Breast cancer markers and uses thereof

Abstract

The present invention relates to compositions and methods for cancer diagnosis, research and therapy, including but not limited to, cancer markers, in particular CTLA4. In particular, the present invention relates to the CTLA4 marker for use in the diagnosis, prognosis, and treatment of breast cancer.

Description

[0001] Atty. Dkt. No.: INVEN-42177.601 BREAST CANCER MARKERS AND USES THEREOF CROSS-REFERENCE TO RELATED APPLICATIONS The present application claims priority to U.S. Provisional Application No.63 / 548248, filed November 13, 2023, which is incorporated herein by reference in its entirety. FIELD OF THE INVENTION The present invention relates to compositions and methods for cancer diagnosis, research and therapy, including but not limited to, cancer markers. In particular, the present invention relates to markers for use in the diagnosis, prognosis, and treatment of breast cancer. BACKGROUND OF THE INVENTION Breast cancer (BC) is the most common cancer in women, with approximately 2.3 million new cases diagnosed and 680,000 deaths worldwide in 2020 (1). Approximately 15 % of patients with newly diagnosed BC have triple-negative disease. Triple-negative breast cancer (TNBC) is defined by the absence or very low expression of the two hormone receptors (HR) estrogen receptor (ER) and progesterone receptor (PR), and the absence of amplification of human epidermal growth factor receptor 2 (HER2). TNBC is an aggressive phenotype with the highest risk of early recurrence. Despite recent therapeutic advances, survival in metastatic TNBC also remains poor (2). To reduce the risk of disease recurrence and death, the majority of patients receive adjuvant or neoadjuvant chemotherapy, with the addition of immunotherapy for selected cases (6-9). While adjuvant treatments significantly reduce recurrence rates and mortality, they also cause considerable acute and long-term side effects, with negative impact on the quality of life of patients during and after treatment (10). Historical data demonstrate that a considerable proportion of patients would be cured by locoregional treatment alone (11). Identifying low-risk patients at the time of diagnosis could allow de-escalation or omission of the chemotherapy regimen. Additional markers for TNBC diagnosis, prognosis, and customized treatment are needed. SUMMARY OF THE INVENTION The present invention relates to compositions and methods for cancer diagnosis, research and therapy, including but not limited to, cancer markers. In particular, the present invention relates to markers for use in the diagnosis, prognosis, and treatment of breast cancer. Atty. Dkt. No.: INVEN-42177.601 Tumor immune cell infiltration is a favorable prognostic factor in triple-negative breast cancer. Most triple-negative tumors belong to the aggressive basal-like subtype. Experiments described herein utilized immune gene expression levels to, for example, stratify patients into groups for whom adjuvant chemotherapy can be de-escalated or is recommended. This improves treatment for TNBC and allows low risk individuals to choose less aggressive treatments with fewer side effects. Accordingly, in some embodiments, provided herein is a method for providing a prognosis for a subject with breast cancer, or selecting a subject with breast cancer for treatment with a particular therapy, comprising: (a) detecting the level of expression of cytotoxic T- lymphocyte-associated protein 4 (CTLA4) in a sample from the subject; and (b) comparing the level of expression of the CTLA4 to a corresponding reference level of expression of the CTLA4, wherein an altered level of expression of the CTLA4 gene relative to the reference level provides an indication selected from the group consisting of an indication of breast cancer recurrence, an indication of survival of the subject, and an indication that the subject is a candidate for treatment with a particular therapy. In some embodiments, an increased level of CTL4 in the sample is indicative of increased immune cell infiltration (e.g., tumor lymphocyte infiltration). In some embodiments, an increased level of CTLA4 in the sample as compared to the reference level is indicative of an increased likelihood of survival and / or a decreased likelihood of recurrence of breast cancer in the subject. In some embodiments, the method further comprises stratifying the subject into an increased likelihood of survival group or a decreased likelihood of survival group or into an increased likelihood of breast cancer recurrence group or a decreased likelihood of breast cancer recurrence group. In some embodiments, the stratifying is used to recommend treatment with a particular therapy. For example, in some embodiments, adjuvant chemotherapy is recommended to the decreased likelihood of survival group or the increased likelihood of breast cancer recurrence group and adjuvant chemotherapy is not recommended to the increased likelihood of survival group or the decreased likelihood of breast cancer recurrence group. In some embodiments, the method further comprises the step of administering adjuvant chemotherapy to the decreased likelihood of survival group or increased likelihood of breast cancer recurrence group. Also provided is a method for treating breast cancer, comprising: (a) detecting the level of expression CTLA4 in a sample from the subject; and (b) administering adjuvant chemotherapy to said subject when said level of CTLA4 is decreased relative to a control level and not administering adjuvant chemotherapy to said subject with said level of expression of CTLA4 is increased relative to a control level. Atty. Dkt. No.: INVEN-42177.601 The present disclosure is not limited to a particular increased level of expression of CTLA4. For example, in certain cases, the increased level is at the 50thpercentile or higher (e.g., at the 55th, 60th, 63rd, or high percentile of expression) from a representative population of patients with early-stage basal-like breast cancer. The present disclosure is not limited to a particular sample type. Examples include but are not limited to, breast tissue (e.g., breast cancer biopsy tissue), breast cells, bone marrow, blood, or serum. In some embodiments, the subject has basal-like breast cancer (e.g., triple-negative breast cancer). In some embodiments, the subject has undergone treatment for breast cancer (e.g., one or more of chemotherapy, surgery and / or radiotherapy) or has not undergone treatment for breast cancer. The present disclosure is not limited to particular methods for detecting the level of expression of CTLA4 (e.g., by detecting the level of CTLA4 mRNA or protein). In some embodiments, detection methods comprise the use of one or more nucleic acid reagents selected from nucleic acid primers or nucleic acid probes or one or more antibodies. In some embodiments, the primers, probes, and / or antibodies comprise a detectable label. Also provided herein is the use of reagent that specifically detects an altered level of expression of CTLA4 in a sample from a subject in the determination of the likelihood of survival of the subject, likelihood of recurrence of breast cancer, stratifying said subject into high and low likelihood of recurrence of breast cancer groups, stratifying subjects into high and low likelihood of survival groups, stratifying subjects into treatment groups, and / or determining that the subject is a candidate for treatment with a particular therapy. Additional embodiments are described herein. DESCRIPTION OF THE FIGURES FIG.1 shows patient / sample disposition. Selection criteria for patients / samples included in the study for each cohort. FIG.2 shows differential gene expression by systemic recurrence. Boxplot of scaled log2- transformed normalized gene expression in patients (n=45) from the Oslo1 cohort with or without subsequent systemic recurrence of breast cancer. FIG.3 shows Kaplan-Meier analysis of disease-specific survival in patients with gene expression above and below median using data from the Oslo1 cohort (n=45). Atty. Dkt. No.: INVEN-42177.601 FIG.4 shows survival and disease recurrence by CTLA4 expression. Overall survival, recurrence-free interval, and disease-specific survival in Oslo1-patients with CTLA4 expression above and below the cutoff at the 63rd percentile. FIG.5 shows survival and disease recurrence by CTLA4 expression. Five-year overall survival, recurrence-free interval, and distant recurrence-free interval in patients with CTLA4 expression above and below the cutoffs at the 63rd (a-c; derived from Oslo1) and the 60th (d-f; 435 derived from SCAN-B) percentile in the SCAN-B cohort. FIG.6 shows survival by CTLA4 expression. Disease-specific and overall survival with CTLA4 expression above and below the cutoff value at the 63rd(a-b) and 60th (c-d) percentile in the METABRIC data set. FIG.7 shows outcomes in patients with and without (neo-) adjuvant chemotherapy 4445-year outcomes by CTLA4 expression in patients with and without chemotherapy in the Oslo1, SCAN-B and METABRIC cohorts. FIG.8 shows CTLA4 expression versus TIL, TLS, and GC score. a: Correlation plot of tumor-infiltrating lymphocytes (TIL) vs CTLA4. b: CTLA4 expression in samples grouped by prevalence of tertiary lymphoid structures (TLS). c: CTLA4 expression in samples grouped by prevalence of germinal centers (GC). FIG.9 shows outcomes by CTLA4 expression in triple-negative breast cancer. Survival / recurrence rates in patients with high and low CTLA4 expression and triple-negative breast cancer (regardless of molecular subtype) in Oslo1 and SCAN-B. FIG.10 shows gene expression correlation. Pairwise correlations between the scaled expression of the 13 genes that were significantly correlated with disease-specific survival in the Oslo1 cohort. FIG.11 shows ROC analysis. ROC analysis was performed with breast cancer-related death as a response variable and CTLA4 expression as a predictor variable. FIG.12 shows ROC analysis. ROC analysis of distant disease recurrence by CTLA4 expression quantiles in the SCAN-B validation cohort. FIG.13 shows outcomes in Oslo1 by 60th percentile cutoff. Overall survival, recurrence- free interval, and disease-specific survival in the Oslo1 cohort with CTLA4 expression above and below the 60th percentile cutoff, derived from ROC analysis in the SCAN-B cohort. FIG.14 shows CTLA4 expression vs NanoString scores. CTLA4 expression above the 63rd percentile is considered high. Atty. Dkt. No.: INVEN-42177.601 FIG.15 shows outcomes by CTLA4 expression in triple-negative breast cancer, cutoff at 60th percentile. Survival / recurrence rates in patients with high and low CTLA4 expression and triple-negative breast cancer (regardless of molecular subtype) in Oslo1 and SCAN-B. FIG.16A-B shows evaluation of tumor-infiltrating lymphocytes, tertiary lymphoid structures, and germinal centers on H&E slides A: Examples of tumors with low (5%) and high (80%) TIL scores. B: Scoring of tertiary lymphoid structures (TLS) on whole tumor sections. C: TLS with and without germinal centers, at enhanced magnification. DEFINITIONS To facilitate an understanding of the present invention, a number of terms and phrases are defined below: As used herein, the terms “detect”, “detecting” or “detection” may describe either the general act of discovering or discerning or the specific observation of a detectably labeled composition. As used herein, the term “subject” refers to any organisms that are screened using the diagnostic methods described herein. Such organisms preferably include, but are not limited to, mammals (e.g., murines, simians, equines, bovines, porcines, canines, felines, and the like), and most preferably includes humans. The term “diagnosed,” as used herein, refers to the recognition of a disease by its signs and symptoms, or genetic analysis, pathological analysis, histological analysis, and the like. A "subject suspected of having cancer" encompasses an