AU2016210735B2 - Gene expression markers for predicting response to chemotherapy - Google Patents

Abstract

The present invention provides sets of genes the expression of which is important in the prognosis of cancer. In particular, the invention provides gene expression information 5 useful for predicting whether cancer patients are likely to have a beneficial treatment response to chemotherapy. 8026117_1 (GHMatters) P62417.AU.5

Description

Gene Expression Markers for Predicting Response to Chemotherapy 2016210735 05 Aug 2016

The entire disciosure in the compJete specification of our AustraJian Patent Application No. 2013206082 is by this cross-reference incorporated into the present 5 specification.

Background of the Invention

Field of the Invention

The present invention provides sets of genes the expression of which is important in 10 the prognosis of cancer. In particular, the invention provides gene expression information useful for predicting whether cancer patients are likely to have a beneficial treatment response to chemotherapy.

Description of the Related Art 15 Oncologists have a number of treatment options available to them, including different combinations of chemotherapeutic dnrgs that are characterized as "standard of care," and a number of drugs that do not carry a label claim for particular cancer, but for which there is evidence of efficacy in that cancer. Best likelihood of good treatment outcome requires that patients be assigned to optimal available cancer treatment, and that this assignment be made 20 as quickly as possible following diagnosis. In particular, it is important to determine the likelihood of patient response to “standard of care” chemotherapy because chemotherapeutic drugs such as anthracyclines and taxanes have limited efficacy and are toxic. The identification of patients who are most or least likely to respond thus could increase the net benefit these drugs have to offer, and decrease the net morbidity and toxicity, via more 25 intelligent patient selection.

Currently, diagnostic tests used in clinical practice are single analyte, and therefore do not capture the potential value of knowing relationships between dozens of different markers. Moreover, diagnostic tests are ftequently not quantitative, relying on immunohistochemistry. This method often yields different results in different laboratories, in part because the 30 reagents are not standardized, and in part because the interpretations are subjective and cannot be easily quantified. RNA-based tests have not often been used because of the problem ofRNA degradation over time and the fact that it is difficult to obtain ftesh tissue samples ftom patients for analysis. Fixed paraffin-embedded tissue is more readily available 1

8026117.1 (GHMatters) P62417.AUS and methods have been established to detect RNA in fixed tissue. However, these methods typically do not allow for the shrdy of large numbers of genes (DNA or RNA) ftom small amounts of material. Thus, traditionally fixed tissue has been rarely used other than for immunohistochhemistry detection of proteins. 2016210735 05 Aug 2016 5 In the last few years, several groups have published shrdies concerning the classification of various cancer types by microarray gene expression analysis (see, e.g. Golub et al., Science 286:531-537 (1999): Bhattachaijae el al., Proc. Natl. Acad. Sci. USA 98:13790-13795 (2001): Chen-Hsiang et al., Bioinformatics 17 (Suppl. 1):S316-S322 (2001): Ramaswamy et al., Proc. Natl. Acad. Sci. USA 98:15149-15154 (2001)). Certain 10 classifications of human breast cancers based on gene expression patterns have also been reported (Martin et al., Cancer Res. 60:2232-2238 (2000): West et al., Proc. Natl. Acad. Sci. USA 98:11462-11467 (2001): Sorlie et al., Proc. Natl. Acad. Sci. USA 98:10869-10874 (2001): Yan et al., Cancer Res. 61:8375-8380 (2001)). However, these studies mostly focus on improving and refining the already established classification of various types of cancer, 15 including breast cancer, and generally do not provide new insights into the relationships of the differentially expressed genes, and do not link the findings to treatment strategies in order to improve the clinical outcome of cancer therapy.

Although modem molecular biology and biochemistry have revealed hundreds of genes whose activities influence the behavior of tumor cells, state of their differentiation, and 20 their sensitivity or resistance to certain therapeutic dmgs, with a few exceptions, the status of these genes has not been exploited for the purpose of routinely making clinical decisions about dmg treatments. One notable exception is the use of estrogen receptor (ER) protein expression in breast carcinomas to select patients to treatment with anti-estrogen drugs, such as tamoxifen. Another exceptional example is the use of ErbB2 (Her2) protein expression in 25 breast carcinomas to select patients with the Her2 antagonist dmg Herceptin Inc., South San Francisco, CA).

Despite recent advances, the challenge of cancer treatment remains to target specific treatment regimens to pathogenically distinct tumor types, and ultimately personalize tumor treatment in order to maximize outcome. Hence, a need exists for tests that simultaneously 30 provide predictive information about patient responses to the variety of treatment options. This is particularly tme for breast cancer, the biology of which is poorly understood. It is clear that the classification of breast cancer into a few subgroups, such as the ErbB2 positive subgroup, and subgroups characterized by low to absent gene expression of the estrogen 2 8026117-1 (GHMahers) Ρ62417.Α٧.5 ح receptor (ER) and a few additional transcriptional factors (Pero 2016210735 lOAug CN (2000)), docs not reflect the cellular and molecular heterogeneity of breast cancer, and does not allow the design oftreatment strategies maximizing patient response.

Breast cancer is the most common type of cancer among women in the tlnited States and is 5 the leading cause of cancer deaths among women ages 40 -59. Therefore, there is a particularly great need for a clinically validated breast cancer test predictive ofpatient response to chemotherapy.

It is to be understood that if any prior art publication is referred to herein, such reference does not constitute an admission that the publication forms a part of the common 10 general knowledge in the art in Australia or any other country.

Summary of the Invention

The present invention provides gene sets usefirl in predicting the response of cancer, e.g. breast cancer patients to chemotherapy. In addition, the invention provides a clinically 15 validated cancer, e.g. breast cancer, test, predictive of patient response to chemotherapy, using multi-gene RNA analysis. The present invention accommodates the use of archived paraffin-embedded biopsy material for assay of all markers in the relevant gene sets, and therefore is compatible with the most widely available type ofbiopsy material. A first aspect provides a method for determining the likelihood of a beneficial 20 response of a human patient with breast cancer to an anthracycline-based chemotherapy, comprising: determining a normalized expression level of an RNA transcript of BAGl in a breast cancer sample obtained fiom said patient؛ and predicting the likelihood of a beneficial response of the patient to the anthracycline-based chemotherapy using said normalized BAGl expression level, wherein said normalized BAGl expression level is negatively 25 correlated with the likelihood of a beneficial response of the patient to the anthracycline-based chemotherapy.

Also disclosed is a method for predicting the response of a subject diagnosed with cancer to chemotherapy comprising determining the expression level of one or more prognostic RNA transcripts or their expression products in a biological sample comprising 30 cancer cells obtained from said subject, wherein the predictive RNA transcri transcript of one or more genes selected fiom the group consisting of TBP؛ ITT.2؛ ABCC5؛ CD18؛ GATA3؛ DICERl؛ MSH3؛ GBPl؛ IRSl؛ CD3z؛ fasl؛ TUBB؛ BAD؛ ERCCl؛ MCM6; 3 9366419-1 (GHMatters) P62417.AUS 10-Aug-17 ؛ΜΑΡΚ14 ؛NPD009 ؛CEGPl ؛A.Catenin ؛ΑΚΤ2 ؛E2F1 ؛KRT18; ESRRG ؛GGPSl ؛APC ؛PR ج ؛CD9 ؛IGFIR ؛BBC3 ؛ERBB4; FUS ؛ΜΤΑ1 ؛FHIT ؛FBX05 ؛G.Catenin ؛N RbWXl; ID2) ؛SGCB ؛HFA.DPBl ؛ERKl ؛STAT3 ؛CDC20 ؛RAFBPl ؛rhoC ؛IGFBP5 ؛MUCl ؛ΤΡ53ΒΡ1 ؛CCNDl ؛ΙΕ6 ؛CDC25B ؛RAPIGDSI ؛ErbB3 ؛ΜΜΡ12 ؛CRIP2 ؛MGMT ؛DHPS ؛CGA FTO; ؛VCAMl ؛51037.Contig ؛ΑΚ055699 ؛CRABPl ؛Hepsin ؛DR4 ؛PRKCD ؛5 CYBA ؛COFlAl ؛CD31 ؛SEMA3F ؛GBP2 ؛MCM2 ؛ZNF38 ؛MCPl ؛RASSFl ؛2.GRB7; ΑΚΑΡ CCNBl, ΤΚ1, ErbB2١ ؛RAB6C ؛PTPDl ؛Wnt.5a ؛STATl ؛COL1A2 ؛ΑΚΤ1 ؛BAGl ؛ER2 BIRC5, STK6, ΜΚΙ67, ΜΥΒΕ2, ΜΜΡ11, CTSF2, CD68, GSTMl, BCF2, ESRl wherein 3a 2016210735 lOAug 9366419-1 (GHMatters)P62417.AU.5 10-Aug-17 (a) for every unit of increased expression of one or more of ILT.2; CD18; GBPl; CD3z; fasl: MCM6; E2F1; Π)2; FBX05; CDC20; HUA.DPBl; CGA; ΜΜΡ12; CDC25B: IL6; CYBA; DR4; CRABPl: Contig.51037; VCAMl; FYN; GRB7; ΑΚΑΡ.2: RASSFl; MCPl; MCM2; GBP2; CD31; ER2; STATl; ΤΚ1; ERBB2, CCNBl, BJRC5, STK6, ΜΚΙ67, 2016210735 05 Aug 2016 5 MYBL2, ΜΜΡ11, CTSL2 and CD68; or the conesponding expression product, said subject is predicted to have an increased likelihood of response to chemotherapy; and (b) for every unit of increased expression of one or more of TBP; ABCC5; GATA3; DICERl; MSH3; IRSl; TUBB; BAD; ERCCl; PR; APC; GGPSl; KRT18; ESRRG; ΑΚΤ2; A.Catenin; CEGPl; NPD009; ΜΑΡΚ14; RUNXl; G.Catenin; FHIT; 10 ΜΤΑ1; ErbB4; FUS; BBC3; IGFIR; CD9; ΤΡ53ΒΡ1; MUCl; IGFBP5; rhoC; RALBPl; STAT3; ERKl; SGCB; DHPS; MGMT; CRJP2; ErbB3; RAPIGDSI; CCNDl; PRKCD; Hepsin; ΑΚ055699; ZNF38; SEMA3F; COLlAl; BAGl; ΑΚΤ1; COL1A2; Wnt.5a; PTPDl; RAB6C; GSTMl, BCL2, ESRl; or the conesponding expression product, said subject is predicted to have a decreased likelihood of response to chemotherapy. 15 In a particular embodiment, in the above method the predictive RNA transcript is the transcript of one or more genes selected ftom the group consisting of TBP; 1LT.2; ABCC5; CD18; GATA3; DICERl; MSH3; GBPl; IRSl; CD3z; fasl; TUBB; BAD; ERCCl; MCM6; PR; APC; GGPSl; KRT18; ESRRG; E2F1; ΑΚΤ2; A.Catenin; CEGPl; NPD009; ΜΑΡΚ14; RUNXl; 1D2; G.Catenin; FBX05; FHIT; ΜΤΑ1; ERBB4; FUS; BBC3; IGFIR; CD9; 20 ΤΡ53ΒΡ1; MUCl; IGFBP5; rhoC; RATBPl; CDC20; STAT3; ERKl; fflADPBl; SGCB; CGA; DHPS; MGMT; CR1P2; ΜΜΡ12; ErbB3; RAPIGDSI; CDC25B; L6; cc^l; CYBA; PRKCD; DR4; Hepsin; CRABPl; ΑΚ055699; Contig.51037; VCAMl; FYN; GRB7; ΑΚΑΡ.2; RASSFl; MCPl; ZNF38; MCM2; GBP2; SEMA3F; CD31; COLlAl; ER2; BAGl; ΑΚΤ1; COL1A2; STATl; Wnt.5a; PTPDl; RAB6C; and ΤΚ1. 25 In another embodiment, the response is a complete pathological response.

In a prefened embodiment, the subject is a human patient.

The cancer can be any types of cancer but preferably is a solid tumor, such as breast cancer, ovarian cancer, gastric cancer, colon cancer, pancreatic cancer, prostate cancer and lung cancer.

30 If the tumor is breast cancer, it can, for example, be invasive breast cancer, or stage II or stage III breast cancer.

In a particular embodiment, the chemotherapy is adjuvant chemotherapy.

In another embodiment, the chemotherapy is neoadjuvant chemotherapy. 4 8026117-1 (GHMatters) Ρ62417.Α٧.5

The neoadjuvant chemotherapy may, for example, comprise the administration of a ح 2016210735 lOAug CN taxane derivativ, such as docetaxel andor paclitaxel, andor other anti-cancer agents, such as, members of the anthracycline class of anti-cancer agents, doxombicin, topoisomerase inhibitors, etc. 5 The method may involve determination of the expression levels of at least two, or at least five, or at least ten, or at least 15 of the prognostic transcripts listed above, or their expression products.

The biological sample may be e.g. a tissue sample comprising cancer cells, where the tissue can be fixed, paraffin-embedded, or fresh, or fiozen. 10 In a particular embodiment, the tissue is fiom fine needle, core, or other types of biopsy.

In another embodiment, the tissue sample is obtained by fine needle aspiration, bronchial lavage, or transbronchial biopsy.

The expression level of said prognostic RNA transcript or transcripts can be 15 determined, for example, by RT-PCR or an other PCR-based method, immunohistochemistry, proteomics techniques, or any other methods known in the art, or their combination.

In an embodiment, the assay for the measurement of said prognostic RNA transcripts or their expression products is provided is provided in the form of a kit or kits. 20 Also disclosed is an array comprising polynucleotides hybridizing to a phrrality of the ؛IRSl ؛CD18; GATA3; DICERl: MSH3; GBPl ؛ABCC5 ؛2.ILT ؛following genes: TBP ؛E2F1 ؛ESRRG ؛KRT18 ؛GGPSl ؛APC ؛PR ؛MCM6 ؛ERCCl ؛TUBB; BAD ؛fasl ؛CD3z ؛FHIT ؛FBX05 ؛G.Catenin ؛RUNXl; ID2 ؛ΜΑΡΚ14 ؛NPD009 ؛CEGPl ؛A.Catenin ؛ΑΚΤ2 ؛RAEBPl ؛rhoC ؛IGFBP5 ؛MUCl ؛ΤΡ53ΒΡ1 ؛CD9 ؛IGFIR ؛BBC3 ؛FUS ؛ERBB4 ؛ΜΤΑ1 ؛ΜΜΡ12 ؛CRIP2 ؛MGMT ؛DHPS ؛CGA ؛SGCB ؛ERKl; HLA.DPBl ؛STAT3 ؛25 CDC20 ؛CRABPl ؛Hepsin ؛DR4 ؛PRKCD ؛CYBA ؛CCNDl ؛IL6 ؛CDC25B ؛RAPIGDSI ؛ErbB3 ؛ZNF38 ؛MCPl ؛RASSFl ؛2.GRB7; ΑΚΑΡ ؛FYN ؛VCAMl ؛51037.Contig ؛ΑΚ055699 ؛Wnt.5a ؛STATl ؛COL1A2 ؛ΑΚΤ1 ؛BAGl ؛ER2 ؛COLlAl ؛CD31 ؛SEMA3F ؛MCM2; GBP2 ,CCNBl, BIRC5, STK6, ΜΚΙ67, MYBL2, ΜΜΡ11, CTSL2 ΤΚ1, ErbB2١ ؛RAB6C ؛PTPDl 30 CD68, GSTMl, BCL2, ESRl.

