Detection of minimal residual disease in cancer patients

Abstract

Compositions and methods are provided for determining minimal residual disease (MRD) in cancer patients following therapy. In some embodiments the patient is a breast cancer patient that has been treated with NAC. The methods, termed spatial MRS (s-MRD) apply blood-based assessment tools to tumor tissue to accurately characterize molecular residual disease.

Description

DETECTION OF MINIMAL RESIDUAL DISEASE IN CANCER PATIENTSCROSS-REFERENCE TO ELATED APPLICATIONS

[0001] Pursuant to 35 U.S.C. § 119 (e), this application claims priority to the filing date of United States Provisional Patent Application Serial No. 63 / 606 / 028, filed December 4, 2023, the disclosure of which application is herein incorporated by reference.BACKGROU D OF THE INVENTION

[0002] Breast cancer is the second most common cancer in the U.S. Due to the high uptake of screening mammography, most cases are diagnosed at curable stages with local or locally advanced disease, but despite this, many people die from disease that spreads outside of the breast each year in the U.S. alone, demonstrating the need for improved treatments.

[0003] Locally advanced disease is increasingly treated with neoadjuvant chemotherapy (NAG) which can down-stage disease prior to surgery, monitor chemo-sensitivity, and provide prognostic information via pathologic response. Achievement of a pathologic complete response (pCR), identified as not having any residual cancer cells under the microscope after NAG at the time of surgery, is prognostic across breast cancer types. This is particularly the case in triple negative and HER2-positive breast cancer where patients with residual disease are given adjuvant treatment to decrease recurrence risk.

[0004] Following NAG, residual cancer assessment is performed using resection samples from the primary breast tumor site and the regional lymph nodes, in order to inform the next treatment steps. Typically, the Residual Cancer Burden (RGB) index is utilized for this assessment. However, it is widely recognized in the field that histopathological tools such as RBC are imperfect at assessing cancer status and predicting recurrence. For example, 12% of patients that achieve pathologic complete response (pCR) will experience disease recurrence, while almost half of subjects that are deemed to have a high burden of disease will actually remain cancer-free.

[0005] Therefore, there is high interest in the development of improved tools, such as molecular diagnostic tools, to assess the risk of recurrence in subjects following NAG in order to steer patients to the most appropriate treatment options. Circulating tumor DNA (ctDNA) has been explored for this purpose, but has limited sensitivity. Indeed, nearly all patients with residual cancer in their breast after NAG have falsely negative ctDNA measurements using current technologies. Because the post-NAC period is when critical treatment decisions are made, improved methods to profile residual disease are needed at this clinically actionable timepoint. Accordingly, there is a need in the art for improved molecular diagnostic tools for the assessment of residual cancer and recurrence risk following NAG.SUMMARY OF THE INVENTION

[0006] Compositions and methods are provided for determining minimal residual disease (MRD) and optimizing treatment of cancer patients following therapy, e.g. neoadjuvant chemotherapy (NAC), surgery, targeted immunotherapy, etc. In some embodiments the cancer is a solid tumor. In some embodiments the MRD is determined following NAC. In some embodiments the patient is a breast cancer patient that has been treated with NAC.

[0007] The methods of the disclosure, termed spatial-MRD (s-MRD) apply blood-based MRD assessment tools to tumor tissue samples in order to accurately characterize molecular residual disease. The methods may be performed, for example, at timepoints when disease burden is low, mis-characterized or undetectable by alternate methods, and when adjuvant treatment decisions to prevent metastatic recurrences are made. The methods disclosed herein utilize tissue biopsy or resection samples for analysis, using assessment of patient-specific mutations for increased sensitivity.

[0008] In some embodiments tissue-optimized s-MRD methods disclosed herein are utilized in the analysis. s-MRD improves sensitivity by i) integrating error-suppressed sequencing methods with ii) tracking greater than 1 , greater than 2, greater than 3, greater than 4, greater than 5 mutation(s) per patient, allowing a higher likelihood of detecting tumor-derived molecules. Further increases in sensitivity can be achieved by the use of hybrid capture techniques to enrich for tumor DNA in samples.

[0009] In some embodiments of the disclosure, a method for detection of MRD in a subject comprises: sequencing polynucleotides, e.g. genomic DNA, of a pre-treatment tumor sample; identifying tumor-specific mutations; analyzing post-treatment tissue from the tumor site for the presence of the tumor-specific mutations of the previously-generated patient-specific mutation panel; determining the subjects MRD status based on the presence of the tumor-specific mutations; and optionally, treating the subject based on the foregoing MRD status determination. The sequencing may be ultra-deep targeted NGS performed via hybrid capture. The pre-treatment tumor sample may be compared to a healthy control sequence from the subject for determination of tumor-specific mutations.

[0010] In an embodiment, the tumor tissue samples comprise tissue resection samples. In one embodiment, the resection samples comprise ten or more tissue samples collected from the tumor and surrounding region.

[0011] The tumor-specific mutation panel may be determined by deep sequencing of collected tumor tissue and comparing the sequences therein against reference samples from healthy tissue, to identify mutations present in the tumor cell DNA. As disclosed herein, such methods may identify at least 10, at least 20, at least 30, at least 50, at least 75, at least 100 or more tumor-specific mutations that are indicative of the patient’s particular cancer genotype. In various implementations, the panel may comprise at least five, at least ten, at least twenty, atleast fifty, at least 75, or at least 100 mutations. The mutations may comprise SNV mutations, SNPs, or other mutations such as indels.

[0012] In an embodiment, the sequencing technique utilized is whole-exome sequencing. In an embodiment, the mutations comprise SNV’s. In an embodiment, the whole exome sequencing method comprises an error-suppression technique. In one embodiment, the whole exome sequencing technique utilizes methods as described in Newman et al. (2014) Nat Med. 20(5):548-54 and WO 2014 / 151 117, each herein specifically incorporated by reference. In one implementation, the sequencing is a tissue-optimized s-MRD process, for example as disclosed in Example 2.

[0013] In an embodiment, the patient-specific mutation panel is augmented with a plurality of additional mutations, for example, a panel of common breast cancer mutations. In one implementation, the plurality of common breast cancer mutations comprises one or more mutations selected TP53, PIK3CA, GATA3, CBFB, PTEN, CDH1 , TBX3, MAP3K1 , MAP2K4, RUNX1 , AKT1 , CDKN1 B, DCAF4L2, PIK3R1 , RB1 , KRAS, KMT2C, CTCF, STK1 1 , ERBB2, CASP8, MEN1 , ARID1 A, SF3B1 , NOTCH1 , CHEK2, BAP1 , SMAD4, ERBB3, MAP3K13, EGFR, JAK1 , ASXL1 , ROS1 , NF1 , FANCA, ATR, ALK, AKT2, KDM6A, EP300, STD2, ERBB4, FLT3, HRAS, CTNNA1 , NF2, PBRM1 , FBXW7, and NRAS, as set forth in FIG. 2E. In some embodiments the panel comprises each of these mutations. The panel may further comprise one or more of BRCA1 , BRCA2, MTOR, POLE, APO, and FGFR2 and may comprise each of these mutations.

[0014] In some embodiments, the subject has breast cancer. In some embodiments, the breast cancer is or has been treated with NAG. Any NAG treatment known in the art may be administered. For example, in some embodiments, NAG comprises chemotherapy, such as anthracyclines (e.g., doxorubicin, epirubicin), taxanes (e.g., paclitaxel, docetaxel), cyclophosphamide, carboplatin, etc., hormone therapy, e.g. tamoxifen, aromatoase inhibitors, such as anastrozole, letrozole, exemestane, tyrosine kinase inhibitos, such as lapatinib or neratinib, immunotherapy such as trastuzumab (Herceptin), pertuzumab (Perjeta), etc.

[0015] Following initiation of therapy, e.g. NAG, e.g. after about 1 month, 2 months, 3 months, 4 months, 5 months, 6 months or more, one or more post-treatment tissue samples are collected from the tumor site, e.g. comprising the tumor and surrounding tissue. Standard sample blocks are prepared from the collected tissue, for example FFPE blocks, as is known in the art. For example, at least five, at least ten, or at least 20 samples per patient may be collected from the tumor site and margins. These individual blocks are then assessed, e.g. by sequencing, to detect the presence of mutations from the selected panel of patient-specific mutations, optionally supplemented with an additional mutation panel as disclosed above.

[0016] In an embodiment, sequencing of the post-treatment samples is preceded by a hybrid capture step. For example, in one embodiment, a patient mutation-specific plurality ofoligonucleotide capture probes is synthesized or otherwise produced comprising sequences designed to capture the tumor-specific mutations of the tumor-specific mutation panel and the panel of common mutations. This hybrid capture technique increases signal-to-noise by selectively enriching mutation-bearing sequences present in the sample.

[0017] Upon assessment of MRD status in the subject, a treatment step may be administered. In one embodiment, the subject is determined to have none or low s-MRD and can be treated with, for example, monitoring. In one embodiment, the subject is determined to have present or high s-MRD. In such cases, the administered treatment can comprise a more aggressive therapy as disclosed herein.

[0018] In an embodiment, the MRD analysis comprises sequencing of patient specific mutations and sequencing of one or more genes in the common mutation panel. In some embodiments, for example where new post-treatment mutations are identified, treatment of the patient takes into account new mutations. For example, patients with mutations in targetable driver lesions, such as PIK3CA mutations, can be treated with an agent targeted to the lesion, such as alpelisib, capivasertib, etc.

[0019] Tumor-infiltrating lymphocyte (TIL) enrichment in primary breast cancers is predictive of treatment response, and specific CD4 and CD8 subsets are associated with neoadjuvant chemotherapy (NAC) and immunotherapy response. The methods of the disclosure allow for spatially definition of T-cell receptor (TCR) evolution patterns in tissues associated with NAC response and survival. In an embodiment, the MRD analysis further comprises sequence analysis of T cell receptor (TCR) sequences, which may be performed pre- and post-NAC. In some embodiments the TCR is TCR-fi. TCR analysis may include analysis of at least 10, at least 25, at least 50, at least 75, at least 100, at least 250, at least 500, at least 750, at least 1000 or more TCR sequences. The resulting TCR clonotype can be compared pre- and posttreatment. Spatially enumeration of TCR clonotype count and composition in each post-NAC sample can be compared to the relative abundance of clones shared with the pretreatment tumor. TIL density is strongly correlated with the presence of post-NAC residual disease.BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The invention is best understood from the following detailed description when read in conjunction with the accompanying drawings. The patent or application file contains at least one drawing executed in color. Copies of this patent or patent application publication with color drawing(s) will be provided by the Office upon request and payment of the necessary fee. It is emphasized that, according to common practice, the various features of the drawings are not to-scale. On the contrary, the dimensions of the various features are arbitrarily expanded or reduced for clarity. Included in the drawings are the following figures.

[0021] FIG. 1. Methods to detect residual disease after neoadjuvant chemotherapy. Workflow of t-s-MRD. After neoadjuvant chemotherapy and surgical resection, DNA is extracted from individual scrolls obtained from corresponding FFPE blocks and used for library preparation for NGS by s-MRD using a bespoke panel for each patient with a backbone of recurrent breast cancer mutations. MRD is assessed using a Monte Carlo statistical framework to integrate all mutations into a single assessment of MRD burden (FFPE: formalin-fixed, paraffin-embedded; MRD: minimal residual disease.

[0022] FIGS. 2A-2E. Improving MRD detection. A. Binomial model of the probability of detecting ctDNA-MRD in a given sample using 1 , 5, or 50 mutations at defined tumor fraction, assuming 3,000x sequencing depth. B. Number of mutations recovered from 1009 breast cancers profiled with WES using a limited 15 gene panel versus WES. C. Predicted limit of detection for error- suppressed s-MRD versus standard approaches. D. Deriving patient-specific single nucleotide variant (SNV) capture baits through whole exome sequencing. E. Fixed backbone panel of mutations recurrently mutated un breast cancer, ordered by mutational burden per kb of genomic space. Six additional genes relevant to breast cancer biology were additionally included.

[0023] FIGS. 3A-3B. Validating the performance of personalized mutation panels. A. Correlation of mean allele frequency (AF) as assessed by s-MRD per sample versus tumor cellularity as assessed by pathology. B. Mean s-MRD AF in blocks detected versus undetected by pathology.

[0024] FIGS. 4A-4D. Evaluating the performance of spatial-MRD in a pilot cohort. A. Pathologic outcomes, clinical courses, and s-MRD statuses of five pilot cases. B. Tumor cellularity as assessed by pathology versus mean s-MRD allele frequency in individual blocks, ordered by case, with color density representing quantity of detected disease. C. ROC classification of true positive samples versus true negative sample by s-MRD. True positive samples were defined as those with disease also seen by pathology, and true negative sample were defined as those where pathology did not see disease. D. Variable clinical courses among two RCB-3 cases, distinguished by s-MRD profiling. Case #26 has diffuse multifocal disease by s-MRD and molecular disease as the surgical margins where not seen by pathology. Case #51 has compact, unifocal disease by s-MRD and no molecular disease at the surgical margins concordant with pathology.

[0025] FIGS. 5A-5C. Description of expanded analytic cohort. A. Patient and tumor characteristics and clinical courses of N=30 patients. B. Progression-free survival by pCR status and C. stage at diagnosis. pCR: pathologic complete response; PFS: progression-free survival.

