WO2016037009A1 - Biomarkers for triple-negative breast cancer - Google Patents

Abstract

Biomarkers useful in the therapy, diagnosis, analysis, and prognostication of triple-negative breast cancer are provided. The biomarkers show low expression in tumors that present a high risk of relapse. The biomarkers in question are CIITA, CD74, HLA-DPA1, HLA-DPB1, HLA-DPB2, HLA-DQA1, HLA-DRB1, HLA-DRB5, HLA-DRB6, CTSH, NCOA1, CD1E, FCGRT, KRT14, LPAR5, FGD3, VAMP2, LRRK2, MBNL1, NTRK3, POLR3GL, PTGDS, SH3BGRL, and TOX.

Description

BIOMARKERS FOR TRIPLE-NEGATIVE BREAST CANCER

BACKGROUND

A. FIELD OF THE DISCLOSURE

The present disclosure relates generally to the treatment, diagnosis, and prognosis of disease.

B. BACKGROUND

Triple negative breast cancer (TNBC) is a form of cancer in which tumors lack expression of estrogen receptor (ER-), progesterone receptor (PR-), or overexpression of HER2/Neu. TNBC has a lower survival rate than most breast cancers, and fewer treatment options.

TNBC tumors are known to behave aggressively and are not candidates for two normally effective forms of therapy: ER or HER2/Neu targeted therapy. Most TNBC patients receive adjuvant or neoadjuvant chemotherapy with or without local radiation treatment. Patient outcome is difficult to predict, with some patients having rapid relapses within two years of diagnosis, and a low relapse rate from years 5-10 (1 ). TNBC tumor types vary in their genetic makeup, with the majority categorized as basal-like (BL) subtype. In general, BL and non-BL subtypes share similar aggressive biology (2).

Over the last 15 years, there has been a major research effort directed at using genomic techniques to analyze the biology of breast cancer and to establish genomic signatures to assess prognosis (3). This has been most notably successful in ER+ breast cancer. Some of these genomic assays have received FDA approval and are used widely to assist therapy decision making in ER+ disease. Prognostic gene expression signatures are not as well developed for TNBC.

Tumor infiltrating lymphocyte (TIL) assessment determined by tumor morphology, immunohistology, and genomic methodologies have also had positive prognostic outcomes in TNBC (8- 10). Recently, a B cell genomic signature was derived from RNA-seq analysis of data from The Cancer Genome Atlas. It was prognostic in a large microarray data set and compared well with multiple other B cell and T cell TIL signatures (1 1 ). The conclusions from many of these TIL studies are that the patient's immune response has a positive effect on progression free survival (PFS), therapy response, and survival, especially in TNBC (12).

SUMMARY

It has been unexpectedly discovered that 24 specific genetic markers are highly predictive of the chance of relapse in patients with TNBC. The level of expression of the markers can be used in the treatment, prevention, and prognostication of TNBC (among other uses).

A method of prognosticating a risk of relapse of TNBC in a subject in need thereof is provided, comprising: (a) measuring a level of expression of each of a set of genes selected from Table 1 in a TNBC tumor from the subject, (b) comparing the level of expression of each of the set of genes to a "Biomarkers For Triple-Negative Breast Cancer" Attorney Docket No. 00H670-301084 corresponding benchmark value of expression of each of the set of genes, and (c) prognosticating an elevated risk of relapse if the level of expression of at least one of the set of genes is below the corresponding benchmark value.

A method of treatment or prophylaxis of a subject at risk of relapse of TNBC is provided, the method comprising: prognosticating the risk of relapse of TNBC in the subject by performing the method above; and providing therapeutic or prophylactic treatment for the TNBC to the subject based on whether the subject is prognosticated to have an elevated risk of relapse.

A kit for analyzing genetic expression of TNBC in a subject is provided, comprising: a means for measuring the expression of a first gene selected from Table 1 ; and means for detecting a second gene selected from Table 1.

This section presents a simplified summary in order to provide a basic understanding of some aspects of the claimed subject matter. This summary is not an extensive overview. It is not intended to identify key or critical elements or to delineate the scope of the claimed subject matter. Its sole purpose is to present some concepts in a simplified form as a prelude to the more detailed description that is presented later.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1. Consensus clustering of gene expression values across all genes identified 3 main groups of TNBC tumors. The heatmap shows the relative similarity of gene expression values in each sample compared to all other samples (darker hue indicates higher similarity). The dendogram at the top of the heatmap shows the pairwise similarity between samples and their assignment into three consensus clusters (Cluster 1 is the middle bar, Cluster 2 is the right bar, and Cluster 3 is the left bar).

FIG. 2. PFS for the three cluster groups.

FIG. 3. PFS for the three cluster groups, showing data from patients with lymph node tumor involvement (+) and those without (-).

FIG. 4. Heatmap of the normalized gene expression values of each of the 24 prognostic genes in each of the 47 patients' tumors. Patients who relapsed are grouped on the left, and patients who did not relapse are grouped on the right. Gene identifiers on the right include the common gene symbol followed by the unique gene identifier used by Ensembl.

FIG. 5. PFS curves for patients whose mean expression of the 24 gene signature was in the top two tertiles compared to the lower tertile (log-rank p-value of 0.00016 and hazard ratio of 0.24).

FIG. 6. The impact of high expression (above median) versus low expression (below median) of CIITA on PFS (log-rank p=0.0006; HR=0.21 ).

FIG. 7. The PFS effect high expression (above median) versus low expression (below median) of CD74 with log-rank p=0.0231 and HR=0.38. "Biomarkers For Triple-Negative Breast Cancer" Attorney Docket No. 00H670-301084

FIG. 8. The PFS curves derived from tertiles (high, intermediate, and low values) for CIITA. The solid line is the high fertile, the dashed line is the intermediate tertile, and the dashed and dotted line is the low tertile.

FIG. 9. The PFS curves derived from tertiles (high, intermediate, and low values) for CD74. The solid line is the high tertile, the dashed line is the intermediate tertile, and the dashed and dotted line is the low tertile.

FIG. 10. Immunohistochemistry (IHC) detection of CD74 and HLA-DPB1 protein expression in TNBC tumor tissue showing staining in 20% of invasive tumor cells. Localization is primarily membranous (90%) with some granular cytoplasmic staining (large image is 10x magnification, inset is 20x magnification).

FIG. 1 1. IHC detection of HLA-DPB1 protein in TNBC tumor tissue shows staining in 20% of invasive tumor cells. Localization is primarily membranous (90%) with some granular cytoplasmic staining (large image is 10x magnification, inset is 20x magnification).

FIG. 12. Kaplan-Meier PFS curves of patients based on mean expression levels of the TNBC prognostic genes in the public microarray data set, showing high expression (upper two tertiles) of the

10 gene signature (dashed) versus the lowest tertile (solid); log-rank p = 9E-07.

FIG. 13. Kaplan-Meier PFS curves of patients based on mean expression levels of the TNBC prognostic genes in the public microarray data set, showing high expression (upper two tertiles) of

CD74 (dashed) versus lowest tertile (solid); log-rank p = 1.9E-06.

DETAILED DESCRIPTION

A. DEFINITIONS

Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art of this disclosure. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the specification and should not be interpreted in an idealized or overly formal sense unless expressly so defined herein. Well known functions or constructions may not be described in detail for brevity or clarity.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.

With reference to the use of the word(s) "comprise" or "comprises" or "comprising" in the foregoing description and/or in the following claims, unless the context requires otherwise, those words are used on the basis and clear understanding that they are to be interpreted inclusively, rather than "Biomarkers For Triple-Negative Breast Cancer" Attorney Docket No. 00H670-301084 exclusively, and that each of those words is to be so interpreted in construing the foregoing description and/or the following claims.

The term "consisting essentially of means that, in addition to the recited elements, what is described or claimed may also contain other elements (steps, structures, ingredients, components, etc.) that do not adversely affect the operability of what is described or claimed for its intended purpose stated in this disclosure. Any additional element that would adversely affect operability for the intended purpose stated in this disclosure is excluded, regardless of whether such additional element would be desirable for some other purpose.

The terms "about" or "approximately" mean within a range of reasonable error around a central value. Such reasonable error may for example stem from the precision of an instrument or method used to measure the value. Specific examples of such limits of reasonable error are 20%, 10%, 5%, 2.5%, and 1 %. Unless specified otherwise, all numerical values may be approximate.

The terms "first", "second", and the like are used herein to describe various features or elements, but these features or elements should not be limited by these terms. These terms are only used to distinguish one feature or element from another feature or element. Thus, a first feature or element discussed below could be termed a second feature or element, and similarly, a second feature or element discussed below could be termed a first feature or element without departing from the teachings of the present disclosure.

The terms "prevention", "prevent", "preventing", "prophylaxis", "suppression", "suppress" and "suppressing" as used herein refer to a course of action initiated prior to the onset of a clinical manifestation of a disease state or condition so as to reduce such clinical manifestation of the disease state or condition. Such reduction of the clinical manifestation need not be absolute to be useful.

The terms "treatment", "treat" and "treating" as used herein refers a course of action initiated after the onset of a clinical manifestation of a disease state or condition so as to eliminate or reduce such clinical manifestation of the disease state or condition. Such treating need not be absolute to be useful.

The term "in need of treatment" as used herein refers to a judgment made by a caregiver that a subject requires or will benefit from treatment. This judgment is made based on a variety of factors that are in the realm of a caregiver's expertise, but that includes the knowledge that the patient is ill, or will be ill, as the result of a condition that is treatable by a method or device of the present disclosure.

The term "in need of prevention" as used herein refers to a judgment made by a caregiver that a patient requires or will benefit from prevention. This judgment is made based on a variety of factors that are in the realm of a caregiver's expertise, but that includes the knowledge that the patient will be ill "Biomarkers For Triple-Negative Breast Cancer" Attorney Docket No. 00H670-301084 or may become ill, as the result of a condition that is preventable by a method or device of the disclosure.

The term "individual", "subject" or "patient" as used herein refers to any animal, including mammals, such as mice, rats, other rodents, rabbits, dogs, cats, swine, cattle, sheep, horses, or primates, and humans. The term may specify male or female or both, or exclude male or female.

The term "highly stringent conditions" as used herein means that the conditions of temperature and ionic strength are selected so that it enables hybridization to be maintained between two complementary nucleic acid fragments. Such conditions can also be affected by the presence of certain enzymes, notably helicase. These conditions are well known by persons skilled in the art, and are described, for example, in the book by Sambrook at el. Molecular Cloning, a Laboratory Manual. Third Edition. CSHL press, Cold Spring Harbor, New York, 2001 , which is incorporated herein by reference to teach how to achieve such conditions. A person of ordinary skill in the art would be able to fluctuate the various factors involved to achieve the desired level of stringency for a given pair of complementary DNA fragments with a known melting point. Typically, hybridization of two strands at high stringency requires that the sequences exhibit a high degree of complementarity over an extended portion of their length. Examples of high stringency conditions include: hybridization to filter-bound DNA in 0.5 M NaHP04, 7% SDS, 1 mM EDTA at 65° C, followed by washing in 0.1 x SSC/0.1 % SDS (where 1 x SSC is 0.15 M NaCI, 0.15 M Na citrate) at 68° C or for oligonucleotide molecules washing in 6 x SSC/0.5% sodium pyrophosphate at about 37° C (for 14 nucleotide-long oligonucleotides), at about 48° C (for about 17 nucleotide-long oligonucleotides), at about 55° C (for 20 nucleotide-long oligonucleotides), and at about 60° C (for 23 nucleotide-long oligonucleotides). In a specific embodiment, the highly stringent conditions are those described in the example below.

B. BIOMARKERS OF TRIPLE NEGATIVE BREAST CANCER

It has been unexpectedly discovered that the expression of 24 specific genes in triple negative forms of breast cancer tumors are highly predictive of relapse, and can be used to guide the course of treatment and prophylaxis. These 24 genes are listed below in Table 1. The studies conducted to establish the prognostic value of these genes are provided in detail in the working example below.

As can be seen in FIG. 5, patients in the lower tertile of expression for the genes listed in Table 1 have a far lower probability of progression-free survival than do patients in the two upper tertiles. The hazard ratio was calculated to be 0.24, with a high level of confidence (p = 1.6E-4).