individual who has received an initial diagnosis (e.g., a CT scan showing a mass) but for whom the stage of cancer or gene expression levels indicative of cancer prognosis is not known. The term further includes people who once had cancer (e.g., an individual in remission). In some embodiments, “subjects” are control subjects that are suspected of having cancer or diagnosed with cancer. As used herein, the term "characterizing cancer in a subject" refers to the identification of one or more properties of a cancer sample in a subject, including but not limited to, the presence of benign, pre-cancerous or cancerous tissue, the stage of the cancer, and the subject's prognosis. Cancers may be characterized by the level of expression of genes described herein in cancer cells. As used herein, the term "characterizing a breast sample in a subject" refers to the identification of one or more properties of a breast tissue sample (e.g., including but not limited to, the presence of cancerous tissue, the level of gene expression of genes described herein, the presence of pre-cancerous tissue that is likely to become cancerous, and the presence of Atty. Dkt. No.: INVEN-42177.601 cancerous tissue that is likely to metastasize, the presence of cancerous tissue that is likely to recur, or the likelihood of breast cancer-specific death). As used herein, the term "stage of cancer" refers to a qualitative or quantitative assessment of the level of advancement of a cancer. Criteria used to determine the stage of a cancer include, but are not limited to, the size of the tumor and the extent of metastases (e.g., localized or distant). As used herein, the term "purified" or "to purify" refers to the removal of components (e.g., contaminants) from a sample. The term “label” refers to a molecule or composition bound to an analyte, analyte analog, detector reagent, antibody, nucleic acid (e.g., primer or probe) or binding partner that is detectable by spectroscopic, photochemical, biochemical, immunochemical, electrical, optical or chemical means. Examples of labels, including enzymes, colloidal gold particles, colored latex particles, have been disclosed (U.S. Pat. Nos.4,275,149; 4,313,734; 4,373,932; and 4,954,452, each incorporated by reference herein). Additional examples of useful labels include, without limitation, radioactive isotopes, co-factors, ligands, chemiluminescent or fluorescent agents, protein-adsorbed silver particles, protein-adsorbed iron particles, protein-adsorbed copper particles, protein-adsorbed selenium particles, protein-adsorbed sulfur particles, protein-adsorbed tellurium particles, protein-adsorbed carbon particles, and protein-coupled dye sacs. The attachment of a compound (e.g., a detector reagent) to a label can be through covalent bonds, adsorption processes, hydrophobic and / or electrostatic bonds, as in chelates and the like, or combinations of these bonds and interactions and / or may involve a linking group. As used herein, the term “reference level,” as in the reference level of CTLA4, refers to a reference level of expression of the CTLA4. A “reference level” of CTLA4 be an absolute or relative amount level of expression, a minimum and / or maximum amount level of expression, a mean level of expression, and / or a median level of expression. Appropriate positive and negative reference levels of an analyte for a particular disease state, phenotype, or lack thereof may be determined by measuring levels of expression of CTLA4 in one or more appropriate subjects, and such reference levels may be tailored to specific populations of subjects (e.g., a reference level may be age-matched so that comparisons may be made between CTLA4 expression levels in samples from subjects of a certain age and reference levels for a particular disease state, phenotype, or lack thereof in a certain age group). As used herein, the term "sample" is used in its broadest sense. In one sense, it is meant to include a specimen or culture obtained from any source, as well as biological and environmental samples. Biological samples may be obtained from animals (including humans) Atty. Dkt. No.: INVEN-42177.601 and encompass fluids, solids, and tissues. Biological samples include blood products, such as plasma, serum and the like. Such examples are not however to be construed as limiting the sample types applicable to the present invention. DETAILED DESCRIPTION OF THE INVENTION The present invention relates to compositions and methods for cancer diagnosis, research and therapy, including but not limited to, cancer markers. In particular, the present invention relates to markers for use in the diagnosis, prognosis, stratification of subjects, and treatment of breast cancer. None of the existing immunohistochemical assays and gene panels for subgrouping of breast cancer incorporate immune markers. Tumor lymphocyte infiltration (TLI) has been used to assess breast cancer tumors. However, these types of assays are difficult to standardize and have not generally been implemented for clinical decision making. To address the problem, the instant disclosure demonstrates that the CTLA4 gene expression biomarker outperforms a state- of-the-art TIL score with regard to prognostic information. In particular, a high level of CTLA4 expression as compared to a control or reference level is indicative of an excellent prognosis and can be used to stratify patients into a group in which adjuvant chemotherapy can be reduced discontinued. Several studies have demonstrated that a high number of TILs is a positive prognostic factor in TNBC, as well as a positive predictive factor for response to systemic therapies (12-17). While various degrees of lymphocyte infiltration can be found in all subtypes of BC, high infiltration is most frequently seen in TNBC (18, 19). The International Immuno-Oncology Biomarker Working Group on Breast Cancer has published guidelines for standardizing the evaluation of TILs and demonstrated that it can be performed in a reproducible manner (20, 21). De Jong et al. (22) reported an excellent survival outcome without (neo-)adjuvant therapy in patients with TIL score ≥ 75% (21% of patients) in a cohort of younger patients with lymph-node negative TNBC. Despite standardization efforts, interobserver variation in TIL quantification remains a challenge (23) and studies with different patient selection criteria and treatment regimens have suggested other prognostic cutoff values. In a pooled analysis of nine studies evaluating TILs as a prognostic marker, Loi and colleagues reported excellent outcomes in lymph node-negative patients with TIL ≥ 30%, corresponding to the upper quartile (24). The 2019 St. Gallen International Consensus Guidelines for the primary treatment of early BC recommended that TIL should be routinely reported in pathology reports for TNBC due to the prognostic value (25). However, as of the most recent 2021 guidelines, the panel does not recommend that TIL Atty. Dkt. No.: INVEN-42177.601 should be used to guide treatment decisions, due to insufficient evidence (6). Perou and colleagues introduced the intrinsic subtypes of breast cancer in 2000, based on microarray analyses of tumor expression of 8000 genes (26). The main subtypes, Luminal A, Luminal B, HER2-enriched, and Basal-like, display different biology, clinical behavior, and response to treatment (27-29). Parker and colleagues (30) showed that reproducible prediction of the intrinsic subtypes can be performed by expression analysis of 50 genes, known as the PAM50 classifier. While tumor gene expression analyses have become widely available only in recent years, routine immunohistochemistry (IHC) evaluation of the expression of estrogen receptor (ER), progesterone receptor (PR), and HER2 has been universally adopted to assess susceptibility to endocrine and HER2-directed treatment. As most basal-like tumors are triple-negative by IHC, triple-negative disease has been used as a surrogate marker for the basal-like subtype, guiding treatment decisions as well as enrollment and stratification in clinical trials. However, 14% of triple-negative tumors are classified as non-basal by PAM50, and tumors of all intrinsic subtypes can be found within the triple-negative category (28). Central properties of the intrinsic subtypes are retained regardless of receptor status (31, 32). This diversity within TNBC may explain some of the difficulties in identifying robust prognostic and predictive biomarkers. Quantification of TIL by histopathological evaluation of H&E slides represents an affordable option. However, the standardization of such methods remains challenging for implementation in the clinical setting. This prognostic information has not been generally implemented to guide treatment decisions. Experiments described herein retrospectively analyzed the expression of a curated set of 753 immune-related genes in basal-like tumors from a prospective study of patients with early- stage BC, with available PAM50-based intrinsic subtype information and known clinical, and histopathological risk factors (33). The aim of the study was to investigate whether immune gene expression patterns can identify patients with low risk of disease recurrence and death, who could benefit from de-escalation or omission of adjuvant chemotherapy. The experiments identified CTLA4 as a marker for breast cancer prognosis and in identifying individuals that are in need of or can forego adjuvant chemotherapy. The levels of CTLA4 correlated with TILs but provide an improved marker for use in prognosis and stratifying subjects into risk and treatment groups. Accordingly, in some embodiments, provided herein is a method for providing a prognosis for a subject with breast cancer, or selecting a subject with breast cancer for treatment with a particular therapy, comprising: (a) detecting the level of expression of cytotoxic T- lymphocyte-associated protein 4 (CTLA4) in a sample from the subject; and (b) comparing the level of expression of the CTLA4 to a corresponding reference level of expression of the CTLA4, wherein an altered level of expression of the CTLA4 gene relative to the reference level provides Atty. Dkt. No.: INVEN-42177.601 an indication selected from the group consisting of an indication of breast cancer recurrence, an indication of survival of the subject, and an indication that the subject is a candidate for treatment with a particular therapy. In some embodiments, an increased level of CTL4 in the sample is indicative of increased immune cell infiltration (e.g., tumor lymphocyte infiltration). In some embodiments, an increased level of CTLA4 in the sample as compared to the reference level is indicative of an increased likelihood of survival and / or a decreased likelihood of recurrence of breast cancer in the subject. In some embodiments, the level of CTLA4 is used to stratify patients into high and low risk groups. Such stratification can then be used to provide a prognosis, recommend treatment, or provide a treatment that is specific for the patient. For example, in some embodiments, the method further comprises stratifying the subject into an increased likelihood of survival group or a decreased likelihood of survival group or into an increased likelihood of breast cancer recurrence group or a decreased likelihood of breast cancer recurrence group. In some embodiments, the stratifying is used to recommend treatment with a particular therapy. For example, in some embodiments, adjuvant chemotherapy is recommended to the decreased likelihood of survival group or the increased likelihood of breast cancer recurrence group and adjuvant chemotherapy is not recommended to the increased likelihood of survival group or the decreased likelihood of breast cancer recurrence group. In some embodiments, the method further comprises the step of administering adjuvant chemotherapy to the decreased likelihood of survival group or increased likelihood of breast cancer recurrence