[0026] FIG. 6. PET CT images prior to treatment show multiple FDG-avid lesions in the right breast. Following chemotherapy, the patient achieves a radiographic complete response (CR), with no FDG avidity seen within the affected breast. The mastectomy specimen was assessedas a pathologic complete response; shown is a representative Faxitron x-ray image of a mastectomy slice from which block B27 is derived, with the cassette guide for this block’s grossing indicated by the yellow square. While histologically negative, this block was s-MRD- positive and immediately adjacent to the site of eventual locally recurrent disease, as seen on PET CT (shadowing in top right reflects implant-based reconstruction).DETAILED DESCRIPTION

[0027] These and other features of the present teachings will become more apparent from the description herein. While the present teachings are described in conjunction with various embodiments, it is not intended that the present teachings be limited to such embodiments. On the contrary, the present teachings encompass various alternatives, modifications, and equivalents, as will be appreciated by those of skill in the art.

[0028] Most of the words used in this specification have the meaning that would be attributed to those words by one skilled in the art. Words specifically defined in the specification have the meaning provided in the context of the present teachings as a whole, and as are typically understood by those skilled in the art. In the event that a conflict arises between an art- understood definition of a word or phrase and a definition of the word or phrase as specifically taught in this specification, the specification shall control.

[0029] It must be noted that, as used in the specification and the appended claims, the singular forms “a,” “an,” and “the” include plural referents unless the context clearly dictates otherwise.

[0030] All publications, patents, and patent applications mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent, or patent application was specifically and individually indicated to be incorporated by reference.

[0031] The present invention incorporates information disclosed in other applications and texts. The following patent and other publications are hereby incorporated by reference in their entireties: Alberts et al., The Molecular Biology of the Cell, 4th Ed., Garland Science, 2002; Vogelstein and Kinzler, The Genetic Basis of Human Cancer, 2d Ed., McGraw Hill, 2002; Michael, Biochemical Pathways, John Wiley and Sons, 1999; Weinberg, The Biology of Cancer, 2007; Immunobiology, Janeway et al. 7th Ed., Garland, and Leroith and Bondy, Growth Factors and Cytokines in Health and Disease, A Multi Volume Treatise, Volumes 1 A and IB, Growth Factors, 1996.

[0032] Unless otherwise apparent from the context, all elements, steps or features of the invention can be used in any combination with other elements, steps or features.

[0033] General methods in molecular and cellular biochemistry can be found in such standard textbooks as Molecular Cloning: A Laboratory Manual, 3rd Ed. (Sambrook et al., Harbor Laboratory Press 2001 ); Short Protocols in Molecular Biology, 4th Ed. (Ausubel et al. eds., JohnWiley & Sons 1999); Protein Methods (Bollag et al., John Wiley & Sons 1996); Nonviral Vectors for Gene Therapy (Wagner et al. eds., Academic Press 1999); Viral Vectors (Kaplift & Loewy eds., Academic Press 1995); Immunology Methods Manual (I. Lefkovits ed., Academic Press 1997); and Cell and Tissue Culture: Laboratory Procedures in Biotechnology (Doyle & Griffiths, John Wiley & Sons 1998). Reagents, cloning vectors, and kits for genetic manipulation referred to in this disclosure are available from commercial vendors such as BioRad, Stratagene, Invitrogen, Sigma-Aldrich, and ClonTech.

[0034] The invention has been described in terms of particular embodiments found or proposed by the present inventor to comprise preferred modes for the practice of the invention. It will be appreciated by those of skill in the art that, in light of the present disclosure, numerous modifications and changes can be made in the particular embodiments exemplified without departing from the intended scope of the invention. Due to biological functional equivalency considerations, changes can be made in protein structure without affecting the biological action in kind or amount. All such modifications are intended to be included within the scope of the appended claims.

[0035] The subject methods are used for prognostic, diagnostic and therapeutic purposes. As used herein, the term "treating" is used to refer to both prevention of relapses, and treatment of pre-existing conditions. The treatment of ongoing cancer to achieve durable clinical benefit is of particular interest.

[0036] The types of cancer that can be assessed using the subject methods of the present invention include but are not limited to adrenal cortical cancer, anal cancer, aplastic anemia, bile duct cancer, bladder cancer, bone cancer, bone metastasis, brain cancers, central nervous system (CNS) cancers, peripheral nervous system (PNS) cancers, breast cancer, cervical cancer, childhood Non-Hodgkin's lymphoma, colon and rectum cancer, endometrial cancer, esophagus cancer, Ewing's family of tumors (e.g. Ewing's sarcoma), eye cancer, gallbladder cancer, gastrointestinal carcinoid tumors, gastrointestinal stromal tumors, gestational trophoblastic disease, hairy cell leukemia, Hodgkin's lymphoma, Kaposi's sarcoma, kidney cancer, laryngeal and hypopharyngeal cancer, acute lymphocytic leukemia, acute myeloid leukemia, children's leukemia, chronic lymphocytic leukemia, chronic myeloid leukemia, liver cancer, lung cancer, lung carcinoid tumors, Non-Hodgkin's lymphoma, male breast cancer, malignant mesothelioma, multiple myeloma, myelodysplastic syndrome, myeloproliferative disorders, nasal cavity and paranasal cancer, nasopharyngeal cancer, neuroblastoma, oral cavity and oropharyngeal cancer, osteosarcoma, ovarian cancer, pancreatic cancer, penile cancer, pituitary tumor, prostate cancer, retinoblastoma, rhabdomyosarcoma, salivary gland cancer, sarcomas, melanoma skin cancer, non-melanoma skin cancers, stomach cancer, testicular cancer, thymus cancer, thyroid cancer, uterine cancer (e.g. uterine sarcoma),transitional cell carcinoma, vaginal cancer, vulvar cancer, mesothelioma, squamous cell or epidermoid carcinoma, bronchial adenoma, choriocarinoma, head and neck cancers, teratocarcinoma, or Waldenstrom's macroglobulinemia. In some embodiments the cancer is a solid tumor. In some embodiments the cancer is breast cancer.

[0037] In breast cancers, ductal adenocarcinoma comprises 50% to 75% of all invasive breast cancers. Clinically, these tumors are often felt as a breast mass secondary to a significant fibrotic reaction. Microscopically, the lesion arises in the terminal duct-lobular unit with abnormal epithelial cells with varying degrees of atypia. These cells invade the basement membrane. Lobular carcinoma: Invasive lobular cancer makes up 10% to 15% of breast cancer and tends to permeate the breast in a single-file nature. This results in tumors that typically remain clinically occult, escaping detection on mammography or physical examination until the disease becomes extensive. Mucinous carcinomas, which make up 2% to 5% of breast cancers, are well-demarcated in older women, typically characterized by mucin production. Tubular carcinoma is microscopically characterized by infiltrating cells with minimal atypia that form small glands and tubules. Medullary carcinomas are poorly differentiated, aggressive tumors seen more commonly in BRCA mutant and younger patients.

[0038] The pathogenesis, treatment, and prognosis are closely associated with the following molecular subtypes of breast cancer: Luminal A: Hormone receptor-positive, human epidermal growth factor receptor (HER)-2 negative; Luminal B: Hormone receptor-positive, HER-2 positive; Basal-like: Hormone receptor and HER-2 negative; and HER-enriched: HER-2 positive, hormone receptor-negative. Hormone receptor-positive tumors (ie, luminal A and B) tend to be less aggressive, with improved survival rates. HER-2 enriched tumors are more aggressive, with a poor prognosis without targeted therapy. Basal-like tumors are negative for the molecular markers and tend to have a worse prognosis, with poor survival rates.

[0039] Breast cancer treatment is based on various factors, including the disease stage, pathology, patient preference, and available resources. In general, breast cancer management approaches are divided into early breast cancer, locally advanced breast cancer, and metastatic breast cancer treatment. Early breast cancer includes tumors <5 cm in size without clinically positive lymph nodes. Treatment involves surgery, chemotherapy, radiation, and hormonal therapy, depending on the stage and molecular profile. In hormone receptor-positive tumors, the decision to initiate chemotherapy is based on risk stratification. HER2-positive patients with tumors >1 cm generally receive anti-HER2-directed therapy. Triple-negative patients with tumors > 1 cm generally receive systemic chemotherapy. Anti-estrogen or aromatase inhibitor therapy is indicated in all hormone receptor-positive patients.

[0040] The terms "subject," "individual," and "patient" are used interchangeably herein to refer to a vertebrate, preferably a mammal, more preferably a human. Mammalian species thatprovide samples for analysis include canines; felines; equines; bovines; ovines; etc. and primates, particularly humans. Animal models, particularly small mammals, e.g. murine, lagomorpha, etc. can be used for experimental investigations. The methods of the invention can be applied for veterinary purposes.

[0041] As used herein, the term "theranosis" refers to the use of results obtained from a diagnostic method to direct the selection of, maintenance of, or changes to a therapeutic regimen, including but not limited to the choice of one or more therapeutic agents, changes in dose level, changes in dose schedule, changes in mode of administration, and changes in formulation. Diagnostic methods used to inform a theranosis can include any that provides information on the state of a disease, condition, or symptom.

[0042] As used herein, "treatment" or "treating," or "palliating" or "ameliorating" are used interchangeably. These terms refer to an approach for obtaining beneficial or desired results including but not limited to a therapeutic benefit and / or a prophylactic benefit. By therapeutic benefit is meant any therapeutically relevant improvement in or effect on one or more diseases, conditions, or symptoms under treatment. For prophylactic benefit, the compositions may be administered to a subject at risk of developing a particular disease, condition, or symptom, or to a subject reporting one or more of the physiological symptoms of a disease, even though the disease, condition, or symptom may not have yet been manifested.

[0043] The term "effective amount" or "therapeutically effective amount" refers to the amount of an agent that is sufficient to effect beneficial or desired results. The therapeutically effective amount will vary depending upon the subject and disease condition being treated, the weight and age of the subject, the severity of the disease condition, the manner of administration and the like, which can readily be determined by one of ordinary skill in the art. The term also applies to a dose that will provide an image for detection by any one of the imaging methods described herein. The specific dose will vary depending on the particular agent chosen, the dosing regimen to be followed, whether it is administered in combination with other compounds, timing of administration, the tissue to be imaged, and the physical delivery system in which it is carried.

[0044] "Suitable conditions" shall have a meaning dependent on the context in which this term is used. That is, when used in connection with an antibody, the term shall mean conditions that permit an antibody to bind to its corresponding antigen. When used in connection with contacting an agent to a cell, this term shall mean conditions that permit an agent capable of doing so to enter a cell and perform its intended function. In one embodiment, the term "suitable conditions" as used herein means physiological conditions.

[0045] The terms "therapeutic agent", "therapeutic capable agent" or "treatment agent" are used interchangeably and refer to a molecule or compound that confers some beneficial effect upon administration to a subject. The beneficial effect includes enablement of diagnostic determinations; amelioration of a disease, symptom, disorder, or pathological condition; reducing or preventing the onset of a disease, symptom, disorder or condition; and generally counteracting a disease, symptom, disorder or pathological condition.

