Tumor marker and application thereof

Abstract

To provide a tumor marker located on chromosome 1, chromosome 2, chromosome 3, chromosome 5, chromosome 7, chromosome 8, chromosome 10, chromosome 11, and chromosome 21 of the human genome, the tumor marker comprising one or more CpG sites capable of undergoing methylation modification, and to provide use thereof; and further to provide a DNA epigenetic modification-related tumor marker that exhibits a significantly high methylation status in tumor patients, which can be applied to clinical auxiliary screening, diagnosis, prognosis of tumors, and design of diagnostic reagents and kits.SOLUTION: The present invention relates to a DNA epigenetic modification-related tumor marker that overcomes defects of the prior art and exhibits a significantly high methylation status in patients with tumor.SELECTED DRAWING: None

Description

[Technical Field]

[0001] Technical Field The present invention relates to the field of biotechnology, and in particular to tumor markers and their uses. [Background technology]

[0002] Background technology Tumor development and progression are complex, multifaceted, and multifactorial dynamic processes involving the interaction of multiple factors, including the external environment, genetic mutations, and epigenetic changes. External environmental factors include physical, chemical, and biological carcinogenic factors, as well as unhealthy lifestyles. Genetic mutations include gene mutations, copy number changes, and chromosomal mismatches. Epigenetic changes primarily involve DNA methylation, histone modifications, and non-coding RNAs. During tumor development and progression, these factors synergistically interact to inactivate a series of tumor suppressor genes and activate oncogenes, ultimately leading to tumorigenesis. Timely detection and diagnosis are crucial for tumor treatment.

[0003] With our deeper understanding of tumors and advances in science and technology, many novel tumor markers have been discovered and are being used in clinical diagnosis. Before the 1980s, tumor markers were primarily cell secretions such as hormones, enzymes, and proteins. For example, carcinoembryonic antigen (CEA) and alpha-fetoprotein (AFP) could be used as markers for various tumors, such as gastric cancer and liver cancer. Although these tumor markers are still used clinically, their sensitivity and accuracy no longer meet current clinical needs. Currently, mutation-based markers, such as those based on tumor suppressor p53 mutations, BRCA gene mutations, and microsatellite instability in colorectal cancer, are becoming more common, but these markers are not very effective for early tumor detection and diagnosis. Using DNA methylation-based markers allows for early diagnosis of tumor progression.

[0004] Epigenomics is a field that studies heritable changes in gene function, resulting in phenotypic changes, even when the DNA sequence of a gene remains unchanged. Epigenomics primarily encompasses biochemical processes such as DNA methylation, histone modification, and changes in microRNA levels. DNA methylation is a deeply studied epigenomic mechanism and is expected to be applied to clinical oncology practice, including diagnosis and treatment. DNA methylation refers to the transfer of a methyl group to a specific base in vivo, catalyzed by DNA methyltransferase (DMT), using S-adenosylmethionine (SAM) as the methyl group donor. In mammals, DNA methylation primarily occurs at the C in 5'-CpG-3', resulting in the generation of 5-methylcytosine (5mC).

[0005] In normal cells, some CpGs are highly methylated and transcriptionally silent. However, in tumor cells, these CpGs are extensively demethylated, leading to transcription of repetitive sequences and transposon activation, resulting in high genome instability and enhanced transcription of oncogenes. Furthermore, CpG islands, which are originally hypomethylated in normal cells, become hypermethylated in tumor cells, resulting in transcriptional inactivation of genes including DNA repair genes, cell cycle control genes, and anti-apoptotic genes. The methylation status of specific sites can be effectively determined by PCR and sequencing after bisulfite treatment of genomic DNA. Using these techniques, these abnormal DNA methylation states can be detected early in the course of tumor development.

[0006] Although the entire sequence of the human genome has been elucidated, the genome sequence is extremely complex, and it is not yet clear which genes or segments are closely related to disease. In addition, the complexity of tumors themselves makes it more difficult to find tumor markers that combine sensitivity and specificity. In this invention, the inventors have used large amounts of data and combined them with more optimized methods to find more accurate tumor markers, providing more tools for tumor diagnosis. Summary of the Invention [Means for solving the problem]

[0007] Contents of the invention The present invention overcomes the deficiencies of the prior art and provides DNA epigenetic modification-related tumor markers that show significant hypermethylation status in tumor patients.

[0008] A first aspect of the present invention provides tumor markers located on human chromosomes 1, 2, 3, 5, 7, 8, 10, 11, and 21, and containing one or more CpG sites at which methylation modification can occur.

[0009] Preferably, the methylation modification comprises a 5-formylation modification, a 5-hydroxymethylation modification, a 5-methylation modification, or a 5-carboxylation modification.

[0010] Preferably, the tumor marker is selected from the group consisting of chr2:105459135-105459190, chr10:124902392-124902455, chr3:157812331-157812498, chr21:38378275-38378539, chr8:97170353-97170404, chr5:134880362-134880455, and chr10:94835119-94835 of the human genome Hg19. 252, chr11:31826557-31826963, chr3:147114032-147114108, chr10:50819227-50819589, chr2:66809255-66809281, chr7:97361393-97361461, chr8:70984200-70984294, chr1:6515341-6515409 (coordinates start from 0).

[0011] Preferably, the chr2:105459135-105459190 region is a) the nucleotide sequence shown in SEQ ID NO: 1; b) a complementary sequence of the nucleotide sequence shown in SEQ ID NO: 1; c) a nucleotide sequence having at least 70% homology with SEQ ID NO: 1 or a complementary sequence of that nucleotide sequence is selected from the group consisting of:

[0012] And / or the chr10:124902392-124902455 region is a) the nucleotide sequence shown in SEQ ID NO: 2; b) a complementary sequence of the base sequence shown in SEQ ID NO: 2; c) a nucleotide sequence having at least 70% homology with SEQ ID NO: 2 or a complementary sequence of that nucleotide sequence is selected from the group consisting of:

[0013] And / or the chr3:157812331-157812498 region is a) the nucleotide sequence shown in SEQ ID NO: 3; b) a complementary sequence of the base sequence shown in SEQ ID NO: 3; c) a nucleotide sequence having at least 70% homology with SEQ ID NO: 3 or a complementary sequence of that nucleotide sequence is selected from the group consisting of:

[0014] And / or the chr21:38378275-38378539 region is a) the nucleotide sequence shown in SEQ ID NO: 4; b) a complementary sequence of the base sequence shown in SEQ ID NO: 4; c) a nucleotide sequence having at least 70% homology with SEQ ID NO: 4 or a complementary sequence of said nucleotide sequence is selected from the group consisting of:

[0015] And / or the chr8:97170353-97170404 region is a) the nucleotide sequence shown in SEQ ID NO: 5; b) a complementary sequence of the base sequence shown in SEQ ID NO: 5; c) a nucleotide sequence having at least 70% homology with SEQ ID NO: 5 or a complementary sequence of that nucleotide sequence is selected from the group consisting of:

[0016] And / or the chr5:134880362-134880455 region is a) the nucleotide sequence shown in SEQ ID NO: 6; b) a complementary sequence of the base sequence shown in SEQ ID NO: 6; c) a nucleotide sequence having at least 70% homology with SEQ ID NO: 6 or a complementary sequence of that nucleotide sequence is selected from the group consisting of:

[0017] And / or the chr10:94835119-94835252 region is a) the nucleotide sequence shown in SEQ ID NO: 7; b) a complementary sequence of the base sequence shown in SEQ ID NO: 7; c) a nucleotide sequence having at least 70% homology with SEQ ID NO: 7 or a complementary sequence of that nucleotide sequence is selected from the group consisting of:

[0018] And / or the chr11:31826557-31826963 region is a) the nucleotide sequence shown in SEQ ID NO: 8; b) a complementary sequence of the base sequence shown in SEQ ID NO: 8; c) a nucleotide sequence having at least 70% homology with SEQ ID NO: 8 or a complementary sequence of that nucleotide sequence is selected from the group consisting of:

[0019] And / or the chr3:147114032-147114108 region is a) the nucleotide sequence shown in SEQ ID NO: 9; b) a complementary sequence of the base sequence shown in SEQ ID NO: 9; c) a nucleotide sequence having at least 70% homology with SEQ ID NO: 9 or a complementary sequence of that nucleotide sequence is selected from the group consisting of:

[0020] And / or the chr10:50819227-50819589 region is a) the nucleotide sequence shown in SEQ ID NO: 10; b) a complementary sequence of the base sequence shown in SEQ ID NO: 10; c) a nucleotide sequence having at least 70% homology with SEQ ID NO: 10 or a complementary sequence of that nucleotide sequence is selected from the group consisting of:

[0021] And / or the chr2:66809255-66809281 region is a) the nucleotide sequence shown in SEQ ID NO: 11; b) a complementary sequence of the base sequence shown in SEQ ID NO: 11; c) a nucleotide sequence having at least 70% homology with SEQ ID NO: 11 or a complementary sequence of that nucleotide sequence is selected from the group consisting of:

[0022] And / or the chr7:97361393-97361461 region is a) the nucleotide sequence shown in SEQ ID NO: 12; b) a complementary sequence of the base sequence shown in SEQ ID NO: 12; c) a nucleotide sequence having at least 70% homology with SEQ ID NO: 12 or a complementary sequence of that nucleotide sequence is selected from the group consisting of:

[0023] And / or the chr8:70984200-70984294 region is a) the nucleotide sequence shown in SEQ ID NO: 13; b) a complementary sequence of the base sequence shown in SEQ ID NO: 13; c) a nucleotide sequence having at least 70% homology with SEQ ID NO: 13 or a complementary sequence of said nucleotide sequence is selected from the group consisting of:

[0024] And / or the chr1:6515341-6515409 region is a) the nucleotide sequence shown in SEQ ID NO: 14; b) a complementary sequence of the base sequence shown in SEQ ID NO: 14; c) a nucleotide sequence having at least 70% homology with SEQ ID NO: 14 or a complementary sequence of said nucleotide sequence is selected from the group consisting of:

[0025] The above sequences are shown in Table 1 below, and their reverse complements are shown in Table 2, where the bold and italic font indicates the CpG site and the numbers below the highlighting symbols indicate the number of the detection site.

