Genomic analysis reveals that immune function genes are strongly linked to clinical outcome in the North Central Cancer Treatment Group n9831 Adjuvant Trastuzumab Trial

Edith A Perez, E Aubrey Thompson, Karla V Ballman, S Keith Anderson, Yan W Asmann, Krishna R Kalari, Jeanette E Eckel-Passow, Amylou C Dueck, Kathleen S Tenner, Jin Jen, Jian-Bing Fan, Xochiquetzal J Geiger, Ann E McCullough, Beiyun Chen, Robert B Jenkins, George W Sledge, Eric P Winer, Julie R Gralow, Monica M Reinholz, Edith A Perez, E Aubrey Thompson, Karla V Ballman, S Keith Anderson, Yan W Asmann, Krishna R Kalari, Jeanette E Eckel-Passow, Amylou C Dueck, Kathleen S Tenner, Jin Jen, Jian-Bing Fan, Xochiquetzal J Geiger, Ann E McCullough, Beiyun Chen, Robert B Jenkins, George W Sledge, Eric P Winer, Julie R Gralow, Monica M Reinholz

Abstract

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.

Trial registration: ClinicalTrials.gov NCT00005970.

Conflict of interest statement

Authors' disclosures of potential conflicts of interest are found in the article online at www.jco.org. Author contributions are found at the end of this article.

© 2015 by American Society of Clinical Oncology.

Figures

Fig 1.
Fig 1.
CONSORT diagram describing the process whereby 1,282 samples were selected for downstream analyses. The Combination Chemotherapy With or Without Trastuzumab in Treating Women With Breast Cancer (North Central Cancer Treatment Group N9831 [NCCTG-N9831]) trial registered 3,505 patients of whom 1,282 (arm A, 433; arm B, 477; arm C, 372) were evaluable for DASL (cDNA-mediated annealing, selection, extension, and ligation) gene expression profiling. The median follow-up time was 6 years and 11 months and included all follow-up available through March 22, 2012. All tumors included in this article were tested for human epidermal growth factor receptor 2 (HER2) protein overexpression by immunohistochemistry and/or gene amplification by fluorescent in situ hybridization at a central laboratory (Mayo Clinic, Rochester, MN), and some tumors were excluded after central review of HER2 status. The largest cause of exclusion was insufficient tissue. Quality control (QC) failure after DASL analysis eliminated a small number of samples.
Fig 2.
Fig 2.
Network models reveal functional connections between genes associated with outcome in the Combination Chemotherapy With or Without Trastuzumab in Treating Women With Breast Cancer (North Central Cancer Treatment Group N9831 [NCCTG-N9831]) trial. The Cytoscape Functional Interactome tool integrates functional relationships defined by multiple bioinformatics tools, including protein-protein and gene-gene interaction data sets. This tool was used to define networks associated with either decreased relapse-free survival (RFS; panels A and C) or increased RFS (panels B and D) in arm A (panels A and B) or arms B/C (panels C and D). Networks were constructed by using genes with significant hazard ratios (P < .01), identified in the Data Supplement. Insertion of a single linker gene was allowed in network construction.
Fig 3.
Fig 3.
A cohort of immune function genes is strongly associated with outcome after trastuzumab treatment in the N9831 trial but has no effect on relapse-free survival (RFS) following chemotherapy alone. Tumors in arm A and arms B/C were “binned” into immune-enriched and not immune-enriched by using the voting model in which enrichment was defined by the m9q41 model. (A) RFS for enriched and not enriched subsets of tumors from both arms. (B) RFS for the enriched subset of tumors from both arms. (C) RFS for the not enriched subset of tumors from both arms. HR, hazard ratio.
Fig A1.
Fig A1.
Cross validation of the immune function score model. The data were randomly split into five cohorts, and the optimal q/m combination was selected based on four cohorts. This q/m relationship was then used to determine whether a tumor was immune enriched (IRE) or not immune enriched (NIRE) in the remaining cohort. Each tumor was classified 100 times (once for each cross validation). The curves show the results of the observed relapse-free survival based on these 100 different cross-validation sets; hence, there is a total of 128,200 observations (arm A: IRE, 18,117 and NIRE, 25,183; arms B/C: IRE, 36,877 and NIRE, 48,023). HR, hazard ratio.

Source: PubMed

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