In an embodiment, the array compises polynucleotides hybridizing to a plurality of ؛IRSl ؛GBPl ؛MSH3 ؛DICERl ؛GATA3 ؛CD18 ؛ABCC5 ؛2.ILT ؛the following genes: TBP ؛E2F1 ؛ESRRG ؛KRT18 ؛GGPSl ؛APC ؛PR ؛MCM6 ؛ERCCl ؛BAD ؛TUBB ؛fasl ؛CD3z 5 9366419-1 (GHMatters) Ρ62417.Α٧.5 10-Aug-17 ΑΚΤ2; A.Catenin; CEGPl; NPD009; ΜΑΡΚ14; RiXl; 1; G.Catenin; FBX05; FHIF; ΜΤΑ1; ERBB4; FUS; BBC3; IGFIR; CD9; ΤΡ53ΒΡ1; MUCl; IGFBP5; rhoC; RALBPl CDC20; SFAF3; ERKl; HLA.DPBl; SGCB; CGA; DHPS; MGMF; CR1P2; ΜΜΡ12; ErbB3; RAPIGDSI; CDC25B; IL6; CCil; CYBA; PRKCD; DR4; Hepsin; CRABPl; 5 ΑΚ055699; Contig.51037; VCAMl; FYN; GRB7; ΑΚΑΡ.2; RASSFl; MCPl; ZNF38; 2016210735 05 Aug 2016 MCM2; GBP2; SEMA3F; CD31; COLlAl; ER2; BAGl; AKFl; C0L1A2; STATl; Wnt.5a; PTPDl; RAB6C; FKl.

In another embodiment, the array comprises polynucleotides hybridizing to a plurality of the following genes: ILF.2; CD18; GBPl؛ CD3z; fasl: MCM6; E2F1; ID2; 10 FBX05; CDC20; HLA.DPBl; CGA; Μ^12; CDC25B: ٤6ذ CYBA: DR4; CRABPl; Contig.51037; VCAMl; FYX; GRB7; ΑΚΑΡ.2; RASSFl; MCPl; MCM2; GBP2; CD31; ER2; SFAFl; FKl; ERBB2, CCNBl, B1RC5, SFK6, ^167, MYBL2, ΜΜΡ11, CFSL2 and CD68.

In yet another embodiment, the array comprises polynucleotides hybridizing to a 15 plurality of the following genes: ILF.2; CD18; GBPl; CD3z; fasl; MCM6; E2F1; 1D2; FBX05; CDC20; HLA.DPBl; CGA; Μ^12; CDC25B; ذ6ع CYBA; DR4; CRABPl; Contig.51037; VCAMl; FYN; GRB7; ΑΚΑΡ.2; RASSFl; MCPl; MCM2; GBP2; CD31; ER2; SFAFl; FKl

In a still further embodiment, the array comprises polynucleotides hybridizing to a 20 plurality of the following genes: FBP; ABCC5; GAFA3; DICERl; MSH3; IRSl; FUBB; BAD; ERCCl; PR; APC; GGPSl; KRF18; ESRRG; AKF2; A.Catenin; CEGPl; NPD009; ΜΑΡΚ14; RiXl; G.Catenin; FHIF; MFAl; ErbB4; FUS; BBC3; IGFIR; CD9; FP53BP1; MUCl; IGFBP5; rhoC; RALBPl; SFAF3; ERKl; SGCB; DHPS; MGMF; CRIP2; ErbB3; RAPIGDSI; CCNDl; PRKCD; Hepsin; ΑΚ055699; ZNF38; SEMA3F; COLlAl; BAGl; 25 AKFl; COL1A2; Wnt.5a; PFPDl; RAB6C; GSFMl, BCL2, ESRl.

In another embodiment, the anay comprises polynucleotides hybridizing to a plurality of the following genes: FBP; ABCC5; GAFA3; DICERl; MSH3; IRSl; FUBB; BAD; ERCCl; PR; APC; GGPSl; KRF18; ESRRG; AKF2; A.Catenin; CEGPl; NPD009; ΜΑΡΚ14; RUNXl; G.Catenin; FHIF; MFAl; ErbB4; FUS; BBC3; IGFIR; CD9; FP53BP1; 30 MUCl; IGFBP5; rhoC; RALBPl; SFAF3; ERKl; SGCB; DHPS; MGMF; CRIP2; ErbB3; RAPIGDSI; CCNDl; PRKCD; Hepsin; ΑΚ055699; ZNF38; SEMA3F; COLlAl; BAGl; AKFl; COL1A2; Wnt.5a; PFPDl; RAB6C. 6 8.^117-1 (GHMallers) Ρ82417.Α٧.5 ,15 In various embodiments, the array comprises at least five, or at least 10, or at least ح 2016210735 lOAug or at least 10 of such polynucleotides.

In a particular embodiment, the array comprises polynucleotides hybridizing to all of the genes listed above. 5 In another particular embodiment, the array comprises more than one polynucleotide hybridizing to the same gene.

In another embodiment, at least one of the the polynucleotides comprises an intron-based sequence the expression of which correlates with the expression of a corresponding exon sequence. 10 In various embodiments, the polynucleotides can be cDNAs or oligonucleotides.

Also disclosed is a method of preparing a personalized genomics profile for a patient comprising the steps of: (a) determining the normalized expression levels ofthe RNA hanscripts or the ;2.ILT ؛expression products of a gene or gene set selected fiom the group consisting of TBP ؛ERCCl ؛TUBB; BAD ؛fasl ؛CD3z ؛IRSl ؛GBPl ؛MSH3 ؛DICERl ؛15 ABCC5; CD18; GATA3 ؛NPD009 ؛CEGPl ؛A.Catenin ؛ΑΚΤ2 ؛E2F1 ؛ESRRG ؛KRT18 ؛GGPSl ؛APC ؛MCM6; PR ؛IGFIR ؛BBC3 ؛FUS ؛ERBB4؛MTAl ؛FHIT ؛FBX05 ؛G.Catenin ؛ID2 ؛RUNXl ؛ΜΑΡΚ14 ؛HLA.DPBl ؛ERKl ؛STAT3 ؛CDC20 ؛RALBPl ؛rhoC ؛IGFBP5 ؛MUCl ؛ΤΡ53ΒΡ1 ؛CD9 ؛IL6 ؛CDC25B ؛RAPIGDSI ؛ErbB3 ؛ΜΜΡ12 ؛CRIP2 ؛MGMT ؛DHPS ؛CGA ؛SGCB ؛VCAMl ؛51037.Contig ؛AK055699؛CRABP1 ؛Hepsin ؛DR4 ؛PRKCD ؛CYBA ؛20 CCNDl ؛CD31 ؛SEMA3F ؛GBP2 ؛MCM2 ؛ZNF38 ؛MCPl ؛RASSFl ؛2.ΑΚΑΡ ؛FYN; GRB7 ,ΤΚ1, ErbB2 ؛RAB6C ؛PTPDl ؛Wnt.5a ؛STATl ؛COL1A2 ؛ΑΚΤ1 ؛BAGl ؛ER2 ؛COLlAl CCNBl, BIRC5, STK6, ΜΚΙ67, MYBL2, ΜΜΡ11, CTSL2, CD68, GSTMl, BCL2, ESRl, and ؛in a cancer cell obtained fiom said patient 25 (b) creating a report summarizing the data obtained by the gene expression analysis. ؛CD18 ؛2.In a specific embodiment, if increased expression of one or more of ILT ؛ΜΜΡ12 ؛CGA ؛HLA.DPBl ؛CDC20 ؛FBX05 ؛ID2 ؛E2F1 ؛MCM6 ؛fasl ؛CD3z ؛GBPl ؛2.ΑΚΑΡ ؛GRB7 ؛FYN ؛VCAMl ؛51037.Contig ؛CRABPl ؛DR4 ؛CYBA ؛IL6 ؛CDC25B ,ERBB2, CCNBl, BIRC5 ؛ΤΚ1 ؛STATl ؛ER2 ؛CD31 ؛GBP2 ؛MCM2 ؛MCPl ؛30 RASSFl or the corresponding expression ؛STK6, ΜΚΙ67, MYBL2, ΜΜΡ11, CTSL2 and CD68 product, is determined, the report includes a prediction that said subject has an increased 7 9366419-1 (GHMalters. Ρ62417.Α٧.5 10-Aug-17 likelihood of response to chemotherapy. In this case, in a particular embodiment, the method includes the additional step oftreating the patient with a chemotherapeutic agent. ؛ABCC5 ؛In the foregoing method, if increased expression of one or more of TBP ؛KRT18 ؛GGPSl ؛APC ؛PR ؛ERCCl ؛BAD ؛TUBB ؛MSH3; IRSl ؛GATA3; DICERl ؛FHIT ؛G.Catenin ؛RUNXl ؛ΜΑΡΚ14 ؛NPD009 ؛CEGPl ؛A.Catenin ؛ΑΚΤ2 ؛ESRRG ؛RALBPl ؛rhoC ؛IGFBP5 ؛MUCl ؛ΤΡ53ΒΡ1 ؛CD9 ؛IGFIR ؛BBC3 ؛FUS ؛ErbB4 ؛ΜΤΑ1 ؛PRKCD ؛CCNDl ؛RAPIGDSI ؛ErbB3 ؛CRIP2 ؛MGMF ؛DHPS ؛SGCB ؛ERKl ؛SFAF3 ؛Wnt.5a ؛COL1A2 ؛ΑΚΤ1 ؛BAGl ؛COLlAl ؛SEMA3F ؛ZNF38 ؛ΑΚ055699 ؛Hepsin or the corresponding expression product, is ؛GSFMl, BCL2, ESRl ؛RAB6C ؛PFPDl determined, the report includes a prediction that said subject has a decreased likelihood of response to chemotherapy. Also disclosed is a method for determining the likelihood of the response of a patient to chemotherapy, comprising: (a) determining the expression levels of the RNA transcripts of following genes .ACFB, BAGl, BCL2, CCNBl, CD68, SCUBE2, CFSL2, ESRl, GAPD, GRB7, GSTMl, GUSB, ERBB2, ΜΚΙ67, MYBL2, PGR, RPLPO, SFK6, ΜΜΡ11, BIRC5, TFRC , or their expression products, and (b) calculating the recurrence score (RS). In an embodiment, patients having an RS > 50 are in the upper 50 percentile of patients who are likely to respond to chemotherapy. In enother embodiment, patients having an RS < 35 are in the lower 50 percentile of patients who are likely to response to chemotherapy. In a fUrther embodiment, RS is determined by creating the following gene subsets: ؛(i) growth factor subset: GRB7 and HER2 ؛ and CEGP1 ii) estrogen receptor subset: ER, PR, Bcl2١) and ؛iii) proliferation subset: SURV, Ki.67, MYBL2, CCNBl, and STK15) ؛(iv) invasion subset: CTSL2, and STMY3 wherein a gene within any of subsets (i)-(iv) can be substituted by substihrte gene ة which coexpresses with said gene in said tumor with a Pearson correlation coefficient of and ؛0.40 (c) calculating the recurrence score (RS) for said subject by weighting the ,contributions of each of subsets (i) - (iv), to breast cancer recurrence

٠ M 5 10 15 20 25 30 2016210735 lOAug 93^419-1 (GHMattCTS) Ρ62417.Α٧.5 1&amp;Aug-17 2016210735 05 Aug 2016 5 10 15 20

The foregoing method may further comprise determining the RNA transcripts of CD68, GSTMl and BAGl or their expression products, or corresponding substitute genes or their expression products, and incJuding the contribution of said genes or substitute genes to breast cancer recurrence in caJcuJating the RS RS may, for exampJe, be determined by using the fohowing equation: RS = (0.23 to 0.70) X GRB7axisthresh - (0.17 to 0.55) X ERaxis t (0.52 to 1.56) X prolifaxisthresh t (0.07 to 0.21) X invasionaxis t (0.03 to 0.15) X CD68 - (0.04 to 0.25) X GSTMl - (0.05 to 0.22) X BAGl wherein (i) GRB7 axis = (0.45 to 1.35) X GRB7 t (0.05 to 0.15) X HER2; (ii) if GRB7 axis < -2, then GRB7 axis thresh = -2, and if GRB7 axis > -2, then GRB7 axis thresh = GRB7 axis; (iii) ERaxis = (Estl +PR + Bcl2 + CEGPl)/4; (iv) prolifaxis = (SURV t Ki.67 t MYBL2 t cc^l t STK15)/5; (v) if prolifaxis < -3.5, then prolifaxisthresh = -3.5, if prolifaxis > -3.5, then prolifaxishresh = prolifaxis; and (vi) invasionaxis = (CTSL2 t STMY3)/2, wherein the individual contributions of the genes in (iii), (iv) and (vi) are weighted by a factor of0.5 to 1.5, and wherein a higher RS represents an increased likelihood ofbreast cancer recurrence. In another embodiment, RS is determined by using the following equation: RS (range, 0 - 100) = t 0.47 X HER2 Group Score - 0.34 X ER Group Score + 1.04Χ Proliferation Group Score t0.10x Invasion Group Score + 0.05 X CD68 - 0.08 X GSTMl - 0.07 X BAGl

Brief Description of the Drawings Figure 1 shows the relationship between recurrence score (RS) and likelihood of 25 patient response to chemotherapy, based on results ftom a clinical trial with patho complete response endpoint. 9 8026117-1 (GHMahers) Ρ62417.Α٧.5 2016210735 05 Aug 2016 5

