer) or has been identified as having a risk (e.g., increased risk) of having or developing a disease (e.g., cancer) by detecting one or more members (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 or more members) of one or more classes of biomarkers and / or the presence of aneuploidy in a sample obtained from the subject. In some embodiments of identifying treatments for a subject who has been diagnosed or identified as having a disease (e.g., cancer) or has been identified as having a risk (e.g., increased risk) of having or developing a disease (e.g., cancer), the presence of one or more members of one or more classes of biomarkers and / or the presence of aneuploidy are tested simultaneously (e.g., in a testing procedure, including embodiments in which the testing procedure itself may include multiple discrete testing methods or systems). In some embodiments of identifying a treatment for a subject who has been diagnosed or identified as having a disease (e.g., cancer) or has been identified as having a risk (e.g., increased risk) of having or developing a disease (e.g., cancer), one or more members of one or more classes of biomarkers are tested sequentially for the presence of aneuploidy (e.g., in two or more different testing procedures performed at two or more different time points, including embodiments in which the testing procedures themselves may include multiple discrete testing methods or systems). In some embodiments of identifying a treatment for a subject who has been diagnosed or identified as having a disease (e.g., cancer) or has been identified as having a risk (e.g., increased risk) of having or developing a disease (e.g., cancer) that includes testing simultaneously or sequentially (or both) for the presence of one or more members of one or more classes of biomarkers and / or the presence of aneuploidy, the testing can be performed on a single sample, or can be performed on two or more different samples (e.g., two or more different samples obtained from the same subject).

[0255] Any of the various detection methods described herein (see, for example, the sections entitled “Detection of Genetic Biomarkers,” “Detection of Protein Biomarkers,” and “Detection of Aneuploidy”) can be used to detect the presence of one or more members of one or more classes of biomarkers and / or the presence of aneuploidy in a sample obtained from a subject. In some embodiments, one or more members of one or more classes of biomarkers and / or one or more classes of biomarkers are associated with a disease in a subject. In some embodiments, aneuploidy is associated with a disease in a subject. In some embodiments, the disease is cancer (e.g., any of the various types of cancer described herein). In some embodiments, the one or more members are members of a class of genetic biomarkers. In some embodiments, the one or more members are members of a class of protein biomarkers. In some embodiments, a method for identifying a treatment for a subject who has been diagnosed or identified as having a disease (e.g., cancer) or has been identified as having a risk (e.g., increased risk) of having or developing a disease (e.g., cancer) by detecting the presence of one or more members of one or more classes of biomarkers in a sample obtained from a subject also includes detecting the presence of aneuploidy in a sample obtained from the subject. For example, a method comprising identifying a treatment for a subject that has been diagnosed or identified as having a disease (e.g., cancer) or has been identified as having a risk (e.g., increased risk) of having or developing a disease (e.g., cancer) by detecting the presence of one or more members of a class of genetic biomarkers in a sample obtained from the subject can also include detecting the presence of aneuploidy in a sample obtained from the subject (e.g., the same sample or two different samples from the subject). As another example, a method comprising identifying a treatment for a subject that has been diagnosed or identified as having a disease (e.g., cancer) or has been identified as having a risk (e.g., increased risk) of having or developing a disease (e.g., cancer) by detecting the presence of one or more members of a class of protein biomarkers in a sample obtained from the subject can also include detecting the presence of aneuploidy in a sample obtained from the subject (e.g., the same sample or two different samples from the subject). In some embodiments, a method comprising identifying a treatment for a subject who has been diagnosed or identified as having a disease (e.g., cancer) or has been identified as having a risk (e.g., increased risk) of having or developing a disease (e.g., cancer) by detecting the presence of one or more members of a class of genetic biomarkers and detecting the presence of one or more members of a class of protein biomarkers in a sample obtained from the subject can also comprise detecting the presence of aneuploidy in a sample obtained from the subject (e.g., the same sample or two or more different samples from the subject).

[0256] In some embodiments, provided herein are methods for identifying a treatment for a subject that has been diagnosed or identified as having a disease (e.g., cancer) or has been identified as having a risk (e.g., increased risk) of having or developing a disease (e.g., cancer) comprising detecting the presence of one or more members of a single class of biomarkers (e.g., genetic biomarkers or protein biomarkers) in one or more samples obtained from the subject. In some embodiments, provided herein are methods for identifying a treatment for a subject that has been diagnosed or identified as having a disease (e.g., cancer) or has been identified as having a risk (e.g., increased risk) of having or developing a disease (e.g., cancer) comprising detecting the presence of one or more members of a single class of biomarkers (e.g., genetic biomarkers or protein biomarkers) in one or more samples obtained from the subject and detecting the presence of aneuploidy in one or more samples obtained from the subject. In some embodiments, provided herein are methods for identifying a treatment for a subject that has been diagnosed or identified as having a disease (e.g., cancer) or has been identified as having a risk (e.g., increased risk) of having or developing a disease (e.g., cancer) comprising detecting the presence of one or more members of a single class of biomarkers (e.g., genetic biomarkers or protein biomarkers) in one or more samples obtained from the subject and detecting the presence of aneuploidy in one or more samples obtained from the subject. In some embodiments, methods provided herein for identifying a treatment for a subject that has been diagnosed or identified as having a disease (e.g., cancer) or has been identified as having a risk (e.g., increased risk) of having or developing a disease (e.g., cancer) include detecting the presence of one or more members of two or more classes of biomarkers (e.g., genetic biomarkers and protein biomarkers) in one or more samples obtained from the subject. In some embodiments, methods provided herein for identifying a treatment for a subject that has been diagnosed or identified as having a disease (e.g., cancer) or has been identified as having a risk (e.g., increased risk) of having or developing a disease (e.g., cancer) include detecting the presence of one or more members of two or more classes of biomarkers (e.g., genetic biomarkers and protein biomarkers) in one or more samples obtained from the subject and detecting the presence of aneuploidy in one or more samples obtained from the subject.

[0257] In some embodiments, a single sample obtained from a subject can be tested to detect the presence of one or more members of one or more classes of biomarkers and / or the presence of an aneuploidy, and when the presence of one or more members of one or more classes of biomarkers and / or the presence of an aneuploidy is detected, the subject can be diagnosed or identified as having a disease (e.g., cancer) or as having a risk (e.g., an increased risk) of having or developing a disease (e.g., cancer) and / or a treatment for the subject can be identified. Alternatively, two or more samples can be obtained from a subject, and each of the two or more samples can be tested separately to detect the presence of one or more members of one or more classes of biomarkers and / or the presence of an aneuploidy, and when the presence of one or more members of one or more classes of biomarkers and / or the presence of an aneuploidy is detected, the subject can be diagnosed or identified as having a risk (e.g., an increased risk) of having or developing a disease (e.g., cancer) and / or a treatment for the subject can be identified. As a non-limiting example, a first sample obtained from a subject can be tested to detect the presence of one or more members of a first category of biomarkers (e.g., genetic biomarkers), and a second sample obtained from the subject can be tested to detect the presence of one or more members of a second category of biomarkers (e.g., protein biomarkers), wherein when the presence of one or more members of the first category of biomarkers is detected and / or the presence of one or more members of the second category of biomarkers is detected (e.g., when the presence of one or more members of the category of biomarkers is detected and the presence of one or more members of the second category of biomarkers is detected), the subject is diagnosed or identified as having a disease (e.g., cancer) or as having a risk (e.g., increased risk) of having or developing a disease (e.g., cancer) and / or a treatment for the subject is identified. As another non-limiting example, a first sample obtained from a subject can be tested to detect the presence of one or more members of a class of biomarkers (e.g., genetic biomarkers or protein biomarkers), and a second sample obtained from the subject can be tested to detect the presence of an aneuploidy, wherein when the presence of one or more members of the class of biomarkers is detected and / or the presence of an aneuploidy is detected (e.g., when the presence of one or more members of the class of biomarkers is detected and the presence of an aneuploidy is detected), the subject is diagnosed or identified as having a disease (e.g., cancer) or as having a risk (e.g., increased risk) of having or developing a disease (e.g., cancer) and / or a treatment for the subject is identified.As another non-limiting example, a first sample obtained from a subject can be tested to detect the presence of one or more members of a first category of biomarkers (e.g., genetic biomarkers) and to detect the presence of one or more members of a second category of biomarkers (e.g., protein biomarkers), while a second sample obtained from the subject can be tested to detect the presence of an aneuploidy, wherein when the presence of one or more members of the first category of biomarkers is detected, the presence of one or more members of the second category of biomarkers is detected, and / or the presence of an aneuploidy is detected (e.g., when the presence of one or more members of the first category of biomarkers is detected, the presence of one or more members of the second category of biomarkers is detected, and the presence of an aneuploidy is detected), the subject is diagnosed or identified as having a disease (e.g., cancer) or as having a risk (e.g., an increased risk) of having or developing a disease (e.g., cancer) and / or a treatment for the subject is identified. As another non-limiting example, a first sample obtained from a subject can be tested to detect the presence of one or more members of a first class of biomarkers (e.g., genetic biomarkers or protein biomarkers) and to detect the presence of an aneuploidy, while a second sample obtained from the subject can be tested to detect the presence of one or more members of a second class of biomarkers (e.g., a class of biomarkers that is different from the first class of biomarkers tested in the first sample), wherein when the presence of one or more members of the first class of biomarkers is detected, the presence of one or more members of the second class of biomarkers is detected, and / or the presence of an aneuploidy is detected (e.g., when the presence of one or more members of the first class of biomarkers is detected, the presence of one or more members of the second class of biomarkers is detected, and the presence of an aneuploidy is detected), the subject is diagnosed or identified as having a disease (e.g., cancer) or as having a risk (e.g., an increased risk) of having or developing a disease (e.g., cancer) and / or a treatment for the subject is identified.

[0258] In some embodiments of identifying a treatment for a subject who has been diagnosed or identified as having a disease, or who has been identified as having a risk (e.g., increased risk) of having or developing a disease, by detecting the presence of one or more members (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 or more members) of one or more classes of biomarkers and / or aneuploidy in a sample obtained from the subject, the treatment is any of the various therapeutic interventions disclosed herein, including but not limited to Limited to chemotherapy, neoadjuvant chemotherapy, radiotherapy, hormone therapy, cytotoxic therapy, immunotherapy, adoptive T cell therapy (e.g., chimeric antigen receptors and / or T cells with wild-type or modified T cell receptors), targeted therapy such as administration of kinase inhibitors (e.g., kinase inhibitors targeting specific genetic lesions (such as translocations or mutations)), (e.g., kinase inhibitors, antibodies, bispecific antibodies), signal transduction inhibitors, bispecific antibodies or antibody fragments (e.g., BiTEs), monoclonal antibodies, immune checkpoint inhibitors, surgery (e.g., surgical resection), or any combination thereof. In some embodiments where the disease is cancer, the identified therapeutic intervention reduces the severity of the cancer, alleviates the symptoms of the cancer, and / or reduces the number of cancer cells present in the subject.

[0259] In identifying some embodiments for having been diagnosed or accredited as suffering from disease or having been accredited as having the risk (for example, increase) of the experimenter suffering from or developing disease (for example, the risk of increase) treatment (for example, by any of various methods as described herein), experimenter is also accredited as will or may be to the experimenter of described treatment reaction.In identifying some embodiments for having been diagnosed or accredited as suffering from disease or having been accredited as having the risk (for example, increase) of the experimenter suffering from or developing disease (for example, the risk of increase) treatment (for example, by any of various methods as described herein), experimenter is also accredited as the candidate for carrying out further diagnostic test.In identifying some embodiments for having been diagnosed or accredited as suffering from disease or having been accredited as having the risk (for example, increase) of the experimenter suffering from or developing disease (for example, the risk of increase) treatment (for example, by any of various methods as described herein), experimenter is also accredited as the candidate for carrying out increase monitoring.In identifying some embodiments for having been diagnosed or accredited as suffering from disease or having been accredited as having the risk (for example, increase) of the experimenter suffering from or developing disease (for example, the risk of increase) treatment (for example, by any of various methods as described herein), also to experimenter, treatment (for example, any of various therapeutic interventions as described herein).

[0260] Identify subjects who will or are likely to respond to treatment

[0261] Also provided herein are methods and materials for identifying a subject who will or may respond to treatment by detecting one or more members (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 or more members) of one or more classes of biomarkers and / or the presence of aneuploidy in a sample obtained from the subject. In some embodiments of identifying a subject who will or may respond to treatment, the presence of one or more members of one or more classes of biomarkers and / or the presence of aneuploidy are tested simultaneously (e.g., in a testing procedure, including embodiments in which the testing procedure itself may include multiple discrete testing methods or systems). In some embodiments of identifying a subject who will or may respond to treatment, the presence of one or more members of one or more classes of biomarkers and / or the presence of aneuploidy are tested sequentially (e.g., in two or more different testing procedures performed at two or more different time points, including embodiments in which the testing procedure itself may include multiple discrete testing methods or systems). In some embodiments that involve simultaneously testing or sequentially testing (or both) for the presence of one or more members of one or more classes of biomarkers and / or the identification of subjects who will or are likely to respond to treatment for the presence of aneuploidy, the testing can be performed on a single sample, or can be performed on two or more different samples (e.g., two or more different samples obtained from the same subject).