[0046] Cancer therapy may include Abitrexate (Methotrexate Injection), Abraxane (Paclitaxel Injection), Adcetris (Brentuximab Vedotin Injection), Adriamycin (Doxorubicin), Adrucil Injection (5-FU (fluorouracil)), Afinitor (Everolimus) , Afinitor Disperz (Everolimus) , Alimta (PEMET EXED), Alkeran Injection (Melphalan Injection), Alkeran Tablets (Melphalan), Aredia (Pamidronate), Arimidex (Anastrozole), Aromasin (Exemestane), Arranon (Nelarabine), Arzerra (Ofatumumab Injection), Avastin (Bevacizumab), Bexxar (Tositumomab), BiCNU (Carmustine), Blenoxane (Bleomycin), Bosulif (Bosutinib), Busulfex Injection (Busulfan Injection), Campath (Alemtuzumab), Camptosar (Irinotecan), Caprelsa (Vandetanib), Casodex (Bicalutamide), CeeNU (Lomustine), CeeNU Dose Pack (Lomustine), Cerubidine (Daunorubicin), Clolar (Clofarabine Injection), Cometriq (Cabozantinib), Cosmegen (Dactinomycin), Cytosarll (Cytarabine), Cytoxan (Cytoxan), Cytoxan Injection (Cyclophosphamide Injection), Dacogen (Decitabine), DaunoXome (Daunorubicin Lipid Complex Injection), Decadron (Dexamethasone), DepoCyt (Cytarabine Lipid Complex Injection), Dexamethasone Intensol (Dexamethasone), Dexpak Taperpak (Dexamethasone), Docefrez (Docetaxel), Doxil (Doxorubicin Lipid Complex Injection), Droxia (Hydroxyurea), DTIC (Decarbazine), Eligard (Leuprolide), Ellence (Ellence (epirubicin)), Eloxatin (Eloxatin (oxaliplatin)), Elspar (Asparaginase), Emcyt (Estramustine), Erbitux (Cetuximab), Erivedge (Vismodegib), Erwinaze (Asparaginase Erwinia chrysanthemi), Ethyol (Amifostine), Etopophos (Etoposide Injection), Eulexin (Flutamide), Fareston (Toremifene), Faslodex (Fulvestrant), Femara (Letrozole), Firmagon (Degarelix Injection), Fludara (Fludarabine), Folex (Methotrexate Injection), Folotyn (Pralatrexate Injection), FUDR (FUDR (floxuridine)), Gemzar (Gemcitabine), Gilotrif (Afatinib), Gleevec (Imatinib Mesylate), Gliadel Wafer (Carmustine wafer), Halaven (Eribulin Injection), Herceptin (Trastuzumab), Hexalen (Altretamine), Hycamtin (Topotecan), Hycamtin (Topotecan), Hydrea (Hydroxyurea), Iclusig (Ponatinib), Idamycin PFS (Idarubicin), Ifex (Ifosfamide), Inlyta (Axitinib), Intron A alfab (Interferon alfa-2a), Iressa (Gefitinib), Istodax (Romidepsin Injection), Ixempra (Ixabepilone Injection), Jakafi (Ruxolitinib), Jevtana (Cabazitaxel Injection), Kadcyla (Ado-trastuzumab Emtansine), Kyprolis (Carfilzomib), Leukeran (Chlorambucil), Leukine (Sargramostim), Leustatin (Cladribine), Lupron (Leuprolide), Lupron Depot (Leuprolide), Lupron DepotPED (Leuprolide), Lysodren (Mitotane), Marqibo Kit (Vincristine Lipid Complex Injection), Matulane (Procarbazine), Megace (Megestrol), Mekinist (Trametinib), Mesnex (Mesna), Mesnex (Mesna Injection), Metastron (Strontium-89 Chloride),Mexate (Methotrexate Injection), Mustargen (Mechlorethamine), Mutamycin (Mitomycin), Myleran (Busulfan), Mylotarg (Gemtuzumab Ozogamicin), Navelbine (Vinorelbine), Neosar Injection (Cyclophosphamide Injection), Neulasta (filgrastim), Neulasta (pegfilgrastim), Neupogen (filgrastim), Nexavar (Sorafenib), Nilandron (Nilandron (nilutamide)), Nipent (Pentostatin), Nolvadex (Tamoxifen), Novantrone (Mitoxantrone), Oncaspar (Pegaspargase), Oncovin (Vincristine), Ontak (Denileukin Diftitox), Onxol (Paclitaxel Injection), Panretin (Alitretinoin), Paraplatin (Carboplatin), Perjeta (Pertuzumab Injection), Platinol (Cisplatin), Platinol (Cisplatin Injection), PlatinolAQ (Cisplatin), PlatinolAQ (Cisplatin Injection), Pomalyst (Pomalidomide), Prednisone Intensol (Prednisone), Proleukin (Aldesleukin), Purinethol (Mercaptopurine), R-CHOP (Rituximab, Cyclophosphamide, Doxorubicin Hydrochloride {Hydroxydaunomycin}, Vincristine Sulfate {Onocvin} and Prednisone), Reclast (Zoledronic acid), Revlimid (Lenalidomide), Rheumatrex (Methotrexate), Rituxan (Rituximab), RoferonA alfaa (Interferon alfa-2a), Rubex (Doxorubicin), Sandostatin (Octreotide), Sandostatin LAR Depot (Octreotide), Soltamox (Tamoxifen), Sprycel (Dasatinib), Sterapred (Prednisone), Sterapred DS (Prednisone), Stivarga (Regorafenib), Supprelin LA (Histrelin Implant), Sutent (Sunitinib), Sylatron (Peginterferon Alfa-2b Injection (Sylatron)), Synribo (Omacetaxine Injection), Tabloid (Thioguanine), Taflinar (Dabrafenib), Tarceva (Erlotinib), Targretin Capsules (Bexarotene), Tasigna (Decarbazine), Taxol (Paclitaxel Injection), Taxotere (Docetaxel), Temodar (Temozolomide), Temodar (Temozolomide Injection), Tepadina (Thiotepa), Thalomid (Thalidomide), TheraCys BCG (BCG), Thioplex (Thiotepa), TICE BCG (BCG), Toposar (Etoposide Injection), Torisel (Temsirolimus), Treanda (Bendamustine hydrochloride), Trelstar (Triptorelin Injection), Trexall (Methotrexate), Trisenox (Arsenic trioxide), Tykerb (lapatinib), Valstar (Valrubicin Intravesical), Vantas (Histrelin Implant), Vectibix (Panitumumab), Velban (Vinblastine), Velcade (Bortezomib), Vepesid (Etoposide), Vepesid (Etoposide Injection), Vesanoid (Tretinoin), Vidaza (Azacitidine), Vincasar PFS (Vincristine), Vincrex (Vincristine), Votrient (Pazopanib), Vumon (Teniposide), Wellcovorin IV (Leucovorin Injection), Xalkori (Crizotinib), Xeloda (Capecitabine), Xtandi (Enzalutamide), Yervoy (Ipilimumab Injection), Zaltrap (Ziv-aflibercept Injection), Zanosar (Streptozocin), Zelboraf (Vemurafenib), Zevalin (Ibritumomab Tiuxetan), Zoladex (Goserelin), Zolinza (Vorinostat), Zometa (Zoledronic acid), Zortress (Everolimus), Zytiga (Abiraterone).

[0047] Radiotherapy means the use of radiation, usually X-rays, to treat illness. X-rays were discovered in 1895 and since then radiation has been used in medicine for diagnosis and investigation (X-rays) and treatment (radiotherapy). Radiotherapy may be from outside the body as external radiotherapy, using X-rays, cobalt irradiation, electrons, and more rarely other particles such as protons. It may also be from within the body as internal radiotherapy, which uses radioactive metals or liquids (isotopes) to treat cancer.

[0048] Treatment for breast cancer may comprise surgical excision, often with radiation therapy, and with or without adjuvant chemotherapy, endocrine therapy, or both. Epithelial cancers may express hormone receptors. Approximately 80% of postmenopausal and 20% of premenopausal patients with breast cancer have an estrogen receptor-positive (ER+) tumor; approximately 70% of all breast cancers are progesterone receptor-positive. Another cellular receptor is human epidermal growth factor receptor 2 (HER2; also called HER2 / neu or ErbB2); its presence correlates with a poorer prognosis at any given stage of cancer. In approximately 15% of patients with breast cancer, HER2 receptors are overexpressed. The majority of breast cancers are hormone receptor-positive and HER2 negative (approximately 70%); 12% are triple negative (hormone receptor-negative and HER2-negative).

[0049] Estrogen and progesterone receptors are nuclear hormone receptors that promote DNA replication and cell division when the appropriate hormones bind to them. Thus, medications that block these receptors are useful in treating and preventing tumors with the receptors. For tumors in which HER2 receptors are overexpressed, medications that block these receptors are part of standard treatment. HER2 overexpressing tumors respond well to these medications because HER2 is a significant driver of cancer cell progression.

[0050] Some oncologists treat with neoadjuvant chemotherapy to shrink the tumor before removing it and applying radiation therapy; thus, some patients who might otherwise have required mastectomy can have breast-conserving surgery.

[0051] Radiation therapy after breast-conserving surgery significantly reduces incidence of local recurrence in the breast and in regional lymph nodes and may improve overall survival. To improve radiation therapy, researchers are studying several new procedures. Many of these procedures aim to target radiation to the cancer more precisely and spare the rest of the breast from the effects of radiation.

[0052] Neoadjuvant chemotherapy for breast cancer, as used herein, refers to a therapeutic approach characterized by the administration of systemic chemotherapy, which may be performed before or after surgery. Neoadjuvant chemotherapy is commonly utilized in the management of locally advanced breast cancer or in cases where initial surgical intervention may be technically challenging due to extensive tumor size.

[0053] Neoadjuvant chemotherapy regimens are often tailored based on the specific characteristics of the tumor, such as hormone receptor status, HER2 / neu expression, and other molecular features. The overall goal of neoadjuvant chemotherapy in breast cancer is to improve long-term outcomes by optimizing the balance between systemic treatment and local intervention while tailoring therapeutic strategies to the individual patient's disease profile.

[0054] Adjuvant systemic therapy includes, for example, endocrine therapy, chemotherapy, or HER2-directed therapy which delays or prevents recurrence in almost all patients and prolongssurvival in some. Hormone positive cancer can be evaluated with Oncotype Dx, which allows targeting chemotherapy and endocrine therapy to the populations most likely to benefit. Hormone negative cancer and HER2 positive cancer are treated with chemotherapy and targeted therapy.

[0055] Decisions about the type of adjuvant therapy are made based on tumor characteristics, including estrogen receptor (ER) and progesterone receptor (PR) status, presence of human epidermal growth factor 2 (HER2) protein, grade and stage (including lymph node involvement), and genomic risk stratification. Some patients are treated with a combination of endocrine therapy and chemotherapy. Chemotherapy is usually begun soon after surgery. If systemic chemotherapy is not required, endocrine therapy is usually begun soon after surgery and is continued for 5 to 10 years. With endocrine therapy (eg, tamoxifen, aromatase inhibitors), benefit depends on estrogen and progesterone receptor expression; benefit is greatest with the strongest level of hormone receptor expression. Medications used for endocrine therapy include tamoxifen and aromatase inhibitors.

[0056] Tamoxifen is a selective estrogen receptor modulator that competitively binds with estrogen receptors. Adjuvant tamoxifen reduces breast cancer mortality for women with tumors that have estrogen receptors. Tamoxifen therapy for 5 years reduces annual odds of death by about 25% in premenopausal and postmenopausal women regardless of axillary lymph node involvement. T reatment for 10 years appears to be even more effective; it prolongs survival and reduces recurrence risk compared with 5 years of treatment.

[0057] Aromatase inhibitors (anastrozole, exemestane, letrozole) block peripheral production of estrogen in postmenopausal women. More effective than tamoxifen, these medications are becoming the preferred treatment for early-stage hormone receptor-positive cancer in postmenopausal patients. Letrozole may be used in postmenopausal women who have completed tamoxifen treatment.

[0058] CDK 4 / 6 inhibitors, such as palbociclib, ribociclib and abemaciclib, are also used for patients with hormone receptor-positive, HER2-negative cancer. Olaparib is used in patients with germline BRCA1 and 2 mutations with HER2-negative breast cancer.

[0059] Combination chemotherapy regimens are more effective than a single medication. Dose-dense regimens given for 4 to 6 months are preferred; in dose-dense regimens, the time between doses is shorter than that in standard-dose regimens. There are many regimens; a commonly used one is ACT (doxorubicin plus cyclophosphamide followed by paclitaxel).

[0060] If the tumor overexpresses HER2 (HER2+), anti-HER2 monoclonal antibodies (trastuzumab, pertuzumab) may be used. Adding the humanized monoclonal antibody trastuzumab to chemotherapy provides substantial benefit. Trastuzumab is usually continued for a year, although the optimal duration of therapy is unknown. If lymph nodes are involved,adding pertuzumab to trastuzumab improves disease-free survival. A serious potential adverse effect of both these anti-HER2 medications is a decreased cardiac ejection fraction.

[0061] In selected cases of HER2-positive breast cancer, individuals determined to have none or low MRD may receive standard adjuvant trastuzumab with or without pertuzumab to complete one year of treatment. In patients with estrogen or progesterone-receptor positive disease, individuals determined to have none or low MRD may receive standard adjuvant endocrine therapy for 5-10 years. If a patient did not undergo a mastectomy, they typically receive radiation therapy after surgery, and some patients who undergo mastectomy also receive standard radiation.

[0062] If there is significant s-MRD at the surgical margins, the patient may be referred for further surgical consultation and consideration of re-resection to obtain s-MRD negative margins. If the s-MRD margins are negative but there is present s-MRD in FFPE sections from the tumor bed or lymph nodes, a patient may receive escalated adjuvant chemotherapy, including further cytotoxic chemotherapy (such as capecitabine), immunotherapy (such as pembrolizumab), aggressive endocrine therapy (such as ovarian suppression with an aromatase inhibitor, with consideration to addition of a CDK4 / 6 inhibitor), antibody-drug conjugates (such as trastuzumab emtansine or trastuzumab-deruxtecan), or molecularly- targeted agents (such as olaparib or other novel agents) that may be derived from the s-MRD mutations present in the post-NAC tissues.

[0063] To “analyze” includes determining a set of values associated with a sample by measurement of a marker (such as, e.g., presence or absence of a marker or constituent expression levels) in the sample and comparing the measurement against measurement in a sample or set of samples from the same subject or other control subject(s). The markers of the present teachings can be analyzed by any of various conventional methods known in the art. To “analyze” can include performing a statistical analysis, e.g. normalization of data, determination of statistical significance, determination of statistical correlations, clustering algorithms, and the like.

[0064] A “sample” in the context of the present teachings refers to any biological sample that is isolated from a subject, for example a biopsy sample, such as a needle biopsy, or a FFPE section of resected tumor bed, breast, or lymph node tissue.

[0065] A “dataset” is a set of numerical values resulting from evaluation of a sample (or population of samples) under a desired condition. The values of the dataset can be obtained, for example, by experimentally obtaining measures from a sample and constructing a dataset from these measurements; or alternatively, by obtaining a dataset from a service provider suchas a laboratory, or from a database or a server on which the dataset has been stored. Similarly, the term “obtaining a dataset associated with a sample” encompasses obtaining a set of data determined from at least one sample. Obtaining a dataset encompasses obtaining a sample, and processing the sample to experimentally determine the data, e.g., via measuring antibody binding, or other methods of quantitating a signaling response. The phrase also encompasses receiving a set of data, e.g., from a third party that has processed the sample to experimentally determine the dataset.

[0066] “Measuring” or “measurement” in the context of the present teachings refers to determining the presence, absence, quantity, amount, or effective amount of a substance in a clinical or subject-derived sample, including the presence, absence, or concentration levels of such substances, and / or evaluating the values or categorization of a subject's clinical parameters based on a control, e.g. baseline levels of the marker.

[0067] Classification can be made according to predictive modeling methods that set a threshold for determining the probability that a sample belongs to a given class. The probability preferably is at least 50%, or at least 60% or at least 70% or at least 80% or higher. Classifications also can be made by determining whether a comparison between an obtained dataset and a reference dataset yields a statistically significant difference. If so, then the sample from which the dataset was obtained is classified as not belonging to the reference dataset class. Conversely, if such a comparison is not statistically significantly different from the reference dataset, then the sample from which the dataset was obtained is classified as belonging to the reference dataset class.

