Citations

Purpose In 1998, the US Food and Drug Administration (FDA) approved human epidermal growth factor receptor 2 (HER2) testing guidelines to determine eligibility for HER2-directed therapy (HDT) in breast cancer. ASCO and the College of American Pathologists published immunohistochemistry (IHC) and fluorescent in situ hybridization (FISH) HER2 testing guidelines in 2007 (AC2007) and updated these guidelines in 2013 (AC2013). We compared the HER2 FISH amplification frequency using these three guidelines. Methods Patient samples that were sent to the Mayo Clinic cytogenetics laboratory for FISH testing (n = 2,851; from November 2013 to October 2014) were analyzed. Frequency of HER2 FISH amplification was examined and impact of AC2013 assessed. Results IHC results were available for 1,922 patient samples (67.4%), 137 of which were from Mayo Clinic. Distribution was 2.4% IHC 0, 7.9% IHC 1+, 84.8% IHC 2+, and 2.5% IHC 3+. Among IHC 2+ patients, HER2 FISH positivity was 11.8% (FDA), 9.4% (AC2007), and 24.1% (AC2013). Overall, 11.8% (n = 339) were positive with a FISH ratio ≥ 2.0, 1.3% (n = 35) with a FISH ratio ≥ 2.0 despite a HER2 signal < 4.0, and 3.0% (n = 86) with HER2 signal ≥ 6.0 despite FISH ratio < 2.0. Among 405 patients (14.2%) who were initially considered FISH-equivocal (ratio < 2.0 with HER2 signal ≥ 4.0, but < 6.0; AC2013), use of an alternative chromosome 17 probe reassigned 212 (7.4% overall) patients to FISH-positive and 36 (1.3% overall) patients to FISH-negative, whereas 157 (5.5% overall) patients remained equivocal. Final HER2 positivity with AC2013 (23.6%) was increased (P < .001) compared with FDA (13.1%) and AC2007 (11%) guidelines. Conclusion In a reference laboratory cohort that was highly enriched for IHC 2+ patient samples, AC2013 guidelines led to a larger number of FISH-equivocal patients. Approximately one half of these FISH-equivocal patients (7.4% overall) became HER2-positive upon alternative FISH probe testing. However, these patients would not have participated in the pivotal HDT trials. Clinical utility data on HDT benefit in these patients and other special subsets are needed.

Abstract The addition of trastuzumab to chemotherapy extends survival among patients with HER2+ breast cancer. Prior work showed that trastuzumab and chemotherapy augments HER2 extracellular domain (ECD)-specific antibodies. The current study investigated whether combination therapy induced immune responses beyond HER2-ECD and, importantly, whether those immune responses were associated with survival. Pretreatment and posttreatment sera were obtained from 48 women with metastatic HER2+ breast cancer on NCCTG (now Alliance for Clinical Trials in Oncology) studies, N0337 and N983252. IgG to HER2 intracellular domain (ICD), HER2-ECD, p53, IGFBP2, CEA, and tetanus toxoid were examined. Sera from 25 age-matched controls and 26 surgically resected HER2+ patients were also examined. Prior to therapy, some patients with metastatic disease had elevated antibodies to IGFBP2, p53, HER2-ICD, HER2-ECD, and CEA, but not to tetanus toxin, relative to controls and surgically resected patients. Treatment augmented antibody responses to HER2-ICD in 69% of metastatic patients, which was highly associated with improved progression-free survival (PFS; HR = 0.5, P = 0.0042) and overall survival (OS; HR = 0.7, P = 0.038). Augmented antibody responses to HER2-ICD also correlated (P = 0.03) with increased antibody responses to CEA, IGFBP2, and p53, indicating that treatment induces epitope spreading. Paradoxically, patients who already had high preexisting immunity to HER2-ICD did not respond to therapy with increased antibodies to HER2-ICD and demonstrated poorer PFS (HR = 1.6, P &lt; 0.0001) and OS (HR = 1.4, P = 0.0006). Overall, the findings further demonstrate the importance of the adaptive immune system in the efficacy of trastuzumab-containing regimens. Cancer Res; 76(13); 3702–10. ©2016 AACR.