[0262] Any of the various detection methods described herein (see, for example, the sections entitled “Detection of Genetic Biomarkers,” “Detection of Protein Biomarkers,” and “Detection of Aneuploidy”) can be used to detect the presence of one or more members of one or more classes of biomarkers and / or the presence of aneuploidy in a sample obtained from a subject. In some embodiments, one or more members of one or more classes of biomarkers and / or one or more classes of biomarkers are associated with a disease in a subject. In some embodiments, aneuploidy is associated with a disease in a subject. In some embodiments, the disease is cancer (e.g., any of the various types of cancer described herein). In some embodiments, the one or more members are members of a class of genetic biomarkers. In some embodiments, the one or more members are members of a class of protein biomarkers. In some embodiments, a method comprising identifying a subject who will or may respond to treatment by detecting the presence of one or more members of one or more classes of biomarkers in a sample obtained from a subject also comprises detecting the presence of aneuploidy in a sample obtained from the subject. For example, a method comprising identifying a subject who will or may respond to treatment by detecting the presence of one or more members of a class of genetic biomarkers in a sample obtained from a subject may also include detecting the presence of aneuploidy in a sample obtained from the subject (e.g., the same sample or two different samples from the subject). As another example, a method comprising identifying a subject who will or may respond to treatment by detecting the presence of one or more members of a class of protein biomarkers in a sample obtained from a subject may also include detecting the presence of aneuploidy in a sample obtained from a subject (e.g., the same sample or two different samples from the subject). In some embodiments, a method comprising identifying a subject who will or may respond to treatment by detecting the presence of one or more members of a class of genetic biomarkers and detecting the presence of one or more members of a class of protein biomarkers in a sample obtained from a subject may also include detecting the presence of aneuploidy in a sample obtained from a subject (e.g., the same sample or two or more different samples from the subject).

[0263] In some embodiments, provided herein are methods for identifying a subject who will or may respond to treatment that includes detecting the presence of one or more members of a single class of biomarkers (e.g., genetic biomarkers or protein biomarkers) in one or more samples obtained from a subject. In some embodiments, provided herein are methods for identifying a subject who will or may respond to treatment that includes detecting the presence of aneuploidy (e.g., genetic biomarkers or protein biomarkers) in one or more samples obtained from a subject. In some embodiments, provided herein are methods for identifying a subject who will or may respond to treatment that includes detecting the presence of one or more members of a single class of biomarkers (e.g., genetic biomarkers or protein biomarkers) in one or more samples obtained from a subject and detecting the presence of aneuploidy in one or more samples obtained from a subject. In some embodiments, provided herein are methods for identifying a subject who will or may respond to treatment that includes detecting the presence of one or more members of a single class of biomarkers (e.g., genetic biomarkers and protein biomarkers) in one or more samples obtained from a subject. In some embodiments, the methods provided herein for identifying a subject who will or is likely to respond to a treatment comprise detecting the presence of one or more members of two or more classes of biomarkers (e.g., genetic biomarkers and protein biomarkers) in one or more samples obtained from the subject and detecting the presence of an aneuploidy in one or more samples obtained from the subject.

[0264] In some embodiments, a single sample obtained from a subject can be tested to detect the presence of one or more members of one or more classes of biomarkers and / or the presence of aneuploidy, and when the presence of one or more members of one or more classes of biomarkers and / or the presence of aneuploidy is detected, the subject can be diagnosed or identified as having a disease (e.g., cancer) or having a risk (e.g., increased risk) of having or developing a disease (e.g., cancer) and / or the subject can be identified as a subject that will or is likely to respond to treatment. Alternatively, two or more samples can be obtained from a subject, and each of the two or more samples can be tested separately to detect the presence of one or more members of one or more classes of biomarkers and / or the presence of aneuploidy, and when the presence of one or more members of one or more classes of biomarkers and / or the presence of aneuploidy is detected, the subject can be diagnosed or identified as having a risk (e.g., increased risk) of having or developing a disease (e.g., cancer) and / or the subject can be identified as a subject that will or is likely to respond to treatment. As a non-limiting example, a first sample obtained from a subject can be tested to detect the presence of one or more members of a first category of biomarkers (e.g., genetic biomarkers), and a second sample obtained from the subject can be tested to detect the presence of one or more members of a second category of biomarkers (e.g., protein biomarkers), wherein when the presence of one or more members of the first category of biomarkers is detected and / or the presence of one or more members of the second category of biomarkers is detected (e.g., when the presence of one or more members of the category of biomarkers is detected and the presence of one or more members of the second category of biomarkers is detected), the subject is diagnosed or identified as having a disease (e.g., cancer) or as having a risk (e.g., increased risk) of having or developing a disease (e.g., cancer) and / or the subject is identified as a subject that will or is likely to respond to treatment. As another non-limiting example, a first sample obtained from a subject can be tested to detect the presence of one or more members of a class of biomarkers (e.g., genetic biomarkers or protein biomarkers), and a second sample obtained from the subject can be tested to detect the presence of an aneuploidy, wherein when the presence of one or more members of the class of biomarkers is detected and / or the presence of an aneuploidy is detected (e.g., when the presence of one or more members of the class of biomarkers is detected and the presence of an aneuploidy is detected), the subject is diagnosed or identified as having a disease (e.g., cancer) or as having a risk (e.g., increased risk) of having or developing a disease (e.g., cancer) and / or the subject is identified as a subject that will or is likely to respond to a treatment.As another non-limiting example, a first sample obtained from a subject can be tested to detect the presence of one or more members of a first category of biomarkers (e.g., genetic biomarkers) and to detect the presence of one or more members of a second category of biomarkers (e.g., protein biomarkers), while a second sample obtained from the subject can be tested to detect the presence of an aneuploidy, wherein when the presence of one or more members of the first category of biomarkers is detected, the presence of one or more members of the second category of biomarkers is detected, and / or the presence of an aneuploidy is detected (e.g., when the presence of one or more members of the first category of biomarkers is detected, the presence of one or more members of the second category of biomarkers is detected, and the presence of an aneuploidy is detected), the subject is diagnosed or identified as having a disease (e.g., cancer) or as having a risk (e.g., an increased risk) of having or developing a disease (e.g., cancer) and / or is identified as a subject that will or is likely to respond to a treatment. As another non-limiting example, a first sample obtained from a subject can be tested to detect the presence of one or more members of a first class of biomarkers (e.g., genetic biomarkers or protein biomarkers) and to detect the presence of an aneuploidy, while a second sample obtained from the subject can be tested to detect the presence of one or more members of a second class of biomarkers (e.g., a class of biomarkers different from the first class of biomarkers tested in the first sample), wherein when the presence of one or more members of the first class of biomarkers is detected, the presence of one or more members of the second class of biomarkers is detected, and / or the presence of an aneuploidy is detected (e.g., when the presence of one or more members of the first class of biomarkers is detected, the presence of one or more members of the second class of biomarkers is detected, and the presence of an aneuploidy is detected), the subject is diagnosed or identified as having a disease (e.g., cancer) or as having a risk (e.g., an increased risk) of having or developing a disease (e.g., cancer) and / or is identified as a subject that will or is likely to respond to a treatment.

[0265] In some embodiments of identifying a subject who will or is likely to respond to a treatment by detecting the presence of one or more members (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 or more members) of one or more classes of biomarkers and / or aneuploidy in a sample obtained from the subject, the subject is identified as a subject who will or is likely to respond to a treatment of any of the various therapeutic interventions disclosed herein, including but not limited to chemotherapy. , neoadjuvant chemotherapy, radiotherapy, hormone therapy, cytotoxic therapy, immunotherapy, adoptive T cell therapy (e.g., chimeric antigen receptors and / or T cells with wild-type or modified T cell receptors), targeted therapy such as administration of kinase inhibitors (e.g., kinase inhibitors targeting specific genetic lesions (such as translocations or mutations)), (e.g., kinase inhibitors, antibodies, bispecific antibodies), signal transduction inhibitors, bispecific antibodies or antibody fragments (e.g., BiTEs), monoclonal antibodies, immune checkpoint inhibitors, surgery (e.g., surgical resection), or any combination thereof. In some embodiments in which the disease is cancer, the subject identified as a subject who will or may respond to the identified therapeutic intervention is identified as a subject in which the therapeutic intervention will or may reduce the severity of the cancer, alleviate the symptoms of the cancer, and / or reduce the number of cancer cells present in the subject.

[0266] In some embodiments, the subject of the subject who is accredited as or may be to treatment response (e.g., using any of the various methods described herein) is also identified to carry out further diagnostic testing. In some embodiments, the subject of the subject who is accredited as or may be to treatment response (e.g., using any of the various methods described herein) is also identified to increase monitoring. Additionally or alternatively, treatment (e.g., any of the various therapeutic interventions described herein) is also administered to the subject who is accredited as or may be to treatment response (e.g., using any of the various methods described herein).

[0267] Methods for identifying subjects as candidates for further diagnostic testing

[0268] Also provided herein are methods and materials for identifying a subject as a candidate for further diagnostic testing by detecting one or more members (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 or more members) of one or more classes of biomarkers and / or the presence of aneuploidy in a sample obtained from the subject. In some embodiments of identifying a subject as a candidate for further diagnostic testing, the presence of one or more members of one or more classes of biomarkers and / or the presence of aneuploidy are tested simultaneously (e.g., in a testing procedure, including embodiments in which the testing procedure itself may include multiple discrete testing methods or systems). In some embodiments of identifying a subject as a candidate for further diagnostic testing, the presence of one or more members of one or more classes of biomarkers and / or the presence of aneuploidy are tested sequentially (e.g., in two or more different testing procedures performed at two or more different time points, including embodiments in which the testing procedure itself may include multiple discrete testing methods or systems). In some embodiments that involve simultaneously testing or sequentially testing (or both) for the presence of one or more members of one or more classes of biomarkers and / or the presence of aneuploidy to identify a subject as a candidate for further diagnostic testing, the testing can be performed on a single sample, or can be performed on two or more different samples (e.g., two or more different samples obtained from the same subject).

[0269] Any of the various detection methods described herein (see, for example, the sections entitled “Detection of Genetic Biomarkers,” “Detection of Protein Biomarkers,” and “Detection of Aneuploidy”) can be used to detect the presence of one or more members of one or more classes of biomarkers and / or the presence of aneuploidy in a sample obtained from a subject. In some embodiments, one or more members of one or more classes of biomarkers and / or one or more classes of biomarkers are associated with a disease in a subject. In some embodiments, aneuploidy is associated with a disease in a subject. In some embodiments, the disease is cancer (e.g., any of the various types of cancer described herein). In some embodiments, the one or more members are members of a class of genetic biomarkers. In some embodiments, the one or more members are members of a class of protein biomarkers. In some embodiments, a method comprising identifying a subject as a candidate for further diagnostic testing by detecting the presence of one or more members of one or more classes of biomarkers in a sample obtained from a subject also comprises detecting the presence of aneuploidy in a sample obtained from the subject. For example, a method comprising identifying a subject as a candidate for further diagnostic testing by detecting the presence of one or more members of a class of genetic biomarkers in a sample obtained from the subject may also include detecting the presence of aneuploidy in a sample obtained from the subject (e.g., the same sample or two different samples from the subject). As another example, a method comprising identifying a subject as a candidate for further diagnostic testing by detecting the presence of one or more members of a class of protein biomarkers in a sample obtained from the subject may also include detecting the presence of aneuploidy in a sample obtained from the subject (e.g., the same sample or two different samples from the subject). In some embodiments, a method comprising identifying a subject as a candidate for further diagnostic testing by detecting the presence of one or more members of a class of genetic biomarkers and detecting the presence of one or more members of a class of protein biomarkers in a sample obtained from the subject may also include detecting the presence of aneuploidy in a sample obtained from the subject (e.g., the same sample or two or more different samples from the subject).

[0270] In some embodiments, provided herein are methods for identifying a subject as a candidate for further diagnostic testing, including detecting the presence of one or more members of a single class of biomarkers (e.g., genetic biomarkers or protein biomarkers) in one or more samples obtained from a subject. In some embodiments, provided herein are methods for identifying a subject as a candidate for further diagnostic testing, including detecting the presence of aneuploidy (e.g., genetic biomarkers or protein biomarkers) in one or more samples obtained from a subject. In some embodiments, provided herein are methods for identifying a subject as a candidate for further diagnostic testing, including detecting the presence of one or more members of a single class of biomarkers (e.g., genetic biomarkers or protein biomarkers) in one or more samples obtained from a subject and detecting the presence of aneuploidy in one or more samples obtained from a subject. In some embodiments, provided herein are methods for identifying a subject as a candidate for further diagnostic testing, including detecting the presence of one or more members of two or more classes of biomarkers (e.g., genetic biomarkers and protein biomarkers) in one or more samples obtained from a subject. In some embodiments, the methods provided herein for identifying a subject as a candidate for further diagnostic testing comprise detecting the presence of one or more members of two or more classes of biomarkers (e.g., genetic biomarkers and protein biomarkers) in one or more samples obtained from the subject and detecting the presence of aneuploidy in one or more samples obtained from the subject.