[0068] The predictive ability of a model can be evaluated according to its ability to provide a quality metric, e.g. AUG or accuracy, of a particular value, or range of values. In some embodiments, a desired quality threshold is a predictive model that will classify a sample with an accuracy of at least about 0.7, at least about 0.75, at least about 0.8, at least about 0.85, at least about 0.9, at least about 0.95, or higher. As an alternative measure, a desired quality threshold can refer to a predictive model that will classify a sample with an AUG (area under the curve) of at least about 0.7, at least about 0.75, at least about 0.8, at least about 0.85, at least about 0.9, or higher.

[0069] As is known in the art, the relative sensitivity and specificity of a predictive model can be “tuned” to favor either the selectivity metric or the sensitivity metric, where the two metrics have an inverse relationship. The limits in a model as described above can be adjusted to provide a selected sensitivity or specificity level, depending on the particular requirements of the test being performed. One or both of sensitivity and specificity can be at least about at least about 0.7, at least about 0.75, at least about 0.8, at least about 0.85, at least about 0.9, or higher.

[0070] The terms “biomarker,” “biomarkers,” “marker” or “markers” for the purposes of the invention refer to, without limitation, genetic mutations that identify an individual or, for the purposes of the disclosure, distinguish between tumor cells and normal cells in an individual.

[0071] Mutations associated with breast cancer include common mutations that are present in multiple subjects, and “private” mutations that are rare, but which are useful in identifying tumor DNA from the individual in which it is found. For example, see Shiovitz S, Korde LA. Ann Oncol. 2015 Jul;26(7):1291 -9. Examples of common breast cancer mutations include the high penetrance genes BRCA1 , BRCA2, CDH1 , PTEN, STK1 1 , TP53, moderate penetrance genes ATM, BRIP1 , CHEK2, PALB2; and other genes including, for example, ALK, APC, BMPR1A, CDC73, CDKN1 C, CDKN2A, EPCAM, FH, FLCN, GPC3, MAX, MEN1 , MET, MLH1 , MSH2, MSH6, MUTYH, NBN, NF1 , NF2, PHOX2B, PMS1 , PMS2, PRKAR1 A, PTCH1 , RAD51 C, RAD51 D, RET, SDHAF2, SDHB, SDHC, SDHD, SMAD4, SUFU, TMEM127, VHL, WT1 .

[0072] In some embodiments a panel of genes in addition to the private, tumor-specific genes, include the sequences set forth in FIG. 2E.

[0073] S-MRD utilizes a next-generation sequencing based method, originally used to quantify circulating DNA in cancer (ctDNA). S-MRD uses population analysis to identify recurrent mutations in a given cancer type. A ‘selector’ is designed which consists of biotinylated DNA oligonucleotide probes targeting the recurrently mutated regions chosen for the specific cancer type. The selector is chosen using a multiphase bioinformatics approach. Using the selector, a probe-based hybridization capture is performed on tumor and normal DNA to discover mutations specific to the patient. The hybridization capture is then also applied to ctDNA to quantify the mutations that were previously discovered. In s-MRD, design of selector can be a crucial step that identifies recurrent mutations in a particular cancer type using publicly available next generation sequencing data. For inclusion in selector, the recurrent mutations that are enriched in a population are described by an index- Recurrence Index (Rl). Rl is the number of mutations per kilobase of a given genomic locus of a patient carrying particular mutations. Rl represents a patient level recurrence frequency estimated for somatic mutations and all mutations. Known and driver recurrent mutations in a population can be ranked based on the Rl and therefore Rl is used to design a selector.

[0074] Hybridization capture with the selector probe set can be performed on tumor DNA from a sample and sequenced. The biotinylated selector probes bind selectively to the regions of the DNA library that were chosen to be where the recurrently mutations occur in the given cancer type. In this way the library of sequences is enriched for only the regions of interest, which can then be sequenced, allowing the determination of patient specific mutations. Hybridization capture with the same selector can then performed on ctDNA from the blood to quantify thepreviously identified mutations in the patient. s-MRD can be applied to ctDNA from multiple blood samples at different time points in order to follow tumor evolution.

[0075] Minimal Residual Disease (MRD) refers to the presence of residual cancer cells at a molecular or cellular level that remains detectable in a patient's body following the completion of treatment for a malignancy. It signifies the persistence of a small number of cancerous cells, often at levels undetectable by conventional imaging or clinical examinations. The assessment of MRD is critical in oncology, including breast cancer management, as it provides insights into the depth of treatment response and the potential risk of disease relapse.

[0076] Determining minimal residual disease (MRD) in breast cancer tissue samples is a crucial aspect of assessing the effectiveness of cancer treatment and predicting patient outcomes. Several statistical tests are employed to analyze the presence of residual cancer cells and quantify their abundance. For example, statistical analysis of qPCR data involves comparing the expression levels of these markers between the patient's post-treatment sample and a baseline sample, often taken before the initiation of therapy. Paired-sample t-tests or nonparametric tests, such as the Wilcoxon signed-rank test, may be employed to assess whether there is a significant difference in marker expression, indicating the presence or absence of minimal residual disease.

[0077] In some embodiments a Monte Carlo statistical framework is used to integrate all personalized mutations per case into a single assessment of s-MRD burden. The threshold for s-MRD positivity was defined as that present in less than 5% of cross-monitored control samples using the summative allele frequency (AF) p-value for each sample.

[0078] For example, integrated information content across multiple samples can be used to generate a detection index. This index is analogous to a false positive rate and is based on a decision tree in which fusion breakpoints take precedence due to their nonexistent background and in which p-values from multiple reporter types are integrated.

[0079] The probability P of recovering at least two reads of a single mutant allele in the tissue for a given depth and detection limit can be modeled by a binomial distribution. Given P, the probability of detecting all identified tumor mutations in the sample is modeled by a geometric distribution. To evaluate the impact of reporter number on tumor burden estimates, Monte Carlo sampling is performed (1 ,000x), varying the number of reporters available {1 ,2,...,max n}.

[0080] For each patient, a ctDNA detection index based on p-value integration from his or her set of reporters. Specifically, for cases where only a single reporter type was present in a patient’s tumor, the corresponding p-value was used. If SNV and indel reporters were detected, and if each independently had a p-value <0.1 , we combined their respective p-values using Fisher’s method. Otherwise, given the prioritization of SNVs in the selector design, the SNV p-value was used. If a fusion breakpoint identified in a tumor sample (i.e., involving ROS1 , ALK, or RET) was recovered in DNA from the same patient, it trumped all other mutation types, and its p-value (~0) was used. If a fusion detected in the tumor was not found in corresponding the test sample, the p-value for any remaining mutation type(s) was used. The detection index was considered significant if the metric was <0.05 (=FPR <5%), the threshold that maximized s-MRD sensitivity and specificity in ROC analyses (determined by Euclidean distance to a perfect classifier; i.e., TPR = 1 and FPR = 0).

[0081] The term "sequencing depth" or "depth" refers to a total number of sequence reads or read segments at a given genomic location or loci from a test sample from an individual.

[0082] The term “selector” or “selector set” refers to an oligonucleotide or a set of oligonucleotides which correspond to specific genomic regions wherein genomic regions may comprise a cancer mutations or a plurality of cancer mutations. A variety of selector and selector sets are known in the art.Methods of the Disclosure

[0083] The general method of the invention encompasses collection of pre-treatment tissue from a tumor, e.g. tissue sections or blocks, and optionally from healthy control tissue. Sequencing of tumor and optionally control tissue sections is performed to identify patientspecific tumor mutations for each patient. The patient is then administered the treatment of interest, including NAC treatment of breast cancer. Post-treatment tissue samples are collected from the tumor site and analyzed for the presence of patient-specific mutations identified in the pretreatment sample. By analysis of mutations present in the samples, the subject’s MRD status is determined. Optionally, a suitable treatment is administered based on the foregoing MRD status determination.

[0084] In some embodiments, a patient-specific panel to capture mutations may be created from the pre-treatment tumor sample. This panel may be used to identify MRD in the posttreatment samples.

[0085] In one embodiment, the diagnostic tumor samples comprise needle biopsy samples that are collected in the routine course of clinical care to facilitate initial diagnosis of the cancer, which is done by trained surgical pathologists. In one embodiment, the resection samples that are collected after chemotherapy are also collected in the routine course of clinical care. For example, following NAC all patients with breast cancer undergo surgery to resect the primary breast tumor site and survey the regional lymph nodes for the presence or absence of cancer cells. Based on the size of the tumor and the clinically-assessed response to chemotherapy, as well as a range of other factors, patients may elect to undergo either lumpectomy in which only the tumor bed and selected lymph nodes are removed, leaving most of the native breast intact,or mastectomy, in which the entire breast and regional lymph nodes are removed. Based on the surgical choice, the number of specimens available for evaluation ranges from 5 to up to 100 individual specimens. These specimens represent spatially distinct regions of the tumor bed, breast, and lymph node tissues that are serially sectioned, with preserved orientation, prior to standard histopathological evaluation (Emmadi et al.. Int J Surg Oncol. 2012;2012:180259. doi: 10.1 155 / 2012 / 180259. Epub 2012 Nov 19. PMID: 23213495; PMCID: PMC3507155).

[0086] The patient-specific mutations that are tracked after treatment comprise an individualized panel. This panel is derived from deep sequencing of collected tumor tissue from the pretreatment (diagnostic) biopsy and comparing the sequences therein against reference samples from healthy tissue, e.g. tissue from the same patient, to identify mutations present in the tumor cell DNA, but not in the healthy control tissue. As disclosed herein, such methods typically identify at least 100 patient-specific mutations indicative of the patient’s particular cancer genotype that are not present in tumors of other patients. In various implementations, the panel may comprise at least five, at least ten, at least twenty, at least fifty, at least 75, or at least 100 mutations. The mutations may comprise SNVs or other mutations such as indels.

[0087] In a primary implementation, the sequencing technique utilized is whole-exome sequencing to derive the personalized panel for each patient's tumor; this whole exome sequencing is performed on the pretreatment tumor and the comparison healthy control tissue. In one implementation, the mutations comprise SNVs or indels. In one implementation, the whole exome sequencing method and computational pipeline for analysis of the sequencing data comprises s-MRD, for example as described in Newman et al (Newman Nat Med. 2014 May; 20(5):548-54), and may include error-suppression techniques to enrich for tumor-specific mutations.

[0088] In one implementation, the patient-specific mutation panel is augmented with a plurality of additional mutations, for example, a panel covering genes that are recurrently-mutated in breast cancer and so considered to comprise common breast cancer mutations. In one implementation, the plurality of common breast cancer mutations comprises one or more mutations selected from the group consisting of the following genes: TP53; PIK3CA; GATA3; CBFB; PTEN; CDH1 ; TBX3; MAP3K1 ; MAP2K4; RUNX1 ; AKT1 ; CDKN1 B; DCAF4L2; PIK3R1 ; RB1 ; KRAS; KMT2C; CTCF; STK11 ; ERBB2; CASP8; MEN1 ; ARID1A; SF3B1 ; NOTCH1 ; CHEK2; BAP1 ; SMAD4; ERBB3; MAP3K13; EGFR; JAK1 ; ASXL1 ; ROS1 ; NF1 ; FANCA; ATR; ALK; AKT2; KDM6A; EP300; SETD2; ERBB4; FLT3; HRAS; CTNNA1 ; NF2; PBRM1 ; FBXW7; NRAS; BRCA1 ; BRCA2; MTOR; POLE; APC; and FGFR2. Oligonucleotides in the panel may be from about 10 to about 50 nt. in length, e.g. from about 15 to about 25 nt. in length, and typically cover the SNV. A panel of mutations may comprise at least about 10, at least about 20, at least about 3, at least about 50 or more distinct tumor-specific mutations.

[0089] In an implementation, the patient-specific mutation panel is augmented with a panel of TOR p sequences. Oligonucleotides in the panel may be from about 10 to about 50 nt. in length, e.g. from about 15 to about 25 nt. in length. A panel of TCR sequences may comprise at least about 10, at least 25, at least 50, at least 75, at least 100, at least 250, at least 500, at least 750, at least 1000 or more TCR sequences. The TCR clonotype may be spatially localized within the plurality of tissue samples.

[0090] A subject with breast cancer may be administered a NAC treatment, which is typically a chemotherapy regimen, but any NAC treatment known in the art may be administered. For example, in some embodiments, the NAC treatment comprises the administration of paclitaxel followed by anthracycline. In some embodiments, the NAC treatment is supplemented with one or more additional agents or consists entirely of immunotherapy agents, therapeutic antibodies or antibody-drug conjugates, kinase inhibitors, or other treatments such as endocrine therapy.

[0091] Following therapy, which is given over several cycles over the course of several months, a plurality of tissue samples is collected from the tumor site, e.g. comprising the tumor and surrounding tissue in order to obtain negative surgical margins as assessed under the microscope by trained surgical pathologists. That is, no tumor cells seen at the margins (Singletary Am J Surg. 2002 Nov;184(5):383-93). Standard sample blocks are prepared from the collected tissue, for example FFPE blocks, as known in the art. For example, at least five, at least ten, or at least 20 samples per patient are collected from the tumor site and margins. These individual blocks are then assessed to detect the presence of mutations from the selected panel of patient-specific mutations, optionally supplemented with an additional mutation panel covering commonly-mutated breast cancer genes. To determine whether a specific mutation is present or absent in an individual sample, its frequency is compared to the null distribution of selector-wide background alleles or mutation-specific background rates and Z statistics.