group. Also provided is a method for treating breast cancer, comprising: (a) detecting the level of expression CTLA4 in a sample from the subject; and (b) administering adjuvant chemotherapy to said subject when said level of CTLA4 is decreased relative to a control level and not administering adjuvant chemotherapy to said subject with said level of expression of CTLA4 is increased relative to a control level. The present disclosure is not limited to a particular sample type. Examples include but are not limited to, breast tissue (e.g., breast cancer biopsy tissue), breast cells, bone marrow, blood, or serum. In some embodiments, the subject has basal-like breast cancer (e.g., triple-negative breast cancer). In some embodiments, the subject has undergone treatment for breast cancer (e.g., one or more of chemotherapy, surgery and / or radiotherapy) or has not undergone treatment for breast cancer. In some embodiments, in addition to CTLA4, one or more additional breast cancer markers are assayed for a level of expression. Examples include but are not limited to, those in Atty. Dkt. No.: INVEN-42177.601 the SCAN-B (Saal et al., Genome Med.2015 Feb 2;7(1):20. doi: 10.1186 / s13073-015-0131-9 and METABRIC (Curtis, C. et al. The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups. Nature 486, 346–352 (2012)) cohorts. The present invention is not limited to particular methods of detecting the level of CTLA4 or other breast cancer markers. CTLA4 may be detected as DNA (e.g., cDNA), RNA (e.g., mRNA), or protein. In some embodiments, nucleic acid sequencing methods are utilized for detection. In some embodiments, the technology provided herein finds use in a Second Generation (a.k.a. Next Generation or Next-Gen), Third Generation (a.k.a. Next-Next-Gen), or Fourth Generation (a.k.a. N3-Gen) sequencing technology including, but not limited to, pyrosequencing, sequencing-by- ligation, single molecule sequencing, sequence-by-synthesis (SBS), semiconductor sequencing, massive parallel clonal, massive parallel single molecule SBS, massive parallel single molecule real-time, massive parallel single molecule real-time nanopore technology, etc. Morozova and Marra provide a review of some such technologies in Genomics, 92: 255 (2008), herein incorporated by reference in its entirety. Those of ordinary skill in the art will recognize that because RNA is less stable in the cell and more prone to nuclease attack experimentally RNA is usually reverse transcribed to DNA before sequencing. A number of DNA sequencing techniques are suitable, including fluorescence-based sequencing methodologies (See, e.g., Birren et al., Genome Analysis: Analyzing DNA, 1, Cold Spring Harbor, N.Y.; herein incorporated by reference in its entirety). In some embodiments, the technology finds use in automated sequencing techniques understood in that art. In some embodiments, the present technology finds use in parallel sequencing of partitioned amplicons (PCT Publication No: WO2006084132 to Kevin McKernan et al., herein incorporated by reference in its entirety). In some embodiments, the technology finds use in DNA sequencing by parallel oligonucleotide extension (See, e.g., U.S. Pat. No.5,750,341 to Macevicz et al., and U.S. Pat. No.6,306,597 to Macevicz et al., both of which are herein incorporated by reference in their entireties). Additional examples of sequencing techniques in which the technology finds use include the Church polony technology (Mitra et al., 2003, Analytical Biochemistry 320, 55-65; Shendure et al., 2005 Science 309, 1728-1732; U.S. Pat. No.6,432,360, U.S. Pat. No.6,485,944, U.S. Pat. No.6,511,803; herein incorporated by reference in their entireties), the 454 picotiter pyrosequencing technology (Margulies et al., 2005 Nature 437, 376-380; US 20050130173; herein incorporated by reference in their entireties), the Solexa single base addition technology (Bennett et al., 2005, Pharmacogenomics, 6, 373-382; U.S. Pat. No.6,787,308; U.S. Pat. No. 6,833,246; herein incorporated by reference in their entireties), the Lynx massively parallel Atty. Dkt. No.: INVEN-42177.601 signature sequencing technology (Brenner et al. (2000). Nat. Biotechnol.18:630-634; U.S. Pat. No.5,695,934; U.S. Pat. No.5,714,330; herein incorporated by reference in their entireties), and the Adessi PCR colony technology (Adessi et al. (2000). Nucleic Acid Res.28, E87; WO 00018957; herein incorporated by reference in its entirety). Next-generation sequencing (NGS) methods share the common feature of massively parallel, high-throughput strategies, with the goal of lower costs in comparison to older sequencing methods (see, e.g., Voelkerding et al., Clinical Chem., 55: 641-658, 2009; MacLean et al., Nature Rev. Microbiol., 7: 287-296; each herein incorporated by reference in their entirety). NGS methods can be broadly divided into those that typically use template amplification and those that do not. Amplification-requiring methods include pyrosequencing commercialized by Roche as the 454 technology platforms (e.g., GS 20 and GS FLX), Life Technologies / Ion Torrent, the Solexa platform commercialized by Illumina, GnuBio, and the Supported Oligonucleotide Ligation and Detection (SOLiD) platform commercialized by Applied Biosystems. Non-amplification approaches, also known as single-molecule sequencing, are exemplified by the HeliScope platform commercialized by Helicos BioSciences, and emerging platforms commercialized by VisiGen, Oxford Nanopore Technologies Ltd., and Pacific Biosciences, respectively. In some embodiments, hybridization methods are utilized. Illustrative non-limiting examples of nucleic acid hybridization techniques include, but are not limited to, in situ hybridization (ISH), microarray, and Southern or Northern blot. In situ hybridization (ISH) is a type of hybridization that uses a labeled complementary DNA or RNA strand as a probe to localize a specific DNA or RNA sequence in a portion or section of tissue (in situ), or, if the tissue is small enough, the entire tissue (whole mount ISH). DNA ISH can be used to determine the structure of chromosomes. RNA ISH is used to measure and localize mRNAs and other transcripts within tissue sections or whole mounts. Sample cells and tissues are usually treated to fix the target transcripts in place and to increase access of the probe. The probe hybridizes to the target sequence at elevated temperature, and then the excess probe is washed away. The probe that was labeled with radio-, fluorescent- or antigen-labeled bases is localized and quantitated in the tissue using autoradiography, fluorescence microscopy or immunohistochemistry. ISH can also use two or more probes, labeled with radioactivity or the other non-radioactive labels, to simultaneously detect two or more transcripts. In some embodiments, markers are detected using fluorescence in situ hybridization (FISH). The preferred FISH assays for methods of embodiments of the present disclosure utilize bacterial artificial chromosomes (BACs). These have been used extensively in the human Atty. Dkt. No.: INVEN-42177.601 genome sequencing project (see Nature 409: 953-958 (2001)) and clones containing specific BACs are available through distributors that can be located through many sources, e.g., NCBI. Each BAC clone from the human genome has been given a reference name that unambiguously identifies it. These names can be used to find a corresponding GenBank sequence and to order copies of the clone from a distributor. Different kinds of biological assays are called microarrays including, but not limited to: microarrays (e.g., cDNA microarrays and oligonucleotide microarrays); protein microarrays; tissue microarrays; transfection or cell microarrays; chemical compound microarrays; and antibody microarrays. A DNA microarray, commonly known as gene chip, DNA chip, or biochip, is a collection of microscopic DNA spots attached to a solid surface (e.g., glass, plastic or silicon chip) forming an array for the purpose of expression profiling or monitoring expression levels for thousands of genes simultaneously. The affixed DNA segments are known as probes, thousands of which can be used in a single DNA microarray. Microarrays can be used to identify disease genes by comparing gene expression in disease and normal cells. Microarrays can be fabricated using a variety of technologies, including but not limited to: printing with fine-pointed pins onto glass slides; photolithography using pre-made masks; photolithography using dynamic micromirror devices; ink-jet printing; or electrochemistry on microelectrode arrays. Southern and Northern blotting may be used to detect specific DNA or RNA sequences, respectively. In these techniques DNA or RNA is extracted from a sample, fragmented, electrophoretically separated on a matrix gel, and transferred to a membrane filter. The filter bound DNA or RNA is subject to hybridization with a labeled probe complementary to the sequence of interest. Hybridized probe bound to the filter is detected. A variant of the procedure is the reverse Northern blot, in which the substrate nucleic acid that is affixed to the membrane is a collection of isolated DNA fragments and the probe is RNA extracted from a tissue and labeled. In some embodiments, marker sequences are amplified (e.g., after conversion to DNA) prior to or simultaneous with detection. Illustrative non-limiting examples of nucleic acid amplification techniques include, but are not limited to, polymerase chain reaction (PCR), reverse transcription polymerase chain reaction (RT-PCR), transcription-mediated amplification (TMA), ligase chain reaction (LCR), strand displacement amplification (SDA), and nucleic acid sequence-based amplification (NASBA). Those of ordinary skill in the art will recognize that certain amplification techniques (e.g., PCR) require that RNA be reversed transcribed to DNA prior to amplification (e.g., RT-PCR), whereas other amplification techniques directly amplify RNA (e.g., TMA and NASBA). Atty. Dkt. No.: INVEN-42177.601 In some embodiments, quantitative evaluation of the amplification process in real-time is performed. Evaluation of an amplification process in “real-time” involves determining the amount of amplicon in the reaction mixture either continuously or periodically during the amplification reaction and using the determined values to calculate the amount of target sequence initially present in the sample. A variety of methods for determining the amount of initial target sequence present in a sample based on real-time amplification are well known in the art. These include methods disclosed in U.S. Pat. Nos.6,303,305 and 6,541,205, each of which is herein incorporated by reference in its entirety. Another method for determining the quantity of target sequence initially present in a sample, but which is not based on a real-time amplification, is disclosed in U.S. Pat. No.5,710,029, herein incorporated by reference in its entirety. Amplification products may be detected in real-time through the use of various self- hybridizing probes, most of which have a stem-loop structure. Such self-hybridizing probes are labeled so that they emit different detectable signals, depending on whether the probes are in a self-hybridized state or an altered state through hybridization to a target sequence. By way of non-limiting example, “molecular torches” are a type of self-hybridizing probe that includes distinct regions of self-complementarity (referred to as “the target binding domain” and “the target closing domain”) which are connected by a joining region (e.g., non-nucleotide linker) and which hybridize to each other under predetermined hybridization assay conditions. In a preferred embodiment, molecular torches contain single-stranded base regions in the target binding domain that are from 1 to about 20 bases in length and are accessible for hybridization to a target sequence present in an amplification reaction under strand displacement conditions. Under