[0026] [Table 1-1]

[0027] [Table 1-2]

[0028] [Table 1-3]

[0029] [Table 2-1]

[0030] [Table 2-2]

[0031] [Table 2-3]

[0032] A second aspect of the present invention provides the use of the tumor markers of the present invention in tumor screening, prognosis, diagnostic reagents and drug targets.

[0033] Preferably, the method comprises detecting the methylation status of CpG sites of the tumor markers; more preferably, the CpG sites are listed in Tables 1 and 2.

[0034] Preferably, the tumors include bladder cancer, cervical cancer, bile duct cancer, colon cancer, esophageal cancer, glioblastoma, head and neck cancer, clear cell renal cell carcinoma, papillary renal cell carcinoma, liver cancer, lung adenocarcinoma, pancreatic cancer, pheochromocytoma and paraganglioma, prostate cancer, sarcoma, melanoma, gastric adenocarcinoma, thyroid cancer, thymic cancer, endometrial cancer, and breast cancer; more preferably, the tumors include breast cancer, cervical cancer, esophageal cancer, head and neck cancer, lung cancer, and pancreatic cancer.

[0035] Preferably, tumors using SEQ ID NO: 1 or SEQ ID NO: 15 as a marker include bladder cancer, cervical cancer, bile duct cancer, colon cancer, esophageal cancer, glioblastoma, squamous cell carcinoma of the head and neck, clear cell renal cell carcinoma, papillary renal cell carcinoma, liver cancer, lung adenocarcinoma, pancreatic cancer, pheochromocytoma and paraganglioma, prostate cancer, sarcoma, melanoma, gastric adenocarcinoma, thyroid cancer, thymic carcinoma, and endometrial cancer; more preferably, tumors using SEQ ID NO: 1 or SEQ ID NO: 15 as a marker include bladder cancer, cervical cancer, bile duct cancer, colon cancer, esophageal cancer, glioblastoma, squamous cell carcinoma of the head and neck, clear cell renal cell carcinoma, papillary renal cell carcinoma, lung adenocarcinoma, pheochromocytoma and paraganglioma, prostate cancer, melanoma, gastric adenocarcinoma, thyroid cancer, thymic carcinoma, and endometrial cancer.

[0036] Preferably, tumors using SEQ ID NO: 2 or SEQ ID NO: 16 as a marker include breast cancer, cervical cancer, esophageal cancer, head and neck cancer, lung cancer, and pancreatic cancer.

[0037] Preferably, tumors using SEQ ID NO: 3 or SEQ ID NO: 17 as a marker include bladder cancer, cervical cancer, bile duct cancer, colon cancer, esophageal cancer, glioblastoma, head and neck squamous cell carcinoma, clear cell renal cell carcinoma, papillary renal cell carcinoma, liver cancer, lung adenocarcinoma, pancreatic cancer, pheochromocytoma and paraganglioma, prostate cancer, sarcoma, melanoma, gastric adenocarcinoma, thyroid cancer, thymic carcinoma, and endometrial cancer.

[0038] Preferably, tumors using SEQ ID NO: 4 or SEQ ID NO: 18 as a marker include bladder cancer, cervical cancer, bile duct cancer, colon cancer, esophageal cancer, glioblastoma, squamous cell carcinoma of the head and neck, clear cell renal cell carcinoma, papillary renal cell carcinoma, liver cancer, lung adenocarcinoma, pancreatic cancer, pheochromocytoma and paraganglioma, prostate cancer, sarcoma, melanoma, gastric adenocarcinoma, thyroid cancer, thymic carcinoma, and endometrial cancer; more preferably, tumors using SEQ ID NO: 4 or SEQ ID NO: 18 as a marker include bladder cancer, cervical cancer, bile duct cancer, colon cancer, esophageal cancer, glioblastoma, squamous cell carcinoma of the head and neck, clear cell renal cell carcinoma, papillary renal cell carcinoma, liver cancer, lung adenocarcinoma, pancreatic cancer, prostate cancer, sarcoma, melanoma, gastric adenocarcinoma, thyroid cancer, thymic carcinoma, and endometrial cancer.

[0039] Preferably, tumors using SEQ ID NO: 5 or SEQ ID NO: 19 as a marker include bladder cancer, cervical cancer, bile duct cancer, colon cancer, esophageal cancer, glioblastoma, squamous cell carcinoma of the head and neck, clear cell renal cell carcinoma, papillary renal cell carcinoma, liver cancer, lung adenocarcinoma, pancreatic cancer, pheochromocytoma and paraganglioma, prostate cancer, sarcoma, melanoma, gastric adenocarcinoma, thyroid cancer, thymic carcinoma, and endometrial cancer; more preferably, tumors using SEQ ID NO: 5 or SEQ ID NO: 19 as a marker include bladder cancer, cervical cancer, bile duct cancer, colon cancer, esophageal cancer, glioblastoma, squamous cell carcinoma of the head and neck, clear cell renal cell carcinoma, papillary renal cell carcinoma, liver cancer (LIHC), lung adenocarcinoma, pancreatic cancer, prostate cancer, sarcoma, melanoma, gastric adenocarcinoma, thyroid cancer, thymic carcinoma, and endometrial cancer.

[0040] Preferably, tumors using SEQ ID NO: 6 or SEQ ID NO: 20 as a marker include bladder cancer, cervical cancer, bile duct cancer, colon cancer, esophageal cancer, glioblastoma, head and neck squamous cell carcinoma, clear cell renal cell carcinoma, papillary renal cell carcinoma, liver cancer, lung adenocarcinoma, pancreatic cancer, pheochromocytoma and paraganglioma, prostate cancer, sarcoma, melanoma, gastric adenocarcinoma, thyroid cancer, thymic cancer, and endometrial cancer; more preferably, tumors using SEQ ID NO: 6 or SEQ ID NO: 20 as a marker include bladder cancer, cervical cancer, bile duct cancer, colon cancer, esophageal cancer, head and neck squamous cell carcinoma, clear cell renal cell carcinoma, papillary renal cell carcinoma, liver cancer, lung adenocarcinoma, pancreatic cancer, prostate cancer, sarcoma, melanoma, gastric adenocarcinoma, thyroid cancer, thymic cancer, and endometrial cancer.

[0041] Preferably, tumors using SEQ ID NO: 7 or SEQ ID NO: 21 as a marker include breast cancer, cervical cancer, head and neck cancer, lung cancer, and pancreatic cancer.

[0042] Preferably, tumors using SEQ ID NO: 8 or SEQ ID NO: 22 as a marker include bladder cancer, cervical cancer, bile duct cancer, colon cancer, esophageal cancer, glioblastoma, head and neck squamous cell carcinoma, clear cell renal cell carcinoma, papillary renal cell carcinoma, liver cancer, lung adenocarcinoma, pancreatic cancer, pheochromocytoma and paraganglioma, prostate cancer, sarcoma, melanoma, gastric adenocarcinoma, thyroid cancer, thymic carcinoma, and endometrial cancer; more preferably, tumors using SEQ ID NO: 8 or SEQ ID NO: 22 as a marker include bladder cancer, cervical cancer, bile duct cancer, colon cancer, esophageal cancer, glioblastoma, head and neck squamous cell carcinoma, clear cell renal cell carcinoma, papillary renal cell carcinoma, liver cancer, lung adenocarcinoma, pancreatic cancer, prostate cancer, sarcoma, melanoma, gastric adenocarcinoma, thyroid cancer, thymic carcinoma, and endometrial cancer.

[0043] Preferably, tumors using SEQ ID NO: 9 or SEQ ID NO: 23 as a marker include breast cancer, cervical cancer, esophageal cancer, head and neck cancer, lung cancer, and pancreatic cancer.