TabJe 1 shows a Jist of genes, the expression of which correJates, positively or negatively, with breast cancer response to adriamycin and taxane neoadjuvant chemotherapy. Results ftom a clinical trial with pathologic complete response endpoint. Statistical analysis utilized univarite generalized linear models with a probit link function. Table 2 presents a list of genes, the expression of which predicts breast cancer response to chemotherapy. Results ftom a retrospective clinical trial. The table includes accession numbers for the genes, sequences for the forward and reverse primers (designated by "ft and "r", respectively) and probes (designated by "p") used for PCR amplification. Table 3 shows the amplicon sequences used in PCR amplification of the indicated 10 genes. 15 20 25 30

Detailed Description A. Definitions fjnless defined otherwise, technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Singleton et al., Dictionary of Microbiology and Molecular Biology 2nd ed., j. Wiley &amp; Sons (New York, NY 1994), and March, Advanced Organic Chemistry Reactions, Mechanisms and Structure 4th ed., John Wiley &amp; Sons (New York, NY 1992), provide one skilled in the art with a general guide to many of the terms used in the present application. One skilled in the art will recognize many methods and materials similar or equivalent to those described herein, which could be used in the practice of the present invention. Indeed, the present invention is in no way limited to the methods and materials described. For purposes of the present invention, the following terms are defined below. In the claims which follow and in the description of the invention, except where the context requires otherwise due to express language or necessary implication, the word “comprise” or variations such as “comprises” or “comprising” is used in an inclusive sense, i.e. to specify the presence of the stated feahrres but not to preclude the presence or addition of further features in various embodiments of the invention. The term "microarray" refers to an ordered arrangement of hybridizable array elements, preferably polynucleotide probes, on a substrate. The term "polynucleotide," when used in singular or plural, generally refers to any polyribonucleotide or polydeoxribonucleotide, which may be unmodified RNA or DNA or modified RNA or DNA. Thus, for instance, polynucleotides as defined herein include, without limitation, single- and double-stranded DNA, DNA including single- and double- 10 6026117.1 (GHMatters) Ρ62417,Α٧.5 stranded regions, single- and double-stranded RNA, and RNA including single- and double-stranded regions, hybrid molecules comprising DNA and RNA that may be single-stranded or, more typically, double-stranded or include single- and double-stranded regions. In addition, the term “polynucleotide” as used herein refers to triple-stranded regions 5 comprising RNA or DNA or both RNA and DNA. The strands in such regions may be ftom the same molecule or ftom different molecules. The regions may include all of one or more of the molecules, but more typically involve only a region of some of the molecules. One of the molecules of a triple-helical region often is an oligonucleotide. The term “polynucleotide” specifically includes cDNAs. The term includes DNAs (including cDNAs) 10 and RNAs that contain one or more modified bases. Thus, DNAs or RNAs with backbones modified for stability or for other reasons are "polynucleotides" as that term is intended herein. Moreover, DNAs or RNAs comprising unusual bases, such as inosine, or modified bases, such as tritiated bases, are included within the term “polynucleotides” as defined herein. In general, the term “polynucleotide” embraces all chemically, enzymatically and/or 15 metabolically modified forms of unmodified polynucleotides, as well as the chemical forms of DNA and RNA characteristic of viruses and cells, including simple and complex cells. 2016210735 05 Aug 2016

The term "oligonucleotide" refers to a relatively short polynucleotide, including, without limitation, single-stranded deoxyribonucleotides, single- or double-stranded ribonucleotides, RNA:DNA hybrids and double-stranded DNAs. Oligonucleotides, such as 20 single-stranded DNA probe oligonucleotides, are often synthesized by chemical methods, for example using automated oligonucleotide synthesizers that are commercially available. However, oligonucleotides can be made by a variety of other methods, including in vitro recombinant DNA-mediated techniques and by expression ofDNAs in cells and organisms.

The terms “differentially expressed gene,” “differential gene expression” and their 25 synonyms, which are used interchangeably, refer to a gene whose expression is activated to a higher or lower level in a subject suffering ftom a disease, specifically cancer, such as breast cancer, relative to its expression in a normal or control subject. The terms also include genes whose expression is activated to a higher or lower level at different stages of the same disease. It is also understood that a differentially expressed gene may be either activated or 30 inhibited at the nucleic acid level or protein level, or may be subject to alternative splicing to result in a different polypeptide product. Such differences may be evidenced by a change in mRNA levels, surface expression, secretion or other partitioning of a polypeptide, for example. Differential gene expression may include a comparison of expression between two 11 6026117.1 (٠HMatters)P62417.AU.5 or more genes or their gene products, or a comparison of the ratios of the expression between two or more genes or their gene products, or even a comparison of two differentiy processed products of the same gene, which differ between normal subjects and subjects suffering ftom a disease, specifically cancer, or between various stages of the same disease. Differential 5 expression includes both quantitative, as well as qualitative, differences in the temporal or cellular expression pattern in a gene or its expression products among, for example, normal and diseased cells, or among cells which have undergone different disease events or disease stages. For the purpose of this invention, “differential gene expression” is considered to be present when there is at least an about two-fold, preferably at least about four-fold, more 10 preferably at least about six-fold, most preferably at least about ten-fold difference between the expression of a given gene in normal and diseased subjects, or in various stages of disease development in a diseased subject. 2016210735 05 Aug 2016

The term “normalized” with regard to a gene transcript or a gene expression product refers to the level of the transcript or gene expression product relative to the mean levels of 15 transcripts/products of a set of reference genes, wherein the reference genes are either selected based on their minimal variation across, patients, tissues or treatments (“housekeeping genes”), or the reference genes are the totality of tested genes. In the latter case, which is commonly referred to as “global normalization”, it is important that the total number of tested genes be relatively large, preferably greater than 50. Specifically, the term 20 ‘normalized’ with respect to an RNA transcript refers to the transcript level relative to the mean of transcript levels of a set of reference genes. More specifically, the mean level of an RNA transcript as measured by TaqMan® RT-PCR refers to the Ct value minus the mean Ct values of a set of reference gene transcripts.

The terms “expression threshold,” and "defined expression threshold" are used 25 interchangeably and refer to the level of a gene or gene product in question above which the gene or gene product serves as a predictive marker for patient response or resistance to a drug. The threshold typically is defined experimentally ftom clinical studies. The expression threshold can be selected either for maximum sensitivity (for example, to detect all responders to a drug), or for maximum selectivity (for example to detect only responders to a 30 drug), or for minimum enor.

The phrase "gene amplification" refers to a process by which multiple copies of a gene or gene ftagment are formed in a particular cell or cell line. The duplicated region (a stretch of amplified DNA) is often refened to as "amplicon." Often, the amount of the 12 8026117.1 (GHMatiers) Ρ62417.Α٧.5 messenger RNA (mRNA) produced, i.e., the Jeve] of gene expression, aJso increases in the proportion to the number of copies made of the particular gene. 2016210735 05 Aug 2016

The term "prognosis" is used herein to refer to the prediction of the likelihood of cancer-attributable death or progression, including recunence, metastatic spread, and dnig 5 resistance, of a neoplastic disease, such as breast cancer. The term “prediction” is used herein to refer to the likelihood that a patient will respond either favorably or unfavorably to a drug or set of dnigs, and also the extent of those responses, or that a patient will survive, following surgical removal or the primary tumor and/or chemotherapy for a certain period of time without cancer recunence. The predictive methods of the present invention can be used 10 clinically to make treatment decisions by choosing the most appropriate trea for any particular patient. The predictive methods of the present invention are valuable tools in predicting if a patient is likely to respond favorably to a treatment regimen, such as surgical intervention, chemotherapy with a given drug or drtig combination, and/or radiation therapy, or whether long-term survival of the patient, following surgery and/or tennination 15 of chemotherapy or other treatment modalities is likely.

The term “long-term” survival is used herein to refer to survival for at least 3 years, more preferably for at least 8 years, most preferably for at least 10 years following surgery or other treatment.

The term "tumor," as used herein, refers to all neoplastic cell growth and 20 proliferation, whether malignant or benign, and all pre-cancerous and cancerous cells and tissues.

The terms "cancer" and "cancerous" refer to or describe the physiological condition in mammals that is typically characterized by unregulated cell growth. Examples of cancer include but are not limited to, breast cancer, colon cancer, lung cancer, prostate cancer, 25 hepatocelhdar cancer, gastric cancer, pancreatic cancer, cervical cancer, ovarian cance cancer, bladder cancer, cancer of the urinary tract, thyroid cancer, renal cancer, carcinoma, melanoma, and brain cancer.

The "pathology" of cancer includes all phenomena that compromise the well-being of the patient. This includes, without limitation, abnormal or uncontrollable cell growth, 30 metastasis, interference with the nomal functioning of neighboring cells, release of cytokines or other secretory products at abnomal levels, suppression or aggravation of inflammatory or immunological response, neoplasia, premalignancy, malignancy, invasion of surrounding or distant tissues or organs, such as lymph nodes, etc. 13 6026117.1 (GHMatters) Ρ62417.Α٧.5 "Patient response" can be assessed using any endpoint indicating a benefit to the patient, incJuding, without limitation, (1) inhibition, to some extent, of tumor growth, including slowing down and complete growth arrest: (2) reduction in the number of tumor cells; (3) reduction in tumor size; (4) inhibition (i.e., reduction, slowing down or complete 5 stopping) of hjmor cell infiltration into adjacent peripheral organs and/or tissues; (5) inhibition (i.e. reduction, slowing down or complete stopping) of metastasis; (6) enhancement of anti-tumor immune response, which may, but does not have to, result in the regression or rejection of the hjmor; (7) relief, to some extent, of one or more symptoms associated with the tumor; (8) increase in the length of survival following treatment; and/or (9) decreased 10 mortality at a given point of time following treatment. 2016210735 05 Aug 2016 "Neoadjuvant therapy" is adjunctive or adjuvant therapy given prior to the primary (main) therapy. Neoadjuvant therapy includes, for example, chemotherapy, radiation therapy, and hormone therapy. Thus, chemotherapy may be administered prior to surgery to shrink the tumor, so that surgery can be more effective, or, in the case of previously 15 unoperable tumors, possible. "Stringency" of hybridization reactions is readily determinable by one of ordinary skill in the art, and generally is an empirical calculation dependent upon probe length, washing temperature, and salt concentration. In general, longer probes require higher temperatures for proper annealing, while shorter probes need lower temperatures. 20 Hybridization generally depends on the ability of denatured DNA to reanneal when complementary strands are present in an environment below their melting temperature. The higher the degree of desired homology between the probe and hybridizable sequence, the higher the relative temperature which can be used. As a result, it follows that higher relative temperatures would tend to make the reaction conditions more stringent, while lower 25 temperatures less so. For additional details and explanation of stringency of hybridization reactions, see Ausubel et al.. Current Protocols in Molecular Biology. Wiley Interscience Publishers, (1995). "Stringent conditions" or "high stringency conditions", as defined herein, typically: (1) employ low ionic strength and high temperature for washing, for example 0.015 M 30 sodium chloride/0.0015 M sodium citrate/0.1% sodium dodecyl sulfate at 50.C; (2) employ during hybridization a denaturing agent, such as formamide, for example, 50% (v/v) formamide with 0.1% bovine serum albumin/0.1% Ficoll/0.1% polyvinylpyrrolidone/50mM sodium phosphate buffer at pH 6.5 with 750 mM sodium chloride, 75 mM sodium citrate at 14 8026117_1 (GHMatiers) Ρ62417.Α٧.5 42.C; or (3) employ 50% formamide, 5 X ssc (0.75 M NaCl, 0.075 M sodium citrate), 50 mM sodium phosphate (pH 6.8), 0.1% sodium pyrophosphate, 5 X Denhardt’s solution, sonicated salmon sperm DNA (50 pg/ml), 0.1% SDS, and 10% dextran sulfate at 42.C, with washes at 42.C in 0.2 X ssc (sodium chloride/sodium citrate) and 50% formamide at 55.C, 5 followed by a high-stringency wash consisting ofO.lxSSC containing EDTA at 55.C. 2016210735 05 Aug 2016 "Moderately stringent conditions" may be identified as described by Sambrook et al.. Molecular Cloning: A Laboratory Manual. New York: Cold Spring Harbor Press, 1989, and include the use of washing solution and hybridization conditions (e.g., temperahjre, ionic strength and %SDS) less stringent that those described above. An example of moderately 10 stringent conditions is overnight incubation at 37.C in a solution comprising: 20% formamide, 5 X ssc (150 mM NaCl, 15 mM trisodium citrate), 50 mM sodium phosphate (pH 7.6), 5 X Denhardt’s solution, 10% dextran sulfate, and 20 mg/ml denahjred sheared salmon sperm DNA, followed by washing the filters in 1 X ssc at about 37-50.C. The skilled artisan will recognize how to adjust the temperahjre, ionic strength, etc. as necessary 15 to accommodate factors such as probe length and the like.

In the context of the present invention, reference to "at least one," "at least two," "at least five," etc. of the genes listed in any particular gene set means any one or any and all combinations of the genes listed. B. Detailed Description 20 The practice of the present invention will employ, unless otherwise indicated, conventional techniques of molecular biology (including recombinant techniques), microbiology, cell biology, and biochemistry, which are within the skill of the art. Such techniques are explained fully in the literature, such as, “Molecular Cloning: A Laboratory Manual”, 2علل edition (Sambrook et al., 1989); “Oligonucleotide Synthesis” (M.J. Gait, ed., 25 1984); “Animal Cell Culture” (R.I. Freshney, ed., 1987); “Methods in Enzymology” (Academic Press, Inc.); “Handbook of Experimental Immunology”, 4لأء edition (D.M. Weir &amp; C.C. Blackwell, eds., Blackwell Science Inc., 1987); “Gene Transfer Vectors for Mammalian Cells” (J.M. Miller &amp; Μ.Ρ. Calos, eds., 1987); “Current Protocols in Molecular Biology” (F.M. Ausubel et al., eds., 1987); and “PCR: The Polymerase Chain Reaction”, (Mullis et al., 30 eds., 1994). 15 6026117-1 (GHMalters) Ρ62417.Α٧.5

Gene Expression Profiling 2016210735 05 Aug 2016

Methods of gene expression profiling include methods based on hybridization analysis of polynucleotides, methods based on sequencing of polynucleotides, and proteomics-based methods. The most commonly used methods known in the art for the 5 quantification of mRNA expression in a sample include northern blotting and in situ hybridization (Parker &amp; Barnes, in Molecular Biology 106:247-283 (1999)); RNAse protection assays (Hod, Biotechniques 13:852-854 (1992)); and PCR-based methods, such as reverse transcription polymerase chain reaction (RT-PCR) (Weis et al., Trends in Genetics 8:263-264 (1992)). Alternatively, antibodies may be employed that can recognize specific 10 duplexes, including DNA duplexes, RNA duplexes, and DNA-RNA hybrid duplexes or DNA-protein duplexes. Representative methods for sequencing-based gene expression analysis include Serial Analysis of Gene Expression (SAGE), and gene expression analysis by massively parallel signature sequencing (MPSS). \5 2.. PCR-based Gene Expression Proftling Methods ¾. Reverse Transcriptase PCR (RT-PCR)

One of the most sensitive and most flexible quantitative PCR-based gene expression profiling methods is RT-PCR, which can be used to compare mRNA levels in different sample populations, in normal and tumor tissues, with or without drug treatment, to 20 characterize patterns of gene expression, to discriminate between closely related mRNAs, and to analyze RNA stnrcture.