strand displacement conditions, hybridization of the two complementary regions, which may be fully or partially complementary, of the molecular torch is favored, except in the presence of the target sequence, which will bind to the single-stranded region present in the target binding domain and displace all or a portion of the target closing domain. The target binding domain and the target closing domain of a molecular torch include a detectable label or a pair of interacting labels (e.g., luminescent / quencher) positioned so that a different signal is produced when the molecular torch is self-hybridized than when the molecular torch is hybridized to the target sequence, thereby permitting detection of probe:target duplexes in a test sample in the presence of unhybridized molecular torches. Molecular torches and a variety of types of interacting label pairs, including fluorescence resonance energy transfer (FRET) labels, are disclosed in, for example U.S. Pat. Nos.6,534,274 and 5,776,782, each of which is herein incorporated by reference in its entirety. Atty. Dkt. No.: INVEN-42177.601 The interaction between two molecules can also be detected, e.g., using fluorescence energy transfer (FRET) (see, for example, Lakowicz et al., U.S. Pat. No.5,631,169; Stavrianopoulos et al., U.S. Pat. No.4,968,103; each of which is herein incorporated by reference). A fluorophore label is selected such that a first donor molecule's emitted fluorescent energy will be absorbed by a fluorescent label on a second, 'acceptor' molecule, which in turn is able to fluoresce due to the absorbed energy. Alternately, the 'donor' protein molecule may simply utilize the natural fluorescent energy of tryptophan residues. Labels are chosen that emit different wavelengths of light, such that the 'acceptor' molecule label may be differentiated from that of the 'donor'. Since the efficiency of energy transfer between the labels is related to the distance separating the molecules, the spatial relationship between the molecules can be assessed. In a situation in which binding occurs between the molecules, the fluorescent emission of the 'acceptor' molecule label should be maximal. A FRET binding event can be conveniently measured through standard fluorometric detection means well known in the art (e.g., using a fluorimeter). Another example of a detection probe having self-complementarity is a “molecular beacon.” Molecular beacons include nucleic acid molecules having a target complementary sequence, an affinity pair (or nucleic acid arms) holding the probe in a closed conformation in the absence of a target sequence present in an amplification reaction, and a label pair that interacts when the probe is in a closed conformation. Hybridization of the target sequence and the target complementary sequence separates the members of the affinity pair, thereby shifting the probe to an open conformation. The shift to the open conformation is detectable due to reduced interaction of the label pair, which may be, for example, a fluorophore and a quencher (e.g., DABCYL and EDANS). Molecular beacons are disclosed, for example, in U.S. Pat. Nos. 5,925,517 and 6,150,097, herein incorporated by reference in its entirety. CTLA4 may be detected as proteins using a variety of protein techniques known to those of ordinary skill in the art, including but not limited to, protein sequencing and immunoassays. Illustrative non-limiting examples of protein sequencing techniques include, but are not limited to, mass spectrometry and Edman degradation. Mass spectrometry can, in principle, sequence any size protein but becomes computationally more difficult as size increases. A protein is digested by an endoprotease, and the resulting solution is passed through a high-pressure liquid chromatography column. At the end of this column, the solution is sprayed out of a narrow nozzle charged to a high positive potential into the mass spectrometer. The charge on the droplets causes them to fragment until only single ions remain. The peptides are then fragmented and the mass-charge ratios of the Atty. Dkt. No.: INVEN-42177.601 fragments measured. The mass spectrum is analyzed by computer and often compared against a database of previously sequenced proteins in order to determine the sequences of the fragments. The process is then repeated with a different digestion enzyme, and the overlaps in sequences are used to construct a sequence for the protein. In the Edman degradation reaction, the peptide to be sequenced is adsorbed onto a solid surface (e.g., a glass fiber coated with polybrene). The Edman reagent, phenylisothiocyanate (PTC), is added to the adsorbed peptide, together with a mildly basic buffer solution of 12% trimethylamine and reacts with the amine group of the N-terminal amino acid. The terminal amino acid derivative can then be selectively detached by the addition of anhydrous acid. The derivative isomerizes to give a substituted phenylthiohydantoin, which can be washed off and identified by chromatography, and the cycle can be repeated. The efficiency of each step is about 98%, which allows about 50 amino acids to be reliably determined. Illustrative non-limiting examples of immunoassays include, but are not limited to: immunoprecipitation; Western blot; ELISA; immunohistochemistry; immunocytochemistry; flow cytometry; and immuno-PCR. Polyclonal or monoclonal antibodies detectably labeled using various techniques known to those of ordinary skill in the art (e.g., colorimetric, fluorescent, chemiluminescent or radioactive) are suitable for use in immunoassays. Immunoprecipitation is the technique of precipitating an antigen out of solution using an antibody specific to that antigen. The process can be used to identify protein complexes present in cell extracts by targeting a protein believed to be in the complex. The complexes are brought out of solution by insoluble antibody-binding proteins isolated initially from bacteria, such as Protein A and Protein G. The antibodies can also be coupled to sepharose beads that can easily be isolated out of solution. After washing, the precipitate can be analyzed using mass spectrometry, Western blotting, or any number of other methods for identifying constituents in the complex. A Western blot, or immunoblot, is a method to detect protein in a given sample of tissue homogenate or extract. It uses gel electrophoresis to separate denatured proteins by mass. The proteins are then transferred out of the gel and onto a membrane, typically polyvinyldiflroride or nitrocellulose, where they are probed using antibodies specific to the protein of interest. As a result, researchers can examine the amount of protein in a given sample and compare levels between several groups. An ELISA, short for Enzyme-Linked ImmunoSorbent Assay, is a biochemical technique to detect the presence of an antibody or an antigen in a sample. It utilizes a minimum of two antibodies, one of which is specific to the antigen and the other of which is coupled to an Atty. Dkt. No.: INVEN-42177.601 enzyme. The second antibody will cause a chromogenic or fluorogenic substrate to produce a signal. Variations of ELISA include sandwich ELISA, competitive ELISA, and ELISPOT. Because the ELISA can be performed to evaluate either the presence of antigen or the presence of antibody in a sample, it is a useful tool both for determining serum antibody concentrations and also for detecting the presence of antigen. Immunohistochemistry and immunocytochemistry refer to the process of localizing proteins in a tissue section or cell, respectively, via the principle of antigens in tissue or cells binding to their respective antibodies. Visualization is enabled by tagging the antibody with color producing or fluorescent tags. Typical examples of color tags include, but are not limited to, horseradish peroxidase and alkaline phosphatase. Typical examples of fluorophore tags include, but are not limited to, fluorescein isothiocyanate (FITC) or phycoerythrin (PE). Flow cytometry is a technique for counting, examining and sorting microscopic particles suspended in a stream of fluid. It allows simultaneous multiparametric analysis of the physical and / or chemical characteristics of single cells flowing through an optical / electronic detection apparatus. A beam of light (e.g., a laser) of a single frequency or color is directed onto a hydrodynamically focused stream of fluid. A number of detectors are aimed at the point where the stream passes through the light beam; one in line with the light beam (Forward Scatter or FSC) and several perpendicular to it (Side Scatter (SSC) and one or more fluorescent detectors). Each suspended particle passing through the beam scatters the light in some way, and fluorescent chemicals in the particle may be excited into emitting light at a lower frequency than the light source. The combination of scattered and fluorescent light is picked up by the detectors, and by analyzing fluctuations in brightness at each detector, one for each fluorescent emission peak, it is possible to deduce various facts about the physical and chemical structure of each individual particle. FSC correlates with the cell volume and SSC correlates with the density or inner complexity of the particle (e.g., shape of the nucleus, the amount and type of cytoplasmic granules or the membrane roughness). Immuno-polymerase chain reaction (IPCR) utilizes nucleic acid amplification techniques to increase signal generation in antibody-based immunoassays. Because no protein equivalence of PCR exists, that is, proteins cannot be replicated in the same manner that nucleic acid is replicated during PCR, the only way to increase detection sensitivity is by signal amplification. The target proteins are bound to antibodies which are directly or indirectly conjugated to oligonucleotides. Unbound antibodies are washed away and the remaining bound antibodies have their oligonucleotides amplified. Protein detection occurs via detection of amplified oligonucleotides using standard nucleic acid detection methods, including real-time methods. Atty. Dkt. No.: INVEN-42177.601 Embodiments of the present invention further provide kits and systems comprising reagents for detection of the recited markers (e.g., primer, probes, etc.). In some embodiments, kits and systems comprise computer systems for analyzing marker levels and providing diagnoses, prognoses, or determining treatment courses of action. In some embodiments, a computer-based analysis program is used to translate the raw data generated by the detection assay (e.g., levels of CTLA4) into data of predictive value for a clinician. The clinician can access the predictive data using any suitable means. Thus, in some preferred embodiments, the present invention provides the further benefit that the clinician, who is not likely to be trained in genetics or molecular biology, need not understand the raw data. The data is presented directly to the clinician in its most useful form. The clinician is then able to immediately utilize the information in order to optimize the care of the subject. The present invention contemplates any method capable of receiving, processing, and transmitting the information to and from laboratories conducting the assays, information provides, medical personal, and subjects. For example, in some embodiments of the present invention, a sample (e.g., a biopsy or a serum) is obtained from a subject and submitted to a profiling service (e.g., clinical lab at a medical facility, genomic profiling business, etc.), located in any part of the world (e.g., in a country different than the country where the subject resides or where the information is ultimately used) to generate raw data. Where the sample comprises a tissue or other biological sample, the subject may visit a medical center to have the sample obtained and sent to the profiling center. Where the sample comprises previously determined biological information, the