Ten of the 24 genes were discovered to be particularly predictive, and are listed below in Table 2. As shown in FIG. 12, patients in the lower tertile of expression for the genes listed in Table 2 have a far lower probability of progression-free survival than do patients in the two upper tertiles. The hazard ratio was calculated to be 0.31 , with a high level of confidence (p = 9E-7). "Biomarkers For Triple-Negative Breast Cancer" Attorney Docket No. 00H670-301084

Two of the genes stand out as having excellent predictive value for prognosticating relapse: CIITA and CD74. As shown in FIGS. 6 and 8, patients with low expression of CIITA are at significantly elevated risk of relapse of TNBC. FIG. 6 illustrates differential progression-free survival of patients depending on whether the expression of CIITA in the patient is above or below the median level; patients with above median expression have a much better prognosis (hazard ratio of 0.21 ). FIG. 8 illustrates differential progression-free survival of patients depending on whether the expression of CIITA in the patient is in the upper, intermediate, or lower tertile. As shown in FIGS. 7 and 9, patients with low expression of CD74 are at significantly elevated risk of relapse of TNBC. FIG. 7 illustrates differential progression-free survival of patients depending on whether the expression of CD74 in the patient is above or below the median level; patients with above median expression have a much better prognosis (hazard ratio of 0.38). FIG. 9 illustrates differential progression-free survival of patients depending on whether the expression of CD74 in the patient is in the upper, intermediate, or lower tertile.

Expression of many of the genes in Table 2 is highly correlated, as shown below in Table 3 (which also shows the hazard ratio of progression-free survival of patients with above median expression versus below median expression of each of the genes in Table 2).

1. Descriptions of Biomarkers

The Class II, Major Histocompatibility Complex, Transactivator (CIITA) gene encodes a protein with an acidic transcriptional activation domain, 4 LRRs (leucine-rich repeats) and a GTP binding domain. The protein is located in the nucleus and acts as a positive regulator of class II major histocompatibility complex gene transcription. The protein also binds GTP and uses GTP binding to facilitate its own transport into the nucleus. Once in the nucleus it does not bind DNA but rather uses an intrinsic acetyltransferase (AT) activity to act in a coactivator-like fashion. Mutations in this gene have been associated with bare lymphocyte syndrome type II (also known as hereditary MHC class II deficiency or HLA class ll-deficient combined immunodeficiency), increased susceptibility to rheumatoid arthritis, multiple sclerosis, and possibly myocardial infarction. Several transcript variants encoding different isoforms have been found for this gene. It is located in the human cytogenetic band 16p13. The gene has at least three known transcript variants, isoforms 1-3. The canonical amino acid sequences of these isoforms can be found under NCBI Reference Sequences NP_001273331.1 (isoform 1 - SEQ ID NO: 1 ), NP_000237.2 (isoform 2 - SEQ ID NO: 2), and NP_001273332.1 (isoform 3 - SEQ ID NO: 3).

The CD74 gene encodes a protein that associates with class II major histocompatibility complex (MHC) and is a chaperone that regulates antigen presentation for immune response. It also serves as cell surface receptor for the cytokine macrophage migration inhibitory factor (MIF) which, "Biomarkers For Triple-Negative Breast Cancer" Attorney Docket No. 00H670-301084 when bound to the encoded protein, initiates survival pathways and cell proliferation. This protein also interacts with amyloid precursor protein (APP) and suppresses the production of amyloid beta. Multiple alternatively spliced transcript variants encoding different isoforms have been identified. It is located in the human cytogenetic band 5q32. It has 3 known isoforms a-c. The canonical amino acid sequences of these isoforms can be found under the NCBI Reference Sequence shown in Table 1.

HLA-DPA1 (MHC class II DP-a-1 ) encodes a protein that belongs to the HLA class II alpha chain paralogues. This class II molecule is a heterodimer consisting of an alpha (DPA) and a beta (DPB) chain, both anchored in the membrane. It plays a central role in the immune system by presenting peptides derived from extracellular proteins. Class II molecules are expressed in antigen presenting cells. The alpha chain is approximately 33-35 kDa and its gene contains 5 exons. Exon one encodes the leader peptide, exons 2 and 3 encode the two extracellular domains, exon 4 encodes the transmembrane domain and the cytoplasmic tail. Within the DP molecule both the alpha chain and the beta chain contain the polymorphisms specifying the peptide binding specificities, resulting in up to 4 different molecules. It is located in the human cytogenetic band 6p21.3. The canonical amino acid sequences of its proteins can be found under the NCBI Reference Sequence shown in Table 1.

The HLA-DPB1 gene encodes a protein that belongs to the HLA class II beta chain paralogues. This class II molecule is a heterodimer consisting of an alpha (DPA) and a beta chain (DPB), both anchored in the membrane. It plays a central role in the immune system by presenting peptides derived from extracellular proteins. Class II molecules are expressed in antigen presenting cells. The beta chain is approximately 26-28 kDa and its gene contains 6 exons. Exon one encodes the leader peptide, exons 2 and 3 encode the two extracellular domains, exon 4 encodes the transmembrane domain and exon 5 encodes the cytoplasmic tail. Within the DP molecule both the alpha chain and the beta chain contain the polymorphisms specifying the peptide binding specificities, resulting in up to 4 different molecules. It is located in the human cytogenetic band 6p21.3. The canonical amino acid sequences of its protein product can be found under the NCBI Reference Sequence shown in Table 1.

The HLA-DPB2 "gene" is actually a pseudogene. It is located in the human cytogenetic band 6p21.3. A provisional cDNA sequence of its transcript can be found under the NCBI Reference Sequence shown in Table 1.

The HLA-DQA1 gene encodes a protein that belongs to the HLA class II alpha chain paralogues. The class II molecule is a heterodimer consisting of an alpha (DQA) and a beta chain (DQB), both anchored in the membrane. It plays a central role in the immune system by presenting peptides derived from extracellular proteins. Class II molecules are expressed in antigen presenting cells. The alpha chain is approximately 33-35 kDa. It is encoded by 5 exons; exon 1 encodes the leader peptide, exons 2 and 3 encode the two extracellular domains, and exon 4 encodes the transmembrane "Biomarkers For Triple-Negative Breast Cancer" Attorney Docket No. 00H670-301084 domain and the cytoplasmic tail. Within the DQ molecule both the alpha chain and the beta chain contain the polymorphisms specifying the peptide binding specificities, resulting in up to four different molecules. Typing for these polymorphisms is routinely done for bone marrow transplantation. It is located in human cytogenic band 6p21.3. The canonical amino acid sequence of its protein product can be found under the NCBI Reference Sequence listed in Table 1.

The HLA-DRB1 gene encodes a protein that belongs to the HLA class II beta chain paralogues. The class II molecule is a heterodimer consisting of an alpha (DRA) and a beta chain (DRB), both anchored in the membrane. It plays a central role in the immune system by presenting peptides derived from extracellular proteins. Class II molecules are expressed in antigen presenting cells. The beta chain is approximately 26-28 kDa. It is encoded by 6 exons. Exon one encodes the leader peptide; exons 2 and 3 encode the two extracellular domains; exon 4 encodes the transmembrane domain; and exon 5 encodes the cytoplasmic tail. Within the DR molecule the beta chain contains all the polymorphisms specifying the peptide binding specificities. Hundreds of DRB1 alleles have been described and DRB1 is expressed at a level five times higher than its paralogs DRB3, DRB4 and DRB5. DRB1 is present in all individuals. It has two known transcript variants (1 and 2). The canonical amino acid sequences of the protein products of both variants can be found under the NCBI Reference Sequence shown in Table 1.

The HLA-DRB5 gene encodes a protein that belongs to the HLA class II beta chain paralogues. This class II molecule is a heterodimer consisting of an alpha (DRA) and a beta (DRB) chain, both anchored in the membrane. It plays a central role in the immune system by presenting peptides derived from extracellular proteins. Class II molecules are expressed in antigen presenting cells. The beta chain is approximately 26-28 kDa and its gene contains 6 exons. Exon one encodes the leader peptide, exons 2 and 3 encode the two extracellular domains, exon 4 encodes the transmembrane domain and exon 5 encodes the cytoplasmic tail. Within the DR molecule the beta chain contains all the polymorphisms specifying the peptide binding specificities. DRB1 is expressed at a level five times higher than its paralogues DRB3, DRB4 and DRB5. It is located in the human cytogenic band 6p21.3. The canonical amino acid sequence of the protein can be found under the NCBI Reference Sequence shown in Table 1.

The HLA-DRB6 gene is actually a pseudogene. It is located in the human cytogenetic band 6p21.3. The canonical cDNA sequence can be found under the NCBI Reference Sequence shown in Table 1.

The CTSH gene encodes a lysosomal cysteine proteinase (cathespin H) important in the overall degradation of lysosomal proteins. It is composed of a dimer of disulfide-linked heavy and light chains, both produced from a single protein precursor. The encoded protein, which belongs to the "Biomarkers For Triple-Negative Breast Cancer" Attorney Docket No. 00H670-301084 peptidase C1 protein family, can act both as an aminopeptidase and as an endopeptidase. Increased expression of this gene has been correlated with malignant progression of prostate tumors. It is located in the human cytogenetic band 15q21.5. The canonical amino acid sequence can be found under the NCBI Reference Sequence shown in Table 1.

The NCOA1 gene encodes nuclear receptor coactivator 1 , which acts as a transcriptional coactivator for steroid and nuclear hormone receptors. It is a member of the p160/steroid receptor coactivator (SRC) family and like other family members has histone acetyltransferase activity and contains a nuclear localization signal, as well as bHLH and PAS domains. The product of this gene binds nuclear receptors directly and stimulates the transcriptional activities in a hormone-dependent fashion. It is located in the human cytogenetic band 2p23. It has 3 known isoforms (1-3). The canonical amino acid sequences of these isoforms can be found under the NCBI Reference Sequence shown in Table 1.

The CD1 E gene encodes a member of the CD1 family of transmembrane glycoproteins, which are structurally related to the major histocompatibility complex (MHC) proteins and form heterodimers with beta-2-microglobulin. The CD1 proteins mediate the presentation of primarily lipid and glycolipid antigens of self or microbial origin to T cells. The human genome contains five CD1 family genes organized in a cluster on chromosome 1. The CD1 family members are thought to differ in their cellular localization and specificity for particular lipid ligands. The protein encoded by this gene localizes within Golgi compartments, endosomes, and lysosomes, and is cleaved into a stable soluble form. The soluble form is required for the intracellular processing of some glycolipids into a form that can be presented by other CD1 family members. It is located in the human cytogenetic band 1 q23.1. Many alternatively spliced transcript variants encoding different isoforms have been described, including 13 known isoforms (a-m, also referred to as 1-13). The canonical amino acid sequences of these isoforms can be found under the NCBI Reference Sequence listed in Table 1.

The FCGRT gene encodes a receptor that binds the Fc region of monomeric immunoglobulin

G. The encoded protein transfers immunoglobulin G antibodies from mother to fetus across the placenta. This protein also binds immunoglobulin G to protect the antibody from degradation. Alternative splicing results in multiple transcript variants. It is located in the human cytogenetic band 19q 13.3. The canonical amino acid sequence can be found under the NCBI Reference Sequence shown in Table 1.

The KRT14 gene encodes keratin 14, type I, a member of the keratin family, the most diverse group of intermediate filaments. It is usually found as a heterotetramer with two keratin 5 molecules, a type II keratin. Together they form the cytoskeleton of epithelial cells. Mutations in the genes for these keratins are associated with epidermolysis bullosa simplex. It is located in the human cytogenetic band "Biomarkers For Triple-Negative Breast Cancer" Attorney Docket No. 00H670-301084

17q21.2. The canonical amino acid sequence can be found under the NCBI Reference Sequence shown in Table 1.

The LPAR5 gene encodes lysophosphatidic acid receptor 5, a member of the rhodopsin class of G protein-coupled transmembrane receptors. This protein transmits extracellular signals from lysophosphatidic acid to cells through heterotrimeric G proteins and mediates numerous cellular processes. It is located in the human cytogenetic band 12p13.21. Transcript variants of this gene have been described, although they encode the same peptide product. The canonical amino acid sequence can be found under the NCBI Reference Sequences shown in Table 1.

The FGD3 gene is a protein encoding gene. It is located on human chromosome 9. It has at least two known isoforms (a and b) and three known transcript variants. The canonical amino acid sequences of these isoforms can be found under the NCBI Reference Sequence shown in Table 1.