[0271] In some embodiments, a single sample obtained from a subject can be tested to detect the presence of one or more members of one or more classes of biomarkers and / or the presence of an aneuploidy, and when the presence of one or more members of one or more classes of biomarkers and / or the presence of an aneuploidy is detected, the subject can be diagnosed or identified as having a disease (e.g., cancer) or at risk (e.g., increased risk) of having or developing a disease (e.g., cancer) and / or the subject can be identified as a candidate for further diagnostic testing. Alternatively, two or more samples can be obtained from a subject, and each of the two or more samples can be tested separately to detect the presence of one or more members of one or more classes of biomarkers and / or the presence of an aneuploidy, and when the presence of one or more members of one or more classes of biomarkers and / or the presence of an aneuploidy is detected, the subject can be diagnosed or identified as having a risk (e.g., increased risk) of having or developing a disease (e.g., cancer) and / or the subject can be identified as a candidate for further diagnostic testing. As a non-limiting example, a first sample obtained from a subject can be tested to detect the presence of one or more members of a first category of biomarkers (e.g., genetic biomarkers), and a second sample obtained from the subject can be tested to detect the presence of one or more members of a second category of biomarkers (e.g., protein biomarkers), wherein when the presence of one or more members of the first category of biomarkers is detected and / or the presence of one or more members of the second category of biomarkers is detected (e.g., when the presence of one or more members of the category of biomarkers is detected and the presence of one or more members of the second category of biomarkers is detected), the subject is diagnosed or identified as having a disease (e.g., cancer) or as having a risk (e.g., an increased risk) of having or developing a disease (e.g., cancer) and / or the subject is identified as a candidate for further diagnostic testing. As another non-limiting example, a first sample obtained from a subject can be tested to detect the presence of one or more members of a class of biomarkers (e.g., genetic biomarkers or protein biomarkers), and a second sample obtained from the subject can be tested to detect the presence of an aneuploidy, wherein when the presence of one or more members of the class of biomarkers is detected and / or the presence of an aneuploidy is detected (e.g., when the presence of one or more members of the class of biomarkers is detected and the presence of an aneuploidy is detected), the subject is diagnosed or identified as having a disease (e.g., cancer) or as having a risk (e.g., an increased risk) of having or developing a disease (e.g., cancer) and / or the subject is identified as a candidate for further diagnostic testing.As another non-limiting example, a first sample obtained from a subject can be tested to detect the presence of one or more members of a first category of biomarkers (e.g., genetic biomarkers) and to detect the presence of one or more members of a second category of biomarkers (e.g., protein biomarkers), while a second sample obtained from the subject can be tested to detect the presence of an aneuploidy, wherein when the presence of one or more members of the first category of biomarkers is detected, the presence of one or more members of the second category of biomarkers is detected, and / or the presence of an aneuploidy is detected (e.g., when the presence of one or more members of the first category of biomarkers is detected, the presence of one or more members of the second category of biomarkers is detected, and the presence of an aneuploidy is detected), the subject is diagnosed or identified as having a disease (e.g., cancer) or as having a risk (e.g., an increased risk) of having or developing a disease (e.g., cancer) and / or is identified as a candidate for further diagnostic testing. As another non-limiting example, a first sample obtained from a subject can be tested to detect the presence of one or more members of a first class of biomarkers (e.g., genetic biomarkers or protein biomarkers) and to detect the presence of an aneuploidy, while a second sample obtained from the subject can be tested to detect the presence of one or more members of a second class of biomarkers (e.g., a class of biomarkers that is different from the first class of biomarkers tested in the first sample), wherein when the presence of one or more members of the first class of biomarkers is detected, the presence of one or more members of the second class of biomarkers is detected, and / or the presence of an aneuploidy is detected (e.g., when the presence of one or more members of the first class of biomarkers is detected, the presence of one or more members of the second class of biomarkers is detected, and the presence of an aneuploidy is detected), the subject is diagnosed or identified as having a disease (e.g., cancer) or as having a risk (e.g., an increased risk) of having or developing a disease (e.g., cancer) and / or is identified as a candidate for further diagnostic testing.

[0272] In some embodiments in which a subject is identified as a candidate for further diagnostic testing by detecting the presence of one or more members (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 or more members) of one or more classes of biomarkers and / or aneuploidy in a sample obtained from the subject, the subject undergoes any of the various types of further diagnostic testing disclosed herein, including, but not limited to, scans (e.g., computed tomography (CT), CT angiography (CTA), ), barium swallow, barium enema, magnetic resonance imaging (MRI), PET scan, positron emission tomography and computed tomography (PET-CT) scan, ultrasound (e.g., endobronchial ultrasound, endoscopic ultrasound), X-ray, or DEXA scan, or a physical examination (e.g., anoscopy, bronchoscopy (e.g., autofluorescence bronchoscopy, white light bronchoscopy, navigational bronchoscopy), colonoscopy, digital breast tomosynthesis, endoscopic retrograde cholangiopancreatography (ERCP), upper endoscopy, mammography, Pap smear, or pelvic examination).

[0273] In some embodiments, the subject of the candidate for further diagnostic testing (e.g., using any of the various methods described herein) is also accredited as a candidate for increased monitoring. Additionally or alternatively, the subject of the candidate for further diagnostic testing (e.g., using any of the various methods described herein) is also accredited as a subject who will or may be responsive to treatment. Additionally or alternatively, treatment (e.g., any of the various therapeutic interventions described herein) is also administered to the subject of the candidate for further diagnostic testing (e.g., using any of the various methods described herein).

[0274] Methods for identifying subjects as candidates for increased monitoring

[0275] Also provided herein are methods and materials for identifying a subject as a candidate for increased monitoring by detecting one or more members (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 or more members) of one or more classes of biomarkers and / or the presence of aneuploidy in a sample obtained from the subject. In some embodiments of identifying a subject as a candidate for increased monitoring, the presence of one or more members of one or more classes of biomarkers and / or the presence of aneuploidy are tested simultaneously (e.g., in a testing procedure, including embodiments in which the testing procedure itself may include multiple discrete testing methods or systems). In some embodiments of identifying a subject as a candidate for increased monitoring, the presence of one or more members of one or more classes of biomarkers and / or the presence of aneuploidy are tested sequentially (e.g., in two or more different testing procedures performed at two or more different time points, including embodiments in which the testing procedure itself may include multiple discrete testing methods or systems). In some embodiments that include simultaneously testing or sequentially testing (or both) for the presence of one or more members of one or more classes of biomarkers and / or the presence of aneuploidy to identify a subject as a candidate for increased monitoring, the testing can be performed on a single sample, or can be performed on two or more different samples (e.g., two or more different samples obtained from the same subject).

[0276] Any of the various detection methods described herein (see, for example, the sections entitled “Detection of Genetic Biomarkers,” “Detection of Protein Biomarkers,” and “Detection of Aneuploidy”) can be used to detect the presence of one or more members of one or more classes of biomarkers and / or the presence of aneuploidy in a sample obtained from a subject. In some embodiments, one or more members of one or more classes of biomarkers and / or one or more classes of biomarkers are associated with a disease in a subject. In some embodiments, aneuploidy is associated with a disease in a subject. In some embodiments, the disease is cancer (e.g., any of the various types of cancer described herein). In some embodiments, the one or more members are members of a class of genetic biomarkers. In some embodiments, the one or more members are members of a class of protein biomarkers. In some embodiments, a method comprising identifying a subject as a candidate for increased monitoring by detecting the presence of one or more members of one or more classes of biomarkers in a sample obtained from a subject also comprises detecting the presence of aneuploidy in a sample obtained from the subject. For example, a method comprising identifying a subject as a candidate for increased monitoring by detecting the presence of one or more members of a class of genetic biomarkers in a sample obtained from the subject can also include detecting the presence of aneuploidy in a sample obtained from the subject (e.g., the same sample or two different samples from the subject). As another example, a method comprising identifying a subject as a candidate for increased monitoring by detecting the presence of one or more members of a class of protein biomarkers in a sample obtained from the subject can also include detecting the presence of aneuploidy in a sample obtained from the subject (e.g., the same sample or two different samples from the subject). In some embodiments, a method comprising identifying a subject as a candidate for increased monitoring by detecting the presence of one or more members of a class of genetic biomarkers and detecting the presence of one or more members of a class of protein biomarkers in a sample obtained from the subject can also include detecting the presence of aneuploidy in a sample obtained from the subject (e.g., the same sample or two or more different samples from the subject).

[0277] In some embodiments, provided herein are methods for identifying a subject as a candidate for increasing monitoring, including the presence of one or more members of a biomarker (e.g., genetic biomarker or protein biomarker) detecting a single category in one or more samples obtained from a subject. In some embodiments, provided herein are methods for identifying a subject as a candidate for increasing monitoring, including the presence of one or more members of a biomarker (e.g., genetic biomarker or protein biomarker) detecting a single category in one or more samples obtained from a subject and detecting the presence of aneuploidy in one or more samples obtained from a subject. In some embodiments, provided herein are methods for identifying a subject as a candidate for increasing monitoring, including the presence of one or more members of a biomarker (e.g., genetic biomarker or protein biomarker) detecting a single category in one or more samples obtained from a subject and detecting the presence of aneuploidy in one or more samples obtained from a subject. In some embodiments, provided herein are methods for identifying a subject as a candidate for increasing monitoring, including the presence of one or more members of a biomarker (e.g., genetic biomarker and protein biomarker) detecting two or more categories in one or more samples obtained from a subject. In some embodiments, the methods provided herein for identifying a subject as a candidate for increased monitoring comprise detecting the presence of one or more members of two or more classes of biomarkers (e.g., genetic biomarkers and protein biomarkers) in one or more samples obtained from the subject and detecting the presence of aneuploidy in one or more samples obtained from the subject.

[0278] In some embodiments, a single sample obtained from a subject can be tested to detect the presence of one or more members of one or more classes of biomarkers and / or the presence of an aneuploidy, and when the presence of one or more members of one or more classes of biomarkers and / or the presence of an aneuploidy is detected, the subject can be diagnosed or identified as having a disease (e.g., cancer) or as having a risk (e.g., an increased risk) of having or developing a disease (e.g., cancer) and / or the subject can be identified as a candidate for increased monitoring. Alternatively, two or more samples can be obtained from a subject, and each of the two or more samples can be tested separately to detect the presence of one or more members of one or more classes of biomarkers and / or the presence of an aneuploidy, and when the presence of one or more members of one or more classes of biomarkers and / or the presence of an aneuploidy is detected, the subject can be diagnosed or identified as having a risk (e.g., an increased risk) of having or developing a disease (e.g., cancer) and / or the subject can be identified as a candidate for increased monitoring. As a non-limiting example, a first sample obtained from a subject can be tested to detect the presence of one or more members of a first category of biomarkers (e.g., genetic biomarkers), and a second sample obtained from the subject can be tested to detect the presence of one or more members of a second category of biomarkers (e.g., protein biomarkers), wherein when the presence of one or more members of the first category of biomarkers is detected and / or the presence of one or more members of the second category of biomarkers is detected (e.g., when the presence of one or more members of the category of biomarkers is detected and the presence of one or more members of the second category of biomarkers is detected), the subject is diagnosed or identified as having a disease (e.g., cancer) or as having a risk (e.g., an increased risk) of having or developing a disease (e.g., cancer) and / or the subject is identified as a candidate for increased monitoring. As another non-limiting example, a first sample obtained from a subject can be tested to detect the presence of one or more members of a class of biomarkers (e.g., genetic biomarkers or protein biomarkers), and a second sample obtained from the subject can be tested to detect the presence of an aneuploidy, wherein when the presence of one or more members of the class of biomarkers is detected and / or the presence of an aneuploidy is detected (e.g., when the presence of one or more members of the class of biomarkers is detected and the presence of an aneuploidy is detected), the subject is diagnosed or identified as having a disease (e.g., cancer) or having a risk (e.g., an increased risk) of having or developing a disease (e.g., cancer) and / or the subject is identified as a candidate for increased monitoring.As another non-limiting example, a first sample obtained from a subject can be tested to detect the presence of one or more members of a first category of biomarkers (e.g., genetic biomarkers) and to detect the presence of one or more members of a second category of biomarkers (e.g., protein biomarkers), while a second sample obtained from the subject can be tested to detect the presence of an aneuploidy, wherein when the presence of one or more members of the first category of biomarkers is detected, the presence of one or more members of the second category of biomarkers is detected, and / or the presence of an aneuploidy is detected (e.g., when the presence of one or more members of the first category of biomarkers is detected, the presence of one or more members of the second category of biomarkers is detected, and the presence of an aneuploidy is detected), the subject is diagnosed or identified as having a disease (e.g., cancer) or as having a risk (e.g., an increased risk) of having or developing a disease (e.g., cancer) and / or is identified as a candidate for increased monitoring. As another non-limiting example, a first sample obtained from a subject can be tested to detect the presence of one or more members of a first class of biomarkers (e.g., genetic biomarkers or protein biomarkers) and to detect the presence of an aneuploidy, while a second sample obtained from the subject can be tested to detect the presence of one or more members of a second class of biomarkers (e.g., a class of biomarkers different from the first class of biomarkers tested in the first sample), wherein when the presence of one or more members of the first class of biomarkers is detected, the presence of one or more members of the second class of biomarkers is detected, and / or the presence of an aneuploidy is detected (e.g., when the presence of one or more members of the first class of biomarkers is detected, the presence of one or more members of the second class of biomarkers is detected, and the presence of an aneuploidy is detected), the subject is diagnosed or identified as having a disease (e.g., cancer) or as having a risk (e.g., an increased risk) of having or developing a disease (e.g., cancer) and / or is identified as a candidate for increased monitoring.