The first step is the isolation of mRNA fiom a target sample. The starting material is typically total RNA isolated ftom human tumors or tumor cell lines, and conesponding nomal tissues or cell lines, respectively. Thus RNA can be isolated ffom a variety of primary 25 tumors, including breast, lung, colon, prostate, brain, liver, kidney, pancreas, spleen, thymus, testis, ovary, uterus, etc., hjmor, or tumor cell lines, with pooled DNA ffom healthy donors. If the source of mRNA is a primary tumor, mRNA can be extracted, for example, ftom ftozen or archived paraffin-embedded and fixed (e.g. formalin-fixed) tissue samples.

General methods for mRNA extraction are well known in the art and are disclosed in 30 standard textbooks of molecular biology, including Ausubel et al., Current Protocols of Molecular Biology. John Wiley and Sons (1997). Methods for RNA extraction ftom paraffin embedded tissues are disclosed, for example, in Rupp and Locker, Lab Invest. 56:Α67 (1987), and De Andes et al., BioTechniques 18:42044 (1995). In particular, RNA isolation 16 8026117-1 (GHMatters) Ρ62417.Α٧.5 can be performed using purification kit, buffer set and protease fiom commercia] manufacfijrers, such as Qiagen, according to the manufacturer’s instnjctions. For example, total RNA fiom cells in culture can be isolated using Qiagen RNeasy mini-columns. Other commercially available RNA isolation kits include MasterPure™ Complete DNA and RNA 5 Purification Kit (EPICENTRE®, Madison, WI), and Paraffin Block RNA Isolation Kit (Ambion, Inc.). Total RNA fiom tissue samples can be isolated using RNA Stat-60 (Tel-Test). RNA prepared fiom hjmor can be isolated, for example, by cesium chloride density gradient centrifugation. 2016210735 05 Aug 2016

As RNA cannot serve as a template for PCR, the first step in gene expression 10 profiling by RT-PCR is the reverse transcription of the RNA template into cDNA, followed by its exponential amplification in a PCR reaction. The two most commonly used reverse transcriptases are avilo myeloblastosis virus reverse transcriptase (AMV-RT) and Moloney murine leukemia vims reverse transcriptase (MMLV-RT). The reverse transcription step is typically primed using specific primers, random hexamers, or oligo-dT primers, depending 15 on the circumstances and the goal of expression profiling. For example, extracted RNA can be reverse-transcribed using a GeneAmp RNA PCR kit (Perkin Elmer, CA, USA), following the manufacturer’s instructions. The derived cDNA can then be used as a template in the subsequent PCR reaction.

Although the PCR step can use a variety of thermostable DNA-dependent DNA 20 polymerases, it typically employs the Taq DNA polymerase, which has a 5’-3’ nuclease activity but lacks a 3’-5’ proofreading endonuclease activity. Thus, TaqMan® PCR typically utilizes the ؟-nuclease activity of Taq or Tth polymerase to hydrolyze a hybridization probe bound to its target amplicon, but any enzyme with equivalent 5’ nuclease activity can be used. Two oligonucleotide primers are used to generate an amplicon typical of a PCR 25 reaction. A third oligonucleotide, or probe, is designed to detect nucleotide sequence located between the two PCR primers. The probe is non-extendible by Taq DNA polymerase enzyme, and is labeled with a reporter fluorescent dye and a quencher fluorescent dye. Any laser-induced emission fiom the reporter dye is quenched by the quenching dye when the two dyes are located close together as they are on the probe. During the amplification reaction, 30 the Taq DNA polymerase enzyme cleaves the probe in a template-dependent manner. The resultant probe ftagments disassociate in solution, and signal fiom the released reporter dye is ftee fiom the quenching effect of the second fluorophore. One molecule of reporter dye is 17 8026117_1 (GHMatters) Ρ62417.Α٧.5 liberated for each new molecule synthesized, and detection of the unquenched reporter dye provides the basis for quantitative interpretation of the data. 2016210735 05 Aug 2016

TaqMan® RT-PCR can be performed using commercially available equipment, such as, for example, ABI PRISM 7700™ Sequence Detection System™ (Perkin-Elmer-Applied 5 Biosystems, Foster City, CA, USA), or Lightcycler (Roche Molecular Biochemicals, Mannheim, Germany). In a preferred embodiment, the 5' nuclease procedure is nm on a real-time quantitative PCR device such as the ABI PRISM 7700™ Sequence Detection System™. The system consists of a thermocycler, laser, charge-coupled device (CCD), camera and computer. The system amplifies samples in a 96-well format on a thermocycler. During 10 amplification, laser-induced fluorescent signal is collected in real-time through fiber optics cables for all 96 wells, and detected at the CCD. The system includes software for nmning the instrument and for analyzing the data. 5'-Nuclease assay data are initially expressed as Ct, or the threshold cycle. As discussed above, fluorescence values are recorded during every cycle and represent the 15 amount of product amplified to that point in the amplification reaction. The point when the fluorescent signal is first recorded as statistically significant is the threshold cycle (Ct).

To minimize enors and the effect of sample-to-sample variation, RT-PCR is usually performed using a reference RNA which ideally is expressed at a constant level among different tissues, and is unaffected by the experimental treatment. RNAs most frequently 20 used to normalize patterns of gene expression are mRNAs for the housekeeping genes glyceraldehyde-3-phosphate-dehydrogenase (GAPD) and p-actin (ACTB). A more recent variation of the RT-PCR technique is the real time quantitative PCR, which measures PCR product accumulation through a dual-labeled fluorigenic probe (i.e., TaqMan® probe). Real time PCR is compatible both with quantitative competitive PCR, 25 where internal competitor for each target sequence is used for normalization, and with quantitative comparative PCR using a normalization gene contained within the sample, or a housekeeping gene for RT-PCR. For fiirther details see, e.g. Held el al., Genome Research 6:986-994 (1996). ١٥. MassARRAYSystem 30 In the MassARRAY-based gene expression profiling method, developed by

Sequenom, Inc. (San Diego, CA) following the isolation of RNA and reverse transcription, the obtained cDNA is spiked with a synthetic DNA molecule (competitor), which matches the targeted cDNA region in all positions, except a single base, and serves as an internal 18 8026117.1 (GHMatters) P62417.AU.5 standard. The cDNA/competitor mixture is PCR amplified and is subjected to a post-PCR shrimp alkaline phosphatase (SAP) enzyme treatment, which results in the dephosphorylation of the remaining nucleotides. After inactivation of the alkaline phosphatase, the PCR products ftom the competitor and cDNA are subjected to primer extension, which generates 5 distinct mass signals for the competitor- and cDNA-derives PCR products. After 2016210735 05 Aug 2016 purification, these products are dispensed on a chip array, which is pre-loaded with components needed for analysis with matrix-assisted laser desorption ionization time-of flight mass spectrometry (MALDI-TOF MS) analysis. The cDNA present in the reaction is then quantified by analyzing the ratios of the peak areas in the mass spectnim generated. For 10 further details see, e.g. Ding and Cantor, Proc. Natl. Acad. Sci. USA 100:3059-3064 (2003). c. Other PCR-based Methods

Further PCR-based techniques include, for example, differential display (Liang and Pardee, Science 257:967-971 (1992)): amplified fragment length polymorphism (iAFLP) (Kawamoto et al.. Genome Res. 12:1305-1312 (1999)): BeadArray™ technology (Illumina, San 15 Diego, CA; Oliphant et al.. Discovery of Markers for Disease (Supplement to

Biotechniques), June 2002؛ Ferguson et al.. Analytical Chemistry 72:5618 (2000)): BeadsAnay for Detection of Gene Expression (BADGE), using the commercially available Luminex'.. LabMAP system and multiple color-coded microspheres (LuminexCorp., Austin, TX) in a rapid assay for gene expression (Yang et al.. Genome Res. 11:1888-1898 (2001)): 20 and high coverage expression profiling (HiCEP) analysis (Fukumura et al., Nucl. Acids. Res. 31(16) e94 (2003)). Ύ Microarrays

Differential gene expression can also be identified, or confirmed using the microanay technique. Thus, the expression profile ofbreast cancer-associated genes can be measured in 25 either ftesh or paraffin-embedded tumor tissue, using microarray technology. In this method, polynucleotide sequences of interest (including cDNAs and oligonucleotides) are plated, or anayed, on a microchip substrate. The arrayed sequences are then hybridized with specific DNA probes ftom cells or tissues of interest. Just as in the RT-PCR method, the source of mRNA typically is total RNA isolated ftom human tumors or tumor cell lines, and 30 corresponding normal tissues or cell lines. Thus RNA can be isolated ftom a variety of primary tumors or tumor cell lines, ff the source of mRNA is a primary tumor, mRNA can be extracted, for example, ftom ftozen or archived paraffin-embedded and fixed (e.g. 19

8026117-1 (GHMatters) P62417.AUS formalin-fixed) tissue samples, which are routinely prepared and preserved in everyday clinical practice. 2016210735 05 Aug 2016

In a specific embodiment of the microarray technique, PCR amplified inserts of cDNA clones are applied to a substrate in a dense anay. Preferably at least 10,000 nucleotide 5 sequences are applied to the substrate. The microanayed genes, immobilized on the microchip at 10,000 elements each, are suitable for hybridization under stringent conditions. Fluorescently labeled cDNA probes may be generated through incorporation of fluorescent nucleotides by reverse transcription of RNA extracted fiom tissues of interest. Labeled cDNA probes applied to the chip hybridize with specificity to each spot ofDNA on the array. 10 After stringent washing to remove non-specifically bound probes, the chip is sc confocal laser microscopy or by another detection method, such as a CCD camera. Quantitation of hybridization of each anayed element allows for assessment of corresponding mRNA abundance. With dual color fluorescence, separately labeled cDNA probes generated ftom two sources of RNA are hybridized pairwise to the array. The relative abundance of the 15 transcripts from the two sources corresponding to each specified gene is thus determi simultaneously. The miniaturized scale of the hybridization affords a convenient and rapid evaluation of the expression pattern for large numbers of genes. Such methods have been shown to have the sensitivity required to detect rare transcripts, which are expressed at a few copies per cell, and to reproducibly detect at least approximately two-fold differences in the 20 expression levels (Schena el al., Proc. Natl. Acad. Sci. USA 93(2):106-149 (1996)). Microanay analysis can be performed by commercially available equipment, following manufacturer's protocols, such as by using the Affymetrix GenChip technology, or Incyte's microarray technology.

The development of microarray methods for large-scale analysis of gene expression 25 makes it possible to search systematically for molecular markers of cancer classification and outcome prediction in a variety of tumor types. 4. Serial Analysis of Gene Expression (SAGE)

Serial analysis of gene expression (SAGE) is a method that allows the simultaneous and quantitative analysis of a large number of gene transcripts, without the need of providing 30 an individual hybridization probe for each transcript. First, a short sequence tag (about 10-14 bp) is generated that contains sufficient information to uniquely identify a transcript, provided that the tag is obtained ftom a unique position within each transcript. Then, many transcripts are linked together to form long serial molecules, that can be sequenced, revealing 20

80^117.1 (QHMallers) P82417.AU.S the identity of the muJtipJe tags simultaneously. The expression pattern of any population of transcripts can be quantitatively evaluated by determining the abundance of individual tags, and identifying the gene conesponding to each tag. For more details see, e.g. Velculescu el al., Science 270:484-487 (1995): and Velculescu etal., Cell 88:243-51 (1997). 2016210735 05 Aug 2016 5 5. Gene Expression Analysis by Massively Parallel Signature Sequencing (MPSSl

This method, described by Brenner et al., Nature Biotechnology 18:630-634 (2000), is a sequencing approach that combines ηοη-gel-based signature sequencing with in vitro cloning of millions of templates on separate 5 pm diameter microbeads. First, a microbead 10 library of DNA templates is constnrcted by in vitro cloning. This is followed by the assembly of a planar array of the template-containing microbeads in a flow cell at a high density (typically greater than 3 X 10٥ microbeads/cm2). The flee ends of the cloned templates on each microbead are analyzed simultaneously, using a fluorescence-based signahire sequencing method that does not require DNA ftagment separation. This method 15 has been shown to simultaneously and accurately provide, in a single operation, hundreds of thousands of gene signature sequences ftom a yeast cDNA library. 6. Iimmohistochemistrv

Immunohistochemistry methods are also suitable for detecting the expression levels of the prognostic markers of the present invention. Thus, antibodies or antisera, preferably 20 polyclonal antisera, and most preferably monoclonal antibodies specific for each marker are used to detect expression. The antibodies can be detected by direct labeling of the antibodies themselves, for example, with radioactive labels, fluorescent labels, hapten labels such as, biotin, or an enzyme such as horse radish peroxidase or alkaline phosphatase. Alternatively, unlabeled primary antibody is used in conjunction with a labeled secondary antibody, 25 comprising antisera, polyclonal antisera or a monoclonal antibody specific for the primary antibody. Immunohistochemistry protocols and kits are well known in the art and are commercially available. ٦. Proteomics

The term “proteome” is defined as the totality of the proteins present in a sample (e.g. 30 tissue, organism, or cell culhrre) at a certain point of time. Proteomics includes, among other things, study of the global changes of protein expression in a sample (also refened to as “expression proteomics”). Proteomics typically includes the following steps: (1) separation of individual proteins in a sample by 2-D gel electrophoresis (2-D PAGE): (2) identification 21

(QHMahers) P82417.AU.S of the individua] proteins recovered ftom the ge], e.g. my mass spectrometry or N-terminal sequencing, and (3) anaJysis of the data using bioinformatics. Proteomics methods are valuable supplements to other methods of gene expression profiling, and can be used, alone or in combination with other methods, to detect the products of the prognostic markers of the 5 present invention. 2016210735 05 Aug 2016 ¾. General Description ofmRNA Isolation. Pwifieation and Amplification