[0092] In one implementation, sequencing of the post-NAC samples is preceded by a hybrid capture step. For example, in one embodiment, a patient-specific plurality of oligonucleotide capture probes is synthesized or otherwise produced comprising sequences designed to capture the specific tumor mutations of the patient-specific mutation panel as well as any mutations derived from the panel of common breast cancer genes. Optionally, an amplification step is performed prior to sequencing. This hybrid capture technique increases signal-to-noise by selectively enriching mutation-bearing sequences present in the sample.

[0093] Sample collection and preparation, DNA extraction, and sequencing may be achieved using standard protocols known in the art, for example for any of the FFPE preparation steps, FFPE scroll cutting, DNA extraction, library preparation, and hybrid capture, deep sequencing, and data analysis steps. In one embodiment, the sequencing process is achieved using a s- MRD process, as described in Newman et al, supra. Sequencing of extracted DNA for pre-NAC determination of the patient-specific mutation panel and for post-NAC assessment of mutationsmay be achieved by any suitable method known in the art, including the modified s-MRD method disclosed herein. In one embodiment, sequencing is achieved by use of NovaSeqXPIus Illumina machines for sequencing, for example by the Novogene platform. As known in the art, deep sequencing refers to sequencing a given region multiple times, e.g. at least about 80x, at least about 100x, at least about 500x, at least about 1000x or more.

[0094] Data analysis is performed on the sequence data to assess the presence and absence of mutations from the patient-specific mutation panel and any supplementary panels using barcode mediated error suppression methods and a Monte Carlo statistical framework as previously described (Newman et al. (2014); and Newman et al. (2016)). This assessment integrates evaluation of all personalized mutations from each patient into a single assessment of molecular disease burden, integrating DNA fractions across all somatic SNVs, performing a position-specific background adjustment, and evaluating statistical significance by Monte Carlo sampling of background alleles across the selector. The threshold for tissue-MRD positive status for a given sample is defined as detection in <5% of cross-monitored (control) samples using the summative allele frequency (AF) p-value for each sample derived from the Monte Carlo framework.

[0095] Upon assessment of MRD status in the subject, the treatment options available to the patient are considered and optional treatment steps may be administered. In one embodiment, the subject is determined to have none or low s-MRD. In such cases, the patient may not require further surgery or further chemotherapy. In selected cases of HER2-positive breast cancer, patients may receive standard adjuvant trastuzumab with or without pertuzumab to complete one year of treatment. In patients with estrogen or progesterone-receptor positive disease, patients may receive standard adjuvant endocrine therapy for 5-10 years. If a patient did not undergo a mastectomy, they typically receive radiation therapy after surgery, and some patients who undergo mastectomy also receive standard radiation.

[0096] In one embodiment, the subject is determined to have present or high s-MRD. In such cases, the administered treatment may comprise a range of options. If there is significant s- MRD at the surgical margins, the patient may be referred for further surgical consultation and consideration of re-resection to obtain s-MRD negative margins. If the s-MRD margins are negative but there is present s-MRD in FFPE sections from the tumor bed or lymph nodes, a patient may receive escalated adjuvant chemotherapy, including further cytotoxic chemotherapy (such as capecitabine), immunotherapy (such as pembrolizumab), aggressive endocrine therapy (such as ovarian suppression with an aromatase inhibitor, with consideration to addition of a CDK4 / 6 inhibitor), antibody-drug conjugates (such as trastuzumab emtansine or trastuzumab-deruxtecan), or molecularly-targeted agents (such as Olaparib, alpelisib, capivasertib ,or other agents) that may be derived from the s-MRD mutations present in the post-NAC tissues.

[0097] In an embodiment, the presence of new mutations after NAC treatment is used to guide therapy, for example where a targetable lesion arises following NAC. Such individuals can be treated with agents that target the lesion, e.g. olaparib, alpelisib, capivasertib, sunitinib, etc.

[0098] An individual personalized panel is used to monitor for residual disease in individual post-NAC blocks. Following a therapy of interest, e.g. NAC, biopsy samples, e.g. needle biopsy samples or FFPE tissue sections, are taken. Polynucleotides from the sample, e.g. genomic DNA, is fragmented and affinity selected to enrich for genes found in an individual’s mutation panel. Ultra-deep targeted NGS is performed via hybrid capture from DNA extracted from each tissue sample. Because pathology specimens are catalogued to capture all regions of the resected specimen, many blocks may be present per case. NGS data may be analyzed with barcode mediated error suppression.

[0099] The presence of residual tumor cells is determined by DNA analysis of the FFPE resection samples, where the presence of the tumor-specific mutations is indicative the tumor cells are present. For example, the tissue minimal residual disease (s-MRD) mean allele frequency (AF) is determined. Criteria for defining an individual as positive, or high MRD is defined variably; in one embodiment, it may be defined as a mean allele frequency across the case of >10%, and low s-MRD may be defined as a mean allele frequency across the cases as less than or equal to 10%, or an alternatively-established threshold. In another embodiment, the s-MRD threshold for s-MRD positivity in a single sample is defined as that present in <5% of cross-monitored control samples using the summative allele frequency (AF) p-value for each sample, and a s-MRD positive case has at least one s-MRD positive sample, while a s-MRD negative case has zero positive samples. In another embodiment, a s-MRD “high” case may be defined as having multiple positive samples, with a threshold such as at least 2, or 3, 5, or 10 blocks across the case, while a s-MRD “low” case would have a number below the established threshold.

[0100] In some embodiments of the invention, methods are provided for the identification of a panel appropriate for a specific tumor. Also provided are oligonucleotide compositions of panels, which may be provided adhered to a solid substrate, tagged for affinity selection, etc.; and kits containing such selector sets. Included, without limitation, is a panel suitable for analysis of breast cancer.

[0101] Fully robotic or microfluidic systems include automated liquid-, particle-, cell- and organism-handling including high throughput pipetting to perform all steps of screening applications. This includes liquid, particle, cell, and organism manipulations such as aspiration, dispensing, mixing, diluting, washing, accurate volumetric transfers; retrieving, and discarding of pipet tips; and repetitive pipetting of identical volumes for multiple deliveries from a single sample aspiration. These manipulations are cross-contamination- free liquid, particle, cell, andorganism transfers. This instrument performs automated replication of microplate samples to filters, membranes, and / or daughter plates, high-density transfers, full-plate serial dilutions, and high capacity operation.

[0102] In some embodiments, platforms for multi-well plates, multi-tubes, holders, cartridges, minitubes, deep-well plates, microfuge tubes, cryovials, square well plates, filters, chips, optic fibers, beads, and other solid-phase matrices or platform with various volumes are accommodated on an upgradable modular platform for additional capacity. This modular platform includes a variable speed orbital shaker, and multi-position work decks for source samples, sample and reagent dilution, assay plates, sample and reagent reservoirs, pipette tips, and an active wash station. In some embodiments, the methods of the invention include the use of a plate reader.

[0103] In some embodiments, interchangeable pipet heads (single or multi-channel) with single or multiple magnetic probes, affinity probes, or pipetters robotically manipulate the liquid, particles, cells, and organisms. Multi-well or multi-tube magnetic separators or platforms manipulate liquid, particles, cells, and organisms in single or multiple sample formats.

[0104] In some embodiments, the instrumentation will include a detector, which can be a wide variety of different detectors, depending on the labels and assay. In some embodiments, useful detectors include a microscope(s) with multiple channels of fluorescence; plate readers to provide fluorescent, ultraviolet and visible spectrophotometric detection with single and dual wavelength endpoint and kinetics capability, fluorescence resonance energy transfer (FRET), luminescence, quenching, two-photon excitation, and intensity redistribution; CCD cameras to capture and transform data and images into quantifiable formats; and a computer workstation.

[0105] In some embodiments, the robotic apparatus includes a central processing unit which communicates with a memory and a set of input / output devices (e.g., keyboard, mouse, monitor, printer, etc.) through a bus. Again, as outlined below, this can be in addition to or in place of the CPU for the multiplexing devices of the invention. The general interaction between a central processing unit, a memory, input / output devices, and a bus is known in the art. Thus, a variety of different procedures, depending on the experiments to be run, are stored in the CPU memory.Tissue-optimized s-MRD process

[0106] As shown in Example 2, a tissue-optimized s-MRD protocol uses an input of at least about 100, at least about 500 ng of genomic DNA. The DNA is treated with an enzyme that generates double-stranded breaks, e.g. KAPA enzyme, for a short period of time, e.g. from about 5-10 minutes, and may be around 7 minutes. The fragmented DNA is subjected to a brief end-repair and A-tailing reaction, e.g. from about 20-30 minutes. The fragmented DNA is ligated to adapters with sequence indexes for identification. After clean-up of the ligated DNA, graftingPCR is performed to add sample barcodes and universal PCR sites, and then PCR amplified, e.g. from about 8-10 amplification cycles.Kits

[0107] In some embodiments, the invention provides kits for the classification, diagnosis, prognosis, theranosis, and / or prediction of an outcome. The kit may further comprise a software package for data analysis of the cellular state and its physiological status, which may include reference profiles for comparison with the test profile and comparisons to other analyses as referred to above. The kit may also include instructions for use for any of the above applications.

[0108] Kits provided by the invention may comprise one or more of the affinity reagents described herein, reagents for isolation and sequencing analysis of cfDNA, etc. A kit may also include other reagents that are useful in the invention, such as modulators, fixatives, containers, plates, buffers, therapeutic agents, instructions, and the like.

[0109] Such kits may additionally comprise one or more therapeutic agents. The kit may further comprise a software package for data analysis of the physiological status, which may include reference profiles for comparison with the test profile.

[0110] Such kits may also include information, such as scientific literature references, package insert materials, clinical trial results, and / or summaries of these and the like, which indicate or establish the activities and / or advantages of the composition, and / or which describe dosing, administration, side effects, drug interactions, or other information useful to the health care provider. Such information may be based on the results of various studies, for example, studies using experimental animals involving in vivo models and studies based on human clinical trials. Kits described herein can be provided, marketed and / or promoted to health providers, including physicians, nurses, pharmacists, formulary officials, and the like. Kits may also, in some embodiments, be marketed directly to the consumer.Reports

[0111] In some embodiments, providing an evaluation of a subject for a classification, diagnosis, prognosis, theranosis, and / or prediction of an outcome includes generating a written report that includes the artisan’s assessment of the subject’s state of health i.e. a “diagnosis assessment”, of the subject’s prognosis, i.e. a “prognosis assessment”, and / or of possible treatment regimens, i.e. a “treatment assessment”. Thus, a subject method may further include a step of generating or outputting a report providing the results of a diagnosis assessment, a prognosis assessment, or treatment assessment, which report can be provided in the form of an electronic medium (e.g., an electronic display on a computer monitor), or in the form of a tangible medium (e.g., a report printed on paper or other tangible medium).

[0112] A “report,” as described herein, is an electronic or tangible document which includes report elements that provide information of interest relating to a diagnosis assessment, a prognosis assessment, and / or a treatment assessment and its results. A subject report can be completely or partially electronically generated. A subject report includes at least a diagnosis assessment, i.e. a diagnosis as to whether a subject will have a particular clinical response, and / or a suggested course of treatment to be followed. A subject report can further include one or more of: 1 ) information regarding the testing facility; 2) service provider information; 3) subject data; 4) sample data; 5) an assessment report, which can include various information including: a) test data, where test data can include an analysis of cellular signaling responses to activation, b) reference values employed, if any.

[0113] The report may include information about the testing facility, which information is relevant to the hospital, clinic, or laboratory in which sample gathering and / or data generation was conducted. This information can include one or more details relating to, for example, the name and location of the testing facility, the identity of the lab technician who conducted the assay and / or who entered the input data, the date and time the assay was conducted and / or analyzed, the location where the sample and / or result data is stored, the lot number of the reagents (e.g., kit, etc.) used in the assay, and the like. Report fields with this information can generally be populated using information provided by the user.

[0114] The report may include information about the service provider, which may be located outside the healthcare facility at which the user is located, or within the healthcare facility. Examples of such information can include the name and location of the service provider, the name of the reviewer, and where necessary or desired the name of the individual who conducted sample gathering and / or data generation. Report fields with this information can generally be populated using data entered by the user, which can be selected from among pre-scripted selections (e.g., using a drop-down menu). Other service provider information in the report can include contact information for technical information about the result and / or about the interpretive report.

[0115] The report may include a subject data section, including subject medical history as well as administrative subject data (that is, data that are not essential to the diagnosis, prognosis, or treatment assessment) such as information to identify the subject (e.g., name, subject date of birth (DOB), gender, mailing and / or residence address, medical record number (MRN), room and / or bed number in a healthcare facility), insurance information, and the like), the name of the subject's physician or other health professional who ordered the susceptibility prediction and, if different from the ordering physician, the name of a staff physician who is responsible for the subject's care (e.g., primary care physician).

[0116] The report may include a sample data section, which may provide information about the biological sample analyzed, such as the source of biological sample obtained from the subject(e.g. blood, type of tissue, etc.), how the sample was handled (e.g. storage temperature, preparatory protocols) and the date and time collected. Report fields with this information can generally be populated using data entered by the user, some of which may be provided as prescripted selections (e.g., using a drop-down menu).

[0117] The report may include an assessment report section, which may include information generated after processing of the data as described herein. The interpretive report can include a prognosis of the likelihood that the patient will develop tumor benefit from immune checkpoint inhibitors. The interpretive report can include, for example, results of the analysis, methods used to calculate the analysis, and interpretation, i.e. prognosis. The assessment portion of the report can optionally also include a Recommendation(s). For example, where the results indicate the subject’s prognosis for propensity to develop tumor benefit from immune checkpoint inhibitors.