[0279] In some embodiments, the subject of the candidate for being accredited to increase monitoring (for example, using any of the various methods described herein) is also accredited as a candidate for further diagnostic testing. Additionally or alternatively, the subject of the candidate for being accredited to increase monitoring (for example, using any of the various methods described herein) is also accredited as will or may be to treatment-responsive subject. Additionally or alternatively, treatment (for example, any of the various therapeutic interventions described herein) is also administered to the subject of the candidate for being accredited to increase monitoring (for example, using any of the various methods described herein).

[0280] Combination of genetic and protein biomarkers

[0281] In one aspect, provided herein are methods and materials for detecting the presence of one or more members of a genetic biomarker panel and one or more members of a protein biomarker panel in one or more samples obtained from a subject. In another aspect, provided herein are methods and materials for diagnosing or identifying the presence of a disease in a subject (e.g., identifying a subject as having cancer) by detecting the presence of one or more members of a genetic biomarker panel and one or more members of a protein biomarker panel in one or more samples obtained from a subject. In another aspect, provided herein are methods and materials for identifying a subject as having (e.g., having an increased risk of) having or developing a disease (e.g., cancer) by detecting the presence of one or more members of a genetic biomarker panel and one or more members of a protein biomarker panel in one or more samples obtained from a subject. In another aspect, provided herein are methods and materials for treating a subject who has been diagnosed or identified as having a disease (e.g., cancer) or has been identified as having (e.g., having an increased risk of) having or developing a disease (e.g., cancer) by detecting the presence of one or more members of a genetic biomarker panel and one or more members of a protein biomarker panel in one or more samples obtained from a subject. In another aspect, provided herein are methods and materials for identifying a treatment for a subject who has been diagnosed or identified as having a disease (e.g., cancer) or has been identified as having a risk (e.g., increased risk) of having or developing a disease (e.g., cancer) by detecting the presence of one or more members of a genetic biomarker panel and one or more members of a protein biomarker panel in one or more samples obtained from the subject. In another aspect, provided herein are methods and materials for identifying a subject who will or is likely to respond to a treatment by detecting the presence of one or more members of a genetic biomarker panel and one or more members of a protein biomarker panel in one or more samples obtained from the subject. In another aspect, provided herein are methods and materials for identifying a subject as a candidate for further diagnostic testing by detecting the presence of one or more members of a genetic biomarker panel and one or more members of a protein biomarker panel in one or more samples obtained from the subject. In another aspect, provided herein are methods and materials for identifying a subject as a candidate for increased monitoring by detecting the presence of one or more members of a genetic biomarker panel and one or more members of a protein biomarker panel in one or more samples obtained from the subject.

[0282] In some embodiments, the methods provided herein comprising detecting the presence of one or more members of a genetic biomarker panel and the presence of one or more members of a protein biomarker panel in one or more samples obtained from a subject provide high sensitivity in the detection or diagnosis of cancer (e.g., a high frequency or incidence of correctly identifying a subject as having cancer). In some embodiments, the methods provided herein comprising detecting the presence of one or more members of a genetic biomarker panel and the presence of one or more members of a protein biomarker panel in one or more samples obtained from a subject provide greater sensitivity in the detection or diagnosis of cancer (e.g., a high frequency or incidence of correctly identifying a subject as having cancer) than the sensitivity provided by detecting the presence of one or more members of a genetic biomarker panel or the presence of one or more members of a protein biomarker panel, respectively. In some embodiments, the methods and materials provided herein comprising detecting the presence of one or more members of a genetic biomarker panel and the presence of one or more members of a protein biomarker panel in one or more samples obtained from a subject provide a sensitivity of at least about 70%, at least about 75%, at least about 80%, at least about 85%, at least about 90%, at least about 91%, at least about 92%, at least about 93%, at least about 94%, at least about 95%, at least about 96%, at least about 97%, at least about 98%, at least about 99% or more. In some embodiments, the methods and materials provided herein comprising detecting the presence of one or more members of a genetic biomarker panel and the presence of one or more members of a protein biomarker panel in one or more samples obtained from a subject provide high sensitivity in detecting a single type of cancer. In some embodiments, the methods and materials provided herein comprising detecting the presence of one or more members of a genetic biomarker panel and the presence of one or more members of a protein biomarker panel in one or more samples obtained from a subject provide high sensitivity in detecting two or more types of cancer. Any of a variety of cancer types can be detected using the methods and materials provided herein (see, e.g., the section entitled "Cancer"). In some embodiments, cancers that can be detected using the methods and materials comprising detecting the presence of one or more members of a genetic biomarker panel and the presence of one or more members of a protein biomarker panel in one or more samples obtained from a subject include pancreatic cancer. In some embodiments, cancers that can be detected using the methods and materials comprising detecting the presence of one or more members of a genetic biomarker panel and the presence of one or more members of a protein biomarker panel in one or more samples obtained from a subject include liver cancer, ovarian cancer, esophageal cancer, gastric cancer, pancreatic cancer, colorectal cancer, lung cancer, or breast cancer.In some embodiments, cancers that can be detected using methods and materials comprising detecting the presence of one or more members of a genetic biomarker panel and the presence of one or more members of a protein biomarker panel in one or more samples obtained from a subject include cancers of the female reproductive tract (e.g., cervical cancer, endometrial cancer, ovarian cancer, or fallopian tube cancer). In some embodiments, cancers that can be detected using methods and materials comprising detecting the presence of one or more members of a genetic biomarker panel and the presence of one or more members of a protein biomarker panel in one or more samples obtained from a subject include bladder cancer or upper urinary tract urothelial cancer.

[0283] In some embodiments, the methods provided herein comprising detecting the presence of one or more members of a genetic biomarker panel and the presence of one or more members of a protein biomarker panel in one or more samples obtained from a subject provide high specificity in the detection or diagnosis of cancer (e.g., a low frequency or incidence of falsely identifying a subject as having cancer when the subject does not have cancer). In some embodiments, the methods provided herein comprising detecting the presence of one or more members of a genetic biomarker panel and the presence of one or more members of a protein biomarker panel in one or more samples obtained from a subject provide higher specificity in the detection or diagnosis of cancer (e.g., a high frequency or incidence of correctly identifying a subject as having cancer) than the specificity provided by detecting the presence of one or more members of a genetic biomarker panel or the presence of one or more members of a protein biomarker panel, respectively. In some embodiments, the methods and materials provided herein comprising detecting the presence of one or more members of a genetic biomarker panel and the presence of one or more members of a protein biomarker panel in one or more samples obtained from a subject provide a specificity of at least about 70%, at least about 75%, at least about 80%, at least about 85%, at least about 90%, at least about 91%, at least about 92%, at least about 93%, at least about 94%, at least about 95%, at least about 96%, at least about 97%, at least about 98%, at least about 99% or more. As will be understood by one of ordinary skill in the art, a specificity of 99% means that only 1% of subjects without cancer are incorrectly identified as having cancer. In some embodiments, the methods and materials provided herein comprising detecting the presence of one or more members of a genetic biomarker panel and the presence of one or more members of a protein biomarker panel in one or more samples obtained from a subject provide high specificity (e.g., a very low probability of incorrectly identifying the subject as having the single cancer type) when detecting a single cancer. In some embodiments, the methods and materials provided herein, which include detecting the presence of one or more members of a genetic biomarker panel and the presence of one or more members of a protein biomarker panel in one or more samples obtained from a subject, provide high specificity in detecting two or more cancers (e.g., a very low probability of falsely identifying that the subject has the two or more types of cancer).

[0284] In some embodiments, the methods provided herein comprising detecting the presence of one or more members of a genetic biomarker panel and the presence of one or more members of a protein biomarker panel in one or more samples obtained from a subject comprise detecting the presence of 1) one or more (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, or 16) of the following genes: NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A, and / or GNAS, and 2) one or more (e.g., 1, 2, 3, 4, 5, 6, 7, or 8) of the following protein biomarkers: CA19-9, CEA, HGF, OPN, CA125, prolactin, TIMP-1, and / or myeloperoxidase (MPO). In some embodiments, the methods provided herein comprising detecting the presence of one or more members of a genetic biomarker panel and the presence of one or more members of a protein biomarker panel in one or more samples obtained from a subject comprise detecting the presence of: 1) one or more genetic biomarkers in each of the following genes: NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A, and GNAS, and 2) one or more (e.g., 1, 2, 3, 4, 5, 6, 7, or 8) of the following protein biomarkers: CA19-9, CEA, HGF, OPN, CA125, prolactin, TIMP-1, and / or myeloperoxidase (MPO). In some embodiments, the methods provided herein comprising detecting the presence of one or more members of a genetic biomarker panel and the presence of one or more members of a protein biomarker panel in one or more samples obtained from a subject comprise detecting the presence of: 1) one or more (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, or 16) of the following genes: NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A, and / or GNAS, and 2) each of the following protein biomarkers: CA19-9, CEA, HGF, OPN, CA125, prolactin, TIMP-1, and myeloperoxidase (MPO).In some embodiments, the methods provided herein comprising detecting the presence of one or more members of a genetic biomarker panel and the presence of one or more members of a protein biomarker panel in one or more samples obtained from a subject comprise detecting the presence of: 1) one or more genetic biomarkers in each of the following genes: NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A and / or GNAS, and 2) each of the following protein biomarkers: CA19-9, CEA, HGF, OPN, CA125, prolactin, TIMP-1 and / or myeloperoxidase (MPO). In some embodiments, the methods provided herein comprising detecting the presence of one or more members of a genetic biomarker panel and one or more members of a protein biomarker panel in one or more samples obtained from a subject comprise detecting the presence of: 1) one or more (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, or 16) of one or more genetic biomarkers in the following genes: NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRA S, KRAS, AKT1, TP53, PPP2R1A and / or GNAS, and 2) one or more (e.g., 1, 2, 3, 4, 5, 6, 7 or 8) of the following protein biomarkers: CA19-9, CEA, HGF, OPN, CA125, prolactin, TIMP-1 and / or myeloperoxidase (MPO), the subject being determined to have (e.g., diagnosed as having) one of the following types of cancer or being determined (e.g., diagnosed as having) an elevated risk of having or developing one of the following types of cancer: liver cancer, ovarian cancer, esophageal cancer, gastric cancer, pancreatic cancer, colorectal cancer, lung cancer and / or breast cancer.

[0285] In some embodiments, the methods provided herein comprising detecting the presence of one or more members of a genetic biomarker panel and one or more members of a protein biomarker panel in one or more samples obtained from a subject comprise detecting the presence of: 1) one or more (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, or 16) of the following genes: NRAS, CTNNB1, PIK3CA, F BXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A and / or GNAS, and 2) one or more (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 or 11) of the following protein biomarkers: CA19-9, CEA, HGF, OPN, CA125, AFP, prolactin, TIMP-1, follistatin, G-CSF and / or CA15-3. In some embodiments, the methods provided herein comprising detecting the presence of one or more members of a genetic biomarker panel and the presence of one or more members of a protein biomarker panel in one or more samples obtained from a subject comprise detecting the presence of: 1) one or more genetic biomarkers in each of the following genes: NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A, and GNAS, and 2) one or more (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or 11) of the following protein biomarkers: CA19-9, CEA, HGF, OPN, CA125, AFP, prolactin, TIMP-1, follistatin, G-CSF, and / or CA15-3.In some embodiments, the methods provided herein comprising detecting the presence of one or more members of a genetic biomarker panel and the presence of one or more members of a protein biomarker panel in one or more samples obtained from a subject comprise detecting the presence of: 1) one or more (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, or 16) of the following genes: NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A, and / or GNAS, and 2) each of the following protein biomarkers: CA19-9, CEA, HGF, OPN, CA125, AFP, prolactin, TIMP-1, follistatin, G-CSF, and CA15-3. In some embodiments, the methods provided herein comprising detecting the presence of one or more members of a genetic biomarker panel and the presence of one or more members of a protein biomarker panel in one or more samples obtained from a subject comprise detecting the presence of: 1) one or more genetic biomarkers in each of the following genes: NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A and / or GNAS, and 2) each of the following protein biomarkers: CA19-9, CEA, HGF, OPN, CA125, AFP, prolactin, TIMP-1, follistatin, G-CSF and / or CA15-3.In some embodiments, the methods provided herein comprising detecting the presence of one or more members of a genetic biomarker panel and one or more members of a protein biomarker panel in one or more samples obtained from a subject comprise detecting the presence of: 1) one or more (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, or 16) of one or more genetic biomarkers in the following genes: NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, S, AKT1, TP53, PPP2R1A and / or GNAS, and 2) one or more (e.g., 1, 2, 3, 4, 5, 6, 7 or 8) of the following protein biomarkers: CA19-9, CEA, HGF, OPN, CA125, AFP, prolactin, TIMP-1, follistatin, G-CSF and / or CA15-3, the subject being determined to have (e.g., diagnosed as having) one of the following types of cancer or being determined (e.g., diagnosed as having) an elevated risk of having or developing one of the following types of cancer: liver cancer, ovarian cancer, esophageal cancer, gastric cancer, pancreatic cancer, colorectal cancer, lung cancer and / or breast cancer.