The VAMP2 gene encodes vesicle-associated membrane protein 2 (synaptobrevin 2), a member of the vesicle-associated membrane protein (VAMP)/synaptobrevin family. Synaptobrevins/VAMPs, syntaxins, and the 25-kD synaptosomal-associated protein SNAP25 are the main components of a protein complex involved in the docking and/or fusion of synaptic vesicles with the presynaptic membrane. The protein forms a stable complex with syntaxin, synaptosomal-associated protein, 25 kD, and synaptotagmin. It also forms a distinct complex with synaptophysin. It is a likely candidate gene for familial infantile myasthenia (FIMG) because of its map location and because it encodes a synaptic vesicle protein of the type that has been implicated in the pathogenesis of FIMG. It is located in the human cytogenetic band 17p13.1. The canonical amino acid sequence can be found under the NCBI Reference Sequence shown in Table 1.

The LRRK2 gene encodes leucine-rich repeat kinase 2, a member of the leucine-rich repeat kinase family and encodes a protein with an ankryin repeat region, a leucine-rich repeat (LRR) domain, a kinase domain, a DFG-like motif, a RAS domain, a GTPase domain, a MLK-like domain, and a WD40 domain. The protein is present largely in the cytoplasm but also associates with the mitochondrial outer membrane. Mutations in this gene have been associated with Parkinson disease-8. It is located in the human cytogenetic band 12q12. The canonical amino acid sequence can be found under the NCBI Reference Sequence shown in Table 1.

The MBNL1 gene encodes muscleblind-like splicing regulator 1. It is located in the human cytogenetic band 3q25. It has at least 7 known isoforms (a-g). The canonical amino acid sequences of these isoforms can be found under the NCBI Reference Sequence shown in Table 1.

The NTRK3 gene encodes neurotrophic tyrosine kinase, receptor, type 3, a member of the neurotrophic tyrosine receptor kinase (NTRK) family. This kinase is a membrane-bound receptor that, upon neurotrophin binding, phosphorylates itself and members of the MAPK pathway. Signaling "Biomarkers For Triple-Negative Breast Cancer" Attorney Docket No. 00H670-301084 through this kinase leads to cell differentiation and may play a role in the development of proprioceptive neurons that sense body position. Mutations in this gene have been associated with medulloblastomas, secretory breast carcinomas and other cancers. Several transcript variants encoding different isoforms have been found for this gene. It is located in the human cytogenetic band 15q25. It has at least 4 known isoforms (a-d). The canonical amino acid sequences of these isoforms can be found under the NCBI Reference Sequence shown in Table 1.

The POLR3GL gene encodes polymerase (RNA) III (DNA directed) polypeptide G (32kD)-like protein, located in the human cytogenetic band 1 q21.1. The canonical amino acid sequence can be found under the NCBI Reference Sequence shown in Table 1.

The PTGDS gene encodes prostaglandin D2 synthase, a glutathione-independent prostaglandin D synthase that catalyzes the conversion of prostaglandin H2 (PGH2) to postaglandin D2 (PGD2). PGD2 functions as a neuromodulator as well as a trophic factor in the central nervous system. PGD2 is also involved in smooth muscle contraction/relaxation and is a potent inhibitor of platelet aggregation. This gene is preferentially expressed in the brain. Studies with transgenic mice overexpressing this gene suggest that this gene may be also involved in the regulation of non-rapid eye movement sleep. It is located in the human cytogenetic band 9q34. The canonical amino acid sequence can be found under the NCBI Reference Sequence found in Table 1.

The SH3BGRL gene encodes SH3 domain binding glutamate-rich protein like protein. It is located in the human cytogenetic band Xq13.3. The canonical amino acid sequence can be found under the NCBI Reference Sequence shown in Table 1.

The TOX gene encodes thymocyte selection-associated high mobility group box, which contains a HMG box DNA binding domain. HMG boxes are found in many eukaryotic proteins involved in chromatin assembly, transcription and replication. This protein may function to regulate T-cell development. It is located in the human cytogenetic band 8q12.1. The canonical amino acid sequence can be found under the NCBI Reference Sequence shown in Table 1.

2. Probes for Measuring Expression of Biomarkers

Probes for detecting and measuring the expression of the biomarkers may be useful in the methods and kits described below. Such probes fall into two general categories: those for measuring nucleic acids and those for measuring proteins. The nucleic acids measured by the probes include mRNA and cDNA of the gene to be detected. The proteins measured by the probes include protein products of the genes.

The nucleic acid probe binds specifically with a target sequence under highly stringent conditions. The target sequence is a sequence of at least 15 base pairs (bp) found in the mRNA or cDNA of the gene the expression of which is to be measured. Such mRNA or cDNA for the gene may "Biomarkers For Triple-Negative Breast Cancer" Attorney Docket No. 00H670-301084 be any that is known in the art. In some cases the mRNA will be non-coding, as in the cases of mRNA for HLA-DPB2 and HLA-DRB6, which are thought to express mRNA corresponding to the cDNA sequences in SEQ ID NOS: 9 and 14 respectively. In some cases the mRNA will comprise a sequence that encodes a protein product of the gene. Some embodiments of the mRNA encode a peptide having at least 90% identity with one of the peptide sequences listed in Table 1 (SEQ ID NOS: 1 -8, 10-13, and 15-54). In other cases the level of identity may be higher, for example 95%, 97.5%, 99%, 99.9%, or 100%. The cDNA may have a sequence that is complementary to any of the foregoing mRNAs, or a sequence that mimics any of the foregoing mRNAs but for the substitution of thymidine for uracil.

In some embodiments of the probe, the polynucleotide part of the probe and its target sequence are of at least 20 bp. In further embodiments of the probe, the polynucleotide part of the probe and its target sequence are of at least 25 bp. In many embodiments, the polynucleotide part of the probe will be single-stranded DNA. In other embodiments the polynucleotide part may be double- stranded DNA, RNA, LNA, or other nucleic acids. The design of nucleotide probes is a well understood technique, and given the knowledge of the target sequence it is within the capabilities of one of ordinary skill to design specific probes for the target. Multiple probes may of course be used to detect the mRNAs and cDNAs of multiple genes as necessary.

If the probe is intended to measure a protein product of the gene, the probe will comprise a ligand group that specifically binds to the protein product of the gene. It may target any known protein product of the gene. Some embodiments of the probe specifically bind a protein product of the gene that has at least 90% sequence identity to any one of the sequences listed above as associated with a protein product of a gene from Table 1. Further embodiments of the probe specifically bind to a peptide that has at least 90% sequence identity to one of the peptide sequences listed in Table 1 (SEQ ID NOS: 1 -8, 10-13, and 15-54). In further embodiments of the probe, the level of identity is selected from 95%, 97.5%, 99%, 99.9%, and 100%. Multiple probes may be used for detecting the expression of more than one gene, each comprising a ligand to a product of one of the genes. The ligand is a compound with a specific affinity for the protein product. Many such ligands are known in the art. For example, the publicly available BioLip database (http://zhanqlab.ccmb.med.umich.edu/BioLiP/), maintained by the University of Michigan, contains over 300,000 protein ligands, and is searchable based on the protein of interest. The ligand may be for example an antigen binding site of an antibody. Antibodies are macromolecular constructs that binds to proteinaceous and other types of targets with high affinity and specificity. Antibodies can be generated by various methods, the simplest of which is challenging a bird or mammal with the target (antigen) and harvesting the antibodies. Antibodies can also be produced monoclonally or polyclonally in cell culture by methods known in the art. Some embodiments of the ligand are a fragment of an antibody. Further embodiments of the ligand may be a "Biomarkers For Triple-Negative Breast Cancer" Attorney Docket No. 00H670-301084

Fab region of an antibody. Still further embodiments of the ligand are a light-chain variable region or a heavy-chain variable region of an antibody.

The ligand may be any that is known to specifically bind to the protein product of the gene. In some embodiments of the probe, the probe binds specifically to an epitope of the protein product of the gene. The epitope may be of any size. In some embodiments of the probe, the epitope is at least 5 residues long. In further embodiments of the probe, the epitope is at least 8 residues long. In still further embodiments of the probe, the epitope is at least 1 1 residues long. In still further embodiments of the probe, the epitope is at least 13 residues long.

The nucleic acid probe or protein probe may comprise a reporter group, which is a chemical group or structure than allows specific detection of the molecule to which the reporter is bound or conjugated. Myriad types of reporters are commercially available; examples include radionuclides, rare stable isotopes, fluorophores, chromophores (i.e., dyes or other groups that confer color in the visible spectrum), enzymes, magnetic particles, and quantum dots. Enzymes that are useful as reporters often generate a reaction product that is visually distinctive, such as precipitates, effervescence, chromophores, or luminescence. Frequently the use of the enzymatic reporter will require that the enzyme's substrate be added to a reaction mixture. Examples of such enzymes that are useful as reporters include horseradish peroxidase and luciferase. Many others are well known in the art.

C. METHODS OF PROGNOSTICATION

A method of prognosticating a risk of relapse of TNBC in a subject in need thereof is provided, comprising: (a) measuring a level of expression of each of a set of genes selected from Table 1 in a TNBC tumor from the subject, (b) comparing the level of expression of each of the set of genes to a corresponding benchmark value of expression of each of the set of genes, and/or (c) prognosticating an elevated risk of relapse if the level of expression of at least one of the set of genes is below the corresponding benchmark value.

The subject in need thereof may be any such subject, including a human or a non-human animal. In some embodiments of the method the subject is a female human subject who has been diagnosed with TNBC. The subject may be in remission or may have active TNBC. In some embodiments of the method, the subject has been in remission for 24 months or less. In further embodiments of the method, the subject has been in remission for 12 months or less. In still further embodiments of the method, the subject has been in remission for 6 months or less.

The set of genes includes at least one gene, and includes at least one gene selected from Table 1. If the set of genes includes only one gene, then the one gene must be selected from Table 1. If the set of genes includes more than one gene, then all or some of the genes may be selected from Table 1. In some embodiments of the method every gene in the set of genes is selected from Table 1. "Biomarkers For Triple-Negative Breast Cancer" Attorney Docket No. 00H670-301084

The expression in each gene of the set may be measured by any method known in the art. In some embodiments of the method, the step of measuring will reveal whether the gene is expressed in a Boolean fashion. In other embodiments of the method, the measurement will reveal the degree of expression as well. The measurement may for example measure the presence or abundance of an mRNA that is specific to the gene in question; as another example, the measurement may measure the presence or abundance on a protein product that is specific to the gene in question. In some embodiments of the method in which protein is measured, the protein that is measured comprises a sequence from Table 1 (SEQ ID NOS: 1-8, 10-13, and 15-54). In some embodiments of the method the mRNA corresponding to one of the genes in Table 1 encodes a peptide that encodes a peptide comprising a sequence from Table 1 (SEQ ID NOS: 1 -8, 10-13, and 15-54).

If the measuring step involves measuring mRNA, the method may further comprise obtaining mRNA from the TNBC tumor, synthesizing a DNA reverse transcript of at least a portion of the mRNA, and hybridizing the DNA reverse transcript with one or more probes. Any of the various methods known in the art may be used to obtain the mRNA, which may include such steps as cellular extraction of the mRNA, purification, isolation, and/or amplification. The DNA reverse transcript will generate a double-stranded cDNA in which one strand is complimentary of the mRNA, and the other strand has a sequence identical to the mRNA but for the substitution of thymidine for uracil. The probe may be any that is disclosed to be suitable above in this disclosure for the measurement of cDNA.

The measuring step may further comprise detecting hybridization between the probe and the analyte mRNA or cDNA. Such detection may be accomplished by any means known in the art. For example, the formation of DNA:DNA duplexes or DNA:RNA duplexes may be detected by spectrophotometry, density gradient centrifugation, and electrophoresis. The probe may further comprise a reporter group, as described above in this disclosure.

If the measuring step involves measuring protein product(s) of the gene(s), the method may further comprise obtaining a protein from the TNBC tumor, and contacting the protein with one or more probes. Any such probe described as suitable above in this disclosure may be used. The protein probe may also include a reporter, which may be any reporter that is described above as suitable for the probes.

The benchmark value may be a measure of central tendency based on typical levels observed in one or more tumor populations. For example, the benchmark value may be a mean level of the gene expression observed in a given tumor population. The given tumor population may be defined by one or more of the patient's geography, age, ethnicity, sex, and medical history. The benchmark value may take into account a measure of variation combined with a measure of central tendency. For example, the benchmark value may be a mean level of the gene expression observed in a given tumor "Biomarkers For Triple-Negative Breast Cancer" Attorney Docket No. 00H670-301084 population, plus or minus a margin of error. Some embodiments of the benchmark value may be a tertile value, instead of a measure of central tendency. A specific embodiment of the benchmark value is mean value for the bottom tertile of the gene expression observed in a given population. Such a mean value may be calculated, for example, by summing the expression measurements of the set of genes and dividing the sum by the total number of measurements. The measurements may be raw measurements (such as fragments of mRNA or cDNA per kb gene length per million reads) or normalized measurements (such as % of normal expression, or expression compared to a constitutively expressed gene with generally low expression, such as the transcriptional repressor CTCF).