information may be directly sent to the profiling service by the subject (e.g., an information card containing the information may be scanned by a computer and the data transmitted to a computer of the profiling center using an electronic communication system). Once received by the profiling service, the sample is processed and a profile is produced (i.e., marker levels) specific for the diagnostic or prognostic information desired for the subject. The profile data is then prepared in a format suitable for interpretation by a treating clinician. For example, rather than providing raw data, the prepared format may represent a diagnosis or risk assessment (e.g., level of CTLA4) for the subject, along with recommendations for particular treatment options. The data may be displayed to the clinician by any suitable method. For example, in some embodiments, the profiling service generates a report that can be printed for the clinician (e.g., at the point of care) or displayed to the clinician on a computer monitor. Atty. Dkt. No.: INVEN-42177.601 In some embodiments, the information is first analyzed at the point of care or at a regional facility. The raw data is then sent to a central processing facility for further analysis and / or to convert the raw data to information useful for a clinician or patient. The central processing facility provides the advantage of privacy (all data is stored in a central facility with uniform security protocols), speed, and uniformity of data analysis. The central processing facility can then control the fate of the data following treatment of the subject. For example, using an electronic communication system, the central facility can provide data to the clinician, the subject, or researchers. In some embodiments, the subject is able to directly access the data using the electronic communication system. The subject may choose further intervention or counseling based on the results. In some embodiments, the data is used for research. For example, the data may be used to further optimize the inclusion or elimination of markers as useful indicators of a particular condition or stage of disease or as a companion diagnostic to determine a treatment course of action. The compositions, kits, systems, uses, and methods described herein find use in the stratification, diagnosis and prognosis of breast cancer, as well as in determining a treatment course of action for a subject diagnosed with breast cancer. For example, in some embodiments, compositions and method described herein are used to provide a prognosis or stratify patients into groups associated with one or more of risk of breast cancer recurrence, risk of risk cancer metastasis, and / or risk of breast cancer-specific death. In some embodiments, such prognoses, along with CTLA4 levels, are used to determine a treatment course of action in a subject diagnosed with breast cancer (e.g., use of adjuvant chemotherapy or elimination of adjuvant chemotherapy). In some embodiments, CTLA4 levels (e.g., in a breast cancer biopsy, blood sample, or bone marrow sample) are tested one or more times before, during, or after breast cancer treatment. In some embodiments, marker levels are used to alter a breast cancer treatment course of action (e.g., stop, start, or change a treatment). In some preferred embodiments, subjects with a decreased level of CTLA4 expression are stratified into a high risk group identified as being at an increased risk for a poor prognosis (e.g., recurrence, metastasis, or death). In such embodiments, subjects are typically offered adjuvant chemotherapy. In contrast, individuals with an increased level of CTLA4 are stratified into a low risk group and are at a decreased risk of a poor prognosis and are offered the option to forego adjuvant chemotherapy. Atty. Dkt. No.: INVEN-42177.601 The present disclosure is not limited to a particular increased level of expression of CTLA4. For example, in certain cases, the increased level is at the 50thpercentile or higher (e.g., at the 55th, 60th, 63rd, or high percentile of expression). The present invention is not limited to the use of any particular adjuvant chemotherapeutic agent. Suitable chemotherapeutic agents include, but are not limited to, epirubicin, doxorubicin, paclitaxel, docetaxel, cyclophosphamide, carboplatin, capecitabine, olaparib, pembrolizumab, cabazitaxel, mitoxantrone, and estramustine. In some embodiments, the present invention provides kits for use in detecting the level of expression of CTLA4. Such kits can be used, for example, to provide a prognosis or treatment to a subject. In some embodiments, the kits of the present invention include one or more detection reagents (e.g., nucleic acid primers or probes, or antibodies), and a carrier means, such as a box, a bag, a satchel, plastic carton (such as molded plastic or other clear packaging), wrapper (such as, a sealed or sealable plastic, paper, or metallic wrapper), or other container. In some examples, kit components will be enclosed in a single packaging unit, such as a box or other container, which packaging unit may have compartments into which one or more components of the kit can be placed. In other examples, a kit includes one or more containers, for instance vials, tubes, and the like that can retain, for example, one or more biological samples to be tested, positive and / or negative control samples or solutions (such as, a positive control serum containing analyte), diluents (such as, phosphate buffers, or saline buffers), detector reagents (e.g., for external application to a kit device), substrate reagents for visualization of detector reagent enzymes (such as, 5-bromo-4-chloro-3- indolyl phosphate, nitroblue tetrazolium in dimethyl formamide), and / or wash solutions (such as, Tris buffers, saline buffer, or distilled water). EXPERIMENTAL The following examples are provided in order to demonstrate and further illustrate certain preferred embodiments and aspects of the present invention and are not to be construed as limiting the scope thereof. Example 1 Materials and methods Ethical approval and the Oslo1 cohort The present study was approved by the Regional Committee for Medical Research Ethics South-East Norway (EC ID: 2015 / 2453). Informed, written consent was obtained from all Atty. Dkt. No.: INVEN-42177.601 patients in the Oslo1 cohort. Formalin-fixed, paraffin-embedded (FFPE) biopsies from primary tumors were collected in a research biobank. Clinical and histopathological variables and data on disease relapse status were obtained from hospital records, with the last update completed in 2005. Survival status and cause of death were obtained from hospital records and the Norwegian Institute of Public Health’s Cause of Death Registry. Survival follow-up was completed on Dec 31, 2014. PAM50 intrinsic subtypes were determined for tumor samples from 666 patients, using the nCounter Analysis System and the Prosigna® algorithm (NanoString Technologies, Seattle, WA, US), as previously described and reported (33). Validation data sets Gene expression data (Illumina RNAseq) from primary tumors of patients with early- stage breast cancer included in the SCAN-B study51 was downloaded from the Gene Expression Omnibus (National Center for Biotechnology Information, series GSE96058, accession date April 12, 2022). Clinicopathological data for the SCAN-B follow-up cohort were obtained from Staaf et al 2022 (52). This data set contains two different classifications of intrinsic tumor subtypes. One corresponds to the original PAM50 schema, whereas the other omits the normal- like centroid when assigning subtype. We performed patient selection based on the latter classification, as it corresponds better to the Prosigna assay used in the Oslo1 data set. The METABRIC data set contains tumor gene expression (Illumina HT-12 v3) and clinicopathological data for 1971 breast cancer patients. We obtained clinicopathological data from Curtis et al 2012 (38), while gene expression data was obtained using R package MetaGxBreast (version 1.12.0, accession date October 7, 2021). RNA expression analysis from FFPE biopsies H&E stained slides from primary tumors from the Oslo1 study were examined by a pathologist in order to identify areas with mainly tumor tissue. RNA was purified from 1-55-µm slides per tumor using the Roche® High Pure FFPET RNA Isolation Kit, in order to obtain a minimum of 100 ng of RNA from each sample. The RNA expression levels of 760 immune- related genes were analyzed using the PanCancer Immune Profiling Panel on the nCounter platform. This assay covers 730 genes related to immune cells, immune checkpoints, and other components of the adaptive and innate immune response. The analysis kits also included 30 custom genes. RNA expression data was obtained from the 69 of the 71 patients with basal-like disease (Fig 1 a). Samples were run on one of two different panels with some difference in the selection of custom genes. Only the genes present in both panels were included in the analysis, Atty. Dkt. No.: INVEN-42177.601 resulting in a data set with 753 genes. Expression values (counts) were normalized based on 40 housekeeping genes predefined by the manufacturer. Analysis of H&E slides The presence and prevalence of TIL, TLS and germinal centers were evaluated on H&E stained FFPE slides from surgical specimens of whole tumors. Quantification of TILs was done by two experienced breast cancer pathologists, according to the 2014 recommendations of the International TILs Working Group 2014. TLS were defined as aggregates of lymphocytes just outside the tumor-normal tissue border and scored on a scale from 0 to 3. Germinal centers were defined as areas of larger lymphoid cells within the TLS and were scored as absent (0) or present (1). Statistical analysis All statistical analyses were done using R software (version 4.2.2). Potentially prognostic genes were identified using the Oslo1 data set as a training set. Genes were filtered by expression level and variance using R package genefilter (version 1.80.3), using a filter requiring that at least 50% of samples have a normalized count > 15 (the upper limit of the 95% CI of the mean signal in negative controls) and a coefficient of variance for gene expression across samples of at least 0.6. After filtering, the expression values were log2 transformed and the expression values of each gene were scaled to a mean of 0 and a standard deviation of 1 (Z transformation). The Wilcoxon rank-sum test was used in differential expression analyses. Feature selection by the lasso method 35 was done using R package glmnet (version 4.1-6). Lasso was applied to a Cox regression model with the scaled expression levels of the 299 filtered genes as independent variables and DSS as the dependent variable, and to a binomial regression model with the binary outcome of cancer-related death. Survival variables were computed and compared between groups using the Kaplan-Meier estimator in R packages survival (version 3.5-0) and survminer (version 0.4.9). Median follow-up times were estimated using the reverse Kaplan-Meier method, which uses censoring as the event. P values for difference in survival between groups were obtained using the log-rank method. The multivariable regression model was created using the Cox proportional hazards model. Intrinsic subtype classification in the METABRIC data set was done by the method described by Lien et al. (53), modified by omitting the normal-like centroid, in order to get classifications equivalent to the Prosigna assay. ROC analyses were done using R package pROC (version 1.18.0).54 Box plots and scatter plots were made using R package ggplot2 (version 3.4.0). Atty. Dkt. No.: INVEN-42177.601 Results Patient selection and characteristics The Oslo Micrometastasis Project (the Oslo1 study) has been described previously (33, 34). In this observational study, 920 patients with early-stage breast cancer were enrolled between 1995 and 1998 