Edith A Perez1, E Aubrey Thompson2, Karla V Ballman2, S Keith Anderson2, Yan W Asmann2, Krishna R Kalari2, Jeanette E Eckel-Passow2, Amylou C Dueck2, Kathleen S Tenner2, Jin Jen2, Jian-Bing Fan2, Xochiquetzal J Geiger2, Ann E McCullough2, Beiyun Chen2, Robert B Jenkins2, George W Sledge2, Eric P Winer2, Julie R Gralow2, Monica M Reinholz2. 1. Edith A. Perez, E. Aubrey Thompson, Yan W. Asmann, and Xochiquetzal J. Geiger, Mayo Clinic, Jacksonville, FL; Karla V. Ballman, S. Keith Anderson, Krishna R. Kalari, Jeanette E. Eckel-Passow, Kathleen S. Tenner, Jin Jen, Beiyun Chen, Robert B. Jenkins, and Monica M. Reinholz, Mayo Clinic, Rochester, MN; Amylou C. Dueck, and Ann E. McCullough, Mayo Clinic, Scottsdale, AZ; Jian-Bing Fan, Illumina, San Diego, CA; George W. Sledge, Stanford School of Medicine, Palo Alto, CA; Eric P. Winer, Harvard Medical School, Boston, MA; and Julie R. Gralow, Seattle Cancer Care Alliance, Seattle, WA. perez.edith@mayo.edu. 2. Edith A. Perez, E. Aubrey Thompson, Yan W. Asmann, and Xochiquetzal J. Geiger, Mayo Clinic, Jacksonville, FL; Karla V. Ballman, S. Keith Anderson, Krishna R. Kalari, Jeanette E. Eckel-Passow, Kathleen S. Tenner, Jin Jen, Beiyun Chen, Robert B. Jenkins, and Monica M. Reinholz, Mayo Clinic, Rochester, MN; Amylou C. Dueck, and Ann E. McCullough, Mayo Clinic, Scottsdale, AZ; Jian-Bing Fan, Illumina, San Diego, CA; George W. Sledge, Stanford School of Medicine, Palo Alto, CA; Eric P. Winer, Harvard Medical School, Boston, MA; and Julie R. Gralow, Seattle Cancer Care Alliance, Seattle, WA.
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 theCombination Chemotherapy With or Without Trastuzumabin 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 receivedchemotherapy 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.
RCT Entities:
PURPOSE: To develop a genomic signature that predicts benefit from trastuzumab in humanepidermal 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.
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