[0286] In some embodiments, the methods provided herein comprising detecting the presence of one or more members of a genetic biomarker panel and the presence of one or more members of a protein biomarker panel in one or more samples obtained from a subject comprise detecting the presence of 1) one or more (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, or 16) of the following genes: NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A, and / or GNAS, and 2) one or more (e.g., 1, 2, 3, 4, 5, 6, 7, 8, or 9) of the following protein biomarkers: CA19-9, CEA, HGF, OPN, CA125, AFP, prolactin, TIMP-1, and / or CA15-3. In some embodiments, the methods provided herein comprising detecting the presence of one or more members of a genetic biomarker panel and the presence of one or more members of a protein biomarker panel in one or more samples obtained from a subject comprise detecting the presence of: 1) one or more genetic biomarkers in each of the following genes: NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A, and GNAS, and 2) one or more (e.g., 1, 2, 3, 4, 5, 6, 7, 8, or 9) of the following protein biomarkers: CA19-9, CEA, HGF, OPN, CA125, AFP, prolactin, TIMP-1, and / or CA15-3. In some embodiments, the methods provided herein comprising detecting the presence of one or more members of a genetic biomarker panel and the presence of one or more members of a protein biomarker panel in one or more samples obtained from a subject comprise detecting the presence of: 1) one or more (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, or 16) of the following genes: NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A, and / or GNAS, and 2) each of the following protein biomarkers: CA19-9, CEA, HGF, OPN, CA125, AFP, prolactin, TIMP-1, and CA15-3.In some embodiments, the methods provided herein comprising detecting the presence of one or more members of a genetic biomarker panel and the presence of one or more members of a protein biomarker panel in one or more samples obtained from a subject comprise detecting the presence of: 1) one or more genetic biomarkers in each of the following genes: NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A, and GNAS, and 2) each of the following protein biomarkers: CA19-9, CEA, HGF, OPN, CA125, AFP, prolactin, TIMP-1, and CA15-3. In some embodiments, the methods provided herein comprising detecting the presence of one or more members of a genetic biomarker panel and one or more members of a protein biomarker panel in one or more samples obtained from a subject comprise detecting the presence of: 1) one or more (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, or 16) of one or more genetic biomarkers in the following genes: NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRA S, KRAS, AKT1, TP53, PPP2R1A and / or GNAS, and 2) one or more (e.g., 1, 2, 3, 4, 5, 6, 7 or 8) of the following protein biomarkers: CA19-9, CEA, HGF, OPN, CA125, AFP, prolactin, TIMP-1 and / or CA15-3, the subject being determined to have (e.g., diagnosed as having) one of the following types of cancer or being determined (e.g., diagnosed as having) an elevated risk of having or developing one of the following types of cancer: liver cancer, ovarian cancer, esophageal cancer, gastric cancer, pancreatic cancer, colorectal cancer, lung cancer and / or breast cancer.

[0287] In some embodiments, the methods provided herein comprising detecting the presence of one or more members of a genetic biomarker panel and the presence of one or more members of a protein biomarker panel in one or more samples obtained from a subject comprise detecting the presence of 1) one or more (e.g., 1, 2, 3, or 4) of the following genetic biomarkers: KRAS (e.g., genetic biomarkers in codons 12 and / or 61), TP53, CDKN2A, and / or SMAD4, and 2) one or more (e.g., 1, 2, 3, or 4) of the following protein biomarkers: CA19-9, CEA, HGF, and / or OPN. In some embodiments, the methods provided herein comprising detecting the presence of one or more members of a genetic biomarker panel and the presence of one or more members of a protein biomarker panel in one or more samples obtained from a subject comprise detecting the presence of: 1) one or more genetic biomarkers in each of the following genes: KRAS (e.g., genetic biomarkers in codons 12 and / or 61), TP53, CDKN2A, and SMAD4, and 2) one or more (e.g., 1, 2, 3, or 4) of the following protein biomarkers: CA19-9, CEA, HGF, and / or OPN. In some embodiments, the methods provided herein comprising detecting the presence of one or more members of a genetic biomarker panel and the presence of one or more members of a protein biomarker panel in one or more samples obtained from a subject comprise detecting the presence of 1) one or more genetic biomarkers in one or more (e.g., 1, 2, 3, or 4) of the following genes: KRAS (e.g., genetic biomarkers in codons 12 and / or 61), TP53, CDKN2A, and / or SMAD4, and 2) each of the following protein biomarkers: CA19-9, CEA, HGF, and OPN. In some embodiments, the methods provided herein comprising detecting the presence of one or more members of a genetic biomarker panel and the presence of one or more members of a protein biomarker panel in one or more samples obtained from a subject comprise detecting the presence of 1) one or more genetic biomarkers in each of the following genes: KRAS (e.g., genetic biomarkers in codons 12 and / or 61), TP53, CDKN2A, and SMAD4, and 2) each of the following protein biomarkers: CA19-9, CEA, HGF, and OPN.In some embodiments, the methods provided herein comprising detecting the presence of one or more members of a genetic biomarker panel and the presence of one or more members of a protein biomarker panel in one or more samples obtained from a subject comprise detecting the presence of 1) one or more genetic biomarkers in one or more (e.g., 1, 2, 3, or 4) of the following genes: KRAS (e.g., genetic biomarkers in codons 12 and / or 61), TP53, CDKN2A, and / or SMAD4, and 2) one or more (e.g., 1, 2, 3, or 4) of the following protein biomarkers: CA19-9, CEA, HGF, and / or OPN, the subject being determined to have (e.g., diagnosed as having) pancreatic cancer or being determined (e.g., diagnosed as) to have an elevated risk of having or developing pancreatic cancer.

[0288] The sample obtained from the subject can be any of the various samples comprising cell-free DNA (e.g., ctDNA) and / or protein as described herein. In some embodiments, the cell-free DNA (e.g., ctDNA) and / or protein in the sample obtained from the subject are derived from tumor cells. In some embodiments, the cell-free DNA (e.g., ctDNA) in the sample obtained from the subject includes one or more genetic biomarkers. In some embodiments, the protein in the sample obtained from the subject includes one or more protein biomarkers. Non-limiting examples of samples in which genetic biomarkers and / or protein biomarkers can be detected include blood, plasma, and serum. In some embodiments, the presence of one or more genetic biomarkers and the presence of one or more protein biomarkers are detected in a single sample obtained from the subject. In some embodiments, the presence of one or more genetic biomarkers is detected in a first sample obtained from the subject, and the presence of one or more protein biomarkers is detected in a second sample obtained from the subject.

[0289] In some embodiments, the methods provided herein include detecting the presence of one or more members of a genetic biomarker panel (e.g., each member of a genetic biomarker panel) and the presence of one or more members of a protein biomarker panel (e.g., each member of a protein biomarker panel) in one or more samples obtained from a subject, and detecting elevated levels of one or more members of the protein biomarker panel. For example, an elevated level of a protein biomarker can be a level that is higher than a reference level. A reference level can be any level of a protein biomarker that is not associated with the presence of cancer. For example, a reference level of a protein biomarker can be a level present in a reference subject that does not have cancer or does not carry cancer cells. A reference level of a protein biomarker can be an average level present in multiple reference subjects that do not have cancer or do not carry cancer cells. A reference level of a protein biomarker in a subject determined to have cancer can be a level present in the subject before the onset of cancer. In some embodiments, the protein biomarker panel wherein one or more members of the protein biomarker panel are present at elevated levels comprises one or more (e.g., 1, 2, 3, 4, 5, 6, 7, or each) of the following: CA19-9, CEA, HGF, OPN, CA125, prolactin, TIMP-1, and / or myeloperoxidase (MPO). In some embodiments, the protein biomarker panel wherein one or more members of the protein biomarker panel are present at elevated levels comprises one or more (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10, or each) of the following: CA19-9, CEA, HGF, OPN, CA125, AFP, prolactin, TIMP-1, follistatin, G-CSF, and / or CA15-3. In some embodiments, the protein biomarker panel wherein one or more members of the protein biomarker panel are present at elevated levels comprises one or more (e.g., 1, 2, 3, 4, 5, 6, 7, 8, or each) of the following: CA19-9, CEA, HGF, OPN, CA125, AFP, prolactin, TIMP-1, and / or CA15-3. In some embodiments, the protein biomarker panel wherein one or more members of the protein biomarker panel are present at elevated levels comprises one or more (e.g., 1, 2, 3, or each) of the following: CA19-9, CEA, HGF, and / or OPN.

[0290] In some embodiments, the methods provided herein include detecting the presence of one or more members of a genetic biomarker panel (e.g., each member of a genetic biomarker panel) and the presence of one or more members of a protein biomarker panel (e.g., each member of a protein biomarker panel) in one or more samples obtained from a subject, and detecting a reduced level of one or more members of the protein biomarker panel. For example, the reduced level of a protein biomarker can be a level below a reference level. The reference level can be any level of a protein biomarker that is not associated with the presence of cancer. For example, the reference level of a protein biomarker can be a level present in a reference subject that does not have cancer or does not carry cancer cells. The reference level of a protein biomarker can be an average level present in multiple reference subjects that do not have cancer or do not carry cancer cells. The reference level of a protein biomarker in a subject determined to have cancer can be a level present in the subject before the onset of cancer. In some embodiments, the protein biomarker panel wherein one or more members of the protein biomarker panel are present at reduced levels comprises one or more (e.g., 1, 2, 3, 4, 5, 6, 7, or each) of the following: CA19-9, CEA, HGF, OPN, CA125, prolactin, TIMP-1, and / or myeloperoxidase (MPO). In some embodiments, the protein biomarker panel wherein one or more members of the protein biomarker panel are present at reduced levels comprises one or more (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10, or each) of the following: CA19-9, CEA, HGF, OPN, CA125, AFP, prolactin, TIMP-1, follistatin, G-CSF, and / or CA15-3. In some embodiments, the protein biomarker panel wherein one or more members of the protein biomarker panel are present at reduced levels comprises one or more (e.g., 1, 2, 3, 4, 5, 6, 7, 8, or each) of the following: CA19-9, CEA, HGF, OPN, CA125, AFP, prolactin, TIMP-1, and / or CA15-3. In some embodiments, the protein biomarker panel wherein one or more members of the protein biomarker panel are present at reduced levels comprises one or more (e.g., 1, 2, 3, or each) of the following: CA19-9, CEA, HGF, and / or OPN.

[0291] In some embodiments, when a subject is determined to have (e.g., diagnosed to have) cancer or is determined to have (e.g., diagnosed to have) an elevated risk of having or developing cancer (e.g., by detecting: 1) the presence of one or more (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, or 16) of one or more genetic biomarkers in the following genes: NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A, and / or GNAS, and 2) one or more proteins in any of the panels described herein as useful with the genetic biomarker panel. In some embodiments, the subject is selected as a candidate for further diagnostic testing (e.g., any of the various further diagnostic testing methods described herein) when a biomarker is detected, the subject is selected as a candidate for increased monitoring (e.g., any of the various increased monitoring methods described herein) (e.g., selected for increased monitoring), the subject is identified as a subject who will or is likely to respond to treatment (e.g., any of the various therapeutic interventions described herein), the subject is selected as a candidate for treatment (e.g., selected for treatment), a treatment for the subject (e.g., any of the various therapeutic interventions described herein) is selected, and / or a treatment (e.g., any of the various therapeutic interventions described herein) is administered to the subject. For example, when a subject is determined to have (e.g., be diagnosed as having) cancer or is determined to have (e.g., be diagnosed as) having an elevated risk of having or developing cancer, the subject can undergo further diagnostic testing that can confirm the presence of cancer in the subject. Additionally or alternatively, the subject can be monitored at an increased frequency. In some embodiments where a subject is determined to have (e.g., be diagnosed as having) cancer or is determined to have (e.g., be diagnosed as) an elevated risk of having or developing cancer, wherein the subject undergoes further diagnostic testing and / or increased monitoring, an additional therapeutic intervention may be administered to the subject. In some embodiments, after a therapeutic intervention is administered to a subject, the subject undergoes additional further diagnostic testing (e.g., further diagnostic testing of the same type as previously performed and / or further diagnostic testing of a different type) and / or continues to increase monitoring (e.g., increased monitoring performed at the same or different frequency as previously). In embodiments, after a therapeutic intervention is administered to a subject and the subject undergoes additional further diagnostic testing and / or additional increased monitoring, another therapeutic intervention (e.g., the same therapeutic intervention as previously administered and / or a different therapeutic intervention) is administered to the subject.In some embodiments, after administering a therapeutic intervention to a subject, the subject is tested for the presence of one or more (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, or 16) of the following genes: NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A, and / or GNAS, and 2) one or more protein biomarkers from any panel described herein as useful with the genetic biomarker panel.