The steps of a representative protocol for profiling gene expression using fixed, paraffin-embedded tissues as the RNA source, including mRNA isolation, purification, primer extension and amplification are given in various published journal articles (for 10 example: Τ.Ε. Godfrey et al.ر. Molec. Diagnostics 2: 84-91 [2000]؛ K. Specht et al.. Am.ر. Pathol. 158: 419-29 [2001]). Briefly, a representative process starts with cutting about 10 pm thick sections of paraffin-embedded hrmor tissue samples. The RNA is then extracted, and protein and DNA are removed. After analysis of the RNA concentration, RNA repair and/or amplification steps may be included, if necessary, and RNA is reverse transcribed using gene 15 specific promoters followed by RT-PCR. Finally, the data are analyzed to identify the best treatment option(s) available to the patient on the basis of the characteristic gene expression pattern identified in the tumor sample examined. 9. Cancer Chemotherapy

Chemotherapeutic agents used in cancer treatment can be divided into several groups, 20 depending on their mechanism of action. Some chemotherapeutic agents directly damage DNA and RNA. By disnrpting replication of the DNA such chemotherapeutics either completely halt replication, or result in the production of nonsense DNA or RNA. This category includes, for example, cisplatin (Platinol®), daunonibicin (Cenibidine®), doxonrbicin (Adriamycin®), and etoposide (VePesid®). Another group of cancer 25 chemotherapeutic agents interfere with the formation of nucleotides or deoxyribonucleotides, so that RNA synthesis and cell replication is blocked. Examples ofdrtigs in this class include methotrexate (Abitrexate®), mercaptopurine (Purinethol®), fluorouracil (Adrticil®), and hydroxyurea (Hydrea®). A third class of chemotherapeutic agents effects the synthesis or breakdown of mitotic spindles, and, as a result, internipt cell division. Examples ofdrtigs in 30 this class include Vinblastine (Velban®), Vincristine (Oncovin®) and taxenes, such as, Pacitaxel (Taxol®), and Tocetaxel (Taxotere®) Tocetaxel is currently approved in the fjnited States to treat patients with locally advanced or metastatic breast cancer after failure of prior 22 8026117.1 (QHMattere) Ρ62417.Α٧.5 chemotherapy, and patients with locally advanced or metastatic ηοη-small cell lung cancer after failure of prior platinum-based chemotherapy. 2016210735 05 Aug 2016 A common problem with chemotherapy is the high toxicity of chemotherapeutic agents, such as anthracyclines and taxenes, which limits the clinical benefits of this treatment 5 approach.

Most patients receive chemotherapy immediately following surgical removal of tumor. This approach is commonly referred to as adjuvant therapy. However, chemotherapy can be administered also before surgery, as so called neoadjuvant treatment. Although the use of neo-adjuvant chemotherapy originates ftom the treatment of advanced and inoperable 10 breast cancer, it has gained acceptance in the treatment of other types of cancers as well. The efficacy of neoadjuvant chemotherapy has been tested in several clinical trials. In the multi-center National Surgical Adjuvant Breast and Bowel Project Β-18 (NSAB Β-18) trial (Fisher et al., j. Clin. Oncology 15:2002-2004 (1997); Fisher et al., ر. Clin. Oncology 16:2672-2685 (1998)) neoadjuvant therapy was performed with a combination of adriamycin and 15 cyclophosphamide ("AC regimen"). In another clinical trial, neoadjuvant therapy was administered using a combination of 5-fluorouracil, epirubicin and cyclophosphamide ("FEC regimen") (van Der Hage et al., ر. Clin. Oncol. 19:4224-4237 (2001)). Newer clinical trials have also used taxane-containing neoadjuvant treatment regiments. See, e.g. Holmes et al.,ر. Natl. Cancer Inst. 83:1797-1805 (1991) and Moliterni et al., Seminars in Oncology, 24:S17-20 10-S-17-14 (1999). For further information about neoadjuvant chemotherapy for breast cancer see, Cleator et al., Endocrine-Related Cancer 9:183-195 (2002). \0. Cancer Gene Set. Assayed Gene Subsequences, and Clinical Application of Gene Expression Data

An important aspect of the present invention is to use the measured expression of 25 certain genes by breast cancer tissue to provide prognostic information. For this purpose it is necessary to correct for (normalize away) differences in the amount of RNA assayed, variability in the quality of the RNA used, and other factors, such as machine and operator differences. Therefore, the assay typically measures and incorporates the use of reference RNAs, including those transcribed ftom well-known housekeeping genes, such as GAPD and 30 ACTB. A precise method for normalizing gene expression data is given in “User Bulletin #2” for the ABI PRISM 7700 Sequence Detection System (Applied Biosystems; 1997). Alternatively, normalization can be based on the mean or median signal (Ct) of all of the assayed genes or a large subset thereof (global normalization approach). In the study 23 8026117-1 (GHMatters) Ρ62417.Α٧.5 described in the fohowing Example, a so called central nomalization strategy was used, which utilized a subset of the screened genes, selected based on lack of conelation with clinical outcome, for normalization. 2016210735 05 Aug 2016 \\. Recurrence and Response to Therapy Scores and their Applications 5 Copending application Serial No. 60/486,302, filed on July 10, 2003, describes an algorithm-based prognostic test for detemining the likelihood of cancer recurrence and/or the likelihood that a patient responds well to a treatment modality. Features of the algorithm that distinguish it fiom other cancer prognostic methods include: 1) a unique set of test mRNAs (or the corresponding gene expression products) used to determine recurrence likelihood, 2) 10 certain weights used to combine the expression data into a formula, and 3) thresholds used to divide patients into groups of different levels of risk, such as low, medium, and high risk groups. The algorithm yields a numerical recunence score (RS) or, if patient response to treatment is assessed, response to therapy score (RTS).

The test requires a laboratory assay to measure the levels of the specified mRNAs or 15 their expression products, but can utilize very small amounts of either ftesh tissue, or ftozen tissue or fixed, paraffin-embedded tumor biopsy specimens that have already been necessarily collected fiom patients and archived. Thus, the test can be noninvasive. It is also compatible with several different methods of tumor tissue hardest, for example, via core biopsy or fine needle aspiration. 20 According to the method, cancer recurrence score (RS) is determined by: (a) subjecting a biological sample comprising cancer cells obtained fiom said subject to gene or protein expression profiling; (b) quantifying the expression level of multiple individual genes [i.e., levels of mRNAs or proteins] so as to determine an expression value for each gene; 25 (c) creating subsets of the gene expression values, each subset comprising expression values for genes linked by a cancer-related biological function and/or by CO-expression; (d) multiplying the expression level of each gene within a subset by a coefficient reflecting its relative contribution to cancer recurrence or response to therapy within said 30 subset and adding the products of multiplication to yield a term for said subset; (e) multiplying the term of each subset by a factor reflecting its contribution to cancer recurrence or response to therapy; and 24 8026117_1 (GHMatiers) Ρ62417.Α٧.5 (f) producing the sum of terms for each subset multiplied by said factor to produce a recurrence score (RS) or a response to therapy (RTS) score, 2016210735 05 Aug 2016 wherein the contribution of each subset which does not show a linear con-elation with cancer recurrence or response to therapy is included only above a predetermined threshold 5 level, and wherein the subsets in which increased expression of the specified genes reduce risk of cancer recurrence are assigned a negative value, and the subsets in which expression of the specified genes increase risk of cancer recurrence are assigned a positive value.

In a particular embodiment, RS is determined by: 10 (a) determining the expression levels of GRB7, HER2١ EstRl, PR, Bcl2, CEGPl, SURV, Ki.67, MYBL2, cc^l, STK15, CTSL2, STMY3, CD68, GSTMl, and BAGl, or their expression products, in a biological sample containing tumor cells obtained ftom said subject; and (b) calculating the recurrence score (RS) by the following equation:

15 RS = (0.23 to 0.70) X GRB7axisthresh - (0.17 to 0.51) X ERaxis t (0.53 to 1.56) X prolifaxisthresh t (0.07 to 0.21) X invasionaxis t (0.03 to 0.15)χ CD68 - (0.04 to 0.25) X GSTMl - (0.05 to 0.22) X BAGl wherein (i) GRB7 axis = (0.45 to 1.35) X GRB7 t (0.05 to 0.15) X HER2; 20 (ii) if GRB7 axis < -2, then GRB7 axis thresh = -2, and if GRB7 axis > -2, then GRB7 axis thresh = GRB7 axis; (iii) ER axis = (Estl tPRt Bcl2 t CEGPl)/4; (iv) prolifaxis = (SURV t Ki.67 t MYBL2 t cc^l t STK15)/5; (٧) ifprolifaxis < -3.5, then prolifaxisthresh = -3.5, 25 if prolifaxis > -3.5, then prolifaxishresh = prolifaxis; and (Vi) invasionaxis = (CTSL2 t STMY3)/2, wherein the terms for all individual genes for which ranges are not specifically shown can vary between about 0.5 and 1.5, and wherein a higher RS represents an increased likelihood of cancer recurience. 30 Further details of the invention will be described in the following non-limiting

Example. 25 80^117.1 (GHMallers) Ρ62417.Α٧.5

Example 2016210735 05 Aug 2016 A Retrospective Study of Neoadjuvant Chemotherapy in Invasive Breast Cancer:

Gene Expression Profiling of Paraffin-Embedded Core Biopsy Tissue

This was a collaborative study involving Genomic Health, Inc., (Redwood City 5 California), and Institute Tumori, Milan, Italy. The primary objective of the shidy was to explore the correlation between pre-treatment molecular profiles and pathologic complete response (pCR) to neoadjuvant chemotherapy in locally advanced breast cancer.

Patient inclusion criteria'.

Histologic diagnosis of invasive breast cancer (date of surgery 1998-2002); diagnosis 10 of locally advanced breast cancer defined by skin infiltration and or Ν2 axillary status and or homolateral supraclavicular positive nodes; core biopsy, neoadjuvant chemotherapy and surgical resection performed at Istituto Nazionale Tumori, Milan; signed informed consent that the biological material obtained for histological diagnosis or diagnostic procedures would be used for research; and histopathologic assessment indicating adequate amounts of 15 tumor tissue for inclusion in this research study.

Exclusion criteria'.

Distant metastases; no tumor block available ftom initial core biopsy or fiom the surgical resection; or no tumor or very little tumor (<5% of the overall tissue on the slide) in block as assessed by examination of the Η&amp;Ε slide by the Pathologist. IQ Study design

Eighty-nine evaluable patients (ftom a set of 96 clinically evaluable patients) were identified and studied. The levels of 384 mRNA species were measured by RTPCR, representing products of candidate cancer-related genes that were selected ftom the biomedical research literature. Only one gene was lost due to inadequate signal. 25 Patient characteristics were as follows: Mean age: 50 years; Tumor grades: 24% Well, 55% Moderate, and 21% Poor; Sixty-three % of patients were ER positive (by immunohistochemistry}; Seventy % of patients had positive lymph nodes.

All patients were given primary neoadjuvant chemotherapy: Doxorubicin plus Taxol 3weeks/3 cycles followed by Taxol® (paclitaxel) lweek/12 cycles. Surgical removal of the 30 hjmor followed completion of chemotherapy. Core tumor biopsy specimens were taken prior to start of chemotherapy, and seized as the source ofRNA for the RT-PCR assay. 26 6026117-1 (GHMatters) Ρ62417.Α٧.5

Materials and Methods 2016210735 05 Aug 2016

Fixed paraffin-embedded (FPE) tumor tissue ftom biopsy was obtained prior to and after chemotherapy. Core biopsies were taken prior to chemotherapy. Jn that case, the pathoJogist seJected the most representative primary tumor bJock, and submitted nine 10 5 micron sections for RNA analysis. Specifically, a total of 9 sections (10 microns in thickness each) were prepared and placed in three Costar Brand Microcentrifuge Tubes (Polypropylene, 1.7 mL tubes, clear; 3 sections in each tube) and pooled.

Messenger RNA was extracted using the MasterPure™ RNA Purification Kit (Epicenfte Technologies) and quantified by the RiboGreen® fluorescence method 10 (Molecular probes). Molecular assays of quantitative gene expression were performed by RT-PCR, using the ABI PRISM 7900™ Sequence Detection System™ (Perkin-Elmer-Applied Biosystems, Foster City, CA, USA). ABI PRISM 7900™ consists of a thermocycler, laser, charge-coupled device (CCD), camera and computer. The system amplifies samples in a 384-well format on a thermocycler. During amplification, laser-induced fluorescent signal is 15 collected in real-time for all 384 wells, and detected at the CCD. The system includes software for running the instrument and for analyzing the data.

Analysis and Results

Tumor tissue was analyzed for 384 genes. The threshold cycle (Ct) values for each patient were normalized based on the median of a subset of the screened genes for that 20 particular patient, selected based on lack of correlation with clinical outcome (central nomalization strategy). Patient beneficial response to chemotherapy was defined as pathologic complete response (pCR). Patients were formally assessed for response at the completion of all chemotherapy. A clinical complete response (cCR) requires complete disappearance of all clinically 25 detectable disease, either by physical examination or diagnostic breast imaging. A pathologic complete response (pCR) requires absence of residual breast cancer on histologic examination ofbiopsied breast tissue, lumpectomy or mastectomy specimens following primary chemotherapy. Residual ductal carcinoma in situ (DCIS) may be present. Residual cancer in regional nodes may not be present. Of the 89 evaluable patients 11 (12%) 30 had a pathologic complete response (pCR). Seven of these patients were ER negative. A partial clinical response was defined as a 50 ح% decrease in tumor area (sum of the products of the longest perpendicular diameters) or a 50 ح% decrease in the sum of the 27 8026117-1 (GHMatters) Ρ62417.Α٧.5 products of the longest perpendicular diameters of multiple lesions in the breast and axilla. No area of disease may increase by > 25% and no new lesions may appear. 2016210735 05 Aug 2016

Analysis was performed by comparing the relationship between normalized gene expression and the binary outcomes ofpCR or no pCR. fjnivariate generalized models were 5 used with probit or logit link functions. See, e.g. Van K. Borooah, LOGIT and PROBIT, Ordered Multinominal Models, Sage University Paper, 2002.