[0044] Preferably, tumors using SEQ ID NO: 10 or SEQ ID NO: 24 as a marker include bladder cancer, cervical cancer, bile duct cancer, colon cancer, esophageal cancer, glioblastoma, head and neck squamous cell carcinoma, clear cell renal cell carcinoma, papillary renal cell carcinoma, liver cancer, lung adenocarcinoma, pancreatic cancer, pheochromocytoma and paraganglioma, prostate cancer, sarcoma, melanoma, gastric adenocarcinoma, thyroid cancer, thymic carcinoma, and endometrial cancer.

[0045] Preferably, tumors using SEQ ID NO: 11 or SEQ ID NO: 25 as a marker include breast cancer, cervical cancer, esophageal cancer, head and neck cancer, lung cancer, and pancreatic cancer.

[0046] Preferably, tumors using SEQ ID NO: 12 or SEQ ID NO: 26 as a marker include bladder cancer, cervical cancer, bile duct cancer, colon cancer, esophageal cancer, glioblastoma, head and neck squamous cell carcinoma, clear cell renal cell carcinoma, papillary renal cell carcinoma, liver cancer, lung adenocarcinoma, pancreatic cancer, pheochromocytoma and paraganglioma, prostate cancer, sarcoma, melanoma, gastric adenocarcinoma, thyroid cancer, thymic carcinoma, and endometrial cancer.

[0047] Preferably, tumors using SEQ ID NO: 13 or SEQ ID NO: 27 as a marker include bladder cancer, cervical cancer, bile duct cancer, colon cancer, esophageal cancer, glioblastoma, head and neck squamous cell carcinoma, clear cell renal cell carcinoma, papillary renal cell carcinoma, liver cancer, lung adenocarcinoma, pancreatic cancer, pheochromocytoma and paraganglioma, prostate cancer, sarcoma, melanoma, gastric adenocarcinoma, thyroid cancer, thymic carcinoma, and endometrial cancer.

[0048] Preferably, tumors using SEQ ID NO: 14 or SEQ ID NO: 28 as a marker include breast cancer, cervical cancer, esophageal cancer, head and neck cancer, lung cancer, and pancreatic cancer.

[0049] A third aspect of the present invention provides a drug that suppresses tumor growth, which drug comprises an inhibitor of a tumor marker according to the present invention.

[0050] Preferably, the inhibitor is a methylation inhibitor; more preferably, the inhibitor is an inhibitor that inhibits methylation of one or more CpG sites in Tables 1 and 2.

[0051] Preferably, the medicament further comprises a pharmaceutically acceptable carrier.

[0052] A fourth aspect of the present invention provides a method for detecting a tumor marker, comprising the steps of: S1, obtain the tissue sample to be detected; S2, extract DNA from the tissue sample to be detected and obtain the methylation value of the sample; S3, calculate the methylation status of each CpG site within the tumor marker sequence region, or the average methylation status of the entire region.

[0053] Preferably, the method for obtaining the methylation value of the sample in step S2 includes sequencing, probes, antibodies, mass spectrometry, and the like.

[0054] A fifth aspect of the present invention provides a tumor marker detection kit comprising a primer or probe that specifically detects a tumor marker according to the present invention.

[0055] Specifically detecting the tumor marker includes specifically detecting methylation of CpG sites of the tumor marker.

[0056] Preferably, the methylation of the CpG site of the tumor marker comprises 5-formylation, 5-hydroxymethylation, 5-methylation or 5-carboxylation.

[0057] The present invention has the advantage over the prior art of providing a DNA epigenetic modification-related tumor marker that indicates a significant hypermethylation state in tumor patients, which can be applied to clinical auxiliary screening, diagnosis, and prognosis of tumors, as well as the design of diagnostic reagents and kits. [Brief explanation of the drawings]

[0058] [Figure 1] FIG. 1 is a diagram of the average methylation value in the TCGA database of the target sequence of SEQ ID NO: 1 in Example 2 of the present invention; [Figure 2] Figure 2 is a diagram of the average methylation value in the TCGA database of the target sequence of SEQ ID NO: 3 in Example 2 of the present invention; [Figure 3] Figure 3 is a diagram of the average methylation value in the TCGA database of the target sequence of SEQ ID NO: 4 in Example 2 of the present invention; [Figure 4] Figure 4 is a diagram of the average methylation value in the TCGA database of the target sequence of SEQ ID NO: 5 in Example 2 of the present invention; [Figure 5] Figure 5 is a diagram of the average methylation value in the TCGA database of the target sequence of SEQ ID NO: 6 in Example 2 of the present invention; [Figure 6] Figure 6 is a diagram of the average methylation value in the TCGA database of the target sequence of SEQ ID NO: 8 in Example 2 of the present invention; [Figure 7] Figure 7 is a diagram of the average methylation value in the TCGA database of the target sequence of SEQ ID NO: 10 in Example 2 of the present invention; [Figure 8] Figure 8 is a diagram of the average methylation value in the TCGA database of the target sequence of SEQ ID NO: 12 in Example 2 of the present invention; [Figure 9] Figure 9 is a diagram of the average methylation value in the TCGA database of the target sequence of SEQ ID NO: 13 in Example 2 of the present invention; [Figure 10] Figure 10 is a heat map of the average methylation values ​​of the target sequences of SEQ ID NO: 1 to SEQ ID NO: 14 in different tumor cell lines in Example 3 of the present invention; [Figure 11] Figure 11 shows the distribution and ROC diagram of the average methylation value of the target sequence of SEQ ID NO: 1 in six types of tumors in Example 4 of the present invention; [Figure 12] Figure 12 shows the distribution and ROC diagram of the average methylation value of the target sequence of SEQ ID NO: 2 in six types of tumors in Example 5 of the present invention; [Figure 13] Figure 13 shows the distribution and ROC diagram of the average methylation value of the target sequence of SEQ ID NO: 3 in six types of tumors in Example 6 of the present invention; [Figure 14] Figure 14 shows the distribution and ROC diagram of the average methylation value of the target sequence of SEQ ID NO: 4 in six types of tumors in Example 7 of the present invention; [Figure 15] Figure 15 shows the distribution and ROC diagram of the average methylation value of the target sequence of SEQ ID NO: 5 in six types of tumors in Example 8 of the present invention; [Figure 16] Figure 16 shows the distribution and ROC diagram of the average methylation value of the target sequence of SEQ ID NO: 6 in five types of tumors in Example 9 of the present invention; [Figure 17] Figure 17 shows the distribution and ROC diagram of the average methylation value of the target sequence of SEQ ID NO: 7 in five types of tumors in Example 10 of the present invention; [Figure 18] Figure 18 shows the distribution and ROC diagram of the average methylation value of the target sequence of SEQ ID NO: 8 in six types of tumors in Example 11 of the present invention; [Figure 19] Figure 19 shows the distribution and ROC diagram of the average methylation value of the target sequence of SEQ ID NO: 9 in six types of tumors in Example 12 of the present invention; [Figure 20] Figure 20 shows the distribution and ROC diagram of the average methylation value of the target sequence of SEQ ID NO: 10 in six types of tumors in Example 13 of the present invention; [Figure 21] Figure 21 shows the distribution and ROC diagram of the average methylation value of the target sequence of SEQ ID NO: 11 in six types of tumors in Example 14 of the present invention; [Figure 22] Figure 22 shows the distribution and ROC diagram of the average methylation value of the target sequence of SEQ ID NO: 12 in six types of tumors in Example 15 of the present invention; [Figure 23] Figure 23 shows the distribution and ROC diagram of the average methylation value of the target sequence of SEQ ID NO: 13 in six types of tumors in Example 16 of the present invention; [Figure 24]Figure 24 shows the distribution and ROC diagram of the average methylation value of the target sequence of SEQ ID NO: 14 in six types of tumors in Example 17 of the present invention; [Example]

[0059] Specific Embodiments The following detailed description of the present invention will be made in more detail with reference to the accompanying drawings and examples. The following examples are provided only to more clearly illustrate the technical solutions of the present invention, and the scope of protection of the present invention is not limited thereby. Experimental methods for which no specific conditions are given in the following examples are selected according to the usual methods and conditions in the art or product specifications.

[0060] Example 1 Detection of methylation levels

[0061] Methylation detection methods such as RRBS (Reduced Representation Bisulfite Sequencing) and WGBS (Whole Genome Bisulfite Sequencing) were adopted, and the main steps were as follows: 1.1. Sample collection: Tumor cell lines were selected, or cancer tissues and paracancerous normal tissues were obtained from clinical sites. 1.2. DNA was extracted from the samples using a DNA extraction kit. 1.3. Whole genome sequencing was performed on the extracted DNA. 1.4 After sequencing, the sequences were aligned to the target sequence, and the methylation status of each CpG site within the target sequence was calculated. The average methylation value of the sequenced CpG sites in the target sequence was calculated, and this was taken as the average methylation value of this target sequence in the sample.

[0062] Example 2: Verification of target sequences of SEQ ID NO: 1 to SEQ ID NO: 14 with methylation chip data in the TCGA database

[0063] 2.1. Target Sequences and Databases The target sequences of SEQ ID NO: 1 to SEQ ID NO: 14 are shown in Table 1.