The method may be performed in vivo or ex vivo. A specific embodiment of the method is performed ex vivo. In such embodiments a sample of tumor material is removed from the subject's body for testing, and it is not thereafter returned.

The set of genes may comprise any combination of the genes in Table 1. In some embodiments, the set of genes may include a gene from Table 1 selected from the group consisting is: LPAR5, LRRK2, POLR3GL, PTGDS, CIITA, CTSH, FGD3, and HLA-DPB2. In further embodiments of the method, the set of genes comprises at least 10 genes selected from Table 1. Still further embodiments of the method involve the use of a set of all 24 genes from Table 1. The use of a larger panel of genetic markers has the advantage of increasing prognostic power. The use of a smaller panel of genetic markers has the advantage of reduced labor and expense.

In some embodiments of the method, at least one gene in the set is selected from Table 2. In some such embodiments of the method, the one or more genes from Table 2 is selected from the group consisting of: CIITA, CTSH, FGD3, and HLA-DPB2. In further embodiments of the method the set of genes comprises all 10 genes in Table 2.

The most predictive genes from Table 1 are CIITA and CD74. In a specific embodiment of the method, the set of genes comprises CIITA and CD74. The set of genes may comprise additional genes from Table 1 (or other genes), or it may consist of CIITA and CD74.

D. METHODS OF TREATMENT AND PROPHYLAXIS

A method of treatment or prophylaxis of a subject at risk of relapse of TNBC is provided. The method comprises prognosticating the risk of relapse of TNBC in the subject by performing any embodiment of the prognostic method above; and providing therapeutic or prophylactic treatment for the TNBC to the subject based on whether the subject is prognosticated to have an elevated risk of relapse. The prognosis will in many cases provide an opportunity for educated intervention that may in turn lessen the likelihood of a relapse or lessen the severity of a relapse.

In some embodiments, the therapeutic or prophylactic treatment may include increased monitoring of the subject's condition. This is a very non-invasive form of intervention. The increased "Biomarkers For Triple-Negative Breast Cancer" Attorney Docket No. 00H670-301084 monitoring may include self-monitoring or monitoring by a medical professional for a symptom of relapse, such as swelling of a breast, skin irritation or dimpling, breast or nipple pain, nipple retraction, redness, scaliness, swelling of nearby lymph nodes, thickening of the nipple or breast skin, or nipple discharge. The increased monitoring may include more frequent radiology procedures, such as mammograms (or other X-rays), PET scan, scintimammography, sonograms, electrical impedance imaging, thermography, and magnetic resonance imaging. In some embodiments of the method the increased monitoring may include a biopsy. The "increased monitoring" will in any case exceed the level and intensity of monitoring that would ordinarily be provided for a TNBC patient in remission.

In some embodiments, the therapeutic or prophylactic treatment may include radiotherapy. In some embodiments, the therapeutic or prophylactic treatment may include chemotherapy. Any forms of radiotherapy or chemotherapy known in the art may be used. The chemotherapy may be for example anthracycline, taxane, or a combination of the two. However, because the prognosis for patients with low expressions of the biomarkers is poor even after the use of conventional therapeutic or prophylactic treatment, in some embodiments of the method the therapeutic or prophylactic treatment is of an alternative type. In one such embodiment of the method the therapeutic or prophylactic treatment is inclusion in a clinical trial for an alternative therapeutic or prophylactic treatment.

In some embodiments of the method, the therapeutic or prophylactic treatment may include neoadjuvant therapy followed by surgical intervention. Neoadjuvant therapy is thought to provide greater benefit to patients with TNBC than in other forms of breast cancer.

In some embodiments, the therapeutic or prophylactic treatment may include surgical intervention. The surgical intervention may be, for example, lumpectomy. The prognosis may guide the medical professional in deciding whether a lump that might otherwise appear benign should be removed as a precaution. In other embodiments, the surgical intervention may include mastectomy. Some patients who are in remission, upon learning that the TNBC tumor expresses markers that are prognostic for relapse, may choose to have a prophylactic mastectomy rather than risk a relapse. E. KITS

A kit is provided for analyzing genetic expression of TNBC in a subject, comprising: a means for measuring the expression of a first gene selected from Table 1 ; and means for detecting a second gene selected from Table 1. Some embodiments of the kit are for the purpose of prognosticating a risk of relapse of TNBC. In specific embodiments of the kit, the means for measuring the expression of the first and second genes may be independently selected from: a means for detecting a first target sequence of at least 15 bp that is present in a first or second cDNA or mRNA of the first or second gene; and a means for detecting a first protein product of the first or second gene. "Biomarkers For Triple-Negative Breast Cancer" Attorney Docket No. 00H670-301084

In some embodiments of the kit, the means for detecting the first target sequence is a first probe that may be any probe disclosed as suitable for measuring mRNA or cDNA above in this disclosure. In some embodiments of the kit, the means for detecting the second target sequence is a second probe that may be any probe disclosed as suitable for measuring mRNA or cDNA above in this disclosure. In some embodiments of the kit that comprise at least one nucleic acid probe, the kit may include a container of a reverse transcriptase for generating a cDNA reverse transcript from an mRNA. Such probes may be components in an expression screening apparatus, such as a DNA array or a DNA microarray.

In some embodiments of the kit, the means for detecting the first protein product is a first probe that may be any probe disclosed as suitable for measuring such protein products above in this disclosure. In some embodiments of kit, the means for detecting the second protein product is a second probe that may be any probe disclosed as suitable for measuring such protein products above in this disclosure. Some versions of the probes may be immobilized to a substrate, such as a bead or multiwell titer plate, or in any other configuration known in the art for the use of protein probes.

The kit may further comprise one or more additional means for detecting the expression of one or more additional genes selected from Table 1. Such additional means may also be any of the nucleic acid probes or protein probes described above.

It is to be understood that the first means for measuring the expression of the first gene and the second means for measuring the expression of the second gene can differ in their nature. For example, the first means could be a nucleic acid probe, and the second means could be a protein probe (and vice versa). The same can be true of any additional means for measuring the expression of additional genes from Table 1.

The first and second genes, and any additional genes are collectively referred to in the rest of this section as constituting a "set of genes." The set of genes may comprise any combination of the genes in Table 1. In some embodiments, the set of genes may include a gene from Table 1 selected from the group consisting of: LPAR5, LRRK2, POLR3GL, PTGDS, CIITA, CTSH, FGD3, and HLA- DPB2. In further embodiments of the method, the set of genes comprises at least 10 genes selected from Table 1 (requiring means for detecting 8 additional genes). Still further embodiments of the method involve the use of a set of all 24 genes from Table 1 (requiring means for detecting 22 additional genes). The use of a larger panel of genetic markers has the advantage of increasing prognostic power. The use of a smaller panel of genetic markers has the advantage of reduced labor and expense.

In some embodiments of the method, the at least one gene in the set of genes is selected from Table 2. In some such embodiments of the method, the one or more genes from Table 2 is selected "Biomarkers For Triple-Negative Breast Cancer" Attorney Docket No. 00H670-301084 from the group consisting of: CIITA, CTSH, FGD3, and HLA-DPB2. In further embodiments of the method the set of genes comprises all 10 genes in Table 2 (requiring means to measure the expression of 8 additional genes).

The most predictive genes from Table 1 are CIITA and CD74. In a specific embodiment of the method, the first and second genes are CIITA and CD74. The set of genes may comprise additional genes from Table 1 (or other genes), or it may consist of CIITA and CD74

F. EXEMPLARY EMBODIMENTS

Claims to the following embodiments are specifically intended to be supported by this disclosure.

Embodiment 1. A method of prognosticating a risk of relapse of triple-negative breast cancer