[0292] In some embodiments, the methods provided herein that include detecting the presence of one or more members of a genetic biomarker panel and the presence of one or more members of a protein biomarker panel in one or more samples obtained from a subject further include detecting the presence of an aneuploidy in a sample obtained from the subject (e.g., the same sample used to detect the presence of one or more members of the genetic biomarker panel and the presence of one or more members of the protein biomarker panel, or a different sample). The presence of an aneuploidy can be detected in any chromosome or portion thereof (e.g., an arm of a chromosome). In some embodiments of the methods that include detecting the presence of genetic biomarkers, protein biomarkers, and aneuploidy, the presence of an aneuploidy is detected on one or more of chromosome arms 5q, 8q, and 9p. In some embodiments of the methods that include detecting the presence of genetic biomarkers, protein biomarkers, and aneuploidy, the presence of an aneuploidy is detected on one or more of chromosome arms 4p, 7q, 8q, and 9q.

[0293] In some embodiments of the methods provided herein that include detecting in one or more samples obtained from a subject the presence of: 1) one or more (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, or 16) of the following genes: NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R 1A and / or GNAS, and 2) one or more (e.g., 1, 2, 3, 4, 5, 6, 7, or 8) of the following protein biomarkers: CA19-9, CEA, HGF, OPN, CA125, prolactin, TIMP-1, and / or myeloperoxidase (MPO), the method further comprising detecting the presence of aneuploidy in a sample obtained from the subject (e.g., the same sample or a different sample used to detect one or both of the presence of one or more members of the genetic biomarker panel and the presence of one or more members of the protein biomarker panel). In some embodiments of the methods provided herein that include detecting in one or more samples obtained from a subject the presence of: 1) one or more genetic biomarkers in each of the following genes: NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A, and GNAS, and 2) one or more (e.g., 1, 2, 3, 4, 5, 6, 7, or 8) of the following protein biomarkers: CA19-9, CEA, HGF, OPN, CA125, prolactin, TIMP-1, and / or myeloperoxidase (MPO), the method further comprises detecting the presence of aneuploidy in the sample obtained from the subject (e.g., the same sample or a different sample used to detect one or both of the presence of one or more members of the genetic biomarker panel and the presence of one or more members of the protein biomarker panel).In some embodiments of the methods provided herein that include detecting in one or more samples obtained from a subject the presence of: 1) one or more (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, or 16) of one or more genetic biomarkers in the following genes: NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A, and / or GNAS, and 2) each of the following protein biomarkers: CA19-9, CEA, HGF, OPN, CA125, prolactin, TIMP-1, and myeloperoxidase (MPO), the method further comprises detecting in the sample obtained from the subject (e.g., the same sample or a different sample used to detect one or both of the presence of one or more members of the genetic biomarker panel and the presence of one or more members of the protein biomarker panel) the presence of aneuploidy. In some embodiments of the methods provided herein that include detecting in one or more samples obtained from a subject the presence of: 1) one or more genetic biomarkers in each of the following genes: NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A, and / or GNAS, and 2) each of the following protein biomarkers: CA19-9, CEA, HGF, OPN, CA125, prolactin, TIMP-1, and / or myeloperoxidase (MPO), the method further comprises detecting the presence of aneuploidy in the sample obtained from the subject (e.g., the same sample or a different sample used to detect one or both of the presence of one or more members of the genetic biomarker panel and the presence of one or more members of the protein biomarker panel).In some embodiments of the methods provided herein that include detecting in one or more samples obtained from a subject the presence of: 1) one or more (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, or 16) of the following genes: NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A, and / or GNAS, 2) one or more (e.g., 1, 2, 3, 4, 5, 6, 7, or 8) of the following protein biomarkers: CA19-9, CEA, HGF, OPN, CA125, prolactin, TIMP-1, and / or myeloperoxidase (MPO), and 3) the presence of aneuploidy, the subject is determined to have (e.g., is diagnosed as having) the following types of cancer or is determined to have (e.g., is diagnosed as having) an elevated risk of having or developing one of the following types of cancer: liver cancer, ovarian cancer, esophageal cancer, gastric cancer, pancreatic cancer, colorectal cancer, lung cancer, and / or breast cancer.

[0294] In some embodiments of the methods provided herein that include detecting in one or more samples obtained from a subject the presence of: 1) one or more (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, or 16) of the following genes: NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A, and / or GNAS , and 2) one or more (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or 11) of the following protein biomarkers: CA19-9, CEA, HGF, OPN, CA125, AFP, prolactin, TIMP-1, follistatin, G-CSF, and / or CA15-3, the method further comprising detecting the presence of aneuploidy in a sample obtained from the subject (e.g., the same sample or a different sample used to detect one or both of the presence of one or more members of the genetic biomarker panel and the presence of one or more members of the protein biomarker panel). In some embodiments of the methods provided herein that include detecting in one or more samples obtained from a subject the presence of: 1) one or more genetic biomarkers in each of the following genes: NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A, and GNAS, and 2) one or more (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or 11) of the following protein biomarkers: CA19-9, CEA, HGF, OPN, CA125, AFP, prolactin, TIMP-1, follistatin, G-CSF, and / or CA15-3, the method further comprises detecting in a sample obtained from the subject (e.g., the same sample or a different sample used to detect one or both of the presence of one or more members of the genetic biomarker panel and the presence of one or more members of the protein biomarker panel) the presence of aneuploidy.In some embodiments, the methods provided herein comprising detecting the presence of one or more members of a genetic biomarker panel and one or more members of a protein biomarker panel in one or more samples obtained from a subject comprise detecting the presence of: 1) one or more (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, or 16) of the following genes: NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, F GFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A and / or GNAS, and 2) each of the following protein biomarkers: CA19-9, CEA, HGF, OPN, CA125, AFP, prolactin, TIMP-1, follistatin, G-CSF and CA15-3, the method further comprising detecting the presence of aneuploidy in a sample obtained from the subject (e.g., the same sample or a different sample used to detect one or both of the presence of one or more members of the genetic biomarker panel and the presence of one or more members of the protein biomarker panel). In some embodiments of the methods provided herein of detecting in one or more samples obtained from a subject the presence of: 1) one or more genetic biomarkers in each of the following genes: NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A, and / or GNAS, and 2) each of the following protein biomarkers: CA19-9, CEA, HGF, OPN, CA125, AFP, prolactin, TIMP-1, follistatin, G-CSF, and / or CA15-3, the method further comprises detecting the presence of aneuploidy in a sample obtained from the subject (e.g., the same sample or a different sample used to detect one or both of the presence of one or more members of the genetic biomarker panel and the presence of one or more members of the protein biomarker panel).In some embodiments of the methods provided herein, detecting in one or more samples obtained from a subject the presence of: 1) one or more (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, or 16) of one or more genetic biomarkers in the following genes: NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A, and / or GNAS, 2) One or more (e.g., 1, 2, 3, 4, 5, 6, 7, or 8) of the following protein biomarkers: CA19-9, CEA, HGF, OPN, CA125, AFP, prolactin, TIMP-1, follistatin, G-CSF, and / or CA15-3, and 3) the presence of aneuploidy, the subject is determined to have (e.g., is diagnosed as having) one of the following types of cancer or is determined to have (e.g., is diagnosed as having an elevated risk of having or developing one of the following types of cancer: liver cancer, ovarian cancer, esophageal cancer, gastric cancer, pancreatic cancer, colorectal cancer, lung cancer, and / or breast cancer.

[0295] In some embodiments of the methods provided herein that include detecting in one or more samples obtained from a subject the presence of: 1) one or more (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, or 16) of the following genes: NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R 1A and / or GNAS, and 2) one or more (e.g., 1, 2, 3, 4, 5, 6, 7, 8, or 9) of the following protein biomarkers: CA19-9, CEA, HGF, OPN, CA125, AFP, prolactin, TIMP-1, and / or CA15-3, the method further comprising detecting the presence of aneuploidy in a sample obtained from the subject (e.g., the same sample or a different sample used to detect one or both of the presence of one or more members of the genetic biomarker panel and the presence of one or more members of the protein biomarker panel). In some embodiments of the methods provided herein that include detecting in one or more samples obtained from a subject the presence of: 1) one or more genetic biomarkers in each of the following genes: NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A, and GNAS, and 2) one or more (e.g., 1, 2, 3, 4, 5, 6, 7, 8, or 9) of the following protein biomarkers: CA19-9, CEA, HGF, OPN, CA125, AFP, prolactin, TIMP-1, and / or CA15-3, the method further comprises detecting the presence of aneuploidy in a sample obtained from the subject (e.g., the same sample or a different sample used to detect one or both of the presence of one or more members of the genetic biomarker panel and the presence of one or more members of the protein biomarker panel).In some embodiments of the methods provided herein that include detecting in one or more samples obtained from a subject the presence of: 1) one or more (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, or 16) of one or more genetic biomarkers in the following genes: NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A, and / or GNAS, and 2) each of the following protein biomarkers: CA19-9, CEA, HGF, OPN, CA125, AFP, prolactin, TIMP-1, and CA15-3, the method further comprises detecting in the sample obtained from the subject (e.g., the same sample or a different sample used to detect one or both of the presence of one or more members of the genetic biomarker panel and the presence of one or more members of the protein biomarker panel) the presence of aneuploidy. In some embodiments of the methods provided herein that include detecting in one or more samples obtained from a subject the presence of: 1) one or more genetic biomarkers in each of the following genes: NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A, and GNAS, and 2) each of the following protein biomarkers: CA19-9, CEA, HGF, OPN, CA125, AFP, prolactin, TIMP-1, and CA15-3, the method further comprises detecting the presence of aneuploidy in a sample obtained from the subject (e.g., the same sample or a different sample used to detect one or both of the presence of one or more members of the genetic biomarker panel and the presence of one or more members of the protein biomarker panel).In some embodiments of the methods provided herein that include detecting in one or more samples obtained from a subject the presence of: 1) one or more (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, or 16) of the following genes: NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A, and / or G NAS, 2) one or more (e.g., 1, 2, 3, 4, 5, 6, 7, or 8) of the following protein biomarkers: CA19-9, CEA, HGF, OPN, CA125, AFP, prolactin, TIMP-1, and / or CA15-3, and 3) the presence of aneuploidy, the subject is determined to have (e.g., is diagnosed as having) one of the following types of cancer or is determined to have (e.g., is diagnosed as having) an elevated risk of having or developing one of the following types of cancer: liver cancer, ovarian cancer, esophageal cancer, gastric cancer, pancreatic cancer, colorectal cancer, lung cancer, and / or breast cancer.

[0296] In some embodiments of the methods provided herein that include detecting in one or more samples obtained from a subject the presence of: 1) one or more (e.g., 1, 2, 3, or 4) of one or more genetic biomarkers in the following genes: KRAS (e.g., genetic biomarkers in codons 12 and / or 61), TP53, CDKN2A, and / or SMAD4, and 2) one or more (e.g., 1, 2, 3, or 4) of the following protein biomarkers: CA19-9, CEA, HGF, and / or OPN, the method further comprises detecting the presence of aneuploidy in the sample obtained from the subject (e.g., the same sample or a different sample used to detect one or both of the presence of one or more members of the genetic biomarker panel and the presence of one or more members of the protein biomarker panel). In some embodiments of the methods provided herein that include detecting in one or more samples obtained from a subject the presence of: 1) one or more genetic biomarkers in each of the following genes: KRAS (e.g., genetic biomarkers in codons 12 and / or 61), TP53, CDKN2A, and SMAD4, and 2) one or more (e.g., 1, 2, 3, or 4) of the following protein biomarkers: CA19-9, CEA, HGF, and / or OPN, the method further comprises detecting the presence of aneuploidy in the sample obtained from the subject (e.g., the same sample or a different sample used to detect one or both of the presence of one or more members of the genetic biomarker panel and the presence of one or more members of the protein biomarker panel). In some embodiments of the methods provided herein that include detecting in one or more samples obtained from a subject the presence of: 1) one or more genetic bioma...

Claims

1. Use of a reagent for detecting at least three proteins selected from CA19-9, CEA, HGF, OPN, CA125, AFP, prolactin, TIMP-1, follistatin, G-CSF and CA15-3 in the preparation of a kit for determining the presence of cancer in a human subject, wherein determining the presence of cancer in a human subject comprises: (a) Detecting the level of each of at least three proteins in a plasma sample obtained from the subject; And (b)(i) Identifying the presence of cancer in the subject based on the levels of at least three proteins detected; or (b)(ii) Identifying the subject as a candidate for further diagnostic testing based on the levels of at least three proteins detected; and For a subject identified as a candidate for further diagnostic testing: (1) Sequencing at least a portion of each of at least 12 genes in cell-free DNA derived from the subject's plasma sample to detect the presence of one or more mutations in each of the at least 12 genes, wherein the at least 12 genes are selected from NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A and GNAS; and (2) Identifying the presence of cancer in the subject based on the presence or absence of mutations detected in the cell-free DNA.