and treated according to national recommendations. The intrinsic subtypes (PAM50) for tumor samples have been determined from 666 patients (33). Samples from 71 patients were classified as basal-like. Using the nCounter PanCancer Immune Profiling Panel, the expression of 7605 immune-related genes was assessed in 69 of these samples. The 45 samples from patients without lymph node metastases were selected for the current study (Fig. 1a). The median follow-up time for this cohort was 7.4 years for progression-free survival (PFS) and 17.7 years for overall survival (OS). Patient clinicopathological features are summarized in Table 1. Identification and selection of prognostic genes Immune-related genes expressed in <50% of samples or with low variance across samples were removed, resulting in a set of 299 genes. Differential expression analysis identified 13 genes significantly associated with systemic disease recurrence, with a cutoff for significance at P < 0.05 without correction for multiple testing. For each of these genes, the expression was higher in the group with no systemic recurrence (Fig.2). The lowest P value was found for Cytotoxic T-lymphocyte-associated protein 4 (CTLA4; P = 0.018). To investigate whether any of these genes could identify a sizable proportion of patients with a favorable prognosis, the disease-specific survival (DSS) was compared in patients dichotomized by the median expression value for each gene. The DSS was significantly better in the high-expression group for 9 of the 13 genes (Fig.3). It is worth noting that there was a high degree of correlation between the expression levels of these genes, as shown in Fig.10. The best DSS in the high-expression group and the highest level of significance were found for CTLA4 and for granzyme B (GZMB), which plays an important role in T and NK cell cytotoxicity. For both genes, the 10-year DSS was 95.5% (95% CI 87.1% - 100%) in the high expression groups versus 54.5% (95% CI 37.2% - 79.9%) in the low expression groups (P = 0.00079). As an alternate feature selection method, Cox regression was performed for DSS with the expression values of the 299 filtered immune genes as predictor variables penalized by the lasso method (35). This analysis identified high CTLA4 expression as the only predictor for DSS. Lasso penalization was applied to a binomial regression model with the 299 gene expression values as independent variables and breast cancer-related death as the dependent variable. This Atty. Dkt. No.: INVEN-42177.601 analysis also resulted in a model with CTLA4 expression as the only predictor. As the differential expression analysis and the two lasso regression approaches all indicated a correlation between CTLA4 expression and DSS, the prognostic value of CTLA4 was investigated. Performing multivariable Cox regression analysis, CTLA4 was the only significant predictor for DSS after the inclusion of age at diagnosis, tumor size, tumor grade, and estrogen receptor expression in the model (P = 0.011; Table 2). Defining a cutoff value for CTLA4 expression In order to define a suitable cutoff value for CTLA4 expression, a ROC analysis was performed with breast cancer-related death as the dependent variable and CTLA4 expression as the independent variable. The highest unweighted Youden index was found at a threshold value corresponding to the 43rd percentile of CTLA4 expression, with a sensitivity of 91.7% and a specificity of 75.8% (Fig 10). The unweighted Youden index gives equal weight to false positive and false negative values. As misclassifying a high-risk patient as low-risk can have serious consequences, the analysis was repeated using the weighted Youden index. This method takes into account the cost of a false negative classification compared to a false positive classification. Setting the relative cost to 3 resulted in a cutoff corresponding to the 63rd percentile of CTLA4 expression, with a sensitivity of 100% and a specificity of 51.5% for breast-cancer specific death. Figure 4 shows overall survival, recurrence-free interval, and disease-specific survival in patients with CTLA4 expression above and below the 63rd percentile. None of the patients in the CTLA4high group suffered disease recurrence within the follow-up period. Validation in other cohorts The results from the Oslo1 cohort indicated that a high CTLA4 gene expression in tumor was associated with excellent prognosis for patients with lymph node-negative basal-like breast cancer. This correlation was validated in other, unrelated patient cohorts. Based on the ROC analysis performed in the Oslo1 training set, a threshold for high CTLA4 expression corresponding to the 63rd percentile was chosen. SCAN-B The Sweden Cancerome Analysis Network - Breast (SCAN-B) study is an ongoing prospective population-based study which has enrolled more than 19,000 breast cancer patients since 2010 (36, 37). Patients receive treatment according to national and regional guidelines. The patients that fulfilled the inclusion criteria were selected as a validation cohort for the current Atty. Dkt. No.: INVEN-42177.601 study (Fig.1b). Patient characteristics are summarized in Table 1. The median follow-up time was 8.9 years for OS and 6.8 years for recurrence-free interval (RFI).5-year OS, RFI, and distant recurrence-free interval (DRFI) was compared in patients with high versus low expression of CTLA4, with a cutoff at the 63rd percentile (Fig.5 a-c). All three outcomes were significantly better in the high expression group. Only two cases of distant recurrence were recorded in the 93 patients in the high-expression group. Five years after diagnosis, 97.2% had no distant recurrence (95% CI 93.5% – 100%) and five-year OS was 93.0% (95% CI 87.8% - 98.6%). Of the six patients in the CTLA4high group that died within five years of diagnosis, three were censored for disease recurrence at the time of death, indicating that a maximum of three of these 93 patients died from breast cancer. To evaluate whether the 63rd percentile cutoff was the best fit for the SCAN-B cohort, the ROC analysis was repeated in the SCAN-B dataset, with distant recurrence as the dependent variable. The weighted Youden index was highest at a threshold corresponding to the 60th percentile (Fig.12). Survival and recurrence outcomes above and below this cutoff in SCAN-B is shown in Figure 5 d-f. The effect of using the 60th percentile of CTLA4 expression to stratify the Oslo1 cohort was assessed, as shown in Figure 13. METABRIC: The METABRIC (Molecular Taxonomy of Breast Cancer International Consortium) dataset includes genomic and transcriptomic analyses of approximately 2000 clinically annotated primary breast cancer specimens from tumor banks in the UK and Canada (38). The 155 samples that fulfilled the inclusion criteria for the current study were included as a validation cohort (Fig.1c). Patient characteristics are summarized in Table 1. The median follow- up time for this cohort was 11.9 years for OS and 10.1 years for DSS. With an expression cutoff for CTLA4 at the 63rd percentile, significantly better 5-year OS and DSS in the CTLA4high group than in the CTLA4low group (Fig.6 a-b) was found. Five-year DSS in the CTLA4high group was 92.5% (95% CI 85.8% - 99.9%) and five-year OS was 90.9 % (95% CI 83.5% - 98.8%). Survival outcomes stratified by the 60th percentile cutoff derived from ROC analysis in the SCAN-B cohort are shown in Fig.6 c-d. The five-year DSS was 93.2% (95% CI 86.9% - 99.9%) in the CTLA4high group, as defined by the 60th percentile. Prognostic value of CTLA4 expression in the absence of adjuvant chemotherapy If the prognostic value of CTLA4 expression is to be used for de-escalation of adjuvant therapy, it is important to exclude that high expression merely predicts favorable chemotherapy responses. Separate survival analyses was performed for patients treated with and without chemotherapy. The proportion of patients receiving chemotherapy in the three studies is shown in Table 1. In all three cohorts, the clinical outcome was better for the CTLA4high group, Atty. Dkt. No.: INVEN-42177.601 regardless of whether patients received chemotherapy or not. The difference was significant (P < 0.05) in Oslo1 and SCAN-B for patients treated with chemotherapy and in METABRIC for those without (Fig.7). For CTLA4high patients who did not receive chemotherapy, 5-year DSS was 100% in Oslo1 and 91.8% (95% CI 84.4% - 99.8%) in METABRIC, while DRFI in SCAN-B was 91.7% (95% CI 77.3% - 100%). For CTLA4high patients who did receive chemotherapy, 5- year DSS was 100% in Oslo1 and METABRIC, while DRFI in SCAN-B was 98.3% (95% CI 95.1% - 100%). Correlation between CTLA4 expression and known prognostic factors The distribution of known prognostic factors in the CTLA4 low / high groups is shown in Table 3. The CTLA4high group had a significantly higher proportion of patients with grade III tumors. There were no significant differences in age, tumor size or receptor status between the groups. Correlation between CTLA4 expression and other measures of tumor inflammation The correlation between CTLA4 expression and other markers of tumor inflammation was compared. Quantification of stromal tumor-infiltrating lymphocytes (TIL) was performed according to international guidelines (20) on hematoxylin and eosin (H&E) stained slides from the 44 Oslo1 patients for whom biopsies were available for evaluation. While a significant correlation was found between CTLA4 expression and TIL, a considerable proportion of the tumors with high CTLA4 expression had low TIL scores (Fig.8a). None of these CTLA4high / TILlow patients died from breast cancer. In line with the findings of Loi and colleagues (24, 39), only one of the 14 patients with TIL ≥ 30% died from breast cancer (5-year DSS 93% vs 76% with TIL < 30%, P = .064). Two patients had TIL scores ≥75%, the prognostic cutoff supported by de Jong et al. (22). These patients were both in the CTLA4high group and none of them had disease recurrence or died from breast cancer during the follow-up period. The prevalence of tertiary lymphoid structures (TLS) and germinal centers on the same H&E slides was evaluated. As shown in Fig 8 b-c, CTLA4 expression levels were higher in tumors with a higher prevalence of TLS, while no significant difference was observed between tumors with and without germinal centers. Finally, CTLA4 expression was compared with each of the signatures provided by NanoString based on gene expression data from the PanCancer Immune assay. As shown in Fig.14, a broad range of immune-related signatures were significantly higher in the CTLA4high group, including B and T cell, cytotoxicity, inflammatory Atty. Dkt. No.: INVEN-42177.601 chemokine, interferon gamma, immune checkpoint, and tumor inflammation signatures40. None of these signatures included CTLA4 expression. Triple-negative breast cancer To investigate whether the findings could be extended to TNBC in general, outcomes of with high and low CTLA4 expression for patients with lymph node-negative TNBC as defined by IHC, regardless of molecular subtype were compared. This analysis was performed in Oslo1 and SCAN-B, whereas IHC data were not available for the METABRIC cohort. The cutoff for high CTLA4 gene expression was kept at the 63rd percentile for basal-like samples in each cohort. As shown in Figure 9, outcomes were numerically favorable for patients with high CTLA4 expression in both cohorts. In the Oslo1 CTLA4high group, 85.7% (95% CI 69.2% - 100%) were recurrence-free after five years, while 5-year DSS was 92.9% (80.3% - 100%).9 In SCAN-B, 98.2% (95% CI 94.6% - 100%) had no distant recurrences after five years, and five- year OS was 94.0% (95% CI 88.5% - 99.9%). The improved outcomes with high CTLA4 were not statistically significant in Oslo1. In SCAN-B, OS, RFI and DRFI were all significantly better for TNBC patients with a high CTLA4 expression. Outcomes stratified by the 60th percentile cutoff are shown in Fig.15.