(TNBC) in a subject in need thereof, the method comprising: (a) measuring a level of expression of each of a set of genes comprising at least one gene selected from Table 1 in a TNBC tumor from the subject; (b) comparing the level of expression of each of the set of genes to a corresponding benchmark value of expression of each of the set of genes; and (c) prognosticating an elevated risk of relapse if the level of expression of at least one of the set of genes is below the corresponding benchmark value. Embodiment 2. The method of embodiment 1 , wherein step (a) comprises: obtaining mRNA from the TNBC tumor; synthesizing a DNA reverse transcript of at least a portion of the mRNA; and hybridizing the DNA reverse transcript with one or more probes, the probes each comprising a polynucleotide of at least 15 bp that hybridizes under highly stringent conditions with a target sequence of at least 15 bp, wherein said target sequence of at least 15 bp is present in a cDNA of one of the set of genes. Embodiment 3. The method of embodiment 2, comprising detecting hybridization between the DNA reverse transcript and the one or more probes. Embodiment 4. The method of embodiment 1 , wherein step (a) comprises: obtaining protein from the TNBC tumor; contacting the protein with one or more probes, the probes each comprising a ligand group that specifically binds to a protein product of one of the set of genes, and a reporter. Embodiment 5. The method of embodiment 4, comprising detecting binding between the protein product and the one or more probes. Embodiment 6. The method of any of embodiments 1 -5, wherein the method is an ex vivo method. Embodiment 7. The method of any of embodiments 1 -6, wherein the set of genes includes LPAR5. Embodiment 8. The method of any of embodiments 1-7, wherein the set of genes includes LRRK2. Embodiment 9. The method of any of embodiments 1-8, wherein the set of genes includes POLR3GL. Embodiment 10. The method of any of embodiments 1-9, wherein the set of genes includes PTGDS. Embodiment 11. The method of any of embodiments 1 -10, wherein the at least one gene is selected from Table 2. Embodiment 12. The method of any of embodiments 1 -1 1 , wherein the set of genes includes CIITA. Embodiment 13. The method of any of embodiments 1-12, "Biomarkers For Triple-Negative Breast Cancer" Attorney Docket No. 00H670-301084 wherein the set of genes includes CTSH. Embodiment 14. The method of any of embodiments 1-13, wherein the set of genes includes FGD3. Embodiment 15. The method of any of embodiments 1 -14, wherein the set of genes includes HLA-DPB2. Embodiment 16. The method of any of embodiments 1- 15, wherein the set of genes includes at least 10 genes selected from Table 1. Embodiment 17. The method of any of embodiments 1 -16, wherein the set of genes includes 24 genes selected from Table 1. Embodiment 18. The method of any of embodiments 1 -17, wherein the set of genes includes at least 10 genes selected from Table 2. Embodiment 19. The method of any of embodiments 1 -18, wherein the set of genes comprises at least two genes selected from Table 1. Embodiment 20. The method of embodiment 19, wherein the set of genes comprises CIITA. Embodiment 21. The method of any of embodiments 19-20, wherein the set of genes includes LPAR5. Embodiment 22. The method of any of embodiments 19-21 , wherein the set of genes includes LRRK2. Embodiment 23. The method of any of embodiments 19-22, wherein the set of genes includes POLR3GL. Embodiment 24. The method of any of embodiments 19-23, wherein the set of genes includes PTGDS. Embodiment 25. The method of any of embodiments 19-24, wherein the set of genes is selected from Table 2. Embodiment 26. The method of any of embodiments 19-25, wherein the set of genes includes CD74. Embodiment 27. The method of any of embodiments 19-26, wherein the set of genes includes HLA-DPB2. Embodiment 28. The method of any of embodiments 19-27, wherein the set of genes includes CTSH. Embodiment 29. The method of any of embodiments 19-28, wherein the set of genes includes FDG3. Embodiment 30. A method of treatment or prophylaxis of a subject at risk of relapse of triple-negative breast cancer (TNBC), the method comprising: prognosticating the risk of relapse of TNBC in the subject by performing the method of any of embodiments 1-30; and providing therapeutic or prophylactic treatment for the TNBC to the subject based on whether the subject is prognosticated to have an elevated risk of relapse. Embodiment 31. The method of embodiment 30, wherein the therapeutic or prophylactic treatment comprises increased monitoring of the subject's condition. Embodiment 32. The method of any of embodiments 30-31 , wherein the therapeutic or prophylactic treatment comprises radiotherapy. Embodiment 33. The method of any of embodiments 30-32, wherein the therapeutic or prophylactic treatment comprises chemotherapy. Embodiment 34. The method of any of embodiments 30-33, wherein the therapeutic or prophylactic treatment comprises surgical intervention. Embodiment 35. The method of any of embodiments 30-34, wherein the therapeutic or prophylactic treatment comprises mastectomy. Embodiment 36. A kit for analyzing genetic expression of TNBC in a subject, comprising: a means for measuring the expression of a first gene selected from Table 1 ; and means for detecting a second gene selected from Table 1. Embodiment 37. The kit of embodiment 36, wherein the kit is for a purpose of prognosticating a risk of relapse of TNBC. Embodiment 38. The kit of any of embodiments 36-37, wherein: the means for "Biomarkers For Triple-Negative Breast Cancer" Attorney Docket No. 00H670-301084 measuring the expression of the first gene is a means for detecting a first protein product of the first gene; and the means for measuring the expression of the second gene is a means for detecting a second protein product of the second gene. Embodiment 39. The kit of embodiment 38, wherein: the means for detecting the first protein product is a first probe comprising a first ligand group that specifically binds to a first protein product of the first gene; and the means for detecting the second protein product is a second probe comprising a second ligand group that specifically binds to a second protein product of the second gene. Embodiment 40. The kit of embodiment 39, wherein the first ligand group is an immunoglobulin. Embodiment 41. The kit of any of embodiments 39-40, wherein the second ligand group is an immunoglobulin. Embodiment 42. The kit of any of embodiments 39-41 , wherein the first probe and the second probe are immobilized to a surface. Embodiment 43. The kit of embodiment 36, wherein: the means for measuring the expression of the first gene is a means for detecting a first target sequence of at least 15 bp that is present in a first cDNA or mRNA of the first gene; and the means for measuring the expression of the second gene is a means for detecting a second target sequence of at least 15 bp that is present in a second cDNA or mRNA of the second gene. Embodiment 44. The kit of embodiment 43, wherein: the means for detecting the first target sequence is a first probe comprising a first polynucleotide of at least 15 bp that hybridizes under highly stringent conditions with the first target sequence of at least 15 bp that is present in the first cDNA or mRNA of the first gene; and the means for detecting the second target sequence is a second probe comprising a second polynucleotide of at least 15 bp that hybridizes under highly stringent conditions with the second target sequence of at least 15 bp that is present in the second cDNA or mRNA of the second gene. Embodiment 45. The kit of embodiment 44, comprising a container of a reverse transcriptase. Embodiment 46. The kit of any of embodiments 44-45 or 39-42, wherein the first probe comprises a first reporter, and the second probe comprises a second reporter. Embodiment 47. The kit of embodiment 46, wherein the first reporter is selected from the group consisting of: a radionuclide, a stable isotope, a fluorophore, a chromophore, an enzyme, a magnetic particle, and a quantum dot; and the second reporter is selected from the group consisting of: a radionuclide, a fluorophore, a chromophore, an enzyme, a magnetic particle, and a quantum dot. Embodiment 48. The kit of any of embodiments 44-47, wherein the first polynucleotide is single stranded DNA; and wherein the second polynucleotide is single stranded DNA. Embodiment 49. The kit of any of embodiments 44-48, wherein the first probe and the second probe are components of a DNA array. Embodiment 50. The kit of any of embodiments 44-49, wherein the first probe and the second probe are components of a DNA microarray. Embodiment 51. The kit of any of embodiments 44-50, wherein the first polynucleotide is at least 20 bp and the second polynucleotide is at least 20 bp. Embodiment 52. The kit of any of embodiments 44-51 , wherein the first polynucleotide is at least 25 bp and the second "Biomarkers For Triple-Negative Breast Cancer" Attorney Docket No. 00H670-301084 polynucleotide is at least 25 bp. Embodiment 53. The kit of any of embodiments 36-52, wherein the first gene is CIITA. Embodiment 54. The kit of any of embodiments 36-53, wherein the first gene is CIITA and the second gene is CD74. Embodiment 55. The kit of any of embodiments 36-52, wherein the first gene is LPAR5. Embodiment 56. The kit of any of embodiments 36-52, wherein the first gene is LRRK2. Embodiment 57. The kit of any of embodiments 36-52, wherein the first gene is P0LR3GL. Embodiment 58. The kit of any of embodiments 36-52, wherein the first gene is PTGDS. Embodiment 59. The kit of any of embodiments 36-52, wherein the first gene is selected from Table 2. Embodiment 60. The kit of embodiments 59, wherein the first gene is HLA-DPB2. Embodiment 61. The kit of embodiments 59, wherein the first gene is CTSH. Embodiment 62. The kit of embodiments 59, wherein the second gene is selected from Table 2. Embodiment 63. The kit of any of embodiments 36-61 , wherein the second gene is CIITA. Embodiment 64. The kit of any of embodiments 36-61 , wherein the second gene is LPAR5. Embodiment 65. The kit of any of embodiments 36-61 , wherein the second gene is LRRK2. Embodiment 66. The kit of any of embodiments 36-61 , wherein the second gene is POLR3GL. Embodiment 67. The kit of any of embodiments 36-61 , wherein the second gene is selected from Table 2. Embodiment 68. The kit of embodiment 67, wherein the second gene is HLA-DPB2. Embodiment 69. The kit of embodiment 67, wherein the second gene is CTSH. Embodiment 70. The kit of embodiment 67, wherein the second gene is FGD3. Embodiment 71 : The kit of any of embodiments 36-70, comprising a means for measuring the expression of a set of genes including one or more additional genes selected from Table 1. Embodiment 72. The kit of embodiment 71 , wherein the set of genes comprises CIITA. Embodiment 73. The kit of any of embodiments 71 -72, wherein the set of genes includes LPAR5. Embodiment 74. The kit of any of embodiments 71 -73, wherein the set of genes includes LRRK2. Embodiment 75. The kit of any of embodiments 71 -74, wherein the set of genes includes POLR3GL. Embodiment 76. The kit of any of embodiments 71-75, wherein the set of genes includes PTGDS. Embodiment 77. The kit of any of embodiments 71-76, wherein the set of genes is selected from Table 2. Embodiment 78. The kit of any of embodiments 71 -77, wherein the set of genes includes CD74. Embodiment 79. The kit of any of embodiments 71-78, wherein the set of genes includes HLA-DPB2. Embodiment 80. The kit of any of embodiments 71-79, wherein the set of genes includes CTSH. Embodiment 81. The kit of any of embodiments 71 -78, wherein the set of genes includes FDG3. G. WORKING EXAMPLE

1. Abstract

Purpose: To identify genes in the tumor tissue from patients with TNBC that are differentially expressed between patients who did, or did not, have disease relapse. Patients and Methods: Forty- seven snap frozen primary TNBC tumor specimens were analyzed using RNA-seq to identify gene "Biomarkers For Triple-Negative Breast Cancer" Attorney Docket No. 00H670-301084 expression differences between 22 patients who relapsed and 25 who did not. Results: Twenty-four genes exhibited significantly higher expression in tumor tissue from patients who did not relapse. Eleven of these genes were integral members of the MHC II antigen presentation pathway. The 24 gene signature was significantly associated with progression free survival (PFS) (HR=0.24; log-rank p=0.00016) and individually, CIITA and CD74 had HR values of 0.21 and 0.38; log-rank p=0.0006 and 0.0231. A public gene expression database of laser capture micro-dissected breast tumors had higher expression of CIITA in tumor cells than stroma (paired T-test p=0.0089) and immunohistochemical analysis detected CD74 and HLA-DPB1 protein in TNBC tumor cells. A large meta-analysis of microarray data from 199 patients with TNBC validated that 10 of the 24 genes (including 6 MHC II genes) were prognostic for PFS with a HR=0.31 (0.19-0.51 ); log-rank p=9e-07. CD74 alone was similarly prognostic with an HR=0.31 (0.18-0.51 ); log-rank p=0.0000019. Conclusion: A 24 gene TNBC prognostic signature includes MHC II genes whose individual expression was similarly prognostic. Tumor MHC II antigen presentation pathway is likely an important component of anti-tumor immunity associated with good prognosis in TNBC.

2. Introduction

In thus study, RNA-seq technology was utilized, which has multiple advantages over microarray genomic platforms (13, 14). The issue of TNBC prognostic genomic analysis was examined by determining which genes had significantly different expression between patients who relapsed versus those with no relapse. Analysis of the transcriptomes of these samples revealed a set of genetic biomarkers expressed in tumor cells in TNBC patients with good outcomes; the biomarkers include many in a the MHC Class II antigen presentation (MHC II) immune system pathway. This study provides a means to assess prognosis in TNBC.

3. Methods

Patient Material - The Tumor Procurement Shared Facility of the UAB Comprehensive Cancer Center has an IRB approved protocol for collection of tumor and normal tissue samples for research purposes using de-identified clinical data and laboratory analysis. Forty-seven TNBC breast cancer tissues were selected for analysis on the basis that the tumors were ER and PR negative, HER2/Neu not over-expressed, snap frozen tissue available, adequate patient follow-up (>24 months), and the patient had received no anti-cancer therapy prior to tissue collection.

Tissue Processing - The tumor tissue underwent standard macro-dissection by a board certified pathologist (WEG) (see Supplemental Data) to enhance tumor cell content. The de-identified tumor specimens had >50% tumor nuclei and were shipped on dry ice to HudsonAlpha Institute for Biotechnology (Huntsville, AL). "Biomarkers For Triple-Negative Breast Cancer' Attorney Docket No. 00H670-301084

RNA-seq - The 47 tumor specimens were weighed and underwent RNA extraction (see Supplemental Data), quantified, RNA-seq libraries were constructed (16), and were quantified using the Qubit dsDNA High Sensitivity Assay Kit and the Qubit 2.0 fluorometer (Invitrogen). Three barcoded libraries were pooled in equimolar quantities per sequencing lane on an lllumina HiSeq 2000 sequencing machine. They were sequenced using paired-end 50 bp reads and a 6 bp index read to a depth of at least 50 million read pairs per library. The RNA-seq data are publicly available through GEO Accession GSE58135 (http://www.ncbi. nlm. nih.gov/geo/querv7acc. cgi?acc=^:GSE58135).

RNA-seq Data Analysis - Gene expression values (fragments per kilobase of transcript per million, FPKMs) were calculated using TopHat v 1.4.1 (16), GENCODE version 9 (17), BEDtools (18), and Cufflinks 1.3.0 with -u option (19) (see Supplemental Data). Identity of subclusters used Consensus Cluster Plus R package (20), and the SAM seq function was used to identify genes differentially expressed between tumors from patients who did or did not relapse with q values of <5% significant. Kaplan-Meier curves and survival analysis were performed using RNA-seq FPKM values and an R script (22) (see Supplemental Data).

Public microarray data analysis - Kaplan-Meier and survival analysis was performed on public microarray data using the Kaplan-Meier Plotter tool

(23). Patients were censored at the follow-up threshold (8-10 years). Only JetSet best probe sets were used for each gene in the microarray data analysis (24). Analysis was restricted to the 199 patients whose tumors were ER-, PR-, and were classified as basal intrinsic breast cancer subtype (25).

Tumor versus Stroma Gene Expression - Five archived de-identified TNBC tumor specimens underwent standard immunohistochemical analysis with anti-CD74 (Leika/Novocastra) and anti HLA-DPB1 (Sigma-Aldrich). An anatomic pathologist estimated the fraction of antibody positive tumor cells and the localization of the staining (see Supplemental Data). To examine gene expression by epithelial tumor cells versus stroma, we utilized a public laser capture micro-dissection dataset (GEO-GSEJ847) (26). The raw dataset (.eel and matrix files) was uploaded to Partek Genomic Suite (PGS, St. Louis, MO) for data background subtraction, quality control, and z-normalization. The 25 ER/PR negative patient material was selected and paired t test was used to compare gene expression.

Statistics - Descriptive analysis was provided for patients' characteristics including student t test and chi-square statistics. The 24 individual genes expression were transformed to best fit a normal distribution using log 2 base (27, 28). High or low expression levels of individual genes were assessed around median value or by tertiles. PFS is defined as the time from diagnosis to the first documented disease progression or death due to any cause, whichever occurs first. Subjects without relapse were considered censored. The Kaplan-Meier method and log-rank test was used to assess the expression "Biomarkers For Triple-Negative Breast Cancer" Attorney Docket No. 00H670-301084 difference. The hazard ratio and its 95% confidence interval from the Cox model (29) with Efron's method were reported (30). Pearson correlation coefficient was estimated to examine the correlation among individual genes.

4. Results

Patients - A total of 47 women with TNBC represent the study population (Table 4). As expected, the relapsed patients had more advanced stage of disease than the no relapse group. Absence of nodal involvement was more prevalent in the no relapse group (60% versus 27%). Adjuvant therapy was similar in both groups with anthracycline combinations used in the majority of patients although five relapse and two no relapse patients received no adjuvant treatment. Similar numbers of patients had conservative surgical management and radiotherapy. Median time to relapse was 18.5 months (8 to 97 months), and the follow-up of non-relapse patients had a median of 96 months (25 to 137 months). Racial makeup of the two groups was similar, and overall 81 % of the tumors were basal-like and similar in both groups.