2. Use of (i) a reagent for detecting one or more mutations in each of at least 12 genes selected from NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A and GNAS and (ii) a reagent for detecting at least three proteins selected from CA19-9, CEA, HGF, OPN, CA125, AFP, prolactin, TIMP-1, follistatin, G-CSF and CA15-3 in the preparation of a kit for determining the presence of cancer in a human subject, wherein determining the presence of cancer in a human subject comprises: (a) Sequencing at least a portion of each of at least 12 genes in cell-free DNA derived from a plasma sample obtained from the subject to detect the presence of one or more mutations in each of the at least 12 genes; (b) Detecting the level of each of at least three proteins in a plasma sample obtained from the subject; And (c) Identifying the presence of cancer in the subject based on the presence or absence of mutations detected in the cell-free DNA and the levels of at least three proteins detected.

3. The use according to claim 2, wherein identifying the presence of cancer in a subject comprises determining a likelihood score using supervised learning techniques, the likelihood score indicating whether cancer is likely to be present in the subject based on the presence or absence of mutations detected in the cell-free DNA and based on the levels of at least three detected proteins, wherein the presence of cancer is identified when the likelihood score is higher than a reference threshold.

4. The use according to claim 3, wherein a linear regression model, a logistic regression model, a neural network, a clustering model, principal component analysis, relevant component analysis, nearest neighbor classifier analysis, linear discriminant analysis, quadratic discriminant analysis, support vector machine, decision tree, random forest, genetic algorithm, classifier optimization using bagging, classifier optimization using boosting, classifier optimization using random subspace method, projection pursuit, and genetic programming and weighted voting, etc., or any combination of the foregoing is used to determine the likelihood score.

5. The use according to claim 3, wherein the supervised learning technique for determining the likelihood score comprises one or more classifiers.

6. The use according to claim 1, wherein identifying the presence of cancer in a subject comprises comparing the detected levels of at least three proteins with the reference levels of the proteins, wherein the presence of cancer is identified when the detected level of at least one of the at least three proteins is higher than its reference level.

7. The use according to claim 1, wherein identifying the presence of cancer in a subject comprises determining a protein likelihood score using supervised learning techniques, the protein likelihood score indicating whether cancer is likely to be present in the subject based on the levels of at least three detected proteins, wherein the presence of cancer is identified when the protein likelihood score is higher than a protein reference threshold.

8. The use according to claim 7, wherein a linear regression model, a logistic regression model, a neural network, a clustering model, principal component analysis, relevant component analysis, nearest neighbor classifier analysis, linear discriminant analysis, quadratic discriminant analysis, support vector machine, decision tree, random forest, genetic algorithm, classifier optimization using bagging, classifier optimization using boosting, classifier optimization using random subspace method, projection pursuit, and genetic programming and weighted voting, etc., or any combination of the foregoing is used to determine the protein likelihood score.

9. The use according to claim 7, wherein the supervised learning technique for determining the protein likelihood score comprises one or more classifiers.

10. The use according to claim 2, wherein identifying the presence of cancer in a subject comprises comparing the detected levels of at least three proteins with the reference levels of the proteins, wherein the presence of cancer is identified when the detected level of at least one of the at least three proteins is higher than its reference level.

11. The use according to claim 2, wherein identifying the presence of cancer in a subject comprises determining a protein likelihood score using supervised learning techniques, the protein likelihood score indicating whether cancer is likely to be present in the subject based on the levels of at least three detected proteins, and wherein the presence of cancer is identified when the protein likelihood score is higher than a protein reference threshold.

12. The use according to claim 11, wherein a linear regression model, a logistic regression model, a neural network, a clustering model, principal component analysis, relevant component analysis, nearest neighbor classifier analysis, linear discriminant analysis, quadratic discriminant analysis, support vector machine, decision tree, random forest, genetic algorithm, classifier optimization using bagging, classifier optimization using boosting, classifier optimization using random subspace method, projection pursuit, and genetic programming and weighted voting, etc. or any combination of the foregoing is used to determine the protein likelihood score.

13. The use according to claim 11, wherein the supervised learning technique for determining the protein likelihood score comprises one or more classifiers.

14. The use according to any one of claims 1, 2, and 6 - 13, wherein the presence of cancer is identified when one or more mutations are present in at least one of at least 12 genes.

15. The use according to any one of claims 1, 2, and 6 - 13, wherein identifying the presence of cancer in a human subject comprises determining a mutation likelihood score using supervised learning techniques, the mutation likelihood score indicating whether cancer is likely to be present in the subject based on the presence or absence of mutations in cell - free DNA, and wherein the presence of cancer is identified when the mutation likelihood score is higher than a mutation reference threshold.

16. The use according to claim 15, wherein a linear regression model, a logistic regression model, a neural network, a clustering model, principal component analysis, relevant component analysis, nearest neighbor classifier analysis, linear discriminant analysis, quadratic discriminant analysis, support vector machine, decision tree, random forest, genetic algorithm, classifier optimization using bagging, classifier optimization using boosting, classifier optimization using random subspace method, projection pursuit, and genetic programming and weighted voting, etc. or any combination of the foregoing is used to determine the mutation likelihood score.

17. The use according to claim 15, wherein the supervised learning technique for determining the mutation likelihood score comprises one or more classifiers.

18. The use of a reagent for detecting at least three proteins selected from CA19 - 9, CEA, HGF, OPN, CA125, AFP, prolactin, TIMP - 1, follistatin, G - CSF, and CA15 - 3 in the preparation of a kit for determining the presence of cancer in a human subject, wherein determining the presence of cancer in a human subject comprises: (a) detecting the level of each of at least three proteins in a plasma sample obtained from the human subject; (b) comparing the detected levels of the at least three proteins with the reference levels of the proteins; and (c)(i) Identifying the presence of cancer in a subject based on the levels of at least three detected proteins, wherein the presence of cancer is identified when the detected level of at least one of the at least three proteins is higher than its reference level; or (c)(ii) Identifying the subject as a candidate for further diagnostic testing based on the levels of at least three detected proteins; and For a subject identified as a candidate for further diagnostic testing: (1) Sequencing at least a portion of each of at least 12 genes in cell-free DNA derived from a plasma sample obtained from the subject to detect the presence of one or more mutations in each of the at least 12 genes in the cell-free DNA, wherein the at least 12 genes are selected from NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A, and GNAS; and (2) Identifying the presence of cancer in the subject based on the presence or absence of mutations detected in the cell-free DNA, wherein the presence of cancer is identified when one or more mutations are detected in at least one of the at least 12 genes.

19. Use of a reagent for detecting at least three proteins selected from CA19-9, CEA, HGF, OPN, CA125, AFP, prolactin, TIMP-1, follistatin, G-CSF, and CA15-3 in the preparation of a kit for determining the presence of cancer in a human subject, wherein determining the presence of cancer in a human subject comprises: (a) Detecting the level of each of at least three proteins derived from a plasma sample obtained from the subject; (b) Using supervised learning techniques to determine a protein likelihood score that indicates whether cancer is likely to be present in the subject based on the levels of the at least three detected proteins; and (c)(i) Identifying the presence of cancer in the subject based on the protein likelihood score, wherein the presence of cancer is identified when the protein likelihood score is higher than a protein reference threshold; or (c)(ii) Identifying the subject as a candidate for further diagnostic testing based on the protein likelihood score; and For a subject identified as a candidate for further diagnostic testing: (1) Sequencing at least a portion of each of at least 12 genes in cell-free DNA derived from a plasma sample obtained from the subject to detect the presence of one or more mutations in each of the at least 12 genes in the cell-free DNA, wherein the at least 12 genes are selected from NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A, and GNAS; and (2) Determine a mutation likelihood score using supervised learning techniques, where the mutation likelihood score indicates the likelihood of cancer in a subject based on the presence or absence of mutations detected in the cell-free DNA; and (3) Identify the presence of cancer in the subject based on the mutation likelihood score, where the presence of cancer is identified when the mutation likelihood score is higher than a mutation reference threshold.

20. The use according to claim 19, wherein one or both of the mutation likelihood score and the protein likelihood score are determined using a linear regression model, a logistic regression model, a neural network, a clustering model, principal component analysis, relevant component analysis, nearest neighbor classifier analysis, linear discriminant analysis, quadratic discriminant analysis, support vector machine, decision tree, random forest, genetic algorithm, classifier optimization using bagging, classifier optimization using boosting, classifier optimization using random subspace method, projection pursuit, and genetic programming and weighted voting, etc., or any combination of the foregoing.

21. The use according to claim 19, wherein the supervised learning techniques for determining the mutation likelihood score, the protein likelihood score, or both include one or more classifiers.

22. The use of (i) a reagent for detecting one or more mutations in each of at least 12 genes selected from NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A, and GNAS and (ii) a reagent for detecting at least three proteins selected from CA19-9, CEA, HGF, OPN, CA125, AFP, prolactin, TIMP-1, follistatin, G-CSF, and CA15-3 in the preparation of a kit for determining the presence of cancer in a human subject, wherein determining the presence of cancer in a human subject comprises: (a) Sequencing at least a portion of each of at least 12 genes in cell-free DNA derived from a plasma sample obtained from the subject to detect the presence or absence of one or more mutations in each of the at least 12 genes in the cell-free DNA; (b) Determine a mutation likelihood score using supervised learning techniques, where the mutation likelihood score indicates the likelihood of cancer in the subject based on the presence or absence of mutations detected in the cell-free DNA; (c) Detect the level of each of at least three proteins in a plasma sample obtained from the subject; (d) Determine a protein likelihood score using supervised learning techniques, where the protein likelihood score indicates the likelihood of cancer in the subject based on the levels of the at least three proteins detected; and (e) Identify the presence of cancer in the subject based on the mutation likelihood score and the protein likelihood score, where the presence of cancer is identified when the mutation likelihood score is higher than a mutation reference threshold, when the protein likelihood score is higher than a protein reference threshold, or when both.

23. The use according to claim 22, wherein one or both of the mutation likelihood score and the protein likelihood score are determined using a linear regression model, a logistic regression model, a neural network, a clustering model, principal component analysis, relevant component analysis, nearest neighbor classifier analysis, linear discriminant analysis, quadratic discriminant analysis, support vector machine, decision tree, random forest, genetic algorithm, classifier optimization using bagging, classifier optimization using boosting, classifier optimization using the random subspace method, projection pursuit, and genetic programming and weighted voting, etc. or any combination of the foregoing.

24. The use according to claim 22, wherein the supervised learning technique for determining the mutation likelihood score, the protein likelihood score, or both includes one or more classifiers.

25. The use according to any one of claims 1-13 and 18-24, wherein the subject is not diagnosed with cancer.

26. The use according to any one of claims 1-13 and 18-24, wherein the cancer is selected from pancreatic cancer, colon cancer, ovarian cancer, liver cancer, lung cancer, breast cancer, and upper gastrointestinal cancer.

27. The use according to any one of claims 1-13 and 18-24, wherein the same plasma sample is used for cell-free DNA and protein.

28. The use according to any one of claims 1-13 and 18-24, wherein the levels of at least three proteins are detected using an antibody-dependent method enzyme-linked immunosorbent assay, a spectroscopic method, or an aptamer-dependent method.

29. The use according to any one of claims 1-13 and 18-24, wherein sequencing at least a portion of each of at least 12 genes involves amplifying at least 12 of the following codons: NRAS codons 3-15, NRAS codons 54-63, CTNNB1 codons 31-39, CTNNB1 codons 38-47, PIK3CA codons 80-90, PIK3CA codons 343-348, PIK3CA codons 541-551, PIK3CA codons 1038-1050, FBXW7 codons 361-371, FBXW7 codons 464-473, FBXW7 codons 473-483, FBXW7 codons 498-507, APC codons 1304-1311, APC codons 1450-1459, EGFR codons 856-868, BRAF codons 591-602, CDKN2A codons 51-58, CDKN2A codons 76-88, PTEN codons 90-98, PTEN codons 125-132, PTEN codons 133-146, PTEN codons 145-154, FGFR2 codons 250-256, HRAS codons 7-19, KRAS codons 7-14, KRAS codons 57-65, KRAS codons 143-148, AKT1 codons 16-18, TP53 codons 10-22, TP53 codons 25-32, TP53 codons 33-40, TP53 codons 40-52, TP53 codons 52-64, TP53 codons 82-94, TP53 codons 97-110, TP53 codons 112-125, TP53 codons 123-125, TP53 codons 126-132, TP53 codons 132-142, TP53 codons 150-163, TP53 codons 167-177, TP53 codons 175-186, TP53 codons 187-195, TP53 codons 195-206, TP53 codons 207-219, TP53 codons 219-224, TP53 codons 226-237, TP53 codons 232-245, TP53 codons 248-261, TP53 codons 261-268, TP53 codons 272-283, TP53 codons 279-290, TP53 codons 298-307, TP53 codons 307-314, TP53 codons 323-331, TP53 codons 333-344, TP53 codons 344-355, TP53 codons 367-375, and TP53 codons 374-386, PPP2R1A codons 175-187 and GNAS codons 199-208.