[0002] Atty. Dkt. No.: INVEN-42177.601 Table 1 | Patient characteristics Distribution of clinical and histopathological variables in the three patient cohorts studied. *Receptor subtypes could not be determined for METABRIC, as progesterone receptor status was not assessed. ER: pos 32 (21%), neg 119 (77%), missing 4 (3%) HER2: pos 10 (6%), neg 57 (37%), missing 88 (57%) HR, Hormone receptor; HER2, human epidermal growth factor receptor. Atty. Dkt. No.: INVEN-42177.601 Table 2 | Multivariable Cox regression Cox regression with disease-specific survival as the dependent variable and CTLA4 expression, age at diagnosis, tumor size, tumor grade and ER status (≥10% positive cells by IHC) as the independent variables. Scaled CTLA4 expression, age (years) and tumor size (cm) were included as continuous variables and TIL as a continuous variable in 10% increments, while tumor grade (grade I-II vs III) and ER status (positive vs negative) were included as categorical variables. CTLA4, cytotoxic T-lymphocyte-associated protein 4; ER, estrogen receptor; IHC, immunohistochemistry; TIL, tumor-infiltrating lymphocytes.

[0003] Atty. Dkt. No.: INVEN-42177.601 Table 3 | Distribution of other risk factors with high and low CTLA4 basal-like BC. High CTLA4 is defined as above the 66th percentile. P values are calculated by Wilcoxon’s rank sum test for continuous variables and by the chi square test for categorical variables. All patients from the Oslo1, SCAN-B, and METABRIC cohorts with available data for each variable were included in the table. References 1. Sung, H., et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin 71, 209-249 (2021). 2. Deluche, E., et al. Contemporary outcomes of metastatic breast cancer among 22,000 women from the multicentre ESME cohort 2008-2016. Eur J Cancer 129, 60-70 (2020). 3. Robson, M.E., et al. 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The tale of TILs in breast cancer: A report from The International Immuno-Oncology Biomarker Working Group. NPJ Breast Cancer 7, 150 (2021). 14. Denkert, C., et al. Tumor-associated lymphocytes as an independent predictor of response to neoadjuvant chemotherapy in breast cancer. J Clin Oncol 28, 105-113 (2010). 15. Adams, S., et al. Prognostic value of tumor-infiltrating lymphocytes in triple-negative breast cancers from two phase III randomized adjuvant breast cancer trials: ECOG 2197 and ECOG 1199. J Clin Oncol 32, 2959-2966 (2014). 16. Park, J.H., et al. Prognostic value of tumor-infiltrating lymphocytes in patients with early- stage triple-negative breast cancers (TNBC) who did not receive adjuvant chemotherapy. Ann Oncol 30, 1941-1949 (2019). 17. Sistrunk, W.E. & Maccarty, W.C. Life Expectancy Following Radical Amputation for Carcinoma of the Breast: A Clinical and Pathological Study of 2018 Cases. Ann Surg 75, 61-69 (1922). 18. Stanton, S.E., Adams, S. & Disis, M.L. Variation in the Incidence and Magnitude of Tumor- Infiltrating Lymphocytes in Breast Cancer Subtypes: A Systematic Review. JAMA Oncology 2, 1354-1360 (2016). 19. Denkert, C., et al. Tumour-infiltrating lymphocytes and prognosis in different subtypes of breast cancer: a pooled analysis of 3771 patients treated with neoadjuvant therapy. Lancet Oncol 19, 40-50 (2018). 20. Salgado, R., et al. The evaluation of tumor-infiltrating lymphocytes (TILs) in breast cancer: recommendations by an International TILs Working Group 2014. Ann Oncol 26, 259-271 (2015). 21. Denkert, C., et al. Standardized evaluation of tumor-infiltrating lymphocytes in breast cancer: results of the ring studies of the international immuno-oncology biomarker working group. Modern Pathology 29, 1155-1164 (2016). 22. de Jong, V.M.T., et al. Prognostic Value of Stromal Tumor-Infiltrating Lymphocytes in Young, Node-Negative, Triple-Negative Breast Cancer Patients Who Did Not Receive (neo)Adjuvant Systemic Therapy. J Clin Oncol 40, 2361-2374 (2022). 23. Van Bockstal, M.R., et al. Interobserver variability in the assessment of stromal tumor- infiltrating lymphocytes (sTILs) in triple-negative invasive breast carcinoma influences the association with pathological complete response: the IVITA study. Mod Pathol 34, 2130-2140 (2021). Atty. Dkt. No.: INVEN-42177.601 24. Loi, S., et al. Tumor-Infiltrating Lymphocytes and Prognosis: A Pooled Individual Patient Analysis of Early-Stage Triple-Negative Breast Cancers. J Clin Oncol 37, 559-569 (2019). 25. Burstein, H.J., et al. Estimating the benefits of therapy for early-stage breast cancer: the St. Gallen International Consensus Guidelines for the primary therapy of early breast cancer 2019. Ann Oncol 30, 1541-1557 (2019). 26. Perou, C.M., et al. Molecular portraits of human breast tumours. Nature 406, 747-752 (2000). 27. Sorlie, T., et al. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci U S A 98, 10869-10874 (2001). 28. Prat, A., et al. Clinical implications of the intrinsic molecular subtypes of breast cancer. Breast 24 Suppl 2, S26-35 (2015). 29. Prat, A., et al. Response and survival of breast cancer intrinsic subtypes following multi- agent neoadjuvant chemotherapy. BMC Med 13, 303 (2015). 30. Parker, J.S., et al. Supervised risk predictor of breast cancer based on intrinsic subtypes. J Clin Oncol 27, 1160-1167 (2009). 31. Prat, A., et al. Molecular characterization of basal-like and non-basal-like triple-negative breast cancer. Oncologist 18, 123-133 (2013). 32. Prat, A., et al. Correlative Biomarker Analysis of Intrinsic Subtypes and Efficacy Across the MONALEESA Phase III Studies. Journal of Clinical Oncology 39, 1458-1467 (2021). 33. Ohnstad, H.O., et al. Prognostic value of PAM50 and risk of recurrence score in patients with early-stage breast cancer with long-term follow-up. Breast Cancer Res 19, 120 (2017). 34. Wiedswang, G., et al. Detection of isolated tumor cells in bone marrow is an independent prognostic factor in breast cancer. J Clin Oncol 21, 3469-3478 (2003). 35. Tibshirani, R. Regression Shrinkage and Selection via the Lasso. Journal of the Royal Statistical Society. Series B (Methodological) 58, 267-288 (1996). 36. Saal, L.H., et al. The Sweden Cancerome Analysis Network - Breast (SCAN-B) Initiative: a largescale multicenter infrastructure towards implementation of breast cancer genomic analyses in the clinical routine. Genome Med 7, 20 (2015). 37. Lund University. Sweden Cancerome Analysis Network - Breast. 38. Curtis, C., et al. The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups. Nature 486, 346-352 (2012). 39. Loi, S., et al. Tumor infiltrating lymphocyte stratification of prognostic staging of early-stage triple negative breast cancer. npj Breast Cancer 8(2022). 40. Ayers, M., et al. IFN-γ–related mRNA profile predicts clinical response to PD-1 blockade. The Journal of Clinical Investigation 127, 2930-2940 (2017).18 Atty. Dkt. No.: INVEN-42177.601 41. Fang, J., et al. Prognostic value of immune checkpoint molecules in breast cancer. Biosci Rep 40(2020). 42. Yuan, Y. Modelling the spatial heterogeneity and molecular correlates of lymphocytic infiltration in triple-negative breast cancer. J R Soc Interface 12(2015). 43. Denkert, C., et al. Tumor-Infiltrating Lymphocytes and Response to Neoadjuvant Chemotherapy With or Without Carboplatin in Human Epidermal Growth Factor Receptor 2– Positive and Triple- Negative Primary Breast Cancers. Journal of Clinical Oncology 33, 983-991 (2015). 44. Carey, L.A. De-escalating and escalating systemic therapy in triple negative breast cancer. The Breast 34, S112-S115 (2017). 45. Vaz-Luis, I., et al. Outcomes by Tumor Subtype and Treatment Pattern in Women With Small, Node-Negative Breast Cancer: A Multi-Institutional Study. Journal of Clinical Oncology 32, 2142- 2150 (2014). 46. de Nonneville, A., et al. Adjuvant chemotherapy in pT1ab node-negative triple-negative breast carcinomas: Results of a national multi-institutional retrospective study. Eur J Cancer 84, 34-43 (2017). 47. Jones, S., et al. Docetaxel With Cyclophosphamide Is Associated With an Overall Survival Benefit Compared With Doxorubicin and Cyclophosphamide: 7-Year Follow-Up of US Oncology Research Trial 9735. Journal of Clinical Oncology 27, 1177-1183 (2009). 48. Stein, R.C., et al. OPTIMA prelim: a randomised feasibility study of personalised care in the treatment of women with early breast cancer. Health Technol Assess 20, xxiii-xxix, 1-201 (2016). 49. Schmid, P., et al. Atezolizumab plus nab-paclitaxel as first-line treatment for unresectable, locally advanced or metastatic triple-negative breast cancer (IMpassion130): updated efficacy results from a randomised, double-blind, placebo-controlled, phase 3 trial. Lancet Oncol 21, 44- 59 (2020). 50. Modi, S., et al. Trastuzumab Deruxtecan in Previously Treated HER2-Low Advanced Breast Cancer. N Engl J Med 387, 9-20 (2022). 51. Brueffer, C., et al. Clinical Value of RNA Sequencing-Based Classifiers for Prediction of the Five Conventional Breast Cancer Biomarkers: A Report From the Population-Based Multicenter Sweden Cancerome Analysis Network-Breast Initiative. JCO Precis Oncol 2(2018). 52. Staaf, J., et al. RNA sequencing-based single sample predictors of molecular subtype and risk of recurrence for clinical assessment of early-stage breast cancer. NPJ Breast Cancer 8, 94 (2022). Atty. Dkt. No.: INVEN-42177.601 53. Lien, T.G., et al. Sample Preparation Approach Influences PAM50 Risk of Recurrence Score in Early Breast Cancer. Cancers (Basel) 13(2021). 54. Robin, X., et al. pROC: an open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinformatics 12, 77 (2011) All publications, patents, patent applications and accession numbers mentioned in the above specification are herein incorporated by reference in their entirety. Although the invention has been described in connection with specific embodiments, it should be understood that the invention as claimed should not be unduly limited to such specific embodiments. Indeed, various modifications and variations of the described compositions and methods of the invention will be apparent to those of ordinary skill in the art and are intended to be within the scope of the following claims.