[0118] It will also be readily appreciated that the reports can include additional elements or modified elements. For example, where electronic, the report can contain hyperlinks which point to internal or external databases which provide more detailed information about selected elements of the report. For example, the patient data element of the report can include a hyperlink to an electronic patient record, or a site for accessing such a patient record, which patient record is maintained in a confidential database. This latter embodiment may be of interest in an in-hospital system or in-clinic setting. When in electronic format, the report is recorded on a suitable physical medium, such as a computer readable medium, e.g., in a computer memory, zip drive, CD, DVD, etc.

[0119] It will be readily appreciated that the report can include all or some of the elements above, with the proviso that the report generally includes at least the elements sufficient to provide the analysis requested by the user (e.g., a diagnosis, a prognosis, or a prediction of responsiveness to a therapy).Computer aspects

[0120] A computational system (e.g., a computer) may be used in the methods of the present disclosure to integrate and to analyze data. A computational unit may include any suitable components for analysis. Thus, the computational unit may include one or more of the following: a processor; a non-transient, computer-readable memory, such as a computer-readable medium; an input device, such as a keyboard, mouse, touchscreen, etc.; an output device, such as a monitor, screen, speaker, etc.; a network interface, such as a wired or wireless network interface; and the like.

[0121] The raw data from measurements can be analyzed and stored on a computer-based system. As used herein, “a computer-based system” refers to the hardware means, software means, and data storage means used to analyze the information of the present invention. The minimum hardware of the computer-based systems of the present invention comprises a centralprocessing unit (CPU), input means, output means, and data storage means. A skilled artisan can readily appreciate that any one of the currently available computer-based system are suitable for use in the present invention. The data storage means may comprise any manufacture comprising a recording of the present information as described above, or a memory access means that can access such a manufacture.

[0122] The analysis may be implemented in hardware or software, or a combination of both. In one embodiment of the invention, a machine-readable storage medium is provided, the medium comprising a data storage material encoded with machine readable data which, when using a machine programmed with instructions for using said data, is capable of displaying a any of the datasets and data comparisons of this invention. Such data may be used for a variety of purposes, such as diagnosis, disease treatment and the like. In some embodiments, the invention is implemented in computer programs executing on programmable computers, comprising a processor, a data storage system (including volatile and non-volatile memory and / or storage elements), at least one input device, and at least one output device. Program code is applied to input data to perform the functions described above and generate output information. The output information is applied to one or more output devices, in known fashion. The computer may be, for example, a personal computer, microcomputer, or workstation of conventional design.

[0123] Each program is preferably implemented in a high level procedural or object oriented programming language to communicate with a computer system. However, the programs can be implemented in assembly or machine language, if desired. In any case, the language can be a compiled or interpreted language. Each such computer program is preferably stored on a storage media or device (e.g., ROM or magnetic diskette) readable by a general or special purpose programmable computer, for configuring and operating the computer when the storage media or device is read by the computer to perform the procedures described herein. The system can also be considered to be implemented as a computer-readable storage medium, configured with a computer program, where the storage medium so configured causes a computer to operate in a specific and predefined manner to perform the functions described herein.

[0124] A variety of structural formats for the input and output means can be used to input and output the information in the computer-based systems of the present invention. One format for an output means test datasets possessing varying degrees of similarity to a trusted profile. Such presentation provides a skilled artisan with a ranking of similarities and identifies the degree of similarity contained in the test pattern.

[0125] The data and analysis thereof can be provided in a variety of media to facilitate their use. “Media” refers to a manufacture that contains the signature pattern information of the present invention. The databases of the present invention can be recorded on computerreadable media, e.g. any medium that can be read and accessed directly by a computer. Such media include, but are not limited to: magnetic storage media, such as floppy discs, hard disc storage medium, and magnetic tape; optical storage media such as CD-ROM; electrical storage media such as RAM and ROM; and hybrids of these categories such as magnetic / optical storage media. One of skill in the art can readily appreciate how any of the presently known computer readable mediums can be used to create a manufacture comprising a recording of the present database information. "Recorded" refers to a process for storing information on computer readable medium, using any such methods as known in the art. Any convenient data storage structure can be chosen, based on the means used to access the stored information. A variety of data processor programs and formats can be used for storage, e.g. word processing text file, database format, etc.

[0126] A variety of structural formats for the input and output means can be used to input and output the information in the computer-based systems. Such presentation provides a skilled artisan with a ranking of similarities and identifies the degree of similarity contained in the test data.

[0127] Further provided herein is a method of storing and / or transmitting, via computer, sequence, and other, data collected by the methods disclosed herein. Any computer or computer accessory including, but not limited to software and storage devices, can be utilized to practice the present invention. Sequence or other data (e.g., immune repertoire analysis results), can be input into a computer by a user either directly or indirectly. Additionally, any of the devices which can be used to sequence DNA or analyze DNA or analyze immune repertoire data can be linked to a computer, such that the data is transferred to a computer and / or computer-compatible storage device. Data can be stored on a computer or suitable storage device (e.g., CD). Data can also be sent from a computer to another computer or data collection point via methods well known in the art (e.g., the internet, ground mail, air mail). Thus, data collected by the methods described herein can be collected at any point or geographical location and sent to any other geographical location.EXPERIMENTAL

[0128] The following examples are given for the purpose of illustrating various embodiments of the invention and are not meant to limit the present invention in any fashion. The present examples, along with the methods described herein are presently representative of preferred embodiments, are exemplary, and are not intended as limitations on the scope of the invention. Changes therein and other uses which are encompassed within the spirit of the invention as defined by the scope of the claims will occur to those skilled in the art.Example 1

[0129] Neoadjuvant chemotherapy (NAC) has become the standard of care for certain forms of breast cancer such as Human Epidermal Growth Factor Receptor 2 (HER2)-positive and triplenegative breast cancers, and it is also being increasingly adopted for all subtypes of breast cancer, including estrogen- or progesterone-receptor positive disease.

[0130] Following NAC, residual cancer assessment is performed by pathologists on resection specimens that come from the primary breast tumor site and the regional lymph nodes, in order to inform the next treatment steps. Pathologists typically report whether the patient has achieved a pathologic complete response (pCR)— that is, no tumor cells seen under the microscope in the breast or lymph node tissue — or whether there is residual tumor seen. An alternative tool that is also utilized for this assessment is called the Residual Cancer Burden (RCB), which categorizes residual disease from class 0-III, with 0 being equivalent to a pCR and III being the greatest burden of residual tumor. However, it is widely recognized in the field that histopathological tools such as pCR vs non-PCR and RCB indices are imperfect at assessing cancer status and predicting recurrence. For example, 12% of patients that achieve a pathologic complete response (pCR) will experience disease recurrence, while almost half of subjects that are deemed to have a high burden of disease (RCB-III) will actually remain cancer- free at ten-year follow-up, when most patients are determined to be cured if their cancer has not recurred.

[0131] Therefore, there is high interest in the development of improved tools, such as molecular diagnostic tools, to assess the risk of recurrence in subjects following NAC in order to steer patients to the most appropriate treatment options - treating higher risk patients with additional agents, and determining that lower risk patients are cured and do not need further treatment. Circulating tumor DNA (ctDNA) has been explored for this purpose, but has limited sensitivity. Indeed, nearly all patients with residual cancer in their breast after NAC have falsely negative ctDNA measurements using current technologies. Because the post-NAC period is when critical treatment decisions are made, improved methods to profile residual disease are needed at this clinically actionable timepoint. Accordingly, there is a need in the art for improved molecular diagnostic tools for the assessment of residual cancer to assess recurrence risk following NAC and to inform adjuvant treatment options.

[0132] Achievement of a pathologic complete response (pCR) is prognostic across breast cancer subtypes and particularly in triple negative breast cancer (TNBC) where patients with residual disease are given adjuvant treatment to decrease recurrence. Increasing residual disease as stratified by the Residual Cancer Burden (RCB) index (Fig. 1a) results in inferior outcomes, but this method is imperfect at predicting recurrence: in patients achieving a pCR, 12% still have disease recurrence, and among those with a high burden of residual disease (RCB-III), 46% are free of recurrence at ten years.

[0133] Emerging role and limitations of ctDNA MRD in breast cancer. Assessment of bloodbased minimal residual disease (MRD) by tracking tumor derived mutations from circulating tumor DNA (ctDNA) has been explored for earlier prognostication (Fig. 1 b) but has limited sensitivity. Because of this, ctDNA is falsely negative at the landmark post-neoadjuvant (NAG) timepoint in most patients with residual disease. Because this is when treatment decisions are made, improved methods are needed. The performance of these approaches underscores the need to quantify residual disease more accurately at a critical, clinically actionable timepoint, when disease burden is low.

[0134] To address this lack of sensitivity, spatial MRD (t-s-MRD) was developed, profiling residual disease in post-NAC resection tissue where tumor molecules may be present in high concentration (Fig. 1c).

[0135] Whole exome sequencing (WES) of diagnostic biopsies and matched germline tissue from patients enrolled in the PrECOG 0105 study of newly diagnosed stage I II I A breast cancer. For a cohort of five patients treated at Stanford achieving a range of pathologic responses, personalized mutation panels and hybrid capture panels were developed, including a bespoke set, combined with a backbone of the most recurrently mutated genes in breast cancer, including TP53 and PIK3CA16. This breast cancer-specific s-MRD panel captures 56 genes covering 225kb.

[0136] Ultra-deep targeted NGS was performed via hybrid capture from DNA extracted from each pathology block from the resection specimens. Because pathology specimens are catalogued to capture all regions of the resected specimen, many blocks are present per case. For these five patients, a total of 1 19 independent post-resection blocks were assessed. NGS data was analyzed with barcode mediated error suppression, and MRD was assessed through a Monte Carlo statistical framework as previously described to integrate all personalized mutations per case into a single assessment of s-MRD burden. The threshold for s-MRD positivity was defined as that present in less than 5% of cross-monitored control samples using the summative allele frequency (AF) p-value for each sample.

[0137] The results were aggregated from each FFPE section over each case to define each patient’s s-MRD profile and compared the performance of s-MRD versus histologic assessment for each block by Spearman correlation and the mean AF of pathology-positive versus pathology-negative samples using the nonparametric Mann-Whitney U test.

[0138] Maximizing sensitivity for breast cancer MRD through personalized mutation tracking. s-MRD improves ctDNA-MRD sensitivity by i) integrating error-suppressed sequencing methods with ii) tracking >1 mutation per patient, allowing a higher likelihood of detecting tumor- derived molecules (Fig. 2a) and has been successfully applied to a diversity of malignancies.

[0139] s-MRD traditionally relies on recurrently mutated genomic regions encompassed in an “off-the-shelf” panel, but these are less common in breast cancer. Exemplifying this, a 15-genepanel of recurrently mutated genes in breast cancer was designed and applied to a TCGA cohort of 1009 patients with whole exome sequencing (WES) data available. Using this, a median of only 1 mutation / patient was identified (Fig. 2b). By contrast, in the whole exome, there were a median of 59 mutations I patient. A higher trackable mutation burden leads to improved MRD sensitivity and a decreased limit of detection (Fig. 2c).

[0140] Upfront WES was used to identify tumor mutations and to design patient-specific oligonucleotide panels to maximize sensitivity (Fig. 2d). The initial panels, which required variants to be called by 2 / 3 mutation callers, included a mean of 162 variants per patient across the exome, and the backbone panel encompassed 56 genes (Fig. 2e). To evaluate MRD reporters with low background detection, targeted resequencing of the pretreatment tumors was performed as well as a panel of control samples. High-confidence variants were included that were captured in the pretreatment tumor and had minimal read support in control samples, representing a mean of 80% of SNVs and 136 mutations / case that were used for subsequent MRD assessment.

[0141] Each patient’s personalized panel was used to monitor for residual disease in individual post-NAC blocks. For each pathology block, the s-MRD mean allele frequency (AF) was compared to tumor cellularity as assessed by pathology, defined as percent cellularity within the region containing viable tumor, and demonstrated strong concordance between these two methods (Spearman r = 0.8915, p<0.0001 ) (Fig. 3a). Within the subset of samples in which we were able to detect s-MRD above the background threshold, six samples were identified where disease was undetectable by pathology; these samples had a lower mean AF than those in which there was histologically detectable residual disease (Mann Whitney U test, p=0.0001 ) (Fig. 3b).

[0142] Evaluating the performance of tissue-MRD in a pilot cohort. The selected pilot cohort of 5 patients representing a range of RGB scores and clinical outcomes was examined in detail (Fig. 4a). Of the 119 post-NAC blocks analyzed across these patients, 25 had pathologic residual disease and 28 had detectable s-MRD. In comparing the performance of s-MRD to histologic assessment in individual blocks, a strong overall concordance with minimal false positive s-MRD detection signal was observed (Fig. 4b). When assessing the performance of s-MRD detection through genomic sequencing, excellent classification of true positive (pathology positive) versus true negative (pathology negative) samples was observed (Fig. 4c). Discordances were found in the two RGB-Ill cases (#26, #51 ), with a more diffuse and extensive t- MRD than that assessed by pathology primarily in case #26, a patient who progressed through chemotherapy and later recurred, while in case #51 , t- MRD assessment was largely concordant with that of pathology in a patient who did not recur (Fig. 4d). In the RCB-II case (#47), minimal s-MRD was observed in a single block, despite this case having moderate gross residualdisease detected in 3 blocks by pathology. A molecular complete response in the pCR (RCB- 0) case (#35) was confirmed.

[0143] These patterns show that s-MRD has excellent performance compared to pathology, and can identify residual disease where it is not seen by pathology.