[0064] Using the TCGA database, we collected DNA methylation chip data from cancer tissues and their paracancerous normal tissues from more than 20 tumor types, including bladder cancer (BLCA), cervical cancer (CESC), cholangiocarcinoma (CHOL), colon cancer (COADREAD), esophageal cancer (ESCA), glioblastoma (GBM), head and neck squamous cell carcinoma (HNSC), clear cell renal cell carcinoma (KIRC), papillary renal cell carcinoma (KIRP), liver cancer (LIHC), lung adenocarcinoma (LUNG), pancreatic cancer (PAAD), pheochromocytoma and paraganglioma (PCPG), prostate cancer (PRAD), sarcoma (SARC), melanoma (SKCM), gastric adenocarcinoma (STAD), thyroid cancer (THCA), thymic carcinoma (THYM), and endometrial cancer (UCEC).

[0065] 2.2, the number of probes contained in each target sequence was obtained, and the results are shown in Table 3; [Table 3]

[0066] 2.3. Following the method of Example 1, the average methylation values ​​of all probes within this target sequence in all cancer samples and normal tissue samples were calculated. The results are shown in Figures 1 to 9. Samples were named using the English name of the cancer, C or N (number), where C represents tumor tissue, N represents normal tissue, and the number represents the sample amount.

[0067] Figure 1 shows the average methylation value of the target sequence of SEQ ID NO: 1 in the TCGA database. As can be seen, the average methylation value of the target sequence of SEQ ID NO: 1 is significantly higher than that of normal samples in 17 types of cancer, including bladder cancer (BLCA), cervical cancer (CESC), bile duct carcinoma (CHOL), colon cancer (COADREAD), esophageal cancer (ESCA), glioblastoma (GBM), head and neck squamous cell carcinoma (HNSC), clear cell renal cell carcinoma (KIRC), papillary renal cell carcinoma (KIRP), lung adenocarcinoma (LUNG), pheochromocytoma and paraganglioma (PCPG), prostate cancer (PRAD), melanoma (SKCM), gastric adenocarcinoma (STAD), thyroid cancer (THCA), thymic carcinoma (THYM), and endometrial cancer (UCEC).

[0068] Figure 2 shows the average methylation value of the target sequence of SEQ ID NO: 3 in the TCGA database. As can be seen, the average methylation value of the target sequence of SEQ ID NO: 3 is significantly higher than that of normal samples in 20 types of cancer, including bladder cancer (BLCA), cervical cancer (CESC), cholangiocarcinoma (CHOL), colon cancer (COADREAD), esophageal cancer (ESCA), glioblastoma (GBM), head and neck squamous cell carcinoma (HNSC), clear cell renal cell carcinoma (KIRC), papillary renal cell carcinoma (KIRP), liver cancer (LIHC), lung adenocarcinoma (LUNG), pancreatic cancer (PAAD), pheochromocytoma and paraganglioma (PCPG), prostate cancer (PRAD), sarcoma (SARC), melanoma (SKCM), gastric adenocarcinoma (STAD), thyroid cancer (THCA), thymic carcinoma (THYM), and endometrial cancer (UCEC).

[0069] Figure 3 shows the average methylation value of the target sequence of SEQ ID NO: 4 in the TCGA database. As can be seen, the average methylation value of the target sequence of SEQ ID NO: 4 is significantly higher than that of normal samples in 19 types of cancer, namely, bladder cancer (BLCA), cervical cancer (CESC), cholangiocarcinoma (CHOL), colon cancer (COADREAD), esophageal cancer (ESCA), glioblastoma (GBM), head and neck squamous cell carcinoma (HNSC), clear cell renal cell carcinoma (KIRC), papillary renal cell carcinoma (KIRP), liver cancer (LIHC), lung adenocarcinoma (LUNG), pancreatic cancer (PAAD), prostate cancer (PRAD), sarcoma (SARC), melanoma (SKCM), gastric adenocarcinoma (STAD), thyroid cancer (THCA), thymic carcinoma (THYM), and endometrial cancer (UCEC). The target sequence of SEQ ID NO: 4 has an average methylation value in pheochromocytoma and paraganglioma (PCPG) that is not significantly different from the average methylation value in normal samples.

[0070] Figure 4 shows the average methylation value of the target sequence of SEQ ID NO: 5 in the TCGA database. As can be seen, the average methylation value of the target sequence of SEQ ID NO: 5 is significantly higher than that of normal samples in 19 types of cancer, including bladder cancer (BLCA), cervical cancer (CESC), bile duct carcinoma (CHOL), colon cancer (COADREAD), esophageal cancer (ESCA), glioblastoma (GBM), head and neck squamous cell carcinoma (HNSC), clear cell renal cell carcinoma (KIRC), papillary renal cell carcinoma (KIRP), liver cancer (LIHC), lung adenocarcinoma (LUNG), pancreatic cancer (PAAD), prostate cancer (PRAD), sarcoma (SARC), melanoma (SKCM), gastric adenocarcinoma (STAD), thyroid cancer (THCA), thymic carcinoma (THYM), and endometrial cancer (UCEC). The target sequence of SEQ ID NO: 5 has a lower average methylation level in pheochromocytoma and paraganglioma (PCPG) than in normal samples.

[0071] Figure 5 shows the average methylation value of the target sequence of SEQ ID NO: 6 in the TCGA database. As can be seen, the average methylation value of the target sequence of SEQ ID NO: 6 is significantly higher than that of normal samples in 18 types of cancer, namely, bladder cancer (BLCA), cervical cancer (CESC), bile duct carcinoma (CHOL), colon cancer (COADREAD), esophageal cancer (ESCA), head and neck squamous cell carcinoma (HNSC), clear cell renal cell carcinoma (KIRC), papillary renal cell carcinoma (KIRP), liver cancer (LIHC), lung adenocarcinoma (LUNG), pancreatic cancer (PAAD), prostate cancer (PRAD), sarcoma (SARC), melanoma (SKCM), gastric adenocarcinoma (STAD), thyroid cancer (THCA), thymic carcinoma (THYM), and endometrial cancer (UCEC). The target sequence of SEQ ID NO: 6 has an average methylation level lower in glioblastoma (GBM), pheochromocytoma and paraganglioma (PCPG) than in normal samples.

[0072] Figure 6 shows the average methylation value of the target sequence of SEQ ID NO: 8 in the TCGA database. As can be seen, the average methylation value of the target sequence of SEQ ID NO: 8 is significantly higher than that of normal samples in 19 types of cancer, including bladder cancer (BLCA), cervical cancer (CESC), bile duct carcinoma (CHOL), colon cancer (COADREAD), esophageal cancer (ESCA), glioblastoma (GBM), head and neck squamous cell carcinoma (HNSC), clear cell renal cell carcinoma (KIRC), papillary renal cell carcinoma (KIRP), liver cancer (LIHC), lung adenocarcinoma (LUNG), pancreatic cancer (PAAD), prostate cancer (PRAD), sarcoma (SARC), melanoma (SKCM), gastric adenocarcinoma (STAD), thyroid cancer (THCA), thymic carcinoma (THYM), and endometrial cancer (UCEC). The target sequence of SEQ ID NO: 8 has a lower average methylation level in pheochromocytoma and paraganglioma (PCPG) than in normal samples.

[0073] Figure 7 shows the average methylation value of the target sequence of SEQ ID NO: 10 in the TCGA database. As can be seen, the average methylation value of the target sequence of SEQ ID NO: 10 is significantly higher than that of normal samples in 20 types of cancer, including bladder cancer (BLCA), cervical cancer (CESC), cholangiocarcinoma (CHOL), colon cancer (COADREAD), esophageal cancer (ESCA), glioblastoma (GBM), head and neck squamous cell carcinoma (HNSC), clear cell renal cell carcinoma (KIRC), papillary renal cell carcinoma (KIRP), liver cancer (LIHC), lung adenocarcinoma (LUNG), pancreatic cancer (PAAD), pheochromocytoma and paraganglioma (PCPG), prostate cancer (PRAD), sarcoma (SARC), melanoma (SKCM), gastric adenocarcinoma (STAD), thyroid cancer (THCA), thymic carcinoma (THYM), and endometrial cancer (UCEC).

[0074] Figure 8 shows the average methylation value of the target sequence of SEQ ID NO: 12 in the TCGA database. As can be seen, the average methylation value of the target sequence of SEQ ID NO: 12 is significantly higher than that of normal samples in 20 types of cancer, including bladder cancer (BLCA), cervical cancer (CESC), cholangiocarcinoma (CHOL), colon cancer (COADREAD), esophageal cancer (ESCA), glioblastoma (GBM), head and neck squamous cell carcinoma (HNSC), clear cell renal cell carcinoma (KIRC), papillary renal cell carcinoma (KIRP), liver cancer (LIHC), lung adenocarcinoma (LUNG), pancreatic cancer (PAAD), pheochromocytoma and paraganglioma (PCPG), prostate cancer (PRAD), sarcoma (SARC), melanoma (SKCM), gastric adenocarcinoma (STAD), thyroid cancer (THCA), thymic carcinoma (THYM), and endometrial cancer (UCEC).