Claims

Atty. Dkt. No.: INVEN-42177.601 CLAIMS We claim:

1. A method for providing a prognosis for a subject with breast cancer, or selecting a subject with breast cancer for treatment with a particular therapy, comprising: (a) detecting the level of expression of cytotoxic T-lymphocyte-associated protein 4 (CTLA4) in a sample from the subject; and (b) comparing the level of expression of the CTLA4 to a corresponding reference level of expression of the CTLA4, wherein an altered level of expression of the CTLA4 gene relative to the reference level provides an indication selected from the group consisting of an indication of breast cancer recurrence, an indication of survival of the subject, and an indication that the subject is a candidate for treatment with a particular therapy.

2. The method of claim 1, wherein an increased level of CTLA4 in the sample as compared to the reference level is indicative of an increased likelihood of survival and / or a decreased likelihood of recurrence of breast cancer in the subject.

3. The method of claim 1 or 2, further comprising stratifying said subject into an increased likelihood of survival group or a decreased likelihood of survival group.

4. The method of claim 3, wherein said stratifying is used to recommend treatment with a particular therapy.

5. The method of claim 4, wherein adjuvant chemotherapy is recommended to said decreased likelihood of survival group and adjuvant chemotherapy is not recommended to said increased likelihood of survival group.

6. The method of claim 4 or 5, further comprising administering adjuvant chemotherapy to said decreased likelihood of survival group.

7. The method of claim 1 or 2, further comprising stratifying said subject into an increased likelihood of breast cancer recurrence or a decreased likelihood of breast cancer recurrence group.Atty. Dkt. No.: INVEN-42177.601 8. The method of claim 7, wherein adjuvant chemotherapy is recommended to said increased likelihood of breast cancer recurrence group and adjuvant chemotherapy is not recommended to said decreased likelihood of breast cancer recurrence group.

9. The method of claim 7 or 8, further comprising administering adjuvant chemotherapy to said increased likelihood of breast cancer recurrence group.

10. The method of any one of the preceding claims, wherein an increased level of CTL4 in the sample is indicative of increased immune cell infiltration.

11. The method of claim 10, wherein said immune cell infiltration is tumor lymphocyte infiltration.

12. The method of any one of the previous claims, further comprising detecting the level of expression of one or more additional breast cancer marker genes.

13. A method for treating breast cancer, comprising: (a) detecting the level of expression CTLA4 in a sample from the subject; and (b) administering adjuvant chemotherapy to said subject when said level of CTLA4 is decreased relative to a control level and not administering adjuvant chemotherapy to said subject with said level of expression of CTLA4 is increased relative to a control level.

14. The method of any one of the previous claims, wherein said increased level of expression of CTLA4 is expression at the 60thpercentile or higher of breast cancer samples from a representative population of patients with early-stage basal-like breast cancer.

15. The method of any one of the previous claims, wherein said increased level of expression of CTLA4 is expression at the 63rdpercentile or higher of breast cancer samples from a representative population of patients with early-stage basal-like breast cancer.

16. The method of any one of the previous claims, wherein the sample is selected from the group consisting of breast tissue, bone marrow, blood, and serum.Atty. Dkt. No.: INVEN-42177.601 17. The method of claim 16, wherein the breast tissue is breast cancer biopsy tissue.

18. The method of claim 16, wherein the sample comprises a breast cancer cell.

19. The method of any one of the previous claims, the subject has undergone chemotherapy, surgery and / or radiotherapy.

20. The method of any one of the previous claims, wherein the detecting comprises the use of one or more nucleic acid reagents selected from the group consisting of nucleic acid primers and nucleic acid probes and one or more antibodies.

21. The method of claim 20, wherein the primers, probes, and / or antibodies comprise a detectable label.

22. The method of any one of the preceding claims, wherein said subject has basal-like breast cancer.

23. The method of claim 22, wherein said subject has triple-negative breast cancer.

24. Reagent that specifically detects an altered level of expression of CTLA4 in a sample from a subject for use in the determination of the likelihood of survival of the subject, likelihood of recurrence of breast cancer, stratifying said subject into high and low likelihood of recurrence of breast cancer groups, stratifying said subject into high and low likelihood of survival groups, and / or determining that the subject is a candidate for treatment with a particular therapy.

25. Adjuvant chemotherapeutic agent for use in treating a subject with breast cancer, wherein the subject has an altered level of expression of the CTLA4 gene relative to the reference level.

26. Use of claim 25, wherein the adjuvant chemotherapeutic agent is selected from the group consisting of epirubicin, doxorubicin, paclitaxel, docetaxel, cyclophosphamide, carboplatin, capecitabine, olaparib, pembrolizumab, cabazitaxel, mitoxantrone, and estramustine.

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