Unsupervised Consensus Clustering Analysis - The analysis identified three main clusters (1 , 2 and 3) composed of 20, 17, and 10 patients as illustrated in Figure 1. The cluster analysis did not simply reflect previously defined TNBC subtypes (31 , 32). Figure 2 provides the PFS for the three cluster groups. Cluster 2 had improved PFS for the groups as a whole (p=0.023) and subdivided based on lymph node involvement (p=0.013). As seen in Table 5, patient tumors in Cluster 2 have higher expression of immunomodulatory genes than tumors in the other clusters. The rate of relapse in Cluster 2 (18%) is significantly lower than in Clusters 1 and 3 (63%); p=0067.

Gene Expression Analysis - Genes in the transcriptome were identified having significant expression differences between tumors from patients who relapsed compared to tumors from patients who did not relapse. Table 1 provides the list of 24 genes identified with a false discovery rate (FDR) of 5% (q-value <.05). A heatmap of the 24 genes is provided in Figure 3. All 24 genes exhibited higher expression in tumors from patients who did not relapse. These genes include the major components of the MHC II antigen presentation pathway (Figure 4). There are strong correlations between the expression of the various members of the MHC II pathway across patient samples as demonstrated in Table 3.

Figure 5 depicts the PFS curves for patients whose mean expression of the 24 gene signature was in the top two tertiles compared to the lower tertile. The hazard ratio was 0.24 and a log-rank p- value of 0.00016. Given the strong correlation among overexpressed MHC II pathway genes, the impact of high and low expression on a single gene basis was examined. Figure 6 illustrates the impact of high expression of CIITA on PFS (log-rank p=0.0006; HR=0.21 ), and 7 illustrates the PFS effect of high expression of CD74 with log-rank p=0.0231 and HR=0.38. A summary of HR values for ten of the "Biomarkers For Triple-Negative Breast Cancer" Attorney Docket No. 00H670-301084 differentially expressed genes is provided in Table 3. Even more dramatic are the PFS curves derived from tertiles (high, intermediate, and low values) for CIITA and CD74 (Figure 8 and 9). High values for CIITA are associated with only 3/16 relapses and two of them occur late (>90 months) after diagnosis. Low values for CD74 are associated with 12/16 relapses, all of which occur within 25 months. There were no statistically different CIITA or CD74 gene expression between basal-like and "other" tumor subtypes in regards to tumor relapse or PFS curves. With median value as a cut point, CIITA is an independent predictor for PFS (p=0.008) by multivariable Cox regression analysis. When controlling for tumor stage, the HR for high versus low CIITA is 0.147 (CI 0.048 - 0.450). Similarly, CD74 is an independent predictor for PFS (p=0.0322) with a HR of 0.362 (0.143 - 0.917) after adjusting for tumor stage.

Cell Source of MHC II Gene Expression - Classically, MHC II antigen processing and display are attributed to dendritic cells, B cells, and macrophages. Figures 10 and 1 1 depict an example of the immunohistochemistry analysis of CD74 (Figure 10) and HLA-DPB1 (Figure 1 1 ) protein expression in a triple negative breast tumor. Consistent with other reports of TNBC tumor cells expressing MHC II proteins (33-35), 4 out of 5 TNBC tumor specimens examined had CD74 protein expression in greater than 20% of cells while 2 of 5 had HLA-DPB1 protein expression in >20% of tumor cells. The gene expression for CIITA and CD74 was examined in the 25 ER- patients who had microarray gene expression analysis (Affymetrix) performed on laser micro-dissected epithelial tumor cells versus stromal cells in a public dataset (26 and GSE5847). In these 25 paired samples, epithelial tumor exceeded values of stroma in 76% and 60% of patients for CIITA and CD74, respectively. Using paired statistical analysis, CIITA expression in tumor was higher than stroma (p=0.0089) while CD74 difference was not statistically significant. Thus, a major component of MHCII gene expression in TNBC tumors reflected tumor cell MHCII pathway expression.

Validation of MHC II Expression as a Good Prognosis Signature - In publicly available gene expression repositories there are too few experiments of RNA-seq performed on TNBC tumors with adequate clinical follow-up to be used for validation. As an alternative, validation was carried out on a large meta-analysis of Affymetrix microarray data that was assembled to encompass gene expression profiles from all available breast cancer studies that had adequate clinical follow-up (25). 199 were analyzed patients in this meta-analysis data set with ER-, PR-, basal intrinsic subtype tumors and examined the expression levels of the 24 gene signature. Seven of the 24 genes were not represented by unambiguous JetSet (24) microarray probes, and 7 additional genes did not generate survival curves with significant log-rank p-values when analyzed individually. The remaining 10 genes from the 24 gene signature identified in our cohort were adequately represented and each produced PFS curves with significant log-rank test p-values (<0.05). The 10 validated genes are CD74, CTSH, "Biomarkers For Triple-Negative Breast Cancer" Attorney Docket No. 00H670-301084

HLA-DPA1 , HLA-DPB1 , HLA-DRB1 , HLA-DRB6, MBNL, CD1 E, PTGDS, and TOX. Figure 12 provides the PFS curves of patients whose mean expression of the 10 gene signature was in the top two tertiles compared to the lower tertile. The high expression group has a much better PFS than the low expression group with a HR=0.31 (0.19 - 0.51 ) with a log-rank of p=9e-07. Further, we examined the ability of CD74 (invariant chain) single gene expression to delineate prognosis. As seen in Figure 13, CD74 expression delineated patients in the top two tertiles that had a good prognosis with similar predictive power as the 10 gene signature. The HR was 0.31 (0.18 - 0.51 ) with a log-rank of p=0.0000019. Despite the variation in gene expression measurement technology, multiple institutions and studies included in the public meta-dataset, MHC II expression was validated as being strongly associated with TNBC prognosis.

5. Discussion

This study of 47 TNBC patient tissues used unsupervised consensus cluster analysis to identify 3 clusters (Figure 1 ) and Cluster 2 had moderate prognostic significance, reduced frequency of patients with relapsed disease (Figure 2 and Table 5), and a large number of immunoregulatory genes (Table 5) similar to prior gene signatures (5-7). Analysis of the differentially expressed genes between relapsed and no relapse patients identified 24 genes (Table 1 ). The 24 gene signature was strongly prognostic (HR=0.24; log-rank p=0.00016; Figure 5A). The genes had strong interaction with Pearson correlative coefficients (Table 3) of 0.68 to 0.92 (p=0.0001 ). Expression levels above or below the median of CIITA or CD74 were strongly prognostic (Figure 6 and 7) as individual genes. The tertile expression PFS curves for CIITA and CD74 revealed that the high level of CIITA had only 3 relapsed patients, and 2 of them relapsed at 98+ months (log-rank p=0.0150) while low levels of CD74 had 12/16 relapses all within 25 months, reflecting the aggressive early relapse rate in TNBC (Figure 8 and 9).

Validation of the role of MHC II gene expression in prognosis utilized a public database from a meta-analysis of microarray gene expression from multiple different institutions and studies (23) which included 199 ER/PR-, basal like tumors. The 10 gene enriched signature produced a highly significant difference in PFS curves (p=9e-07) with a HR=0.31 (0.19-0.51 ; Figure 8A) as did single gene CD74 (Figure 8B) with log-rank p=1.9e-6 and HR=0.31 (0.18-0.51 ).

Having validated these MHC II signatures as prognostic, we examined the role of tumor cell or stromal cell expression of these genes. Immunohistology demonstrated CD74 and HLA-DPB1 protein in TNBC tumor cells (Figure 7) similar to other reports (33-35). In addition, some basal-like breast cancer cell lines express MHC II genes or can be induced to express them by gamma interferon or other drugs (36). Further, gene expression of the ER- breast cancer samples from a public database of micro-dissected paired epithelial and stroma breast tissues was examined (24). In the majority of tissue "Biomarkers For Triple-Negative Breast Cancer" Attorney Docket No. 00H670-301084 samples, CIITA and CD74 had higher expression in tumor cells and in paired t test analysis, CIITA expression was significantly higher in tumor cells (p=0.0089).

The RNA-seq studies described in this report add clarity to the presence and role of MHC II display on the TNBC tumor surface. Without wishing to be bound by any hypothetical model, the strong prognostic influence of the pathway and individual MHC II genes along with correlation of pathway members with each other might point to an important role of MHC II on the patient's anti-tumor immune efficacy. Tumor cells expressing MHC II have been shown to function as antigen presenting cells (APCs) (43, 44). They not only process exogenous proteins/antigens but also have access to endogenous proteins/antigens via autophagosome/lysosome fusion (45, 46). The success of the immune response may be reflected in the excellent prognosis of TNBC patients that express the biomarkers discovered in this report, which include members of the MCH II pathway. The relationship of MHC II tumor cell expression and tumor infiltrating lymphocytes will require ongoing additional studies. It does appear that the use of RNA-seq technology has contributed insight into anti-tumor immunity in TNBC patients.

6. Supplemental Information Regarding Methods

Tissue Processing - The tumor tissue underwent macro-dissection to enhance the tumor content of the study material. A frozen aliquot of tissue at dry ice temperature (-78°C) was placed in the center of a frozen section cryo-mold and then surrounded by room temperature OCT matrix and immediately frozen on a cryostat chuck (-20°C). The tissue specimen was not permitted to thaw except at the superficial edges at the OCT-tissue interface. After the chuck with the specimen was mounted in the cryostat, frozen sections were removed in order to efface the block and demonstrate the whole aliquot. A frozen section was cut at 8μ stained with hematoxylin and eosin (H&E) and a coverslip applied. A Sharpie black pen was used to orientate the aliquot by marking the OCT adjacent to the specimen and the coverslip over the frozen section was similarly marked with the Sharpie pen so that the orientation of the H&E frozen section could be matched closely to the OCT block. The pathologist (WEG) then reviewed the orientated H&E frozen section and marked on the coverslip using a blue Sharpie pen (ultra-fine point) the areas of the specimen that will be removed (e.g., areas of uninvolved breast and/or of leukocytic infiltration) to enrich the specimen with malignant cells. The % tumor and % malignant cells are visually estimated and recorded. Using the marked H&E slide as a guide, the pathologist, with a single edge razor blade, cut away unnecessary and unwanted tissue from the orientated OCT specimen. The remaining specimen was removed from the OCT block and if too thick, was trimmed to a thickness of less than 1 mm and OCT was removed from the edges of the specimen. The trimmed specimen was then wrapped in aluminum foil, placed into a tissue cassette and returned "Biomarkers For Triple-Negative Breast Cancer" Attorney Docket No. 00H670-301084 to a -80°C freezer until shipped on dry ice to HudsonAlpha Institute for Biotechnology. The de- identified shipped tumor specimens had >50% tumor nuclei.

RNA-seq - Upon arrival, the 47 frozen breast tumor tissue specimens were weighed and transferred to 15 mL conical tubes containing 10OuL of ceramic beads (Lysing Matrix D from MP Biomedicals). Lysis buffer composed of RLT Buffer (Qiagen) supplemented with 1 % BME was added so that each tube contained 35 uL of buffer for each milligram of tissue. To homogenize the tissue the conical tubes containing tissue, ceramic beads, and buffer were then shaken in a MP Biomedicals FastPrep machine for 90 seconds at 6.5 meters per second. The homogenized tissue was stored at - 80° C. For analysis, total RNA was extracted from 350 uL of tissue homogenate (equivalent to 10 mg of tissue) using the Norgen Animal Tissue RNA Purification Kit with the optional Proteinase K treatment and on-column DNAse treatment according to the manufacturer's instructions (Norgen Biotek Corporation). Total RNA was quantified using the Qubit RNA Assay Kit and the Qubit 2.0 fluorometer (Invitrogen). RNA-seq libraries for each sample were constructed from 250 ng total RNA using the polyA selection and transposase-based non-stranded library construction (Tn-RNA-seq) described previously (15).