Table 1 presents pathologic response correlations with gene expression, and lists the 86 genes for which the p-value for the differences between the groups was <0.1. The second column (with the heading “Direction”) denotes whether increased expression conelates with 10 decreasing or increasing likelihood of response to chemotherapy. The statistical significance of the predictive value for each gene is given by p-value (right hand column) 28

80^117-1 (QHMatters) P62417.AU.S 2016210735 05 Aug 2016

Probit Link Gene Direction Intercept Sl.pe P-value TRP Decreasing 0.0575 2.4354 0.0000 ΙΙΤ.2 Increasing 0.5273 -0.9489 0.0003 ABCC5 Decreasing 0.9872 0.8181 0.0003 CD18 Increasing 3.4735 -1.0787 0.0007 GATA3 Decreasing 0.6175 0.2975 0.0008 DICERI Decreasing -0.9149 1.4875 0.0013 MSH3 Decreasing 2.6875 0.9270 0.0013 GBPI Increasing 1.7649 -0.5410 0.0014 IRSI Decreasing 1.3576 0.5214 0.0016 c٥3z Increasing 0.1567 -0.5162 0.0018 Fas\ Increasing -0.6351 -0.4050 0.0019 TUBB Decreasing 1.2745 0.8267 0.0025 BAD Decreasing 0.9993 1.1325 0.0033 ERCCI Decreasing 0.0327 1.0784 0.0039 MCM6 Increasing 0.1371 -0.8008 0.0052 PR Decreasing 1.6079 0.1764 0.0054 APC Decreasing 0.7264 1.0972 0.0061 GGPSI Decreasing 1.0906 0.8124 0.0062 KRT18 Decreasing -0.8029 0.4506 0.0063 ESRRG Decreasing 2.0198 0.2262 0.0063 E2F١ Increasing 0.2188 -0.5277 0.0068 ΑΚΤ2 Decreasing -1.3566 1.1902 0.0074 A.Catenin Decreasing -0.6859 0.9279 0.0079 CEGPI Decreasing 1.3355 0.1875 0.0091 NPD009 Decreasing 1.3996 0.2971 0.0092 ΜΑΡΚ14 Decreasing 2.6253 1.6007 0.0093 RUNXI Decreasing -0.4138 0.7214 0.0103 ID2 Increasing 1.7326 -0.7032 0.0104 G.Catenin Decreasing -0.1221 0.5954 0.0110 FBX05 Increasing 0.3421 -0.4935 0.0110 FHIT Decreasing 1.9966 0.4989 0.0113 ΜΤΑ1 Decreasing 0.3127 0.6069 0.0133 ERBB4 Decreasing 1.4591 0.1436 0.0135 FUS Decreasing -0.6150 0.9415 0.0137 BBC3 Decreasing 2.4796 0.6495 0.0138 IGFIR Decreasing 1.1998 0.3116 0.0147 CD9 Decreasing -0.9292 0.5747 0.0156 ΤΡ53ΒΡ1 Decreasing 1.4325 0.8122 0.0169 MUCI Decreasing 0.8881 0.2140 0.0175 IGFBP5 Decreasing -0.6180 0.4880 0.0181 rtioC Decreasing -0.1726 0.6860 0.0184 RAIBPI Decreasing 0.2383 0.9509 0.0185 CDC20 Increasing 1.3204 -0.4390 0.0186 STAT3 Decreasing -0.9763 0.7023 0.0194 ERKI Decreasing 0.8577 0.6496 0.0198 HlA.DPBI Increasing 3.6300 -0.6035 0.0202 SGCB Decreasing 0.6171 0.7823 0.0208 29 8026117-1 (GHMallers) P62417.AU.5 ٠ (N Probit Link ٥٠ Gene Direction Intercept Sl.pe P-value CGA Increasing 0.0168 0.0209 ؛> -0.1450 DHPS Decreasing 0.2957 0.7840 0.0216 ٠ MGMT Decreasing 0.9238 0.6876 0.0226 CRIP2 Decreasing 0.5524 0.4394 0.0230 ΜΜΡ12 Increasing 0.4208 -0.2419 0.0231 If) ErbB3 Decreasing 0.9438 0.2798 0.0233 t٣١ RAPIGDSI Decreasing 0.2617 0.7672 0.0235 ٠ CDC25B Increasing 1.6965 -0.5356 0.0264 lift Increasing 0.0592 -0.2388 0.0272 (N CCNDI Decreasing 0.2260 0.2992 0.0272 ه١ا CYBA Increasing 2.6493 -0.5175 0.0287 s PRKCD Decreasing 0.2125 0.6745 0.0291 (N DR4 Increasing 0.3039 -0.5321 0.0316 Hepsin Decreasing 1.9211 0.1873 0.0318 CRABPI Increasing 1.0309 -0.1287 0.0320 ΑΚ055699 Decreasing 2.0442 0.1765 0.0343 Contig.51037 Increasing 0.7857 -0.1131 0.0346 \ICI٦ Increasing 1.1866 -0.3560 0.0346 FYU Increasing 1.5502 -0.5624 0.0359 GRB7 Increasing 1.3592 -0.1646 0.0375 ΑΚΑΡ.2 Increasing 1.7946 -0.7008 0.0382 F٦،؟،؟\Rf Increasing 1.1972 -0.0390 0.0384 MCPI Increasing 1.3700 -0.3805 0.0388 ZNF38 Decreasing 1.7957 0.4993 0.0395 MCM2 Increasing 1.0574 -0.4695 0.0426 GBP2 Increasing 1.4095 -0.4559 0.0439 SEMA3F Decreasing 1.2706 0.3725 0.0455 CD31 Increasing 1.9913 -0.5955 0.0459 COLIAI Decreasing -1.9861 0.3812 0.0466 ΈΚ2. Increasing -0.5204 -0.2617 0.0471 BAGI Decreasing 0.6731 0.5070 0.0472 ΑΚΤ1 Decreasing -0.4467 0.5768 0.0480 COL1A2 Decreasing -1.0233 0.3804 0.0490 STATI Increasing 1.9447 -0.4062 0.0498 Wnt.5a Decreasing 2.2244 0.2983 0.0518 PTPDI Decreasing 1.2950 0.4834 0.0552 RAB6C Decreasing 0.4841 0.5635 0.0717 ΤΚ1 Increasing 0.6127 -0.3625 0.0886 Bc!2 Decreasing 1.1459 0.2509 0.0959

Based on the data set forth in Table 1, increased expression of the following genes correlates with increased likelihood of complete pathologic response to treatment: ILT.2; CD18; GBPl; CD3z: fasl: MCM6: E2F1: Π)2; FBX05; CDC20; HLADPBl: CGA; 5 ΜΜΡ12; CDC25B; ذ6دلآ CYBA; DR4: CRABPl; Contig.51037; VCAMl; FYN؛ GRB7: ΑΚΑΡ.2; RASSFl; MCPl: MCM2; GBP2: CD31; ER2; STATl; ΤΚ1; while increased expression of the fohowing genes correlates with decreased likelihood of complete pathologic response to treatment: TBP; ABCC5; GATA3; DICERl; MSH3; IRSl; TUBB; BAD; ERCCl; PR; APC; GGPSl; KRT18; ESRRG; ΑΚΤ2; A.Catenin; CEGPl; NPD009; ΜΑΡΚ14; RiXl; G.Catenin; FHIT; ΜΤΑ1; ErbB4; FUS; BBC3; IGFIR; CD9; ΤΡ53ΒΡ1; 2016210735 05 Aug 2016 5 MUCl; IGFBP5; rhoC; RALBPl; SFAT3; ERKl; SGCB; DHPS; MGMF; CRIP2; ErbB3; RAPIGDSI; CCil; PRKCD; Hepsin; ΑΚ055699; ZNF38; SEMA3F; COLlAl; BAGl; AKFl; COL1A2; Wnt.5a; PFPDl; RAB6C; Bcl2.

Fhe relationship between the recurrence risk algorithm (described in copending U.S. application Serial No. 60/486,302) and pCR was also investigated. The algorithm 10 incorporates the measured levels of 21 mRNA species. Sixteen mRNAs (named below) were candidate clinical markers and the remaining 5 (ACTB, GAPD, GFJSB, RPLPO, and TFRC) were reference genes. Reference-normalized expression measurements range ftom 0 to 15, where a one unit increase reflects a 2-fold increase in RNA.

The Recunence Score (RS) is calculated ftom the quantitative expression of four sets 15 of marker genes (an estrogen receptor group of4 genes—ESRl, PGR, BCL2, and SCUBE2; a proliferation set of 5 genes—ΜΚΙ67, MYBL2, B1RC5, CCNBl, and STK6; a HER2 set of 2 genes—ERBB2 and GRB7, an invasion group of 2 genes—MMP11 and CTSL2) and 3 other individual genes—GSTMl, BAGl, and CD68.

Although the genes and the multiplication factors used in the equation may vary, in a 20 typical embodiment, the following equation may be used to calculate RS: RS (range, 0 - 100) = t 0.47 X HER2 Group Score - 0.34 X ER Goup Score + 1.04Χ Proliferation Group Score t0.10x Invasion Group Score + 0.05 X CD68 - 0.08 X GSTMl - 0.07 X BAGl

Application of this algorithm to study clinical and gene expression data sets yields a continuous cuive relating RS to pCR values, as shown in Figure 1. Examination of these data 25 shows that patients with RS > 50 are in the upper 50 percentile of patients in terms of 31 (GHMallers) Ρ62417.Α٧.5 likelihood of response to chemotherapy, and that patients with RS < 35 are in the lower 50 percentile of patients in terms of likelihood of response to chemotherapy. 2016210735 05 Aug 2016

All references cited throughout the disclosure are hereby expressly incorporated by reference. 5 While the invention has been described with emphasis upon certain specific embodiments, it is be apparent to those skilled in the art that variations and modification in the specific methods and techniques are possible. Accordingly, this invention includes all modifications encompassed within the spirit and scope of the invention as defined by the following claims. 10 32 3026117-1 (GHMahers) P62417.AU.5 33 2016210735 05 Aug 2016 TABLE 2 A-Catenin ΝΜ.00190 S2138/AGate.ra cgttccgatcctctAtactgcat 23 A-Catenin ΝΜΟ0190 S2139/A-Cate.r2 AGGTCCCTGTTGGCCTTATAGG 22 A"Catenin NM_00190S4725/ACate.p2 ATGCCTACAGCACCCTGATGTCGCA 25 ABCC5 ΝΜ.00568 S5605/ABCC5.f1 TGCAGACTGTACCATGCTGA 20 ABCC5 ΝΜ.00568 S5606/ABCC5.r1 . GGCCAGCACCATAATCCTAT 20 ABCC5 NM_0Q568S5607/ABCC5.p1 CTGCACACGGTTCTAGGCTCCG 22 ΑΚ055699 ΑΚ055699 δ2097/ΑΚ0556.ί1 CTGCATGTGATTGAATAAGAAACAAGA 27 AK0S5699 ΑΚ055699 S2098/AK0556.r1 TGTGGACCTGATCCCTGTACAC 22 ΑΚ055699 ΑΚ055699 S5057/AK0556.p1 TGACCACACCAAAGCCTCCCTGG 23 ΑΜΡ-2 NM_00720S1374ZAKAP-2.fi ACGAAnGTCGGTGAGGTCT 20 ΑΚΑΡ-2 NM_00720S1375/AKAP-2.r1 GTCCATGCTGAAATCATTGG 20 ΑΚΑΡ-2 NM_00720S4934/AKAP-2.p1 CAGGATACCACAGTCCTGGAGACCC 25 ΑΚΤ1 3أ. ΝΜ.00516 SOOIQ/AKT1 CGCTTCTATGGCGCTGAGAT 20 ΑΚΤ1 NM_00516S0012/AKT1.r3 TCCCGGTACACCACGTTCn 20 ΑΚΤ1 ΝΜ.00516 S4776/AKT1 .ρ3 CAGCCCTGGACTACCTGCACTCGG 24 ΑΚΤ2 ΝΜ.00162 S0828/AKT2.f3 TCCTGCCACCCTTCAAACC ب 19 ΑΚΤ2 NM_00162S0829/AKT2.r3,. GGCGGTAAATTCATCATCGAA 21 ΑΚΤ2 NM_00162S4727/AKT2.p3 CAGGTCACGTCCGAGGTCGACACA 24 APC ΝΜ.00003 S0022/APC.f4 GGACAGCAGGAATGTGTTTC 20 APC NM_0٥Q03 S0024/APC.r4 ACCCACTCGATTTGTTTCTG 20 APC NM_00003S4888/APC.p4 cattggctccccgtgaccTgta . 22 BAD. NM 03298 S2011/BAD.fl GGGTCAGGTGCCTCGAGAT 19 BAD NM 03298 S2012/BAD.٢1 . CTGCTCACTCGGCTCAAACTC - 21 BAD NM' 03298 S5058ZBAD.pl TGGGCCCAGAGCATGTTCCAGATC 24 BAGI NM 00432 S1386/BAG1.f2 CGnGTCAGCACTTGGAATACAA 23 BAGI NM 00432 S1387/BAG1.r2 ,GTTCAACCTCnCCTGTGGACTGT 24 BAGI NM 00432 S4731/BAG1.P2 CCCAAnAACATGACCCGGCAACCAT 26 BBC3 NM 01441 S1584/BBC3٠f2 CCTGGAGGGTCCTGTACAAT 20 BBC3 ΝΜ.01441 S1585/BBC3٠r2 CTAATTGGGCTCCATCTCG 19 BBC3 NM 01441 S4890/BBC3.P2. CATCATGGGACTCCTGCCCTTACC 24 Bc!2 NM 00063 S0043/Bcl2.f2 CAGATGGACCTAGTACCCACTGAGA 25 Bcl2 NM 00063 S0045/Bc!2.٢2 CCTATGATTTAAGGGCATT^CC 24 Bc!2 NM 00063 S4732'/Bcl2.p2 TTCCACGCCGAAGGACAGCGAT 22 CCNDI NM 00175S0058/CCND1.f3 GCATGTTCGTGGCCTCTAAGA 21 CCNDI NM 00175 S0060/CCND1.r3 cGGTG7AGA7GCACAGCnCTC 22 CCNDI NM 00175S4986/CCND1.P3 AAGGAGACCATCCCCCTGACGGC 23 CD18 ΝΜ.00021 S0061/CD18.f2 CGTCAGGACCCACCATGTCT 20 CD18 NM 00021 S0063/CD18.٢2 GGTTAAnGGTGACATCCTCAAGA 24 CD18 Ν.Μ 00021 S4987/CD18.p2 CGCGGCCGAGACATGGCTTG 20 CD31 NM 00044 S14Q7ZCD31 .f3 TGTATTTCAAGACCTCTGTGCACn . 25 CD31 ΝΜ 00044 S1408ZCD31 .r3 TTAGCCTGAGGAAnGCTGTG٦٦ 23 CD31 ΝΜ-00044 S4939ZCD31.P3 TTTATGAACCTGCCCTGCTCCCACA 25 CD3z ΝΜ-00073 S0064/CD3z.f1 AGATGAAGTGGAAGGCGCTT 20 CD3z ΝΜ.00073 S0066/CD3z.r1 TGCCTCTGTAATCGGCAACTG 21 CD3z ΝΜ.00073 S4988/CD3z.p1 CACCGCGGCCATCCTGCA 18 CD9 ΝΜ_00176 S0686/CD9.f1 GGGCGTGGAACAGTTTATCT 20 CD9 ΝΜ-00176 S0687/CD9.r1 CACGGTGAAGGTTTCGAGT 19 CD9 ΝΜ.00176 S4792/CD9.p1 AGACATCTGCCCCAAGAAGGACGT 24 CDC20 ΝΜ-00125 S4447/CDC20.f1 TGGATTGGAGTOTGGGAATG ..21 CDC20 NM_0O125S4448/CDC2O.r1 GCTTGCACTCCACAGGTACACA 22 CDC20 ΝΜ.00125 S4449/CDC20.p1 ACTGGCCGTGGCACTGGACAACA 23 CDC25B ΝΜ.02187 S1160ZCDC25B.fi AAACGAGCAGTTTGCCATCAG 21 2016210735 05 Aug 2016