[0075] Figure 9 shows the average methylation value of the target sequence of SEQ ID NO: 13 in the TCGA database. As can be seen, the average methylation value of the target sequence of SEQ ID NO: 13 is significantly higher than that of normal samples in 20 types of cancer, including bladder cancer (BLCA), cervical cancer (CESC), cholangiocarcinoma (CHOL), colon cancer (COADREAD), esophageal cancer (ESCA), glioblastoma (GBM), head and neck squamous cell carcinoma (HNSC), clear cell renal cell carcinoma (KIRC), papillary renal cell carcinoma (KIRP), liver cancer (LIHC), lung adenocarcinoma (LUNG), pancreatic cancer (PAAD), pheochromocytoma and paraganglioma (PCPG), prostate cancer (PRAD), sarcoma (SARC), melanoma (SKCM), gastric adenocarcinoma (STAD), thyroid cancer (THCA), thymic carcinoma (THYM), and endometrial cancer (UCEC).

[0076] As can be seen, in the majority of the above tumor types, the target sequences SEQ ID NO: 1, SEQ ID NO: 3, SEQ ID NO: 4, SEQ ID NO: 5, SEQ ID NO: 6, SEQ ID NO: 8, SEQ ID NO: 10, SEQ ID NO: 12, SEQ ID NO: 13 have higher average methylation values ​​in tumor samples than in normal tissues.

[0077] Example 3 Methylation levels of target sequences of SEQ ID NO: 1 to SEQ ID NO: 14 in tumor cell lines

[0078] Eleven tumor cell line samples were collected, including those from cholangiocarcinoma, breast cancer, colorectal cancer, gallbladder cancer, kidney cancer, leukemia, liver cancer, lung cancer, pancreatic cancer, prostate cancer, and gastric cancer. According to the method described in Example 1, the average methylation level of each of the 14 target sequences was obtained using RRBS methylation sequencing technology. The results are shown in Figure 10. In the figure, white indicates undetected or substandard sequencing quality, and darker colors indicate higher average methylation levels. As can be seen, the methylation status of the target sequences SEQ ID NO:1, SEQ ID NO:2, SEQ ID NO:3, SEQ ID NO:4, SEQ ID NO:5, SEQ ID NO:8, SEQ ID NO:9, SEQ ID NO:12, and SEQ ID NO:13 could be detected in all 11 tumor cell lines, and the average methylation levels were high in all 11 tumor cell lines. The methylation status of the target sequences SEQ ID NO:6, SEQ ID NO:7, SEQ ID NO:10, SEQ ID NO:11, and SEQ ID NO:14 was only detected in some tumor cell lines.

[0079] Example 4 Use of the target sequence of SEQ ID NO: 1 in a clinical test

[0080] Samples: Six types of tumor tissues and their paracancerous normal tissue samples were collected from breast cancer (5 cancer tissues, 5 paracancerous normal tissues), cervical cancer (4 cancer tissues, 5 paracancerous normal tissues), esophageal cancer (3 cancer tissues, 1 paracancerous normal tissue), head and neck cancer (4 cancer tissues, 5 paracancerous normal tissues), lung cancer (5 cancer tissues, 5 paracancerous normal tissues), and pancreatic cancer (5 cancer tissues, 5 paracancerous normal tissues).

[0081] According to the method of Example 1, the average methylation values ​​of the target sequence of SEQ ID NO: 1 in these 26 tumor tissues and 26 paracancerous normal tissues were obtained using RRBS methylation sequencing technology. The results are shown in Figure 11. The figure contains six graph sets, A, B, C, D, E, and F. Each graph set contains two graphs. The left graph is a box plot of the distribution of the average methylation values ​​of the target sequence in tumor samples and cancer-normal samples (controls), which reveals the difference in methylation of the target sequence between tumor samples and normal samples; the right graph is a ROC curve of the detected values, which reveals the specificity of the difference results. Here, A: breast cancer samples and their controls; B: cervical cancer samples and their controls; C: esophageal cancer samples and their controls; D: head and neck cancer samples and their controls; E: lung cancer samples and their controls; and F: pancreatic cancer samples and their controls. As can be seen, the average methylation values ​​of the target sequence of SEQ ID NO: 1 in tumor samples are all higher than in paracancerous normal tissues in the six tumor types. Based on the average methylation value of the target sequence of SEQ ID NO: 1 in the sample, tumor samples can be accurately distinguished from cancer normal tissues.

[0082] Example 5 Use of the target sequence of SEQ ID NO: 2 in a clinical test

[0083] Samples: Six types of tumor tissues and their paracancerous normal tissue samples were collected from breast cancer (4 cancer tissues, 5 paracancerous normal tissues), cervical cancer (4 cancer tissues, 5 paracancerous normal tissues), esophageal cancer (3 cancer tissues, 1 paracancerous normal tissue), head and neck cancer (4 cancer tissues, 5 paracancerous normal tissues), lung cancer (5 cancer tissues, 5 paracancerous normal tissues), and pancreatic cancer (5 cancer tissues, 5 paracancerous normal tissues).

[0084] According to the method of Example 1, the average methylation values ​​of the target sequence of SEQ ID NO:2 in these 25 tumor tissues and 26 paracancerous normal tissues were obtained using RRBS methylation sequencing technology. The results are shown in Figure 12. The figure contains six graph sets, A, B, C, D, E, and F. Each graph set contains two graphs. The left graph is a box plot of the distribution of the average methylation values ​​of the target sequence in tumor samples and cancer-normal samples (controls), which reveals the difference in methylation of the target sequence between tumor samples and normal samples; the right graph is a ROC curve of the detected values, which reveals the specificity of the differential results. A: breast cancer samples and their controls; B: cervical cancer samples and their controls; C: esophageal cancer samples and their controls; D: head and neck cancer samples and their controls; E: lung cancer samples and their controls; and F: pancreatic cancer samples and their controls. As can be seen, the average methylation values ​​of the target sequence of SEQ ID NO:2 in tumor samples are all higher than in paracancerous normal tissues in the six tumor types. Based on the average methylation value of the target sequence of SEQ ID NO: 2 in the sample, tumor samples can be accurately distinguished from cancer normal tissues.

[0085] Example 6 Use of the target sequence of SEQ ID NO: 3 in a clinical test

[0086] Samples: Six types of tumor tissues and their paracancerous normal tissue samples were collected from breast cancer (5 cancer tissues, 5 paracancerous normal tissues), cervical cancer (5 cancer tissues, 5 paracancerous normal tissues), esophageal cancer (5 cancer tissues, 4 paracancerous normal tissues), head and neck cancer (5 cancer tissues, 5 paracancerous normal tissues), lung cancer (4 cancer tissues, 2 paracancerous normal tissues), and pancreatic cancer (2 cancer tissues, 2 paracancerous normal tissues).

[0087] According to the method of Example 1, the average methylation values ​​of the target sequence of SEQ ID NO:3 in these 26 tumor tissues and 23 paracancerous normal tissues were obtained using RRBS methylation sequencing technology. The results are shown in Figure 13. The figure contains six graph sets, A, B, C, D, E, and F. Each graph set contains two graphs. The left graph is a box plot of the distribution of the average methylation values ​​of the target sequence in tumor samples and cancer-normal samples (controls), which reveals the difference in methylation of the target sequence between tumor samples and normal samples. The right graph is a ROC curve of the detected results, which reveals the specificity of the differential results. A: breast cancer samples and their controls; B: cervical cancer samples and their controls; C: esophageal cancer samples and their controls; D: head and neck cancer samples and their controls; E: lung cancer samples and their controls; F: pancreatic cancer samples and their controls. As can be seen, in the five types of tumors, the average methylation values ​​of the target sequence of SEQ ID NO: 3 in tumor samples were all higher than those in the paracancerous normal tissues; in esophageal cancer, the average methylation values ​​in most tumor samples were higher than those in the paracancerous normal tissues. Based on the average methylation values ​​of the target sequence of SEQ ID NO: 3 in the samples, most tumor samples and cancer normal tissues could be accurately distinguished.

[0088] Example 7 Use of the target sequence of SEQ ID NO: 4 in a clinical test

[0089] Samples: Six types of tumor tissues and their paracancerous normal tissue samples were collected from breast cancer (4 cancer tissues, 4 paracancerous normal tissues), cervical cancer (5 cancer tissues, 2 paracancerous normal tissues), esophageal cancer (5 cancer tissues, 4 paracancerous normal tissues), head and neck cancer (2 cancer tissues, 4 paracancerous normal tissues), lung cancer (5 cancer tissues, 5 paracancerous normal tissues), and pancreatic cancer (5 cancer tissues, 5 paracancerous normal tissues).