30. The use according to any one of claims 1-13 and 18-24, wherein sequencing at least a part of each of at least 12 genes detects the presence or absence of at least the following mutations: When at least 12 genes include NRAS, the 175G>A, 35G>A, and 182A>G mutations in NRAS, When at least 12 genes include CTNNB1, the 134C>T, 121A>G, 127G>A, 133T>G, 113G>A, 110C>T, 104T>G, 98C>A, 101G>T, and 100G>A mutations in CTNNB1, When at least 12 genes include PIK3CA, the 3140A>G, 3137C>T, 1635G>T, 1624G>A, 1634A>C, 1633G>A, 3141T>G, 3132T>A, 3145G>C, 241G>A, 1637A>G, 1030G>A, 3140A>T, 1035T>A, 3131A>G, 263G>A, 1638G>T, and 1633G>C mutations in PIK3CA, When at least 12 genes include FBXW7, the 1393C>T, 1514G>A, 1394G>A, 1436G>A, 1435C>T, 1412insA, 1105G>T, and 1099C>T mutations in FBXW7, When at least 12 genes include APC, the 3916G>T, 4348C>T, 3927delAAAGA, and 3931insA mutations in APC, When at least 12 genes include EGFR, the 2570G>A, 2590G>A, 2588G>A, 2603A>G, and 2573T>G mutations in EGFR, When at least 12 genes include BRAF, the 1798G>A, 1781A>G, 1801A>G, 1799T>A, 1796C>T, 1785T>G, 1790T>G, 1792G>A, and 1786G>C mutations in BRAF, When at least 12 genes include CDKN2A, the 226G>A, 251A>T, 172C>T, 236C>T, 250G>T, 227C>T, 151G>C, 247C>T, 260G>A, and 262G>T mutations in CDKN2A, When at least 12 genes include PTEN, the 388C>G, 406T>C, 377C>T, 376G>T, 275A>C, 389G>A, 451G>A, and 388C>T in PTEN, When at least 12 genes include FGFR2, the 758C>G mutation in FGFR2, When at least 12 genes include HRAS, the 35G>A, 38G>T, and 34G>A mutations in HRAS, When at least 12 genes contain KRAS, the 38G>A, 34G>T, 35G>A, 181C>A, 35G>T, 437C>T, 436G>A, 40G>A, 32C>T, 35G>C, 34G>A, 169G>A, 38G>T, 34G>C, 31G>A, 176C>A, 35G>T, 183A>C, 175G>A, and 183A>T mutations in KRAS, When at least 12 genes include AKT1, the 49G>A mutation in AKT1, When at least 12 genes include TP53, 747G>T, 742C>T, 818G>T, 473G>A, 743G>A, 818G>A, 844C>T, 455C>T, 817C>T, 527G>T, 524G>A, 733G>A, and 659A>G mutations in TP53, When at least 12 genes include PPP2R1A, the 547C>T, 544C>T, and 551C>T mutations in PPP2R1A, and When at least 12 genes contained GNAS, the 602G>A, 601C>T, 608T>C, and 601C>A mutations in GNAS were detected.

31. The use of any one of claims 1-13 and 18-24, wherein identifying the presence of cancer further comprises sequencing at least a portion of each of at least 12 genes in genomic DNA from a white blood cell sample derived from the subject to detect the presence or absence in the genomic DNA of each mutation detected in the cell-free DNA, wherein the presence of cancer in the subject is identified based on the presence of the mutation detected in the cell-free DNA and the absence of the mutation detected in the genomic DNA.

32. The use of any one of claims 1-13 and 18-24, wherein detecting the presence or absence of one or more mutations comprises amplifying the cell-free DNA to form a family of amplicons, wherein each member of the family is derived from a single template molecule in the cell-free DNA, each member of the family comprises a common oligonucleotide barcode, and each family comprises a different oligonucleotide barcode.

33. The use according to claim 32, wherein the oligonucleotide barcode is introduced into the template molecule by a step of amplification with a population of primers that together comprise a plurality of oligonucleotide barcodes.

34. The use of claim 32, wherein the oligonucleotide barcode is endogenous to the template molecule and an adaptor comprising a DNA synthesis priming site is ligated to the end of the template molecule adjacent to the oligonucleotide barcode.

35. The use of any one of claims 1-13 and 18-24, wherein detecting the presence of one or more mutations comprises: (a) assigning a unique identifier (UID) to each of a plurality of cell-free DNA template molecules; (b) Amplifying each cell-free DNA template molecule with a unique tag to generate a UID family; as well as (c) Redundant sequencing of the amplified products.

36. A computer-implemented method for identifying whether a subject has a risk of developing cancer, comprising: (a) receiving data in a computer comprising a processor and a computer-readable medium, wherein the data comprises: (i) sequence information for each of at least twelve of the following genes in a sample obtained from the subject: NRAS, CTNNB1, PIK3CA, FBXW7, APC, EGFR, BRAF, CDKN2A, PTEN, FGFR2, HRAS, KRAS, AKT1, TP53, PPP2R1A, and GNAS; and (ii) the levels of at least three proteins in a sample obtained from the subject, wherein the at least three proteins are selected from CA19-9, CEA, HGF, OPN, CA125, AFP, prolactin, TIMP-1, follistatin, G-CSF, and CA15-3; and (b) executing instructions of the computer-readable medium, wherein the instructions are executed by the processor to identify the cancer risk of the subject based on the identification of one or more mutations in each of the at least twelve genes and / or the identification of the levels of the at least three proteins.

37. The computer-implemented method according to claim 36, wherein when one or more mutations are detected in at least one of the at least 12 genes, the processor identifies the cancer risk of the subject.

38. The computer-implemented method according to claim 36, wherein the computer comprises a database containing reference values for at least three proteins, and wherein the processor compares the levels of the at least three proteins in the sample with the reference levels in the database and identifies the cancer risk of the subject when the level of at least one of the detected at least three proteins is higher than its reference level.

39. The computer-implemented method according to claim 36, wherein the processor generates a likelihood score for the subject, the likelihood score indicating whether the subject is likely to have cancer based on the identification of one or more mutations and / or the determined levels of the at least three proteins.

40. The computer-implemented method according to claim 39, wherein the likelihood score is generated using supervised learning techniques.

41. The computer-implemented method according to claim 39, wherein a linear regression model, a logistic regression model, a neural network, a clustering model, principal component analysis, relevant component analysis, nearest neighbor classifier analysis, linear discriminant analysis, quadratic discriminant analysis, support vector machine, decision tree, random forest, genetic algorithm, classifier optimization using bagging, classifier optimization using boosting, classifier optimization using random subspace method, projection pursuit, and genetic programming and weighted voting, etc., or any combination of the foregoing are used to generate the likelihood score.

42. The computer-implemented method according to claim 40, wherein the supervised learning techniques for determining the likelihood score include one or more classifiers.

43. The computer-implemented method according to claim 39, wherein the likelihood score is a protein likelihood score indicating the likelihood of the presence of cancer in a subject based on the levels of at least three detected proteins, a mutation likelihood score indicating the likelihood of the presence of cancer in a subject based on the presence or absence of mutations detected in a sample, or both the protein likelihood score and the mutation likelihood score are generated simultaneously.

44. The computer-implemented method according to claim 43, wherein one or both of the mutation likelihood score and the protein likelihood score are generated using supervised learning techniques.

45. The computer-implemented method according to claim 43, wherein one or both of the mutation likelihood score and the protein likelihood score are determined using a linear regression model, a logistic regression model, a neural network, a clustering model, principal component analysis, relevant component analysis, nearest neighbor classifier analysis, linear discriminant analysis, quadratic discriminant analysis, support vector machines, decision trees, random forests, genetic algorithms, classifier optimization using bagging, classifier optimization using boosting, classifier optimization using the random subspace method, projection pursuit, and genetic programming and weighted voting, etc., or any combination of the foregoing.

46. The computer-implemented method according to claim 44, wherein the supervised learning technique for determining the mutation likelihood score, the protein likelihood score, or both includes one or more classifiers.

47. The computer-implemented method according to any one of claims 36-46, wherein the subject has not been diagnosed with cancer.

48. The computer-implemented method according to any one of claims 36-46, wherein the cancer is selected from pancreatic cancer, colon cancer, ovarian cancer, liver cancer, lung cancer, breast cancer, and upper gastrointestinal cancer.

49. The computer-implemented method according to any one of claims 36-46, wherein the data of (i) and (ii) are obtained from a plasma sample.

50. The computational implementation method according to any one of claims 36-46, wherein the sequence information includes sequences of at least 12 of the following codons: NRAS codons 3-15, NRAS codons 54-63, CTNNB1 codons 31-39, CTNNB1 codons 38-47, PIK3CA codons 80-90, PIK3CA codons 343-348, PIK3CA codons 541-551, PIK3CA codons 1038-1050, FBXW7 codons 361-371, FBXW7 codons 464-473, FBXW7 codons 473-483, FBXW7 codons 498-507, APC codons 1304-1311, APC codons 1450-1459, EGFR codons 856-868, BRAF codons 591-602, CDKN2A codons 51-58, CDKN2A codons 76-88, PTEN codons 90-98, PTEN codons 125-132, PTEN codons 133-146, PTEN codons 145-154, FGFR2 codons 250-256, HRAS codons 7-19, KRAS codons 7-14, KRAS codons 57-65, KRAS codons 143-148, AKT1 codons 16-18, TP53 codons 10-22, TP53 codons 25-32, TP53 codons 33-40, TP53 codons 40-52, TP53 codons 52-64, TP53 codons 82-94, TP53 codons 97-110, TP53 codons 112-125, TP53 codons 123-125, TP53 codons 126-132, TP53 codons 132-142, TP53 codons 150-163, TP53 codons 167-177, TP53 codons 175-186, TP53 codons 187-195, TP53 codons 195-206, TP53 codons 207-219, TP53 codons 219-224, TP53 codons 226-237, TP53 codons 232-245, TP53 codons 248-261, TP53 codons 261-268, TP53 codons 272-283, TP53 codons 279-290, TP53 codons 298-307, TP53 codons 307-314, TP53 codons 323-331, TP53 codons 333-344, TP53 codons 344-355, TP53 codons 367-375, and TP53 codons 374-386, PPP2R1A codons 175-187, and GNAS codons 199-208.

51. The sequence information according to any one of claims 36 - 46, wherein the sequence information identifies the presence or absence of the following mutations: When at least 12 genes contain NRAS, the 175G>A, 35G>A, and 182A>G mutations in NRAS, When at least 12 genes contain CTNNB1, the 134C>T, 121A>G, 127G>A, 133T>G, 113G>A, 110C>T, 104T>G, 98C>A, 101G>T, and 100G>A mutations in CTNNB1, When at least 12 genes contain PIK3CA, the 3140A>G, 3137C>T, 1635G>T, 1624G>A, 1634A>C, 1633G>A, 3141T>G, 3132T>A, 3145G>C, 241G>A, 1637A>G, 1030G>A, 3140A>T, 1035T>A, 3131A>G, 263G>A, 1638G>T, and 1633G>C mutations in PIK3CA, When at least 12 genes contain FBXW7, the 1393C>T, 1514G>A, 1394G>A, 1436G>A, 1435C>T, 1412insA, 1105G>T, and 1099C>T mutations in FBXW7, When at least 12 genes contain APC, the 3916G>T, 4348C>T, 3927delAAAGA, and 3931insA mutations in APC, When at least 12 genes contain EGFR, the 2570G>A, 2590G>A, 2588G>A, 2603A>G, and 2573T>G mutations in EGFR, When at least 12 genes contain BRAF, the 1798G>A, 1781A>G, 1801A>G, 1799T>A, 1796C>T, 1785T>G, 1790T>G, 1792G>A, and 1786G>C mutations in BRAF, When at least 12 genes contain CDKN2A, the 226G>A, 251A>T, 172C>T, 236C>T, 250G>T, 227C>T, 151G>C, 247C>T, 260G>A, and 262G>T mutations in CDKN2A, When at least 12 genes contain PTEN, the 388C>G, 406T>C, 377C>T, 376G>T, 275A>C, 389G>A, 451G>A, and 388C>T in PTEN, When at least 12 genes contain FGFR2, the 758C>G mutation in FGFR2, When at least 12 genes contain HRAS, the 35G>A, 38G>T, and 34G>A mutations in HRAS, When at least 12 genes contain KRAS, the mutations of 38G>A, 34G>T, 35G>A, 181C>A, 35G>T, 437C>T, 436G>A, 40G>A, 32C>T, 35G>C, 34G>A, 169G>A, 38G>T, 34G>C, 31G>A, 176C>A, 35G>T, 183A>C, 175G>A and 183A>T in KRAS, When at least 12 genes contain AKT1, the 49G>A mutation in AKT1, When at least 12 genes contain TP53, the mutations of 747G>T, 742C>T, 818G>T, 473G>A, 743G>A, 818G>A, 844C>T, 455C>T, 817C>T, 527G>T, 524G>A, 733G>A and 659A>G in TP53, When at least 12 genes contain PPP2R1A, the mutations of 547C>T, 544C>T and 551C>T in PPP2R1A, and When at least 12 genes contain GNAS, the mutations of 602G>A, 601C>T, 608T>C and 601C>A in GNAS.

Images