3لألاا 96911Ζ حج9ا/3لا.1'لح 3لااؤا 81'l*y3/09SlS 96911Ζ 3لاد3ا 1 861.00 ج7ا3/026ية133'zd 3لاد3ا ZJ٠133d3/88l7ZS 86100 ΙΛΙΝ 3لة133 1...86100 2il33٤J3/Z8l72S 3لأ39 ed٠wgy3/t68Sera٥0٠WN 3لا۶33 SJ'^aay3/2S2tSSZS00 Ι^Ν 3لأ799ا ا.3/1821582900لا789ا'81 3ل3٩ح 86100.1 ld'89٩J3/Z009S 3ل3٩ح lJ'89٩J3/frll0S86100٠l 3ل3٩ج 861.00 ^1Νج0ا.1ة/3ل3٩ح'ز.1 3لاة Zd'zy3/1009S 8^100 1Λ1Ν 3لاح 1 ۶1.00ح05ا.اا/3لا2'ل2 3لاة 1 Zl'2y3/6010S8frl00 1.323 1 22900 ٠13Z3/12817Sه8 ' .1.323 ٠13Ζ3/ΐ7908δ22900 ΙΛ1Νل8. 323ا 1 22900 ج323/8908-81.1 0لأ7ا 1 178800 2d'۶ya/S6S 0لا7ا 1 ya/888ZSl78800؛ZJ Zl'frya/Z89ZSl78800 1 frya ه331لأا 1 Zd'iy33ia/96Z9S8frZZl ه331لأ.1 ZJ'iy33ia/96Z9S8frZZl 1Λ1Ν ه331لاا ε^ΖΖΙ. 1ΛΙΝ ج29ح/ه1د3لا.1'21 8d'SdHa/129l7S0fr810 1 SdHO 029frS0fr810 WN SdHO/8J'SdH٥ SdHO ٠٠ 81٠SdHa/6(.9t7S0^810 1 ٧aA3/Z089S01000 1 va٨3'ld 01000 WN vaAOج٧9٨3/1088'ل1 ٧aA3/0088S 01000 ΙΛΙΝ V9A3'll 8d'2dld3/8^9SS 18100 1 2dld3 18100 ΙΛΙΝ 2dld3 ج99دد/3لأ1ك2'ل8 81'2dld3/9^9S'S 18100 ΙΛΙΝ 2dld3 8d'ld8٧y3/8l7fr9SZ8l700 ΙΛΙΝ lda٧d3 8J'lda٧y3/Z۶fr9SZ8l700 ΙΛΙΝ Id9٧d3 ei'ldavdo/wssΖ81 ΙΛΙΝ lda٧d3 3هلاا!d'6!ju٠3SS09S 176890. ΙΛΙΧ019.6,) 1٧٥3!tJ'S!lu٥3/!02S 176890 ΙΛΙΧ019β ' 3هلاا!6 019 ll'S!l٧٠3/0Z0ZS 176890 ΙΛ1Χ 2٧1٦03 ld'2٧l٦03/989frS80000 ΙΛΙΝ 2٧1٦03 03S88S 80000 ΙΛΙΝ!lJ'2٧ 1103^2. 11٠2V1٦03/1788173 80000 ΙΛΙΝ 1٧1103 80000 ΙΛΙΝج7ا٦03/889ا٧ا'ه1 80000 ΙΛΙΝ 1٧1٦Ρ3 ج1٧1٦03/289۶'ل1 1٧1٦٥3 ll'l٧l٦03/189۶s80000 ΙΛΙΝ ٧33 (3) VS3/179Z8S ΖΖ100.1 3Η3'ε٥ 3) V53/ZZZ8S Ζ2100 ΙΛΙΝ3Η3) V33'ل8 ٧33 (٧33/lZZ8SZZ100"l3H3 (81'3 Zd'ld333/98Zl7SZ60Z0 1 ld333 2J'ld333/96frlSZ6020 1 ld333 21' Id333/fc6frIS Ζ60ΖΟ ΙΛΙΝ ld333 992303 ld'asZ3٥3/ZWl7SZ81Z0 ΙΛΙΝ. 892303 1 8120^1J'99Z303/1911S 3د٧3د033د3333د٧3إ3٧د 333٧ثم١د3٧3٧3د٧33٧33ر3١ S133V33W3330333V33V3 3ة٧33٧333د٧3٧0٧د3لد٧ 3د33٧33د٧33د3د٧3٧٧٧3 د3د٧٧33٧333د٧٧د333د٧٧٧لد3د٧33ة ٧333٧٧3د٧د٧33د33د٧3د3٧٧٧د د333د3دد٧٧د3٧3دلد33دد33٧د 33دس33١د3٧د333د33د33333 3٧333٧3٧313٧٧0د33٧٧٧0٧٧3 333دد٧د3د٧3د٧3٧333د3٧3٧ ٧.ل3د3.ل٧د3333يس33١د3مد3٧3د333د د3لد3د٧333٧د3لد33لد٧3د٧ د33د٧33د3٧3333لد٧د٧3 3م3١٠م٠س33٧3٧٧3١د3333٧333٧3د 3333٧3د3٧3لد33لد3٧3د 3٧د333د3ذ333٧لد٧33٧3 ٧٧3د33لد33ثم٧٧3٧١دلد3للده3لد333 3iV3Vi3i33W3ViILV313iV3iL31 د333٧3٧3٧33د3د333لد3٧ ' 3٧س33١د3للد3د3د3333ثم٧33١ 3٧333د٧5333٧٧3س3١د A3A3V3AV33V3313W333 3د٧3لد33٧33٧33٧3333للد33 33بم١د3٧333٧3د33د3ص3١د 1V33VAW31V3333W3V333

33V3VW3V3V333V33V33Z3VZ 3د3333٧33لد3لد33د3لد 33د333د3٧د٧33لد3313 ٧333د3لد3333٧3للد333د3 33333٧3لد3د33د٧3٧د3د 3د33د333٧3333٧د3لذ 333د333٧33د3د33د3دد٧3 د333س3١ذ33د3٧33لد0 ^3لد00٧٧3د00٧٧0٧003 33د33د33د3دد33د3٧333د٧٧د33د 333د33د٧33٧3٧3٧د٧3٧33د 3٧3٧33لمد٧333د3٧٧٧3دد3د٧٧ د3د33د33٧3٧333٧د3للد3لد3د33لد3 م٠سس3١د333د33٧333ى3 3٧٧3٧٧333٧3د33د٧د33٧33٧د د33د3333؟د31٧3د3٧33د3 3٧3د30د33٧.ل٧3د3لد3د٧303 3د٧3333د33٧33د33٧3 د33د٧3د3د3333د3د33لد33 د3333٧٧٧٧د3د3لدد3لد3 0د33٧33٧٧3د3د33٧3٧٧د 33333٧3د3دد3333٧33.3د د3د3٧3د3333٧3٧د٧3د33س١ د٧٧3٧3د33٧3٧33٧3د٧33د . 33د٧33333٧3د3٧3٧د3س333١ 3لد33د٧3د3.لل٧333لأ٧33 ع* 02 02’. 12 02 08 92 92 92 72ا. 82 08 82 . 02 PZ 02 02 62 82 12 92 02 02 172 12 22 ج 61 22 02 81 -2؛ 02 LZ 22 »2 08 61 172 12 82 81 22 02 02 02 82 12 172 02 2016210735 05 Aug 2016 ERKI 211696 ,, S4882/ERK1.P3 ESRRG ΝΜΟ0143 S6130/ESRRG.f3 ESRRG ΝΜ.00143 S6131/ESRRG.r3 ESRRG ΝΜ.00143 S6132/ESRRG.p3 fasl . ΝΜ-00063 SOI 21/fasl.f2 fasl ΝΜ.00063 S0123/fasl.r2 fasl NM_00063S5004/fasl.p2 FBX05 NM_01217S2017/FBXO5.r1 . FBX05 ΝΜ.01217 S2018/FBXO5.f1 FBX05 NM٠01217S5061/FBXO5.p1 FHIT ΝΜ-00201 S2443/FHlT.f1 . FHIT ΝΜ-00201 S2444/FHlT.r1 FHIT ΝΜ.00201 S4921/FHIT.p1 FUS NM_00496S2936/FUS.f1 FUS ΝΜ.00496 S2937/FUS.r1 FUS NM_00496 S4801/FUS.p1 FYN NM 00203 S5695/FYN.f3 FYN ΝΜ.00203 S5696/FYN.r3 FYN ΝΜ-00203 S5697/FYN.p3 G-Catenin NM_00223S2153/G-Cate.f1 . G-Catenin ΝΜ-00223 S2154/G-Cate.٢1 G-Catenin ΝΜ.00223 S5044/G-Cate.p1 GATA3 ΝΜ.00205 S0127/GATA3.f3 GATA3 NM_00205S0129/GATA3.r3 GATA3 ΝΜ.00205 S5005/GATA3.p3 GBPI ΝΜ-00205 S5698/GBP1 .fl GBPI ΝΜ.00205 S5699/GBP1 .rl GBPI NM_00205S5700/GBP1.p1 GBP2 NM_00412S5707/GBP2.f2 GBP2 ΝΜ.00412 S5708/GBP2.r2 GBP2 NM.00412S5709GBP2.p2 GGPSI ΝΜ.00483 SI 590/GGPS1 .fl GGPSI ΝΜ.00483 SI 591/GGPS1 .rl GGPSI ΝΜ.00483 S4896/GGPS1 .pi GRB7 NM 00531 S0130/GRB7.f2 GRB7 ΝΜ_005,31 S0132/GRB7.r2 GRB7 ΝΜ.00531 S4726/GRB7.p2 Hepsin NM_00215S2269/Heps!n.f1 Hepsin ΝΜ.00215 S2270/Hepsin.r1 Hepsin NM_00215S2271/Hepsin.p1 HfA-DPBI ΝΜ.00212 S4573/HLA-DP.f1 HLA-DPBI ΝΜ.00212 S4574/HfA-DP.r1 HfA-DPBI ΝΜ.00212 S4575/HfA-DP.p1 1D2 NM_00216S0151/ID2.f4 ID2 - NM.00216S0153ZlD2.r4 ID2 ΝΜ.00216 S5009/ID2.p4 IGFIR ΝΜ—0008Τ S1249/IGF1 R.f3 IGFIR ΝΜ.00087 SI 250/IGF1 R.r3 IGFIR ΝΜ.00087 S4895/IGF1 R.p3 16ا N.M_00060S0760/!L6.f3 116 ΝΜ.00060 S0761/l(6.3 IL6 NM_0O06OS480O/IL6.p3 35

CGCTGGCTCACCCCTACCTG CCAGCACCATTGTTGAAGAT AGTCTCTTGGGCATCGAGTT CCCCAGACCAAGTGTGAATACATGCT GCACTTTGGGATTCTTTCCATTAT . GCATGTAAGAAGACCCTCACTGAA ACAACAnCTCGGTGCCTGTAACAAAGAA GGATTGTAGACTGTCACCGAAATTC GGCTATTCCTCATTTTCTCTACAAAGTG cctccaggaggctaccttcttcatgttcAc CCAG٢GGAGCGCnCCA٣.