[0090] According to the method of Example 1, the average methylation values ​​of the target sequence of SEQ ID NO: 4 in these 26 tumor tissues and 24 paracancerous normal tissues were obtained using RRBS methylation sequencing technology. The results are shown in Figure 14. The figure contains six graph sets, A, B, C, D, E, and F. Each graph set contains two graphs. The left graph is a box plot of the distribution of the average methylation values ​​of the target sequence in tumor samples and cancer-normal samples (controls), which reveals the difference in methylation of the target sequence between tumor samples and normal samples. The right graph is a ROC curve of the detected results, which reveals the specificity of the differential results. A: breast cancer samples and their controls; B: cervical cancer samples and their controls; C: esophageal cancer samples and their controls; D: head and neck cancer samples and their controls; E: lung cancer samples and their controls; F: pancreatic cancer samples and their controls. As can be seen, the average methylation values ​​of the target sequence of SEQ ID NO: 4 in breast cancer samples, head and neck cancer samples, and esophageal cancer samples are all higher than the average methylation values ​​in paracancerous normal tissues. In esophageal cancer samples, cervical cancer samples, and lung cancer samples, the average methylation values ​​of the target sequence of SEQ ID NO: 4 are mostly higher than the average methylation values ​​in paracancerous normal tissues, and the average methylation values ​​are all higher than the average methylation values ​​in paracancerous normal tissues. Based on the average methylation value of the target sequence of SEQ ID NO: 4 in the samples, it is possible to accurately distinguish most tumor samples from cancer normal tissues.

[0091] Example 8 Use of the target sequence of SEQ ID NO: 5 in a clinical test

[0092] Samples: Six types of tumor tissues and their paracancerous normal tissue samples were collected from breast cancer (5 cancer tissues, 5 paracancerous normal tissues), cervical cancer (3 cancer tissues, 4 paracancerous normal tissues), esophageal cancer (4 cancer tissues, 3 paracancerous normal tissues), head and neck cancer (4 cancer tissues, 5 paracancerous normal tissues), lung cancer (2 cancer tissues, 2 paracancerous normal tissues), and pancreatic cancer (3 cancer tissues, 2 paracancerous normal tissues).

[0093] According to the method of Example 1, the average methylation values ​​of the target sequence of SEQ ID NO:5 in these 21 tumor tissues and 21 paracancerous normal tissues were obtained using RRBS methylation sequencing technology. The results are shown in Figure 15. The figure contains six graph sets, A, B, C, D, E, and F. Each graph set contains two graphs. The left graph is a box plot of the distribution of the average methylation values ​​of the target sequence in tumor samples and cancer-normal samples (controls), which reveals the difference in methylation of the target sequence between tumor samples and normal samples. The right graph is a ROC curve of the detected results, which reveals the specificity of the difference results. A: breast cancer samples and their controls; B: cervical cancer samples and their controls; C: esophageal cancer samples and their controls; D: head and neck cancer samples and their controls; E: lung cancer samples and their controls; F: pancreatic cancer samples and their controls. As can be seen, in breast cancer samples, cervical cancer samples, and lung cancer samples, the average methylation value of the target sequence of SEQ ID NO: 4 is higher than the average methylation value in paracancerous normal tissues. In esophageal cancer, head and neck cancer, and lung cancer samples, the average methylation value of the target sequence of SEQ ID NO: 5 is mostly higher than the average methylation value in paracancerous normal tissues, and the average methylation values ​​are all higher than the average methylation value in paracancerous normal tissues. Based on the average methylation value of the target sequence of SEQ ID NO: 5 in the samples, most tumor samples can be accurately distinguished from cancer normal tissues.

[0094] Example 9 Use of the target sequence of SEQ ID NO: 6 in a clinical test

[0095] Samples: Five types of tumor tissues and their paracancerous normal tissue samples were from breast cancer (5 cancer tissues, 5 paracancerous normal tissues), esophageal cancer (2 cancer tissues, 1 paracancerous normal tissue), head and neck cancer (5 cancer tissues, 5 paracancerous normal tissues), lung cancer (3 cancer tissues, 1 paracancerous normal tissue), and pancreatic cancer (2 cancer tissues, 1 paracancerous normal tissue).

[0096] According to the method of Example 1, the average methylation values ​​of the target sequence of SEQ ID NO:6 in these 17 tumor tissues and 13 paracancerous normal tissues were obtained using RRBS methylation sequencing technology. The results are shown in Figure 16. The figure contains five graph sets, A, B, C, D, and E. Each graph set contains two graphs. The left graph is a box plot of the distribution of the average methylation values ​​of the target sequence in tumor samples and cancer-normal samples (controls), which reveals the difference in methylation of the target sequence between tumor samples and normal samples; the right graph is a ROC curve of the detected values, which reveals the specificity of the differential results. A: breast cancer samples and their controls; B: esophageal cancer samples and their controls; C: head and neck cancer samples and their controls; D: lung cancer samples and their controls; E: pancreatic cancer samples and their controls. As can be seen, in all five tumor types, the average methylation values ​​of the target sequence of SEQ ID NO:6 in tumor samples are higher than in paracancerous normal tissues. Based on the average methylation value of the target sequence of SEQ ID NO: 6 in the sample, tumor samples can be accurately distinguished from cancer normal tissues.

[0097] Example 10 Use of the target sequence of SEQ ID NO: 7 in a clinical test

[0098] Samples: Five types of tumor tissues and their paracancerous normal tissue samples were from breast cancer (5 cancer tissues, 4 paracancerous normal tissues), cervical cancer (2 cancer tissues, 1 paracancerous normal tissue), head and neck cancer (2 cancer tissues, 2 paracancerous normal tissues), lung cancer (3 cancer tissues, 3 paracancerous normal tissues), and pancreatic cancer (4 cancer tissues, 5 paracancerous normal tissues).

[0099] According to the method of Example 1, the average methylation values ​​of the target sequence of SEQ ID NO:7 in these 16 tumor tissues and 15 paracancerous normal tissues were obtained using RRBS methylation sequencing technology. The results are shown in Figure 17. The figure contains five graph sets, A, B, C, D, and E. Each graph set contains two graphs. The left graph is a box plot of the distribution of the average methylation values ​​of the target sequence in tumor samples and cancer-normal samples (controls), which reveals the difference in methylation of the target sequence between tumor samples and normal samples; the right graph is a ROC curve of the detected values, which reveals the specificity of the difference results. A: breast cancer samples and their controls; B: cervical cancer samples and their controls; C: head and neck cancer samples and their controls; D: lung cancer samples and their controls; E: pancreatic cancer samples and their controls. As can be seen, the average methylation values ​​of the target sequence of SEQ ID NO:7 in tumor samples are all higher than in paracancerous normal tissues in the five tumor types. Based on the average methylation value of the target sequence of SEQ ID NO: 7 in the sample, tumor samples can be accurately distinguished from cancer normal tissues.

[0100] Example 11 Use of the target sequence of SEQ ID NO: 8 in a clinical test

[0101] Samples: Six types of tumor tissues and their paracancerous normal tissue samples were collected from breast cancer (5 cancer tissues, 5 paracancerous normal tissues), cervical cancer (4 cancer tissues, 5 paracancerous normal tissues), esophageal cancer (4 cancer tissues, 5 paracancerous normal tissues), head and neck cancer (4 cancer tissues, 5 paracancerous normal tissues), lung cancer (5 cancer tissues, 5 paracancerous normal tissues), and pancreatic cancer (4 cancer tissues, 5 paracancerous normal tissues).

[0102] According to the method of Example 1, the average methylation values ​​of the target sequence of SEQ ID NO:8 in these 26 tumor tissues and 30 paracancerous normal tissues were obtained using RRBS methylation sequencing technology. The results are shown in Figure 18. The figure includes six graph sets, A, B, C, D, E, and F. Each graph set contains two graphs. The left graph is a box plot of the distribution of the average methylation values ​​of the target sequence in tumor samples and cancer-normal samples (controls), which reveals the difference in methylation of the target sequence between tumor samples and normal samples. The right graph is a ROC curve of the detected results, which reveals the specificity of the differential results. A: breast cancer samples and their controls; B: cervical cancer samples and their controls; C: esophageal cancer samples and their controls; D: head and neck cancer samples and their controls; E: lung cancer samples and their controls; F: pancreatic cancer samples and their controls. As can be seen, in breast cancer samples, cervical cancer samples, lung cancer, head and neck cancer, and pancreatic cancer samples, the average methylation values ​​of the target sequence of SEQ ID NO: 8 are all higher than the average methylation value in paracancerous normal tissues. In esophageal cancer samples, the average methylation values ​​of the target sequence of SEQ ID NO: 8 are mostly higher than the average methylation value in paracancerous normal tissues, and the average of these average methylation values ​​is also higher than the average average methylation value in paracancerous normal tissues. Based on the average methylation value of the target sequence of SEQ ID NO: 8 in the samples, most tumor samples can be accurately distinguished from cancer normal tissues.