RNA-seq data analysis - RNA-seq read pairs (50 million per sample) were aligned to the transcriptome using TopHat v1.4.1 (16) and GENCODE version 9 (17) was used as the transcript reference. Bedtools (18) was used to calculate the read count per reference gene. Gene expression values (Fragments Per Kilobase of transcript Per Million reads, FPKMs) were calculated for each GENCODE transcript using Cufflinks 1.3.0 with the -u option (19). To identify subclusters of samples within our dataset the ConsensusClusterPlus R package (20) the analysis was performed on normalized gene read counts. The following k-means clustering options were used: maxK=10, reps=1000, clusterAlg="km", distance- 'Euclidean". Analysis of the Consensus Cumulative Distribution Function (CDF) and Delta Area Plot produced by the software indicated that at three clusters (k=3) the CDF reaches a maximum and there is diminishing increases in consensus at higher values of k.

The SAMseq function, part of the same R library (21 ) (http://cran.fhcrc.org/web/packages/samr/index.html), was used to identify genes that are significantly differentially expressed between consensus Clusters 1 , 2, and 3. Each tumor was classified as belonging to Cluster 1 , Cluster 2, or Cluster 3 and the gene read counts were analyzed using the following SAMseq options: resp.type- 'Multiclass", nperms=1000, fdr.output=0.05. The genes that were significantly differentially expressed between classes (q-value<5%), with a positive contrast in Cluster 1 "Biomarkers For Triple-Negative Breast Cancer" Attorney Docket No. 00H670-301084 and negative contrast in the other two clusters were identified as specifically highly expressed in Cluster 1. This process was repeated for Cluster 2 and Cluster 3.

SAMseq (21 ) was also used to identify genes that are significantly differentially expressed between tumors from patients who relapsed and tumors from patients who did not relapse. Gene read count values were the input for SAMseq and the following options were used: resp.type="Two class unpaired", fdr.output=0.05, nperms=1000. Genes with q-values <5% were considered significant.

A heatmap depicting the expression of differentially expressed genes across patient samples was created using the Heatplus library in R

(http://www.bioconductor.org/packaqes/release/bioc/html/Heatplus.html). The heatmap gene expression values were FPKMs with a plus 1 pseudocount added for accurate log base 2 transformation, i.e. log2 (FPKMs+1 ). Euclidean distance and complete linkage were used to cluster the genes. Patient samples were ordered based upon whether they experienced a relapse or not.

Kaplan-Meier curves and survival analysis was performed using RNA-seq FPKM values and an R script (http://kmplot.eom/analvsis/studies/Supplemental%20R%20script%201.R) (22). Patients were split into two groups using the optimal threshold, which split the lower tertile from the upper two tertiles.

Immunohistochemistry - Five archived de-identified TNBC tumor cases with sufficient tumor embedded in FFPE for immunohistochemical analysis were selected. Five 4 microns thick sections were cut from each FFPE block and placed on positively charged slides (plus slides). The slides were melted at 60°C for 30 minutes and placed in a Ventana automated stainer (Ventana Medical Systems, Inc.) for de-paraffinization with EZ Prep, treatment with Cell Conditioning Solution 1 (pH 8.0) 95°C for 64 minutes, and primary antibody incubation at a 1 :320 dilution for 40 minutes at 37°C. The primary antibody for detection of CD74 was obtained from Leica/Novocastra (catalog number NCL-LN2) and the primary antibody for detection of HLA-DPB1 was obtained from Sigma-Aldrich (catalog number HPA01 1078). The ultra View Universal DAB detection kit (Ventana Medical Systems, Inc.) was used to detect primary antibody staining followed by a hematoxylin counterstain for 8 minutes. The slides were washed with a mixture of water and Dawn soap to remove oil from the automated instrument, followed by water washes to remove the soap. A 30 second iodine wash was performed to remove any metal precipitates from the fixation, followed by a 30 second wash in sodium thiosulfate to remove residual iodine. The slides were then dehydrated in graded alcohols (70%, 95%, and 100%) followed by 4 xylene washes. Coverslips were applied and the slides were air-dried. An anatomic pathologist reviewed the stained slides and estimated the fraction of positive tumor cells and described the localization of the staining.

7. References

1. Dent R, Trudeau M, Pritchard Kl, et al: Triple-negative breast cancer: clinical features "Biomarkers For Triple-Negative Breast Cancer" Attorney Docket No. 00H670-301084 and patterns of recurrence. Clin Cancer Res 13:4429-34, 2007.

2. Blows FM, Driver KE, Schmidt MK, et al: Subtyping of breast cancer by immunohistochemistry to investigate a relationship between subtype and short and long term survival: a collaborative analysis of data for 10,159 cases from 12 studies. PLoS Med 7:e1000279, 2010.

3. Criscitiello C, Azim HA Jr, Schouten PC, et al: Understanding the biology of triple-negative breast cancer. Ann Oncol 23:vi13-8, 2012 (suppl 6).

4. Desmedt C, Haibe-Kains B, Wirapati P, et al: Biological processes associated with breast cancer clinical outcome depend on the molecular subtypes. Clin Cancer Res 14:5158-65, 2008.

5. Teschendorff AE, Miremadi A, Pinder SE, et al: An immune response gene expression module identifies a good prognosis subtype in estrogen receptor negative breast cancer. Genome Biol 8:R157,

2007.

6. Sabatier R, Finetti P, Cervera N, et al: A gene expression signature identifies two prognostic subgroups of basal breast cancer. Breast Cancer Res Treat 126:407-20, 2011.

7. Yau C, Esserman L, Moore DH, et al: A multigene predictor of metastatic outcome in early stage hormone receptor-negative and triple-negative breast cancer. Breast Cancer Res 12:R85, 2010.

8. Denkert C, Loibl S, Noske A, et al: Tumor-associated lymphocytes as an independent predictor of response to neoadjuvant chemotherapy in breast cancer. J Clin Oncol 28:105-13, 2010.

9. Adams S, Gray RJ, Demaria 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 2014 (Epub ahead of print).

10. Rody A, Holtrich U, Pusztai L, et al: T-cell metagene predicts a favorable prognosis in estrogen receptor-negative and HER2-positive breast cancers. Breast Cancer Res 11 :R15, 2009.

11. Iglesia MD, Vincent BG, Parker JS, et al: Prognostic B-cell signatures ssing mRNA-seq in patients with subtype-specific breast and ovarian cancer. Clin Cancer Res 20:3818-29, 2014.

12. Loi S: Host antitumor immunity plays a role in the survival of patients with newly diagnosed triple-negative breast cancer. J Clin Oncol 2014 (Epub ahead of print).

13. Xu X, Zhang Y, Williams J, et al: Parallel comparison of lllumina RNA-seq and Affymetrix microarray platforms on transcriptomic profiles generated from 5-aza-deoxy-cytidine treated HT-29 colon cancer cells and simulated datasets. BMC Bioinformatics 14:S1 , 2013 (suppl 9).

14. Guo Y, Sheng Q, Li J, et al: Large scale comparison of gene expression levels by microarrays and RNAseq using TCGA data. PLoS One 2013 8:e71462, 2013.

15. Gertz J, Varley KE, Davis NS, et al: Transposase mediated construction of RNA-seq libraries. Genome Res 22:134-141 , 2012. "Biomarkers For Triple-Negative Breast Cancer" Attorney Docket No. 00H670-301084

16. Trapnell C, Pachter L, Salzberg SL: TopHat: discovering splice junctions with RNA-Seq. Bioinformatics 25: 1105-1 11 1 , 2009.

17. Harrow J, Denoeud F, Frankish A, et al: GENCODE: producing a reference annotation for ENCODE. Genome Biol 7:S4 1-9, 2006 (suppl 1 ).

18. Quinlan AR, Hall IM: BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26:841 -842, 2010.

19. Trapnell C, Williams BA, Pertea G, et al: Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat Biotechnol 28:511 - 515, 2010.

20. Wilkerson MD, Hayes DN: ConsensusClusterPlus: a class discovery tool with confidence assessments and item tracking. Bioinformatics 26:1572-1573, 2010.

21. Li J, Tibshirani R: Finding consistent patterns: a nonparametric approach for identifying differential expression in RNA-Seq data. Stat Methods Med Res 22:519-536, 2013.

22. Mihaly Z, Gyorffy B: Improving pathological assessment of breast cancer by employing array- based transcriptome analysis. Microarrays 2:228-242, 2013.

23. Gyorffy B, Lanczky A, Eklund AC, et al: An online survival analysis tool to rapidly assess the effect of 22,277 genes on breast cancer prognosis using microarray data of 1 ,809 patients. Breast Cancer Res Treat 123:725-731 , 2010.

24. Li Q, Birkbak NJ, Gyorffy B, et al: Jetset: selecting the optimal microarray probe set to represent a gene. BMC Bioinformatics 12:474, 201 1.

25. Mihaly Z, Kormos M, Lanczky A, et al: A meta-analysis of gene expression-based biomarkers predicting outcome after tamoxifen treatment in breast cancer. Breast Cancer Res Treat 140:219-232, 2013.

26. Boersma BJ, Reimers M, Yi M, et al: A stromal gene signature associated with inflammatory breast cancer. Int J Cancer 122:1324-32, 2008.

27. Auer PL, Doerge RW: Statistical design and analysis of RNA sequencing data. Genetics 185:405-16, 2010.

28. Zwiener I, Frisch B, Binder H: Transforming RNA-seq data to improve the performance of prognostic gene signatures. PLoS One 9:e85150, 2014.

29. Cox DR, Oakes D: Analysis of Survival Data. London, NY, Chapman & Hall Ltd, 1984.

30. Efron, B: The efficiency of Cox's likelihood function for censored data. J Am Stat Assoc 72:557- 565, 1977.

31. Lehmann BD, Bauer JA, Chen X, et al: Identification of human triple-negative breast cancer subtypes and preclinical models for selection of targeted therapies. J Clin Invest 121 : 2750-2767, 2011. "Biomarkers For Triple-Negative Breast Cancer" Attorney Docket No. 00H670-301084

32. Chen X, Li J, Gray WH, et al: TNBCtype: A subtyping tool for triple-negative breast cancer. Cancer Inform 11 :147-156, 2012.

33. Moller P, Mattfeldt T, Gross C, et al: Expression of HLA-A, -B, -C, -DR, -DP, -DQ, and of HLA- D-associated invariant chain (li) in non-neoplastic mammary epithelium, fibroadenoma, adenoma, and carcinoma of the breast. Am J Pathol 135:73-83, 1989.

34. Ruiz-Cabello F, Klein E, Garrido F: MHC antigens on human tumors. Immunol

Lett 29:181-9, 1991.

35. Oldford SA, Robb JD, Codner D, et al: Tumor cell expression of HLA-DM associates with a Th1 profile and predicts improved survival in breast carcinoma patients. Int Immunol 18:1591 -602, 2006. 36. Gastl G, Marth C, Leiter E, et al: Effects of human recombinant alpha 2 arg-interferon and gamma-interferon on human breast cancer cell lines: dissociation of antiproliferative activity and induction of HLA-DR antigen expression. Cancer Res 45:2957-61 , 1985.

37. Mortara L, Castellani P, Meazza R, et al: CIITA-induced MHC class II expression in mammary adenocarcinoma leads to a Th1 polarization of the tumor microenvironment, tumor rejection, and specific antitumor memory. Clin Cancer Res 12:3435-43, 2006.

38. Meazza R, Comes A, Orengo AM, et al: Tumor rejection by gene transfer of the MHC class II transactivator in murine mammary adenocarcinoma cells. Eur J Immunol 33:1183-92, 2003.

39. Frangione V, Mortara L, Castellani P, et al: CIITA-driven MHC-II positive tumor cells: preventive vaccines and superior generators of antitumor CD4+ T lymphocytes for immunotherapy. Int J Cancer 127:1614-24, 2010.

40. Accolla RS, Lombardo L, Abdallah R, et al: Boosting the MHC class ll-restricted tumor antigen presentation to CD4+ T helper cells: A critical issue for triggering protective immunity and re-orienting the tumor microenvironment toward an anti-tumor state. Front Oncol 4:32, 2014.

41. Armstrong TD, Clements VK, Martin BK, et al: Major histocompatibility complex class II- transfected tumor cells present endogenous antigen and are potent inducers of tumor-specific immunity. Proc Natl Acad Sci U S A 94:6886-91 , 1997.

42. Hillman GG, Kallinteris NL, Lu X, et al: Turning tumor cells in situ into T-helper cell-stimulating, MHC class II tumor epitope-presenters: immuno-curing and immuno-consolidation. Cancer Treat Rev 30:281-90, 2004.

43. Jabrane-Ferrat N, Campbell MJ, Esserman LJ, et al: Challenge with mammary tumor cells expressing MHC class II and CD80 prevents the development of spontaneously arising tumors in MMTV-neu transgenic mice. Cancer Gene Ther 13:1002-10, 2006. "Biomarkers For Triple-Negative Breast Cancer" Attorney Docket No. 00H670-301084

44. Thompson JA, Dissanayake SK, Ksander BR, et al: Tumor cells transduced with the MHC class II transactivator and CD80 activate tumor-specific CD4+ T cells whether or not they are silenced for invariant chain. Cancer Res 66:1147-54, 2006.