Abstract Motivation: Single-cell RNA-sequencing technology allows detection of gene expression at the single-cell level. One typical feature of the data is a bimodality in the cellular distribution even for highly expressed genes, primarily caused by a proportion of non-expressing cells. The standard and the over-dispersed gamma-Poisson models that are commonly used in bulk-cell RNA-sequencing are not able to capture this property. Results: We introduce a beta-Poisson mixture model that can capture the bimodality of the single-cell gene expression distribution. We further integrate the model into the generalized linear model framework in order to perform differential expression analyses. The whole analytical procedure is called BPSC. The results from several real single-cell RNA-seq datasets indicate that ∼90% of the transcripts are well characterized by the beta-Poisson model; the model-fit from BPSC is better than the fit of the standard gamma-Poisson model in &gt; 80% of the transcripts. Moreover, in differential expression analyses of simulated and real datasets, BPSC performs well against edgeR, a conventional method widely used in bulk-cell RNA-sequencing data, and against scde and MAST, two recent methods specifically designed for single-cell RNA-seq data. Availability and Implementation: An R package BPSC for model fitting and differential expression analyses of single-cell RNA-seq data is available under GPL-3 license at https://github.com/nghiavtr/BPSC . Contact: yudi.pawitan@ki.se or mattias.rantalainen@ki.se Supplementary information: Supplementary data are available at Bioinformatics online.

Abstract We previously reported, on the basis of a genome-wide association study for aromatase inhibitor-induced musculoskeletal symptoms, that single-nucleotide polymorphisms (SNPs) near the T-cell leukemia/lymphoma 1A (TCL1A) gene were associated with aromatase inhibitor-induced musculoskeletal pain and with estradiol (E2)-induced TCL1A expression. Furthermore, variation in TCL1A expression influenced the downstream expression of proinflammatory cytokines and cytokine receptors. Specifically, the top hit genome-wide association study SNP, rs11849538, created a functional estrogen response element (ERE) that displayed estrogen receptor (ER) binding and increased E2 induction of TCL1A expression only for the variant SNP genotype. In the present study, we pursued mechanisms underlying the E2-SNP-dependent regulation of TCL1A expression and, in parallel, our subsequent observations that SNPs at a distance from EREs can regulate ERα binding and that ER antagonists can reverse phenotypes associated with those SNPs. Specifically, we performed a series of functional genomic studies using a large panel of lymphoblastoid cell lines with dense genomic data that demonstrated that TCL1A SNPs at a distance from EREs can modulate ERα binding and expression of TCL1A as well as the expression of downstream immune mediators. Furthermore, 4-hydroxytamoxifen or fulvestrant could reverse these SNP-genotype effects. Similar results were found for SNPs in the IL17A cytokine and CCR6 chemokine receptor genes. These observations greatly expand our previous results and support the existence of a novel molecular mechanism that contributes to the complex interplay between estrogens and immune systems. They also raise the possibility of the pharmacological manipulation of the expression of proinflammatory cytokines and chemokines in a SNP genotype-dependent fashion.

Abstract Breast cancer is the most common invasive cancer in women worldwide and treatment related toxicity has high inter-patient variability. Our goal was to identify additional genetic predictors of toxicity by completing a pathway based analysis taking advantage of the genotyping results obtained through a GWAS of the same patients. For our analysis, we have utilized GWA data from the SUCCESS-A trial in which 3,754 breast cancer patients were treated with adjuvant chemotherapy. We have included SNPs associated with 112 genes involved in drug disposition and 375 genes in selected cancer pathways. We identified 35 SNPs associated with neutropenia (P-value &lt;1×10−4). These patients initially received three cycles consisting of 