[0144] s-MRD measurement by t-s-MRD as a predictive biomarker in breast cancer. Based on the initial data indicating the feasibility of detecting s-MRD, these results were extended to a final cohort of 30 well-annotated breast cancer cases (Fig. 5a) with a diversity of clinical outcomes (N=10 events, Fig. 5b-c). s-MRD analysis is performed on all samples from this expanded analytic cohort which will encompass >900 FFPE blocks.

[0145] In this study, we designed personalized patient-specific assays to track tumor-derived mutations through chemotherapy in individual pathology specimens via ultra-deep targeted hybrid capture. For a cohort of five patients encompassing 1 19 individual samples, we assessed each sample-representing spatially distinct regions of the tumor bed-for the presence of MRD by integrating multiple tumor mutations into a single assessment of disease burden. We aggregated results across all samples from each case to define each patient’s s-MRD profile and assessed the performance of s-MRD versus gold standard pathologic assessment.

[0146] We tracked a mean of 136 MRD reporters per case across 1 19 post-NAC blocks derived from five patients. Twenty-five samples had pathologic residual disease and 28 had detectable s-MRD. There was strong concordance between s-MRD mean allele frequency (AF) and tumor cellularity as assessed by pathology (Spearman r = 0.8915, p<0.0001 ), and excellent classification of true positive pathology samples by genomic sequencing (AUG = 0.9675, p < 0.0001 ). Samples (n = 6) where s-MRD but not pathologic residual disease was detected had a lower mean AF than those where there was also histologic residual disease (p=0.0001 ). Among the five studied cases, we confirmed a molecular complete response with no s-MRD detected in the RCB-0 case (0 / 44 s-MRD positive blocks). In the two RGB-Ill cases, we observed more diffuse s-MRD than that assessed by pathology (n = 4 additional blocks with s- MRD but not pathologic disease detected), and in the RCB-II case, we detected minimal s-MRD in only a single block where pathology did not detect residual disease.

[0147] Cancer therapeutics are increasingly guided by molecular information about the tumor, which can evolve through chemotherapy. The ability to accurately profile residual disease at the genomic level after upfront chemotherapy is critical to predict risk and to determine which patients require further treatment. s-MRD can also guide targeted treatments based on the persistent mutational burden and composition. This novel platform demonstrated outstanding concordance with standard pathologic assessment, with minimal false positive signal and - importantly - the ability to detect additional molecular residual disease where it is not seen under the microscope, with most of this detection in a patient whose cancer later recurred.These findings highlight that s-MRD has the potential to outperform standard pathologic and ctDNA assessment at predicting recurrence by more accurately defining the MRD profile.References:

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[0173] Chandran SS, Ma J, Klatt MG, et al. Immunogenicity and therapeutic targeting of a public neoantigen derived from mutated PIK3CA. Nat Med. May 2022;28(5):946-957.Example 2Pilot: protocol with enzymatic fragmentationProtocol

[0174] Day 1. Dilute total DNA input (500ng) in 10 mM Tris-HCI (pH 8.0 - 8.5) in a total of 35 pL (Only if DNA solution does not contain EDTA). **note: this is significantly higher DNA input than used for blood-based ctDNA. Mix by gentle vortexing or pipetting up and down. On ice, add the following components in this order:Fragmentation reactionComponent Volume (pL)Double-stranded DNA 35KAPA Frag Master Mix* 15Total volume: 50Fragmentation Master MixComponent Volume (pL)KAPA Frag Buffer (10X) 5KAPA Frag Enzyme 10Total volume: 15

[0175] The KAPA Frag Buffer and Enzyme may be pre-mixed and kept on ice prior to reaction setup, and dispensed as a single solution. Please note the volume of buffer is less than the volume of enzyme in this reaction. Vortex gently and spin down briefly. Put the tube(s) back on ice. Incubate in a thermocycler, pre-cooled to 4°C and programmed as outlined below:Fragmentation protocolStep Temp (°C) Time (min)Pre-cool block 4 N / AFragmentation (200-350bp) 37 7HOLD 4

[0176] This is a significantly-reduced fragmentation time compared to other protocols and other tissue types, which preserves fragment length for sequencing and was optimized. Put the reactions on ice, and proceed immediately to End Repair and A-tailing.

[0177] In the same tube(s) in which enzymatic fragmentation was performed, add End Repair & A-Tailing reaction components:End Repair & A-Tailing reactionComponent Volume (pL)Fragmented, double-stranded DNA 50End Repair & A-Tailing Master Mix 10Total volume: 60End Repair & A-Tailing Master MixComponent Voc lume (pL) - 1X***End Repair & A-Tailing Buffer* 7HyperPrep / HyperPlus ERAT Enzyme Mix** 3Total volume: 10

[0178] The buffer and enzyme mix should preferably be pre-mixed and added in a single pipetting step. Premixes are stable for <24 hrs at room temperature, for <3 days at 2°C to 8°C, and for <4 weeks at -15°C to -25°C. **Use either the HyperPrep ERAT Enzyme Mix (existing chemistry) or the HyperPlus ERAT Enzyme Mix (enhanced chemistry). ***lnclude 5% excess volume for sample handling. Vortex gently and spin down briefly. Put the reaction tube(s) back on ice. Incubate in a thermocycler programmed as outlined below. A heated lid is required for this step. If possible, set the temperature of the heated lid to ~85°C (instead of the usual 105°C).End Repair & A-Tailing protocolStep Temp (°C) Time (min)End repair and A-tailing 65* 30HOLD 4**

[0179] * Both the fragmentation and end repair enzymes are inactivated at 65°C. When reactions are set up according to recommendations, additional fragmentation should be negligible. The brief period of end repair is sufficient for enzymatically fragmented DNA. ** If proceeding to the adapter ligation reaction setup without any delay, the reaction may be cooled to 20°C instead of 4°C. Proceed immediately to Adapter Ligation. Perform the ligation reaction by combining the following components:Flex adapter ligation reactionComponent Volume (pL)*End repair / A-tailing reaction product 60KAPA Ligation Master Mix (Ligation buffer: 30 pL + DNA ligase: 10 pL) 40 Flex adapters (3 pL Flex adapters [15pM] + 7 pL H2O)** 10Total volume: 110**note: this is a significant molar excess of universal adapters to ensure ligation of all available DNA molecules.

[0180] Mix thoroughly and centrifuge briefly. Incubate the ligation reaction at 16 degrees C for 1 hour or overnight at 4C. **Note: this revision of the protocol to permit a one-hour rather than overnight ligation permits protocol completion in one day with equivalent library yields and quality.Day 2Reaction cleanup #1

[0181] Reaction cleanup: Add 110uL of SPRIselect beads to the 1 10uL reaction volume and mix thoroughly by pipetting or vortex. (Note: This is a 1 X size-selective cleanup intended to select against adapter dimers). Incubate at room temperature for 15 minutes. Place the tubes on a magnet to collect the beads (wait until beads are fully collected on the magnet). Remove the supernatant and discard it. Keeping the tubes on the magnet, add 200uL of freshly-made 80% ethanol. Incubate the tubes at room temperature for 30 seconds or more. Remove the supernatant and discard it. Repeat steps for a total of two washes with 200uL of 80% ethanol. After the last 80% ethanol wash has been removed: 1 ) Go through and remove any residual 80% ethanol with a P200 pipette. 2) Spin the tubes to collect residual 80% ethanol from the sides. 3) Place the tubes back on the magnet and use a P20 to remove the residual 80% ethanol that was collected by centrifugation. Allow the beads to dry by opening the caps of the tubes and leaving them at room temperature for 2 minutes. Remove the tubes from the magnet and elute the DNA in 23uL of nuclease free water (DNA is in the supernatant now). Mix thoroughly by pipetting up and down several times or by flicking and quick spinning the tubes. Incubate the samples at room temperature for 3 minutes. Place the tubes on a magnet to collect the beads. Transfer the supernatant into new strip tubes and discard the dry bead pellets. Repeat the reaction clean-up. This second reaction clean-up removes any excess adapters prior to grafting of individual barcodes.Grafting PCRPerform “Grafting PCR” (Grafting oligos contain: sample barcodes + universal PCR sites): Grafting PCR reactionComponent Volume (pL)KAPA HiFi HotStart ReadyMix (2X) 25Paired Grafting oligos (i7 + i5, 12uM) 2Adapter-ligated library 23Total volume: 50

[0182] Mix thoroughly by pipetting up and down or by vortexing and quick spinning the tubes. Transfer samples to a thermocycler for 5 cycles of grafting PCR.Grafting PCR protocolTemperature Time Cycles98°C 4 min98°C 30 sec60°C 30 sec 672°C 30 sec72°C 4 min4°C Forever

[0183] To each tube containing 50pl library amplification reaction, add 50|iL of SPRIselect beads, for a total volume of 100uL.

[0184] Reaction cleanup # 2: Repeat the cleanup procedure described above in steps 13-22.Elute in 24uL of water. Perform universal PCR reaction:Universal PCR reactionComponent Volume (pL)KAPA HiFi HotStart ReadyMix (2X) 25Illumina Universal Primer - FW + RV (1 OOpiM each) 2Grafting PCR product 23Total volume: 50

[0185] **note: this is doubling of the typical primer amount given the increased upfront DNA input. Mix thoroughly by pipetting up and down or by vortexing and quick spinning the tubes. Amplify the samples with the following PCR conditions:Universal PCR protocolTemperature Time Cycles98°C 45 sec98°C 15 sec60°C 30 sec 872°C 30 sec72°C 1 min4°C hold

[0186] This is an increased number of universal PCR cycles to permit adequate library yields for downstream hybrid capture. To each well / tube containing 50pl library amplification reaction add 50uL of SPRI beads for a total volume of 100uL (1X size-selective cleanup). Reaction cleanup # 3: Repeat the cleanup procedure described above. Remove the tubes from the magnet and add 60uL of water to the dried beads to elute the DNA off of the beads. Mix thoroughly by pipetting up and down or vortexing and quick spinning the tubes. Incubate the samples at room temperature for 3 minutes. Place the tubes on a magnet to collect the beads. Transfer the supernatant into new strip tubes and discard the dry bead pellets.Example 3Enhanced spatial detection of post-neoadjuvant breast cancer minimal residual disease by tissue-based Cancer Personalized Profiling by Deep Sequencing.

[0187] Circulating tumor DNA (ctDNA) is undetectable after neoadjuvant chemotherapy (NAG) in most breast cancer patients with residual disease, limiting its utility to inform adjuvant treatment. The current standard-of-care for assessing NAC response is pathologic evaluation of resection tissues. Many patients without histologically detected post-NAC disease, however, go on to recur, and many with significant gross residual disease are cured, highlighting the need to more accurately quantify low-burden post-NAC MRD, when adjuvant treatment decisions are made.

[0188] We performed spatial post-NAC MRD detection by tissue-based Cancer Personalized Profiling by Deep Sequencing (s-MRD), profiling tissue-based MRD in breast and lymph node resection tissues. Using personalized oligonucleotide hybrid capture panels derived from whole exome sequencing (WES) along with a fixed panel of recurrently mutated and biologically relevant breast cancer genes, we established spatial MRD detection across numerous spatially catalogued samples per case using barcode mediated error suppression and a Monte Carlo statistical framework. We compared sMRD to pathologic detection in matched samples and described patterns of quantitative sMRD measurement that predict recurrence risk.

[0189] We followed a median of 36 (range: 1 -112) single nucleotide variants (SNVs) / case derived from WES and a fixed panel of 56 common breast cancer genes spanning 225kb across 29 tumors representing a range of breast cancer subtypes. Nine (33%) and 10 (37%) tumors harbored TP53 and PIK3CA mutations, respectively. We genotyped 797 individual spatially resolved post-surgical specimen spanning these cases (median 24 post-treatment blocks / case, range: 12-46) and established strong concordance between genomic and histologic MRD detection (considering histology as the gold standard, sensitivity=78.8%, specificity=83.3%), with excellent classification of histologic status by s-MRD (AUC=0.92). s-MRD positive samples undetected by pathology had lower mean allele frequencies (AFs) than those detected by both methods (p<0.001 ), suggesting a superior limit of detection by s-MRD. With a cohort median progression-free survival (PFS) of 140 months, we identified 8 progression events, including two local recurrences adjacent to a s-MRD-positive surgical margin that was histologically negative for invasive carcinoma. One of these recurrences was identified post-mastectomy in a pathologic complete response case. Both s-MRD positive margins contained missense PIK3CA SNVs that were absent from the pretreatment tumor, representing identification of targetable (alpelisib, capivasertib) post-NAC driver lesions that were selected under the pressure of chemotherapy. In the overall cohort, higher mean s-MRD AF across the resection tissues was associated with inferior PFS (HR 1.29, 95% Cl 1.08-1.55, p = 0.004). We defined s-MRD high status as a mean case AF >3%, which predicted inferior PFS (p=0.034) and identified four genes (CSPP1, POLE, DNAAF4, PONT) containing SNVs in post-NAC tissues that were significantly correlated with inferior PFS across the cohort (Cox proportional hazards model, p<0.05).

[0190] Here we introduce s-MRD, a novel MRD detection platform that outperforms surgical pathology for MRD assessment, quantitatively and spatially profiling patterns of genomic lesions under the selection pressure of treatment that are associated with clinical progression. s-MRD- based interventional adjuvant approaches will motivate movement of molecularly targeted therapies into the adjuvant setting, leading to superior survival outcomes and challenging current treatment paradigms.Example 4Spatially defining T-cell clonal evolution in post-neoadjuvant breast cancer and association with molecular residual disease.