45. Strawbridge AB, Blum JS: Autophagy in MHC class II antigen processing. Curr Opin Immunol 19:87-92, 2007.

46. Schmid D, Pypaert M, Munz C: MHC class II antigen loading compartments continuously receive input from autophagosomes. Immunity 26:79-92, 2007.

47. Brown SD, Warren RL, Gibb EA, et al: Neo-antigens predicted by tumor genome meta-analysis correlate with increased patient survival. Genome Res 24:743-50, 2014.

48. Cancer Genome Atlas Network: Comprehensive molecular portraits of human breast tumours. Nature 490:61-70, 2012.

49. Bos R, Marquardt KL, Cheung J, et al: Functional differences between low- and high-affinity CD8(+) T cells in the tumor environment. Oncoimmunology 1 :1239-1247, 2012.

50. Bevan MJ: Helping the CD8(+) T-cell response. Nat Rev Immunol 4:595-602, 2004.

B. CONCLUSIONS

It is to be understood that any given elements of the disclosed embodiments of the invention may be embodied in a single structure, a single step, a single substance, or the like. Similarly, a given element of the disclosed embodiment may be embodied in multiple structures, steps, substances, or the like.

The foregoing description illustrates and describes the processes, machines, manufactures, compositions of matter, and other teachings of the present disclosure. Additionally, the disclosure shows and describes only certain embodiments of the processes, machines, manufactures, compositions of matter, and other teachings disclosed, but, as mentioned above, it is to be understood that the teachings of the present disclosure are capable of use in various other combinations, modifications, and environments and is capable of changes or modifications within the scope of the teachings as expressed herein, commensurate with the skill and/or knowledge of a person having ordinary skill in the relevant art. The embodiments described hereinabove are further intended to explain certain best modes known of practicing the processes, machines, manufactures, compositions of matter, and other teachings of the present disclosure and to enable others skilled in the art to utilize the teachings of the present disclosure in such, or other, embodiments and with the various modifications required by the particular applications or uses. Accordingly, the processes, machines, manufactures, compositions of matter, and other teachings of the present disclosure are not intended to limit the exact embodiments and examples disclosed herein. Any section headings herein are provided "Biomarkers For Triple-Negative Breast Cancer" Attorney Docket No. 00H670-301084 only for consistency with the suggestions of 37 C.F.R. § 1.77 or otherwise to provide organizational queues. These headings shall not limit or characterize the invention(s) set forth herein.

"Biomarkers For Triple-Negative Breast Cancer" Attorney Docket No. 00H670-301084

TABLE 1

All reference sequences are incorporated herein by reference. "Biomarkers For Triple-Negative Breast Cancer" Attorney Docket No. 00H670-301084

TABLE 1 (continued)

All reference sequences are incorporated herein by reference.

"Biomarkers For Triple-Negative Breast Cancer" Attorney Docket No. 00H670-301084

TABLE 2

"Biomarkers For Triple-Negative Breast Cancer" Attorney Docket No. 00H670-301084

"Biomarkers For Triple-Negative Breast Cancer" Attorney Docket No. 00H670-301084

"Biomarkers For Triple-Negative Breast Cancer" Attorney Docket No. 00H670-301084

Claims

"Biomarkers For Triple-Negative Breast Cancer" Attorney Docket No. 00H670-301084 CLAIMS What is claimed:

1. A method of prognosticating a risk of relapse of triple-negative breast cancer (TNBC) in a subject in need thereof, the method comprising: (a) measuring a level of expression of each of a set of genes comprising at least one gene selected from Table 1 in a TNBC tumor from the subject; (b) comparing the level of expression of each of the set of genes to a corresponding benchmark value of expression of each of the set of genes; and (c) prognosticating an elevated risk of relapse if the level of expression of at least one of the set of genes is below the corresponding benchmark value.

2. The method of claim 1 , wherein step (a) comprises: obtaining mRNA from the TNBC tumor;

synthesizing a DNA reverse transcript of at least a portion of the mRNA; and hybridizing the DNA reverse transcript with one or more probes, the probes each comprising a polynucleotide of at least 15 bp that hybridizes under highly stringent conditions with a target sequence of at least 15 bp, wherein said target sequence of at least 15 bp is present in a cDNA of one of the set of genes.

3. The method of claim 2, comprising detecting hybridization between the DNA reverse transcript and the one or more probes.

4. The method of claim 1 , wherein step (a) comprises: obtaining protein from the TNBC tumor; contacting the protein with one or more probes, the probes each comprising a ligand group that specifically binds to a protein product of one of the set of genes, and a reporter.

5. The method of claim 4, comprising detecting binding between the protein product and the one or more probes.

6. The method of claim 1 , wherein the method is an ex vivo method.

7. The method of claim 1 , wherein the set of genes includes LPAR5.

8. The method of any one of claim 1 , wherein the set of genes includes LRRK2.

9. The method of claim 1 , wherein the set of genes includes POLR3GL.

10. The method of claim 1 , wherein the set of genes includes PTGDS.

11. The method of claim 1 , wherein the at least one gene is selected from Table 2.

12. The method of claim 1 1 , wherein the set of genes includes CIITA.

13. The method of claim 1 1 , wherein the set of genes includes CTSH.

14. The method of claim 1 1 , wherein the set of genes includes FGD3.

15. The method of claim 1 1 , wherein the set of genes includes HLA-DPB2.

16. The method of claim 15, wherein the set of genes includes at least 10 genes selected from Table 1.

17. The method of claim 16, wherein the set of genes includes 24 genes selected from Table 1.

18. The method of claim 16, wherein the set of genes includes at least 10 genes selected from Table 2. "Biomarkers For Triple-Negative Breast Cancer" Attorney Docket No. 00H670-301084

19. The method of claim 1 , wherein the set of genes comprises at least two genes selected from Table 1.

20. The method of claim 19, wherein the set of genes comprises CIITA.

21. The method of claim 20, wherein the set of genes includes LPAR5.

22. The method of claim 20, wherein the set of genes includes LRRK2.

23. The method of claim 20, wherein the set of genes includes POLR3GL.

24. The method of claim 20, wherein the set of genes includes PTGDS.

25. The method of claim 20, wherein the set of genes is selected from Table 2.

26. The method of claim 25, wherein the set of genes includes CD74.

27. The method of claim 25, wherein the set of genes includes HLA-DPB2.

28. The method of claim 25, wherein the set of genes includes CTSH.

29. The method of claim 25, wherein the set of genes includes FDG3.

30. A method of treatment or prophylaxis of a subject at risk of relapse of triple-negative breast cancer (TNBC), the method comprising: prognosticating the risk of relapse of TNBC in the subject by performing the method of claim 1 ; and providing therapeutic or prophylactic treatment for the TNBC to the subject based on whether the subject is prognosticated to have an elevated risk of relapse.

31. The method of claim 30, wherein the therapeutic or prophylactic treatment comprises increased monitoring of the subject's condition.

32. The method of claim 30, wherein the therapeutic or prophylactic treatment comprises radiotherapy.

33. The method of claim 30, wherein the therapeutic or prophylactic treatment comprises chemotherapy.

34. The method of claim 30, wherein the therapeutic or prophylactic treatment comprises surgical intervention.

35. The method of claim 34, wherein the therapeutic or prophylactic treatment comprises mastectomy.

36. A kit for analyzing genetic expression of TNBC in a subject, comprising: a means for measuring the expression of a first gene selected from Table 1 ; and a means for detecting a second gene selected from Table 1.

37. The kit of claim 36, wherein the kit is for a purpose of prognosticating a risk of relapse of TNBC.

38. The kit of claim 36, wherein: the means for measuring the expression of the first gene is a means for detecting a first protein product of the first gene; and the means for measuring the expression of the second gene is a means for detecting a second protein product of the second gene.

39. The kit of claim 38, wherein: the means for detecting the first protein product is a first probe comprising a first ligand group that specifically binds to a first protein product of the first gene; and the "Biomarkers For Triple-Negative Breast Cancer" Attorney Docket No. 00H670-301084 means for detecting the second protein product is a second probe comprising a second ligand group that specifically binds to a second protein product of the second gene.

40. The kit of claim 39, wherein the first ligand group is an immunoglobulin.

41. The kit of claim 39, wherein the second ligand group is an immunoglobulin.

42. The kit of claim 39, wherein the first probe and the second probe are immobilized to a surface.

43. The kit of claim 36, wherein: the means for measuring the expression of the first gene is a means for detecting a first target sequence of at least 15 bp that is present in a first cDNA or mRNA of the first gene; and the means for measuring the expression of the second gene is a means for detecting a second target sequence of at least 15 bp that is present in a second cDNA or mRNA of the second gene.

44. The kit of claim 43, wherein: the means for detecting the first target sequence is a first probe comprising a first polynucleotide of at least 15 bp that hybridizes under highly stringent conditions with the first target sequence of at least 15 bp that is present in the first cDNA or mRNA of the first gene; and the means for detecting the second target sequence is a second probe comprising a second polynucleotide of at least 15 bp that hybridizes under highly stringent conditions with the second target sequence of at least 15 bp that is present in the second cDNA or mRNA of the second gene.

45. The kit of claim 44, comprising a container of a reverse transcriptase.

46. The kit of claim 44 or claim 39, wherein the first probe comprises a first reporter, and the second probe comprises a second reporter.

47. The kit of claim 46, wherein the first reporter is selected from the group consisting of: a radionuclide, a stable isotope, a fluorophore, a chromophore, an enzyme, a magnetic particle, and a quantum dot; and the second reporter selected from the group consisting of: a radionuclide, a fluorophore, a chromophore, an enzyme, a magnetic particle, and a quantum dot.

48. The kit of claim 44, wherein the first polynucleotide is single stranded DNA; and wherein the second polynucleotide is single stranded DNA.

49. The kit of claim 44, wherein the first probe and the second probe are components of a DNA array.

50. The kit of claim 44, wherein the first probe and the second probe are components of a DNA microarray.

51. The kit of claim 44, wherein the first polynucleotide is at least 20 bp and the second polynucleotide is at least 20 bp.

52. The kit of claim 44, wherein the first polynucleotide is at least 25 bp and the second polynucleotide is at least 25 bp.

53. The kit of claim 36, wherein the first gene is CIITA.

54. The kit of claim 36, wherein the first gene is CIITA and the second gene is CD74.

40 "Biomarkers For Triple-Negative Breast Cancer" Attorney Docket No. 00H670-301084

55. The ki of claim 36, wherein the first gene is LPAR5.

56. The ki of claim 36, wherein the f irst gene is LRRK2.

57. The ki of claim 36, wherein the fi irst gene is POLR3GL.

58. The ki of claim 36, wherein the first gene is PTGDS.

59. The ki of claim 36, wherein the first gene is selected from Table 2.

60. The ki of claim 59, wherein the first gene is HLA-DPB2.

61. The ki of claim 59, wherein the first gene is CTSH.

62. The ki of claim 59, wherein the second gene is selected from Table 2.

63. The ki of claim 36, wherein the second gene is CIITA.

64. The ki of claim 36, wherein the second gene is LPAR5.

65. The ki of claim 36, wherein the second gene is LRRK2.

66. The ki of claim 36, wherein :he second gene is POLR3GL.

67. The ki of claim 36, wherein :he second gene is selected from Table 2.

68. The ki of claim 67, wherein :he second gene is HLA-DPB2.

69. The ki of claim 67, wherein :he second gene is CTSH.

70. The ki of claim 67, wherein the second gene is FGD3.

71. The ki of claim 36, comprising a means for measuring the expression of a set of genes including one or mo^■e additional genes selected from Table 1.

72. The ki of claim 71 , wherein the set of genes comprises CIITA.

73. The ki of claim 71 wherein the set of genes includes LPAR5.

74. The ki of claim 71 wherein the set of genes includes LRRK2.

75. The ki of claim 71 wherein the set of genes includes POLR3GL.

76. The ki of claim 71 wherein the set of genes includes PTGDS.

77. The ki of claim 71 wherein the set of genes is selected from Table 2.

78. The ki of claim 71 wherein the set of genes includes CD74.

79. The ki of claim 71 wherein the set of genes includes HLA-DPB2.

80. The ki of claim 71 wherein the set of genes includes CTSH.

81. The ki of claim 71 , wherein the set of genes includes FDG3.