[0103] Example 12 Use of the target sequence of SEQ ID NO: 9 in a clinical test

[0104] Samples: Six types of tumor tissues and their paracancerous normal tissue samples were collected from breast cancer (5 cancer tissues, 5 paracancerous normal tissues), cervical cancer (4 cancer tissues, 5 paracancerous normal tissues), esophageal cancer (5 cancer tissues, 4 paracancerous normal tissues), head and neck cancer (4 cancer tissues, 4 paracancerous normal tissues), lung cancer (5 cancer tissues, 4 paracancerous normal tissues), and pancreatic cancer (5 cancer tissues, 5 paracancerous normal tissues).

[0105] According to the method of Example 1, the average methylation values ​​of the target sequence of SEQ ID NO:9 in these 28 tumor tissues and 27 paracancerous normal tissues were obtained using RRBS methylation sequencing technology. The results are shown in Figure 19. The figure includes six graph sets, A, B, C, D, E, and F. Each graph set contains two graphs. The left graph is a box plot of the distribution of the average methylation values ​​of the target sequence in tumor samples and cancer-normal samples (controls), which reveals the difference in methylation of the target sequence between tumor samples and normal samples. The right graph is a ROC curve of the detected results, which reveals the specificity of the difference results. A: breast cancer samples and their controls; B: cervical cancer samples and their controls; C: esophageal cancer samples and their controls; D: head and neck cancer samples and their controls; E: lung cancer samples and their controls; F: pancreatic cancer samples and their controls. As can be seen, in breast cancer samples, cervical cancer samples, lung cancer, head and neck cancer, and pancreatic cancer samples, the average methylation values ​​of the target sequence of SEQ ID NO: 9 are all higher than the average methylation value in paracancerous normal tissues. In esophageal cancer samples, the average methylation values ​​of the target sequence of SEQ ID NO: 9 are mostly higher than the average methylation value in paracancerous normal tissues, and the average methylation values ​​are all higher than the average methylation value in paracancerous normal tissues. Based on the average methylation value of the target sequence of SEQ ID NO: 9 in the samples, most tumor samples can be accurately distinguished from cancerous normal tissues.

[0106] Example 13 Use of the target sequence of SEQ ID NO: 10 in clinical testing

[0107] Samples: Six types of tumor tissues and their paracancerous normal tissue samples were collected from breast cancer (5 cancer tissues, 5 paracancerous normal tissues), cervical cancer (4 cancer tissues, 3 paracancerous normal tissues), esophageal cancer (4 cancer tissues, 5 paracancerous normal tissues), head and neck cancer (4 cancer tissues, 5 paracancerous normal tissues), lung cancer (4 cancer tissues, 3 paracancerous normal tissues), and pancreatic cancer (4 cancer tissues, 5 paracancerous normal tissues).

[0108] According to the method of Example 1, the average methylation values ​​of the target sequence of SEQ ID NO: 10 in these 25 tumor tissues and 26 paracancerous normal tissues were obtained using RRBS methylation sequencing technology. The results are shown in Figure 20. The figure includes six graph sets, A, B, C, D, E, and F. Each graph set contains two graphs. The left graph is a box plot of the distribution of the average methylation values ​​of the target sequence in tumor samples and cancer-normal samples (controls), which reveals the difference in methylation of the target sequence between tumor samples and normal samples. The right graph is a ROC curve of the detected results, which reveals the specificity of the difference results. A: breast cancer samples and their controls; B: cervical cancer samples and their controls; C: esophageal cancer samples and their controls; D: head and neck cancer samples and their controls; E: lung cancer samples and their controls; F: pancreatic cancer samples and their controls. As can be seen, in breast cancer samples, cervical cancer samples, lung cancer, head and neck cancer samples, the average methylation values ​​of the target sequence of SEQ ID NO: 10 are all higher than the average methylation value in paracancerous normal tissues. In esophageal cancer samples, the average methylation values ​​of the target sequence of SEQ ID NO: 10 are mostly higher than the average methylation value in paracancerous normal tissues, and the average methylation values ​​are all higher than the average methylation value in paracancerous normal tissues. Based on the average methylation value of the target sequence of SEQ ID NO: 10 in the samples, most tumor samples can be accurately distinguished from cancer normal tissues.

[0109] Example 14 Use of the target sequence of SEQ ID NO: 11 in a clinical test

[0110] Samples: Six types of tumor tissues and their paracancerous normal tissue samples were collected from breast cancer (5 cancer tissues, 5 paracancerous normal tissues), cervical cancer (2 cancer tissues, 5 paracancerous normal tissues), esophageal cancer (1 cancer tissue, 3 paracancerous normal tissues), head and neck cancer (5 cancer tissues, 5 paracancerous normal tissues), lung cancer (4 cancer tissues, 4 paracancerous normal tissues), and pancreatic cancer (3 cancer tissues, 3 paracancerous normal tissues).

[0111] According to the method of Example 1, the average methylation values ​​of the target sequence of SEQ ID NO: 11 in these 20 tumor tissues and 25 paracancerous normal tissues were obtained using RRBS methylation sequencing technology. The results are shown in Figure 21. The figure includes six graph sets, A, B, C, D, E, and F. Each graph set contains two graphs. The left graph is a box plot of the distribution of the average methylation values ​​of the target sequence in tumor samples and cancer-normal samples (controls), which reveals the difference in methylation of the target sequence between tumor samples and normal samples; the right graph is a ROC curve of the detected results, which reveals the specificity of the difference results. A: breast cancer samples and their controls; B: cervical cancer samples and their controls; C: esophageal cancer samples and their controls; D: head and neck cancer samples and their controls; E: lung cancer samples and their controls; F: pancreatic cancer samples and their controls. As can be seen, in breast cancer samples, cervical cancer samples, lung cancer, esophageal cancer and pancreatic cancer samples, the average methylation values ​​of the target sequence of SEQ ID NO: 11 are all higher than the average methylation value in paracancerous normal tissues. In head and neck cancer samples, the average methylation values ​​of the target sequence of SEQ ID NO: 11 are mostly higher than the average methylation value in paracancerous normal tissues, and the average of these average methylation values ​​is also higher than the average average methylation value in paracancerous normal tissues. Based on the average methylation value of the target sequence of SEQ ID NO: 11 in the samples, most tumor samples and cancer normal tissues can be accurately distinguished.

[0112] Example 15 Use of the target sequence of SEQ ID NO: 12 in clinical testing

[0113] Samples: Six types of tumor tissues and their paracancerous normal tissue samples were collected from breast cancer (5 cancer tissues, 5 paracancerous normal tissues), cervical cancer (3 cancer tissues, 5 paracancerous normal tissues), esophageal cancer (4 cancer tissues, 3 paracancerous normal tissues), head and neck cancer (5 cancer tissues, 5 paracancerous normal tissues), lung cancer (5 cancer tissues, 5 paracancerous normal tissues), and pancreatic cancer (5 cancer tissues, 5 paracancerous normal tissues).

[0114] According to the method of Example 1, the average methylation values ​​of the target sequence of SEQ ID NO: 12 in these 27 tumor tissues and 28 paracancerous normal tissues were obtained using RRBS methylation sequencing technology. The results are shown in Figure 22. The figure includes six graph sets, A, B, C, D, E, and F. Each graph set contains two graphs. The left graph is a box plot of the distribution of the average methylation values ​​of the target sequence in tumor samples and cancer-normal samples (controls), which reveals the difference in methylation of the target sequence between tumor samples and normal samples. The right graph is a ROC curve of the detected results, which reveals the specificity of the difference results. A: breast cancer samples and their controls; B: cervical cancer samples and their controls; C: esophageal cancer samples and their controls; D: head and neck cancer samples and their controls; E: lung cancer samples and their controls; F: pancreatic cancer samples and their controls. As can be seen, in breast cancer samples, cervical cancer samples, head and neck cancer samples, esophageal cancer samples, and pancreatic cancer samples, the average methylation values ​​of the target sequence of SEQ ID NO: 12 are all higher than the average methylation value in paracancerous normal tissues. In lung cancer samples, the average methylation values ​​of the target sequence of SEQ ID NO: 12 are mostly higher than the average methylation value in paracancerous normal tissues, and the average of these average methylation values ​​is also higher than the average average methylation value in paracancerous normal tissues. Based on the average methylation value of the target sequence of SEQ ID NO: 12 in the samples, most tumor samples can be accurately distinguished from cancer normal tissues.

[0115] Example 16 Use of the target sequence of SEQ ID NO: 13 in clinical testing

[0116] Samples: Six types of tumor tissues and their paracancerous normal tissue samples were collected from breast cancer (5 cancer tissues, 5 paracancerous normal tissues), cervical cancer (1 cancer tissue, 5 paracancerous normal tissues), esophageal cancer (2 cancer tissues, 1 paracancerous normal tissue), head and neck cancer (5 cancer tissues, 5 paracancerous normal tissues), lung cancer (4 cancer tissues, 5 paracancerous normal tissues), and pancreatic cancer (5 cancer tissues, 5 paracancerous normal tissues).