5-fluorouracil (5-FU), cyclophosphamide, and epirubicin. Currently we are characterizing the function of three SNPs located within an intron of the hyaluronan mediated motility receptor (HMMR) gene that are associated with the neutropenia phenotype (P-value &lt;1×10−4). These SNPs are highly associated with the expression of a gene encoding a B-cell survival factor, TNFSF13B, (P-value &lt;1×10−5). Our in vitro studies using lymphoblastoid cell lines (LCLs) selected based on the genotypes of HMMR gene showed that heterozygous and homozygous variant cells (n = 6) have an increased sensitivity to 5-fluorouracil, but not cyclophosphamide or epirubicin when compared with homozygous wild-type cells (n = 6). LCLs exposed to the previously mentioned chemotherapeutic agents resulted in an upregulation of TNFSF13B gene expression and downregulation of HMMR gene expression. We have utilized a pathway based approach to analyzing GWA data to identify several SNPs in the HMMR gene highly associated with the expression of one of the top signals in the cytopenia GWAS. Our goal is to further characterize the role of HMMR gene variants in chemotherapy response by assessing whether combinations of these agents in vitro (including 5-FU) also have a genotype dependent response to cytotoxicity. Citation Format: Behzad Bidadi, Krishna R. Kalari, Matthias Rubner, Alexander Hein, Matthias W. Beckmann, Peter A. Fasching, Brigitte Rack, Wolfgang Janni, Richard Weinshilboum, Liewei Wang. Utilizing a pathway based analysis of genome wide association data to identify biomarkers of toxicity in breast cancer patients. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 5488. doi:10.1158/1538-7445.AM2015-5488

Abstract Introduction: Triple negative breast cancers (TNBC) are characterized as lacking estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2) expression and TNBC patients have higher rates of recurrence and death compared with other breast cancer subtypes. For TNBC patients who fail standard chemotherapy, there are a lack of novel drug therapies, given the absence of well-defined molecular targets. Recently, a microarray meta-analysis identified 7 triple negative subtypes, including the validation of the luminal androgen receptor (LAR) positive subtype [Lehmann, 2011]. However, microarray technology is dependent on probe-target specificity and the 7 subtypes have yet to be validated using RNA sequencing data, and the presences of recurrent genomic alterations in the 7 subtypes are unknown. METHODS: We obtained 1106 breast cancer RNA-Seq bam files from The Cancer Genome Atlas (TCGA) and aligned with Tophat v1.3. The PAM50 intrinsic gene signature was used to extract a cohort of 128 TNBC samples. Consensus clustering of genes, greater than 75th percentile of variance, was performed using Kmeans clustering in Spearman's correlation space. A nearest centroid prediction model was developed from genes differentially expressed among the clusters. Eighty independent TNBC RNA sequencing samples were obtained (British Colombia; BC) [Shah, 2012] which were calibrated to our TNBC conditional quantile normalized cohort and sub-typed by our model. RESULTS: Using RNA-Seq gene expression count data, we identified 5 clusters, all of which were stable, including the LAR cluster. Signaling pathway impact analysis (SPIA) implicated cytokine-cytokine receptor interaction, leukocyte transendothelial migration, and regulation of actin cytoskeleton pathways commonly altered in the non-LAR TNBC subtypes. In contrast, cell cycle, ECM-receptor interaction, endocrine regulated calcium reabsorption, and insulin signaling pathways were altered in the LAR versus non-LAR subtypes. Neuroactive ligand-receptor interactions were observed to be altered commonly between all sub-types. We then applied our model to the Shah, et al cohort. In this cohort, the LAR subtype was consistent with Shah's classification of ‘other’ TNBC and contained no basal samples by PAM50 intrinsic modeling. Analysis of sub-type specific mutation data from the BC cohort demonstrates an increased mutational load in ECM-related proteins, particularly the myosins, along with increased TP53 clonality in the non-LAR subtypes. CONCLUSIONS: Using TCGA