CTCTCTGGGTCGTCTGAAACAA

TCGGCCACTTCATCAGGACGCAG

GGATAATTCAGACAACA4CACCATCT

TGAAGTAATCAGCCACAGACTCAAT

TCAATTGTAACATTCTCACCCAGGCCTTG

GAAGCGCAGATCATGAAGAA

CTCCTCAGACACCACTGCAT

CTGAAGCACGACAAGCTGGTCCAG

TCAGCAGCAAGGGCATCAT

GGTGGTTTTCTTGAGCGTGTACT

CGCCCGCAGGCCTCATCCT

CAAAGGAGCTCACTGTGGTGTCT

GAGTCAGAATGGCTTATTCACAGATG

TGTCCAACCACTGAATCTGGACC

TTGGGAAATATTTGGGCATT

AGAAGCTAGGGTGGTTGTCC

TTGGGACATTGTAGACTTGGCCAGAC

GCATGGGAACCATCAACCA

TGAGGAGTTTGCC٠٢TGATTCG

CCATGGACCAACTTCACTATGTGACAGAGC

CTCCGACGTGGCTTTCCA

CGTAATTGGCAGAATTGATGACA

TGGCCCACAGCATCTATGGAATCCC

CCATCTGCATCCATCTTGTT

GGCCACCAGGGTATTATCTG

CTCCCCACCCTTGAGAAGTGCCT

AGGCTGCTGGAGGTCATCTC

CTTCCTGCGGCCACAGTCT

CCAGAGGCCGTTTCTTGGCCG

TCCATGATGGTTCTGCAGGTT

TGAGCAGCACCATCAGTAACG ccccggaCagtggctctgacg

AACGACTGCTACTCCAAGCTCAA

GGATTTCCATCTTGCTCACCTT

TGCCCAGCATCCCCCAGAACAA

GCATGGTAGCCGAAGATTTCA

TTTCCGGTAATAGTCTGTCTCATAGATATC

CGCGTCATACCAAAATCTCCGATTTTGA

CCTGAACCTTCCAAAGATGG

ACCAGGCAAGTCTCCTCATF

CCAGA٦٢GGAAGCA٦CCA٦٠C-CA

20 20 20 26 24 24 .29 25 28 -30 18 22 23 26 25 29 20 20 24 19 23 19 23 26 24 20 20 26 19 21 30 18 25 20 20 23 20 19 21 21 21. 21 22 22 21 30 28 20 20 ZT 36 2016210735 05 Aug 2016 1LT-2 NM_00666S16U/ILT-2.f2 AGCCATCACTCTCAGTGCAG 20 ILT-2 ΝΜ.00666 S1612/lLT-2.r2 ACTGCAGAGTCAGGGTCTCC 20' ΙΤ-2 NM_00666S4904/lUT-2.p2 CAGGTCCTATCGTGGCCCCTGA- 22 IRSI NM_00554S1943/IRS1.f3 GCACAGCTCACCTTCTGTCA 20 IRS1 - NM_00554S1944/IRS1.r3 CCTCAGTGCCAGTCTCTTCC 20 IRSI NM_00554S5050/IRS1.p3 TCCATCCCAGCTCCAGCCAG 20 KRT18 ΝΜ.00022 S1710/KRT18.f2 AGAGATCGAGGCTCTCAAGG 20 KRT18 NM_OO022S1711/KRT18.r2 GGCCTTTTACTTCCTCTTCG 20 KRT18 NM_00023S4762ZKRT18.p2 TGGTTCTTCTTCATGAAGAGCAGCTCC 27 ΜΑΡΚ14 ΝΜ.13901 S5557/MAPK14.f2 TGAGTGGAAAAGCCTGACCTATG 23 ΜΑΡΚ14 ΝΜ-13901 S5558/MAPK14.r2 GGACTCCATCTCTTCTTGGTCAA 23 ΜΑΡΚ14 ΝΜ.13901 S5559/MAPKl4.p2 TGAAGTCATCAGCmGTGCCACCACC 27 MCM2 NM-00452S1602/MCM2T2 GACTTTTGCCCGCTACCTTTC 21 MCM2 ΝΜ.00452 S1603/MCM2.٢2 GCCACTAACTGCTTCAGTATGAAGAG 26 MCM2 NM_00452S4900/MCM2.p2 ACAGCTCATTGTTGTCACGCCGGA 24 MCM6 ΝΜ~00591 S1704/MCM6.f3 TGATGGTCCTATGTGTCACATTCA 24 MCM6 ΝΜ-00591 S1705/MCM6r3 TGGGACAGGAAACACACCAA 20 MCM6 ΝΜ.00591 S4919/MCM6.P3 CAGGTTTCATACCAACACAGGCTTCAGCAC 30 MCPI ΝΜ.00298 SI 955/MCP1 .fl CGCTCAGCCAGATGCAATC IS MCPI ΝΜ.00298 S1956/MCP1 .٢1 GCACTGAGATCTTCCTATTGGTGAA 25 MCPI NM.00298S5.52/MCP1.p1 TGCCCCAGTCACCTGCTGTTA '21 MGMT ΝΜ-00241 S1922/MGMT.f1 GTGAAATGAAACGCACCACA 20 MGMT NM 00241 S1923/MGMT.r1 GACCCTGCTCACAACCAGAC 20 MGMT ΝΜ-00241 S5045/MGMT.p1 CAGCCCTTTGGGGAAGCTGG 20 ΜΜΡ12 ΝΜ-00242 S4381/MMP12.f2 CCAACGCTTGCCAAATCCT 19 ΜΜΡ12 ΝΜ.00242 S4382/MMP12.r2 ACGGTAGTGACAGCATCAAAACTC 24 ΜΜΡ12 ΝΜ.00242 S4383/MMP12.p2 ' AACCAGCTCTCTGTGACCCCAATT 24 MSH3 ΝΜ.00243 S5940/MSH3.f2 TGATTACCATCATGGCTCAGA 21 MSH3 NM 00243 S5941/MSH3.r2 CTTGTGAAAATGCCATCCAC 20 MSH3 ΝΜ.00243 S5942/MSH3.P2 TCCCAATTGTCGCTTCTTCTGCAG 24 ΜΤΑ1 ΝΜ.00468 S2369/MTA1 .fl ' CCGCCCTCACCTGAAGAGA 19 ΜΤΑ1 ΝΜ.00468 S2370/MTA1 .rl GGAATAAGTTAGCCGCGCTTCT 22 ΜΤΑ1 ΝΜ.00468 S4855/MTA1.P1 CCCAGTGTCCGCCAAGGAGCG 21 MUCI NM 00245 S0782/MUC1 .f2 GGCCAGGATCTGTGGTGGTA 20 MUCI ΝΜ-00245 S0783/MUC1.I-2 CTCCACGTCGTGGACATTGA 20 MUCI NM_00245S4807/MUC1.p2 CTCTGGCCTTCCGAGAAGGTACC 23 NPDOOS (م ΝΜ-02068 S4474/NPD009.f3 GGCTGTGGCTGAGGCTGTAG 20 NPD009 (م ΝΜ_٥2068 S4475/NPD009.r3 ' GGAGCATTCGAGGTCAAATCA 21 NPD009 (م ΝΜ.02068 S4476/NPD009.p3 . TTCCCAGAGTGTCTCACCTCCAGCAGAG '28 PR ΝΜ.00092 S1336/PR.f6 gcatcaGgctgtcattatgg 20 PR ΝΜ.00092 S1337/PR.r6 AGTAGTTGTGCTGCCCTTCC 20 PR ΝΜ.00092 S4743/PR.P6 TGTCCTTACCTGTGGGAGCTGTAAGGTC 28 PRKCD ΝΜΟ0625 S1738/PRKCDT2 CTGACACTTGCCGCAGAGAA 20 PRKCD ΝΜ.00625 SI 739/PRKCD.r2 AGGTGGTCCTTGGTCTGGAA 20 PRKCD ΝΜ.00625 S4923/PRKCD.p2 CCCTTTCTCACCCACCTCATCTGCAC 26 PTPDI ΝΜ-00703 S3069/PTPD1.f2 CGCTTGCCTAACTCATACTTTCC 23 PTPDI ΝΜ-00703 S3070/PTPD1.r2 ccattCagactgcgccactt 20 PTPDI ΝΜ.00703 S4822/PTPD1 .p2 TCCACGCAGCGTGGCACTG 19 RABSC ΝΜ.03214 S5535/RAB6C.f1 GCGACAGCTCCTCTAGTTCCA 21 RAB6C ΝΜ.03214 S5537/RAB6C.p1 TTCCCGAAGTCTCCGCCCG 19 RAB6C ΝΜ.03214 S5538/RAB6C.٢1 GGAACACCAGCTTGAATTTCCT 22 RAIBPI ΝΜ-00678 S5853/RADBP1 .fl -GGTGTCAGATATAAATGTGCAAATGC 26 37 2016210735 05 Aug 2016 RALBP1 ΝΜ.00678 S5854/RAUBP1 .rl ttCgatattgccagcagctataaa 24 RALBPI NMO0678S5855/RAEBP1.p1' TGCTGTCCTGTCGGTCTCAGTACGTTCA 28 RAPIGDS ΝΜ.02115 S5306/RAP1 GD.f2 TGTGGATGCTGGATTGATTT 20 RAPIGDS ΝΜ-02115 S5307/RAP1 GD.r2 AAGCAGCACTTCCTGGTC^ 20 RAPIGDS NM 02115S5308/RAP1GD.p2 CCACTGGTGCAGCTGCTAAATAGCA 25 RASSFI NM_00718S2393/RASSF1.f3 AGTGGGAGACACCTGACCTT 20 RASSFI' 1..00718 S2394/RASSF1 ٠r3 TGATCTGGGCATTGTACTCC 20 RASSFI NM 00718 S4909/RASSF1 ٠p3 TTGATCTTCTGCTCAATCTCAGCTTGAGA 29 rhoC- ΝΜ.00516 S2162/rh٥c.f1 CCCGTTCGGTCTGAGGAA 18 rhoC ΝΜ.00516 S2163/rhoC.r1 GAGCACTCAAGGTAGCCAAAGG 22 rhoC ΝΜ.00516 S5042/rhoC.p1 TCCGGTTCGCCATGTCCCG 19 RUNXI NM 00175 S4S88/RUNX1.f2 4ACAGAGACATTGCCAACCA 20 RUNXI ΝΜ.00175 S4589/RUNX1 .r2 GTGATTTGCCCAGGAAGTTT 20 RUNXI NM 00175 S4590/RUNX1.P2 nGGATCTGCTTGCTGTCCAAACC .. 24 SEMA3F NM 00418 S2857/SEMA3F.f3 CGCGAGCCCCTCATTATACA 20 SEMA3F ΝΜΟ0418 S2858SEMA3F.3 CACTCGCCGTTGAGATCCT 19 SEMA3F ΝΜ-00418 S4972/SEMA3F.p3 CTCCCCACAGCGCATCGAGGAA 22 SGCB ΝΜ.00023 S5752/SGCB.f1 CAGTGGAGACCAGTTGGGTAGTG 23 SGCB ΝΜ-00023 S5753/SGCB.r1 ., CCTTGAAGAGCGTCCCATCA 20 SGCB ΝΜ.00023 S5754/SGCB.p1 CACACATGCAGAGCTTGTAGCGTACCCA 28 STATI ΝΜΟ0731 S1542/STAT1.f3 GGGCTCAGCTTTCAGAAGTG 20 STATI ΝΜ-00731 S1543/STAT1.r3 ACATGTTCAGCTGGTCCACA 20 STATI NM 00731 S4878/STAT1.P3 TGGCAGTTTTCTTCTGTCACCAAAA 25 STAT3 NM 00315 SI 545/STAT3.f1 TCACATGCCACmGGTGTT 20 STAT3 NM٠00315S1546/STAT3.r1 cttgcagGaagcggctatac 20 STAT3 ΝΜ.00315 S4881/STAT3.p1 TCCTGGGAGAGATTGACCAGCA 22 TBP NM 00319S0262^BP.f1 GcccgaaacGccgaatata 19 TBP NM 00319 S0264/TBP.r1 CGTGGCTCTCTTATCCTCATGAT 23 TBP NM 00319 S4751/TBP.p1 taccgcaGcaaaccgcttggg 2Λ ΤΚ1 NM 00325 S0866/TK1 ٠f2 GCCGGGAAGACCGTAATTGT 20 ΤΚ1 NM 00325 S0927TTK1 .r2 CAGCGGCACCAGGTTCAG 18 ΤΚ1 NM 00325 S4798/TK1 .p2 CAAATGGCTTCCTCTGGAAGGTCCCA 26 ΤΡ53ΒΡ1 NM 00565 S1747/TP53BP.f2 TGCTGTTGCTGAGTCTGTTG 20 ΤΡ53ΒΡ1 NM 00565S17487٢P53BP.r2 CTTGCCTGGCTTCACAGATA 20 'ΤΡ53ΒΡ1 NM 00^65 S4924/TP53BP.P2 CCAGTCCCCAGAAGACCATGTCTG 24 TUBB NM 00106 S5826/TUBB.f3 TGTGGTGAGGAAGGAGTCAG 20 TUBB NM_00106S5827/TUBB٠r3 CCCAGAGAGTGGGTCAGC 18 TUBB' NM 00106 S5828/TUBB.p3 CTGTGACTGTCTCCAGGGCTTCCA 24 NiCl NM 00107 S3505/VCAM1.f1 TGGCTTCAGGAGCTGAATACC 21 VCAMI NM 00107 S3506/VCAM1.r1 tgctgtCgtgatgagaaaatagtg . 24 VCAMI NM 00107 S3507/VCAM1 .pi CAGGCACACACAGGTGGGACACAAAT 26 Wnt-5a ΝΜ_00339 S6183/Wnt٠5a.f1 GTATCAGGACCACATGCAGTACATC 25 Wnt-5a NM_00339S6184/Wnt٠5a.r1 TGTCGGAATTGATACTGGCATT 22 WntSa NM 00339 S6185/Wnt-5a.p1 TTGATGCC'TGTCTTCGCGCCTTCT 24 ZNF38 ΝΜ-14591 S5593/ZNF38T3 TTTCCAAACATCAGCGAGTC 20 ZNF38 ΝΜ-14591 S5594/ZNF38.r3 ... AACAGGAGCGCTTGAAAGTT 20 ZNF38 NM 14591 S5595/ZNF38.P3 ACGGTGCTTCTCCCTCTCCAGTG 23 2016210735 05 Aug 2016 ؛ i Sequence ; ٠٠ ٠٣ TABLE 3

FBX05 NM01217GGCTAICTCATTTTCTCTACAMGT0GCCTCAGTGAACATGMGAAGGTAGCCTCCTGGAGGAGAATrTCGGTGACAGTCTACAATCC

π CTCA

GBpf'^Ioo^OsiGG^TAmGlc^G^^GCcLTCTACMTGTCCC^TC^^CAACCACCC^kGCTrCT GGPSI νμΟ٥483 CTCCGACGTGGcTracAGTGGcccACAGCATCTATGGAATCC 2016210735 05 Aug 2016 II يى

Claims (13)

1. WHAT IS CLAIMED IS:

   1. A method for determining the likelihood of a beneficial response of a human patient with breast cancer to an anthracycline-based chemotherapy, comprising: determining a normalized expression level of an RNA transcript of BAG1 in a breast cancer sample obtained from said patient; and predicting the likelihood of a beneficial response of the patient to the anthracycline-based chemotherapy using said normalized BAG1 expression level, wherein said normalized BAG1 expression level is negatively correlated with the likelihood of a beneficial response of the patient to the anthracycline-based chemotherapy.
2. 2. The method of claim 1, wherein said breast cancer is invasive breast cancer.
3. 3. The method of claim 1 or claim 2, wherein the anthracycline-based chemotherapy comprises administering doxorubicin.
4. 4. The method of any one of claims 1 to 3, wherein the anthracycline-based chemotherapy comprises administration of a taxane in addition to an anthracycline.
5. 5. The method of claim 4, wherein the taxane is docetaxel.
6. 6. The method of claim 4, wherein said taxane is paclitaxel.
7. 7. The method of any one of claims 1 to 6, wherein said chemotherapy is adjuvant chemotherapy.
8. 8. The method of any one of claims 1 to 6, wherein said chemotherapy is nonadjuvant chemotherapy.
9. 9. The method of any one of claims 1 to 8, wherein said breast cancer sample is fixed, paraffin-embedded, fresh, or frozen.
10. 10. The method of any one of claims 1 to 9, wherein said RNA is isolated from a fixed, paraffin-embedded breast cancer sample of said patient.
11. 11. The method of any one of claims 1 to 10, wherein the beneficial response is a clinical complete response.
12. 12. The method of any one of claims 1 to 10, wherein the beneficial response is a pathological complete response.
13. 13. The method of any one of claims 1 to 12, wherein the expression level of said RNA transcript is determined by RT-PCR.