[0117] According to the method of Example 1, the average methylation values ​​of the target sequence of SEQ ID NO: 13 in these 22 tumor tissues and 26 paracancerous normal tissues were obtained using RRBS methylation sequencing technology. The results are shown in Figure 23. The figure includes six graph sets, A, B, C, D, E, and F. Each graph set contains two graphs. The left graph is a box plot of the distribution of the average methylation values ​​of the target sequence in tumor samples and cancer-normal samples (controls), which reveals the difference in methylation of the target sequence between tumor samples and normal samples. The right graph is a ROC curve of the detected results, which reveals the specificity of the differential results. A: breast cancer samples and their controls; B: cervical cancer samples and their controls; C: esophageal cancer samples and their controls; D: head and neck cancer samples and their controls; E: lung cancer samples and their controls; F: pancreatic cancer samples and their controls. As can be seen, in breast cancer samples, cervical cancer samples, head and neck cancer samples, esophageal cancer samples, and pancreatic cancer samples, the average methylation values ​​of the target sequence of SEQ ID NO: 13 are all higher than the average methylation value in paracancerous normal tissues. In lung cancer samples, the average methylation values ​​of the target sequence of SEQ ID NO: 13 are mostly higher than the average methylation value in paracancerous normal tissues, and the average of these average methylation values ​​is also higher than the average average methylation value in paracancerous normal tissues. Based on the average methylation value of the target sequence of SEQ ID NO: 13 in the samples, most tumor samples can be accurately distinguished from cancer normal tissues.

[0118] Example 17 Use of the target sequence of SEQ ID NO: 14 in clinical testing

[0119] Samples: Six types of tumor tissues and their paracancerous normal tissue samples were collected from breast cancer (5 cancer tissues, 5 paracancerous normal tissues), cervical cancer (3 cancer tissues, 5 paracancerous normal tissues), esophageal cancer (3 cancer tissues, 1 paracancerous normal tissue), head and neck cancer (4 cancer tissues, 5 paracancerous normal tissues), lung cancer (3 cancer tissues, 3 paracancerous normal tissues), and pancreatic cancer (2 cancer tissues, 2 paracancerous normal tissues).

[0120] According to the method of Example 1, the average methylation values ​​of the target sequence of SEQ ID NO: 14 in these 20 tumor tissues and 21 paracancerous normal tissues were obtained using RRBS methylation sequencing technology. The results are shown in Figure 24. The figure includes six graph sets, A, B, C, D, E, and F. Each graph set contains two graphs. The left graph is a box plot of the distribution of the average methylation values ​​of the target sequence in tumor samples and cancer-normal samples (controls), which reveals the difference in methylation of the target sequence between tumor samples and normal samples. The right graph is a ROC curve of the detected results, which reveals the specificity of the difference results. A: breast cancer samples and their controls; B: cervical cancer samples and their controls; C: esophageal cancer samples and their controls; D: head and neck cancer samples and their controls; E: lung cancer samples and their controls; F: pancreatic cancer samples and their controls. As can be seen, in breast cancer samples, cervical cancer samples, head and neck cancer samples, esophageal cancer samples, and lung cancer samples, the average methylation values ​​of the target sequence of SEQ ID NO: 14 are all higher than the average methylation value in paracancerous normal tissues. In pancreatic cancer samples, the average methylation values ​​of the target sequence of SEQ ID NO: 14 are mostly higher than the average methylation value in paracancerous normal tissues, and the average of these average methylation values ​​is also higher than the average average methylation value in paracancerous normal tissues. Based on the average methylation value of the target sequence of SEQ ID NO: 14 in the samples, most tumor samples can be accurately distinguished from cancer normal tissues.

[0121] Although specific embodiments of the present invention have been described in detail above, these are merely examples, and the present invention is not limited to the above-described specific embodiments. Any modifications and replacements equivalent to the present invention that are within the scope of the present invention are also within the scope of the present invention. Therefore, all equivalent modifications and changes made within the scope of the present invention that do not deviate from the spirit and scope of the present invention are intended to be included within the scope of the present invention.

Claims

1. A use of a tumor marker for detecting the methylation status in a sample, wherein the tumor marker is located on human genome chromosomes 1, 2, 3, 5, 7, 8, 10, 11, and 21 and contains one or more CpG sites at which methylation modification can occur, and further, the tumor marker is located on the following chromosomes with reference to human genome Hg19: chr2: 105459135-105459190, chr10: 124902392-124902455, chr3: 157812331-157812498, chr21: 38378275-38378539, chr8: 97170353-9 7170404, chr5:134880362-134880455, chr10:94835119-94835252, chr11:31826557-31 826963, chr3:147114032-147114108, chr10:50819227-50819589, chr2:66809255-6680 9281, chr7:97361393-97361461, chr8:70984200-70984294, chr1:6515341-6515409, wherein the tumor is breast cancer, cervical cancer, esophageal cancer, head and neck cancer, lung cancer, or pancreatic cancer.

2. The use according to claim 1, wherein the methylation modification comprises a 5-formylation modification, a 5-hydroxymethylation modification, a 5-methylation modification, or a 5-carboxylation modification.

3. The chr2:105459135-105459190 region a) the base sequence shown in SEQ ID NO: 1; b) A complementary sequence to the base sequence shown in SEQ ID NO: 1 Selected from the group consisting of: And / or the chr10:124902392-124902455 region is a) the base sequence shown in SEQ ID NO: 2; b) A complementary sequence to the base sequence shown in SEQ ID NO: 2 Selected from the group consisting of: And / or the chr3:157812331-157812498 region is a) the base sequence shown in SEQ ID NO: 3; b) A complementary sequence of the base sequence shown in SEQ ID NO: 3 Selected from the group consisting of: And / or the chr21:38378275-38378539 region is a) the base sequence shown in SEQ ID NO: 4; b) A complementary sequence to the base sequence shown in SEQ ID NO: 4 Selected from the group consisting of: And / or the chr8:97170353-97170404 region is a) the base sequence shown in SEQ ID NO: 5; b) A complementary sequence of the base sequence shown in SEQ ID NO: 5 Selected from the group consisting of: And / or the chr5:134880362-134880455 region is a) the base sequence shown in SEQ ID NO: 6; b) A complementary sequence of the base sequence shown in SEQ ID NO: 6 Selected from the group consisting of: And / or the chr10:94835119-94835252 region is a) the base sequence shown in SEQ ID NO: 7; b) A complementary sequence of the base sequence shown in SEQ ID NO: 7 Selected from the group consisting of: And / or the chr11:31826557-31826963 region is a) the base sequence shown in SEQ ID NO: 8; b) A complementary sequence of the base sequence shown in SEQ ID NO: 8 Selected from the group consisting of: And / or the chr3:147114032-147114108 region is a) the base sequence shown in SEQ ID NO: 9; b) A complementary sequence of the base sequence shown in SEQ ID NO: 9 Selected from the group consisting of: And / or the chr10:50819227-50819589 region is a) the base sequence shown in SEQ ID NO: 10; b) A complementary sequence of the base sequence shown in SEQ ID NO: 10 Selected from the group consisting of: And / or the chr2:66809255-66809281 region is a) the base sequence shown in SEQ ID NO: 11; b) A complementary sequence of the base sequence shown in SEQ ID NO: 11 Selected from the group consisting of: And / or the chr7:97361393-97361461 region is a) the base sequence shown in SEQ ID NO: 12; b) A complementary sequence of the base sequence shown in SEQ ID NO: 12 Selected from the group consisting of: And / or the chr8:70984200-70984294 region is a) the base sequence shown in SEQ ID NO: 13; b) A complementary sequence of the base sequence shown in SEQ ID NO: 13 Selected from the group consisting of: And / or the chr1:6515341-6515409 region is a) the base sequence shown in SEQ ID NO: 14; b) A complementary sequence of the base sequence shown in SEQ ID NO: 14 Selected from the group consisting of 3. The use according to claim 2 .

4. Use of a tumor marker as defined in any one of claims 1 to 3 in tumor screening, prognosis, diagnostic reagent and drug target in a non-human subject.

5. The use according to claim 4, characterized in that it comprises detecting the methylation status of CpG sites of said tumor marker.

6. A method for detecting a tumor marker, comprising the steps of: S1, obtaining a tissue sample to be detected; S2, extract DNA from the tissue sample to be detected and obtain the methylation value of the sample; S3: Calculating the methylation status of each CpG site within the tumor marker sequence region defined in any one of claims 1 to 3, or the average methylation status of the entire region.

7. The method of claim 6, wherein the method for obtaining the methylation value of the sample in step S2 includes sequencing, probes, antibodies, mass spectrometry, etc.

8. A tumor marker detection kit, comprising a primer or probe that specifically detects the tumor marker defined in any one of claims 1 to 3.

9. The tumor marker detection kit according to claim 8, wherein specifically detecting the tumor marker comprises specifically detecting methylation of a CpG site of the tumor marker.

10. 10. The tumor marker detection kit according to claim 9, wherein the methylation of the CpG site of the tumor marker includes 5-formylation, 5-hydroxymethylation, 5-methylation, or 5-carboxylation.

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