RNASeq data, we have confirmed the presence of 5 major TNBC subtypes, including the LAR; which was negligible in basal composition by PAM50 intrinsic modeling. SPIA pathway analysis indicates a core set of pathways demonstrating altered expression across the TNBC sub-types and the identification of molecular targets within each subtype is ongoing. Citation Format: Kevin J. Thompson, Xiaojia Tang, Zhifu Sun, Jason P. Sinnwell, Hugues Sicotte, Douglas W. Mahoney, Steven Hart, Peter T. Vedell, Poulami Barman, Jeanette E. Eckel Passow, Eric D. Wieben, James N. Ingle, Judy C. Boughey, Liewei Wang, Richard Weinshilboum, Krishna R. Kalari, Matthew P. Goetz. Molecular classification of triple negative breast cancer via RNA-sequencing data. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 5592. doi:10.1158/1538-7445.AM2014-5592

Abstract INTRODUCTION Next generation sequencing (NGS) of patients has significantly changed our ways to study cancer genomics as it provides precise estimates of gene expression, fusion transcripts, expressed single nucleotide variants (eSNVs), splice variants and copy number variants. The Breast Cancer Genome Guided Therapy (BEAUTY) is an ongoing clinical study in which RNA sequencing (RNAseq) and whole exome sequencing (WES) are performed prior to, during and after neoadjuvant chemotherapy. Here we report the use of these sequencing technologies to investigate gene expression levels and mutational profiles in a triple negative breast cancer (TNBC) patient enrolled in BEAUTY whose disease did not respond to neoadjuvant paclitaxel and anthracycline/cycphosphamide. METHODS Computational approaches were used to integrate WES and RNAseq data obtained before therapy (V1T), after 12 weekly paclitaxel treatments (V2T) and after anthracycline-based regimen at surgical resection (V3T) to study a single patient with persistent TNBC disease after neoadjuvant chemotherapy. RESULTS Using RNA-Seq data, we identified an inter-chromosomal fusion transcript between chromosome 20 and 22 (GNAS-TTC38) that was highly expressed at V1T, V2T and V3T. We also identified intra-chromosomal fusion transcripts that were expressed at two time points, such as fusion transcript (KANSL1-ARL17A) on chromosome 17 for V1T and V2T and fusion transcript (RBM12B-LINC00535) on chromosome 8 for V2T and V3T time points. Several gene expression changes were also observed. Gene expression analysis of V1T, V2T and V3T tumors was performed. Differential temporal gene expression profiles of 9884 genes that were significant and varying at different time points were obtained for pathway analysis. Pathway analysis of 9884 genes identified up regulation and down regulation of several transcription factors with a fold change of 2x or more. When compared to blood, DNA tumor and RNA-Seq data, we identified 81 common somatic eSNVs that were expressed in both V1T and V2T time points and we are in the process of investigating V3T data. We found alterations of key transporter domains (CD225, Coatamer_beta_C, DUF2435, Dynamitin, EI24, GLTP, LMF1, Porin_3, V-ATPase_C) in our V1T and V2T SNV data. Similar to gene expression analysis, we are in the process of obtaining the list of mutations at various time points to identify driver and passenger mutation candidate genes for this specific TNBC patient. CONCLUSIONS Our initial time-series analysis of eSNV, fusion transcripts and gene expression data demonstrate that intensive analysis for individual patients is feasible. Further investigation of drug transporters and transcription regulators may help develop personalized treatment strategies for patients with disease resistant to current regimens. Citation Format: Krishna R. Kalari, Xiaojia Tang, Kevin J. Thompson, Douglas W. Mahoney, Poulami Barman, Jason P. Sinnwell, Hugues Sicotte, Peter Vedell, Steven N. Hart, Travis J. Dockter, Katie N. Jones, Amy L. Conners, Ann M. Moyer, Daniel W. Visscher, Jia Yu, Bowen Gao, Sarah A. McLaughlin, John A. Copland, Alvaro Moreno-Aspitia, Donald W. Northfelt, Richard J. Gray, Vera J. Suman, Jeanette E. Eckel Passow, Jean-Pierre A. Kocher, Eric D. Wieben, Gianrico Farrugia, Cloann G. Schultz, James N. Ingle, Richard Weinshilboum, Matthew P. Goetz, Liewei Wang, Judy C. Boughey. Analysis of sequencing data to identify potential drug targets for an individual newly diagnosed with basal breast cancer who failed to respond to current standard neoadjuvant chemotherapy. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 4185. doi:10.1158/1538-7445.AM2014-4185