[0191] Tumor-infiltrating lymphocyte (TIL) enrichment in primary breast cancers is predictive of treatment response, and specific CD4 and CD8 subsets are associated with neoadjuvant chemotherapy (NAG) and immunotherapy response. Spatially defined T-cell receptor (TOR) evolution patterns in resection tissues associated with NAG response and survival have not been described.

[0192] To define such patterns, we applied high-throughput TCR profiling to pre- and post-NAC tissues and associated immune dynamics with tumor evolution and clinical outcomes. We generated TCR repertoires of 29 primary breast cancers and 768 spatially catalogued, post- NAC specimens from matched cases (median 24 post-treatment samples / case) using Sequence Affinity capture & analysis By Enumeration of cell-free Receptors (SABER) applied to tissue-based Cancer Personalized Profiling by Deep Sequencing. To profile each primary tumor’s genomic and immunologic response to NAG, we designed personalized oligonucleotide panels using pretreatment whole exome sequencing and a fixed panel of recurrently mutated genes to capture emergent alterations, as well as a comprehensive panel of TCR-|3 regions. Leveraging information from fragmented TCRs in FFPE tissues, we spatially enumerated TCR clonotype count and composition in each post-NAC sample and compared the relative abundance of clones shared with each pretreatment tumor. For a subset of cases, we enumerated TILs and tumor cellu larity in post-NAC samples (N = 119). To interrogate clonotype composition, we computed Jaccard similarity indices between each pre- and post-NAC sample pair. We associated post-NAC clonal abundance and clonotype composition with s-MRD burden and genomic composition. Finally, we associated TCR repertoire dynamics with quantitative s-MRD assessment and survival.

[0193] TIL density was strongly correlated with the presence of post-NAC residual disease (R=0.94, p<0.001 for histologic invasive carcinoma cellularity; R=0.6, p<0.001 for mean s-MRD allele frequency (AF)). Because TILs are defined in the presence of histologic residual disease, we defined s-MRD-TILs by TCRs sequenced in s-MRD positive tissues, which demonstrated greater repertoire diversity than non-s-MRD TCRs (greater ShannonE and inverse Simpsondiversity indices, p=.007 and p=1.3e-5, respectively), suggesting a spatially defined tumor neoantigen response. Within cases with low s-MRD burden (mean AF <3%), which experienced longer progression-free survival than those with high s-MRD burden (p=0.034), we observed greater TCR clone count in the post-NAC tissue (p=.012) , greater shared clone count with the pretreatment tumor (p=5.7e-8), and greater similarity of the post-NAC clonotypes to the pretreatment tumor (p=5.1 e-6, Wilcoxon test of Jaccard indices). Presence of a pretreatment CSPP1 lesion was associated with decreased TCR repertoire diversity in chemotherapy-treated resection tissues (ShannonE index, p=0.00056), and CSPPTmutated s-MRD was associated with inferior PFS (HR 23.45, p=.0007)

[0194] By spatially defining changes in the genomic and immunologic microenvironment following NAC, we found superior molecular response is correlated with preservation of the clonal relationship between s-MRD-TILs and the primary tumor with simultaneous generation of a rich TCR repertoire. Computationally predicting neoantigen targets of clonally dominant s- MRD-TILs through NAC provide an avenue for refining selection of molecularly targeted adjuvant therapies.Example 5Spatial methods for clonal architecture mapping

[0195] Beyond s-MRD quantitative metrics, qualitative features including patterns of clonal evolution through chemotherapy and spatially across the resection bed can be determined. To map clonal evolution in 3D space, clustered s-MRD single nucleotide and copy number variant calls are overlaid with each Faxitron-based spatial rendering and define the polarity of clonal progression across the tumor bed, with attention to genomic composition of s-MRD “private” regions that are histologically normal, as well as at the surgical margins and in the axillary nodes to characterize event timing in the context of recurrent potential. Cohort-level patterns of emergent subclonal lesions associated with recurrence are analyzed, with attention to targetable driver genes and base substitution signatures under positive or negative selection. s-MRD lesions are identified under immunologic selection through chemotherapy, which will inform candidate neoantigen peptide selection.

[0196] In a sample mastectomy pCR case with a subsequent local recurrence, s-MRD was detected in the resected nipple bed which, on 3D reconstruction, mapped to the recurrence site (Fig. 6). This s-MRD positive block contained a missense PIK3CA mutation absent from the pretreatment tumor, representing identification of targetable (alpelisib, capivasertib) post-NAC driver lesion clonally selected under the pressure of chemotherapy.

[0197] Mapping s-MRD clonal evolution across the resection bed will permit association of tumor progression dynamics with recurrence risk, e.g. at diagnosis and post-NAC. Copy numbervariant calls are used to support clonal lineage reconstructions of each tumor in time and in 3D space, which will provide orthogonal support for the validity of emergent disease.

[0198] A prospective, randomized two-arm interventional trial is performed of patients not achieving a pCR to NAG, in which adjuvant treatment is guided by pathologic evaluation alone (standard-of-care arm) or additionally with s-MRD genomic data (experimental arm) with the option to offer adjuvant targeted therapies typically used in the metastatic setting. Clonal evolution trajectories beyond NAG that lead to recurrence are longitudinally characterized, s- MRD-targeted cytotoxic adjuvant therapies are expected to decrease recurrence relative to pCR-informed approaches. This model assumes that post-NAC residual genomic lesions serve as surrogates for disseminated micrometastatic disease, and that targeting localized disease lesions will improve survival outcomes.

[0199] Identification of immunogenic genomic lesions associated with tumor-infiltrating lymphocytes (TILs) and their ability to elicit neoantigen-specific T cell responses. HLA genotype TILs from WES data with T1 K and derive candidate s-MRD lesions to computationally predict immunogenic epitopes in the context of HLA class II and class I presentation. Pre- and posttreatment TOR repertoires are generated for each patient using immunoSEQ and use GLIPH2 to cluster TCRs recognizing shared epitopes and TAPIR to predict TCRs targeted against cancer-specific epitopes. TCR clonotype composition and density is overlaid with s-MRD Faxitron-based case reconstructions to spatially align the tumor-directed immune response with residual and resolved disease case regions. To functionally evaluate CD4+and CD8+T cell reactivity, each patient’s top 20 peptide candidates are ranked according to bioinformatically predicted high-affinity HLA-II and -I binding, as well as s-MRD expression levels. TILs are isolated from pretreatment tumor biopsies and peripheral blood mononuclear cells (PBMCs) from patients enrolled in the s-MRD trial, and used to derive separate TIL and PBMC cultures. These T-cells are co-cultured with matched patient dendritic cells transfected with pools of In- vitro-transc bed RNAs generated from each patient’s candidate lesions, allowing processing and presentation of all candidate peptides in the context of each patient’s MHC I and II molecules for deconvolution of productively recognized epitopes via TScan-ll and T-scan, respectively. Finally, validated peptide pools are synthesized into mRNA vaccine vectors for in vivo study.

[0200] NAC-responsive tumors are expected to bear dominant TCR clones directed against mutated public (shared) and private (patient-specific) cancer antigens. s-MRD-derived epitopes that are bioinformatically supported may serve as strong immunogenic lesions for functional validation and to inform an eventual mRNA vaccine approach. s-MRD data will guide epitope selection such that resolved lesions (present at diagnosis but not post-NAC) will elicit the strongest antitumor responses, with epitope spreading to augment a weaker response to “escape lesions” that persist or emerge through NAG. This polytopic response may eradicateresidual micrometastatic disease and could be further augmented by an immunotherapyvaccine approach.

[0201] The method for MRD detection may be validated compared to gold-standard pathologic assessment. To do this, a detection threshold using a Monte Carlo statistical framework to integrate all personalized mutations per sample is calibrated into a single assessment of s-MRD burden. s-MRD positivity is defined as that present in less than 5% of control samples. The ability of s-MRD to classify true positive (pathology positive) from true negative (pathology negative) samples is determined using criterion values in Receiver-Operator Curve (ROC) analysis. Discordant results are adjudicated in review with surgical pathology to confirm the presence or absence of histologic disease. The pretreatment mutational profile to each post- NAC specimen is analyzed using summary statistics and paired sample t-tests to evaluate for change from the pretreatment level. Using TCR sequencing data the Jaccard similarity indices are calculated between pre- and post-NAC samples, as well as between s-MRD positive and negative blocks within each case and compare differences between groups using a Wilcoxon rank-sum test.

[0202] Quantitative s-MRD features that predict 5-year recurrence-free survival (RFS-5) are assessed, defining a s-MRD high risk group with an RFS-5 <20% and a low risk group with an RFS-5 >80%, and determining the s-MRD features that enable detection of differences between these groups with 80% power and a type-l error rate of 0.05. Given anticipated sample dropout with historical samples handled in numerous assays, N=30 cases are targeted, which will provide 93% post-hoc power. Univariate Cox proportional hazards models of RFS-5, assessing individual metrics including s-MRD case density (mean s-MRD AF across the case), span (number and 3-D volume of detected blocks), and peak density (maximal s-MRD AF across the case) via log-rank test analysis, and compare predictive response criteria derived from s-MRD to response to NAC by pCR status. A multivariate Lasso Cox proportional hazards regression model, which uses L1 regularization to facilitate automatic feature selection for inclusion of the most predictive s-MRD and clinicopathological features in the model is also built. Clinical characteristics including breast cancer subtype, age at diagnosis, chemotherapy regimen, and menopausal status, and s-MRD quantitative and mutation compositional features are included. This model will be fit using the Glmnet R package which performs cross-validation to mimic the effect of a test set and prevents model overfitting. This will also address collinearity among predictors. Further post hoc analysis is used to determine the unique and overlapping contributions of individual features.

Claims

WHAT IS CLAIMED IS:

1. A method of assessing minimal residual disease (MRD) status in a subject following treatment, comprising the steps of:(a) performing deep sequencing of DNA of a pre-treatment tumor sample of the subject;(b) identifying tumor-specific mutations in the pre-treatment tumor sample DNA;(c) performing deep sequencing of DNA from post-treatment tissue of the subject’s tumor site;(d) determining the presence of the tumor-specific mutations in the post-treatment tissue;(e) determining the subject’s MRD status based on the presence of the tumor-specific mutations.

2. The method of claim 1 , wherein a patient-specific mutation panel is generated from the pre-treatment tumor sample, and this patient-specific mutation panel is used to identify MRD status in the post treatment sample.

3. A method of claim 1 , where a sample from healthy control tissue from the subject is also sequenced and used as a comparator in step (a).

4. The method of any of claims 1-3, wherein the tumor sample is a section of resected tumor bed, breast, or lymph node tissue.

5. A method of assessing MRD status in a subject following treatment, comprising the steps of:(a) performing deep sequencing of DNA of a pre-treatment tumor sample and a healthy control tissue sample of the subject;(b) identifying tumor-specific mutations in the pre-treatment tumor sample DNA relative to the control tissue and generating a patient-specific mutation panel;(c) performing deep sequencing of DNA from post-treatment tissue of the subject’s tumor site(d) determining the presence of the tumor-specific mutations in the previously-generated patient-specific mutation panel in the post-treatment tissue;(e) determining the subject’s MRD status based on the presence of the tumor-specific mutations.

6. The method of any of the preceding claims, wherein step (c) further comprises sequencing one or more common breast cancer mutations.

7. The method of claim 6, wherein the one or more common breast cancer mutations comprise sequences of: TP53; PIK3CA; GAT A3; CBFB; PTEN; CDH1 ; TBX3; MAP3K1 ; MAP2K4; RUNX1 ; AKT1 ; CDKN1 B; DCAF4L2; PIK3R1 ; RB1 ; KRAS; KMT2C; CTCF; STK11 ; ERBB2; CASP8; MEN1 ; ARID1 A; SF3B1 ; NOTCH1 ; CHEK2; BAP1 ; SMAD4; ERBB3; MAP3K13; EGFR; JAK1 ; ASXL1 ; ROS1 ; NF1 ; FANCA; ATR; ALK; AKT2; KDM6A; EP300; SETD2; ERBB4; FLT3; HRAS; CTNNA1 ; NF2; PBRM1 ; FBXW7; NRAS; BRCA1 ; BRCA2; MTOR; POLE; APC; and FGFR2.

8. The method of any of the previous claims, wherein step (a) and step (c) further comprise sequencing of T cell receptor (TOR) sequences.

9. The method of claim 8, wherein the TOR sequences are spatially localized over tissue sections.

10. The method of any of the preceding claims, further comprising treating the subject based on the foregoing MRD status determination.

11. The method of claim 10, wherein treatment comprises administration of an agent targeted to a post-NAC mutation.

12. The method of any of the preceding claims, wherein the tumor is breast cancer.

13. The method of any of the preceding claims, wherein the treatment is neoadjuvant chemotherapy.

14. The method of any of the preceding claims, wherein at least twenty, at least fifty, at least 75, or at least 100 tumor-specific mutations are identified.

15. The method of any of the preceding claims wherein the sequencing in step (a) is whole-exome sequencing.

16. The method of any of the preceding claims, wherein the tumor-specific mutations comprise SNV mutations.

17. The method of any of the preceding claims, wherein prior to step (c), the samples are enriched for DNA corresponding to genes of the tumor-specific mutations.

18. The method of Claim 13, wherein the enrichment is achieved by hybrid capture using one or more mutation-specific capture probes.

19. The method of any of the preceding claims, wherein MRD status is assessed by a Monte Carlo statistical framework and assessment of individual SNV status in each sample and across each case.

20. The method of any of claims 10-19, wherein a subject determined to have low MRD burden / risk is treated with observation or standard-of-care treatment.

21. The method of any of claims 10-19, wherein a subject determined to have high MRD burden / risk is treated accordingly.

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