Abstract Background Cancer genomic investigations have identified recurrent genomic aberrations critical for cancer initiation, progression, and metastases. However, these investigations are typically performed in isolation, and the effects of treatment on the clonal selection of tumor cells are mostly unknown. We hypothesized that molecular profiling of residual tumors after neoadjuvant chemotherapy (NAC) would identify new drug targets/pathways in patients at high risk for disease recurrence. To better identify clonal populations of resistant breast cancer cells, we utilized DNA content-based flow sorting of nuclei to identify and isolate clonal populations for aCGH and next generation sequencing (NGS) both before and after NAC. Methods The Breast Cancer Genome Guided Therapy Study (BEAUTY) (NCT 02022202) is a prospective study of patients with high-risk breast cancer treated with neoadjuvant 12 weekly paclitaxel (T) +/- trastuzumab followed by 4 cycles of anthracycline based chemotherapy. Tumor tissue from baseline, residual disease from surgery, distant metastases, and patient derived xenografts (PDX) are obtained for cell sorting by DNA ploidy, aCGH, RNA and exome sequencing. Results: 140 patients have been enrolled, 104 have completed surgery and 30 unique PDX have been established corresponding to 26 patients prior to chemotherapy and 4 from residual disease at surgery. Baseline exome and RNA sequencing is complete in 140. Currently, genomic analyses of flow sorted matched baseline, surgical, PDX, and distant disease samples are available in 6 patients. Substantial genomic variation was observed in the surgical sample compared to the primary tumor including gain of oncogenic drivers (EGFR) and loss of negative regulators (ATG5) (Table). The PDX recapitulated these events with excellent fidelity compared to the corresponding human tumor. In patients with TNBC, RNA seq obained from matched samples demonstrated changes in immune related pathways. Evaluation of drug targets/pathways identified in the resistant tumors are ongoing using the PDX and sequencing of the remaining matched baseline/surgical disease will be reported. Clonal changes occurring over time in patients with residual disease or disease recurrence after NACTumor SubtypeResidual Cancer BurdenDisease StatusClonal Aberration Changes (baseline and post NAC)TNBC (AR subtype)3Contralateral lymph node recurrence at 150 days2p25.2 - p25.1 amplicon lost at recurrence; 6p21.32 -p21.31 amplicon lost at recurrenceTNBC (BL 1)3Bone/liver/lymph node recurrence at 135 days5q11.2 amplicon gained at surgery; 12p13.33 - p13.2 amplicon gained at surgeryTNBC (BL 1)3Disease-free at day 1506q21 amplicon lost at sugeryTNBC (BL 2)0Brain recurrence at 390 daysChr 2 chromothripsis at surgeryLuminal B3Progression during chemotherapy7p12.1 - p11.2 amplicon gained at surgeryLuminal HER23Disease-free at day 3609q33.2 amplicon lost at surgery; 15q13.1 - q13.3 amplicon lost at surgery; 15q22.2 - q24.1 amplicon lost at surgery Conclusions: We observed substantial evolutionary changes in residual breast tumors remaining after NAC. Our findings suggest that a comprehensive assessment of the mutational landscape that has evolved during NAC can inform drug development in high risk breast cancer patients. Citation Format: Matthew P Goetz, Michael T Barrett, Krishna R Kalari, Vera J Suman, Sarah A McLaughlin, Alvaro Moreno-Aspitia, Ann M Moyer, Donald W Northfelt, Richard J Gray, Jason Sinnwell, Douglas Mahoney, Poulami Barman, Peter Vedell, Xiaojia Tang, Kevin Thompson, Travis Dockter, Katie Jones, Sara J Felten, Amy Conners, Jeanette Eckel-Passow, Hughes Sicotte, Steven N Hart, Jia Yu, Daniel W Visscher, Eric D Wieben, Cloann Schultz, Minetta C Liu, James N Ingle, Liewei Wang, Richard W Weinshilboum, Judy C Boughey. Impact of neoadjuvant chemotherapy on the clonal composition of breast cancer [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr PD3-3.

Abstract INTRODUCTION Patient derived xenografts (PDX) may better reflect individual patient (pt) tumor biology; however, the feasibility of collecting PDX from percutaneous tumor biopsies (PTB) in the neoadjuvant setting is unknown. Furthermore, drug response phenotypes observed in PDX have not been prospectively compared to the corresponding pt clinical outcomes. METHODS The Breast Cancer Genome Guided Therapy Study (BEAUTY) is a prospective Mayo study of pts with high-risk breast cancer treated with neoadjuvant weekly paclitaxel (T) +/- trastuzumab followed by anthracycline based chemotherapy. PTB (at baseline) and residual surgical tissue (after all chemotherapy) are obtained for next generation sequencing (NGS) and PDX. Tumor biopsies (1-2 cores from 14 gauge needle) were implanted with Matrigel &lt;1 hour of collection in the flanks of NOD-SCID or NSG mice. Low dose estradiol was supplemented in the drinking water. Primary outgrowth rate was defined as PDX tumor volume &gt;50 mm3. Take rate was defined as development of at least 1 stably transplantable xenograft line/pt. To determine whether clinical T response assessed by MRI corresponded with in vivo T response, pretreatment PDX from 5 pts were injected into NOD-SCID mice (20 mice per pt PDX) and when tumors reached 100-200mm3, mice were randomized to no treatment vs T (20 mg/kg, ip. every 3-4 days). Two of these 5 patients had a MRI response defined as &gt;30% decrease in longest lesion. RESULTS Pretreatment PTB from 81 unique pts were implanted in 251 mice (2-4 mice/pt). PDX outgrowth rates were 33.3% (27/81 pts) and 22 stable PDX were established (overall take rate 27.2%). Take rates were as follows: triple negative breast cancer (46%; 13/28); HER2 (27%; 6/22), Luminal B (13%; 3/22), and luminal A (0%; 0/9). Residual surgical tumor (after all treatment) from 17 pts was injected into 85 mice (average 5 mice/pt) and the initial outgrowth rate was 23% (4/17) with 3 stably transplantable lines established. PDX, derived from pretreatment PTB of 5 pts (2 responders and 3 non-responders), were assessed for in vivo T response. The size of the T treated group was significantly smaller than the no treatment group for the PDX derived from the 2 clinical responders, with complete disappearance of tumor by 18 days. In contrast, the PDX derived from the 3 clinical non-responders had no evidence for T response. CONCLUSIONS We have demonstrated the feasibility of using PTB to establish PDX in a prospective neoadjuvant clinical study and have demonstrated similar T drug response phenotypes in in the PDX as seen in the corresponding pt. These data suggest that PDX generated prospectively may be useful for biomarker validation and the development and individualization of new drug therapy. Funded by the Mayo Clinic Center for Individualized Medicine and the Mayo Clinic Cancer Center Citation Format: Jia Yu, Ping Yin, Bowen Gao, Jason P. Sinnwell, Ann M. Moyer, Daniel W. Visscher, Amy L. Conners, Travis J. Dockter, Krishna R. Kalari, Xiaojia Tang, Kevin J. Thompson, Hugues Sicotte, Douglas W. Mahoney, Steven N. Hart, Peter T. Vedell, Poulami Barman, Katie N. Jones, Sarah A. McLaughlin, John A. Copland, Alvaro Moreno Aspitia, Donald W. Northfelt, Richard J. Gray, Vera J. Suman, Jeanette E. Eckel Passow, Eric D. Wieben, James N. Ingle, Zhenkun Lou, Gianrico Farrugia, Richard Weinshilboum, Matthew P. Goetz, Judy C. Boughey, Liewei Wang. Feasibility of using percutaneous tumor biopsies from a prospective neoadjuvant breast cancer study to develop patient derived xenografts and assess in vivo chemotherapy sensitivity. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 1195. doi:10.1158/1538-7445.AM2014-1195

Purpose To develop a genomic signature that predicts benefit from trastuzumab in human epidermal growth factor receptor 2–positive breast cancer. Patients and Methods DASL technology was used to quantify mRNA in samples from 1,282 patients enrolled onto the Combination Chemotherapy With or Without Trastuzumab in Treating Women With Breast Cancer (North Central Cancer Treatment Group N9831 [NCCTG-N9831]) adjuvant trastuzumab trial. Cox proportional hazard ratios (HRs), adjusted for significant clinicopathologic risk factors, were used to determine the association of each gene with relapse-free survival (RFS) for 433 patients who received chemotherapy alone (arm A) and 849 patients who received chemotherapy plus trastuzumab (arms B and C). Network and pathway analyses were used to identify key biologic processes linked to RFS. The signature was built by using a voting scheme. Results Network and functional ontology analyses suggested that increased RFS was linked to a subset of immune function genes. A voting scheme model was used to define immune gene enrichment based on the expression of any nine or more of 14 immune function genes at or above the 0.40 quantile for the population. This model was used to identify immune gene–enriched tumors in arm A and arms B and C. Immune gene enrichment was linked to increased RFS in arms B and C (HR, 0.35; 95% CI, 0.22 to 0.55; P < .001), whereas arm B and C patients who did not exhibit immune gene enrichment did not benefit from trastuzumab (HR, 0.89; 95% CI, 0.62 to 1.28; P = .53). Enriched immune function gene expression as defined by our predictive signature was not associated with increased RFS in arm A (HR, 0.90; 95% CI, 0.60 to 1.37; P = .64). Conclusion Increased expression of a subset of immune function genes may provide a means of predicting benefit from adjuvant trastuzumab.