Predicting degree of benefit from adjuvant trastuzumab in NSABP trial B-31

TY - JOUR

T1 - Predicting degree of benefit from adjuvant trastuzumab in NSABP trial B-31

AU - Pogue-Geile, Katherine L

AU - Kim, Chungyeul

AU - Jeong, Jong-Hyeon

AU - Tanaka, Noriko

AU - Bandos, Hanna

AU - Gavin, Patrick G

AU - Fumagalli, Debora

AU - Goldstein, Lynn C

AU - Sneige, Nour

AU - Burandt, Eike

AU - Taniyama, Yusuke

AU - Bohn, Olga L

AU - Lee, Ahwon

AU - Kim, Seung-Il

AU - Reilly, Megan L

AU - Remillard, Matthew Y

AU - Blackmon, Nicole L

AU - Kim, Seong-Rim

AU - Horne, Zachary D

AU - Rastogi, Priya

AU - Fehrenbacher, Louis

AU - Romond, Edward H

AU - Swain, Sandra M

AU - Mamounas, Eleftherios P

AU - Wickerham, D Lawrence

AU - Geyer, Charles E

AU - Costantino, Joseph P

AU - Wolmark, Norman

AU - Paik, Soonmyung

PY - 2013/12/4

Y1 - 2013/12/4

N2 - BACKGROUND: National Surgical Adjuvant Breast and Bowel Project (NSABP) trial B-31 suggested the efficacy of adjuvant trastuzumab, even in HER2-negative breast cancer. This finding prompted us to develop a predictive model for degree of benefit from trastuzumab using archived tumor blocks from B-31.METHODS: Case subjects with tumor blocks were randomly divided into discovery (n = 588) and confirmation cohorts (n = 991). A predictive model was built from the discovery cohort through gene expression profiling of 462 genes with nCounter assay. A predefined cut point for the predictive model was tested in the confirmation cohort. Gene-by-treatment interaction was tested with Cox models, and correlations between variables were assessed with Spearman correlation. Principal component analysis was performed on the final set of selected genes. All statistical tests were two-sided.RESULTS: Eight predictive genes associated with HER2 (ERBB2, c17orf37, GRB7) or ER (ESR1, NAT1, GATA3, CA12, IGF1R) were selected for model building. Three-dimensional subset treatment effect pattern plot using two principal components of these genes was used to identify a subset with no benefit from trastuzumab, characterized by intermediate-level ERBB2 and high-level ESR1 mRNA expression. In the confirmation set, the predefined cut points for this model classified patients into three subsets with differential benefit from trastuzumab with hazard ratios of 1.58 (95% confidence interval [CI] = 0.67 to 3.69; P = .29; n = 100), 0.60 (95% CI = 0.41 to 0.89; P = .01; n = 449), and 0.28 (95% CI = 0.20 to 0.41; P < .001; n = 442; P(interaction) between the model and trastuzumab < .001).CONCLUSIONS: We developed a gene expression-based predictive model for degree of benefit from trastuzumab and demonstrated that HER2-negative tumors belong to the moderate benefit group, thus providing justification for testing trastuzumab in HER2-negative patients (NSABP B-47).

AB - BACKGROUND: National Surgical Adjuvant Breast and Bowel Project (NSABP) trial B-31 suggested the efficacy of adjuvant trastuzumab, even in HER2-negative breast cancer. This finding prompted us to develop a predictive model for degree of benefit from trastuzumab using archived tumor blocks from B-31.METHODS: Case subjects with tumor blocks were randomly divided into discovery (n = 588) and confirmation cohorts (n = 991). A predictive model was built from the discovery cohort through gene expression profiling of 462 genes with nCounter assay. A predefined cut point for the predictive model was tested in the confirmation cohort. Gene-by-treatment interaction was tested with Cox models, and correlations between variables were assessed with Spearman correlation. Principal component analysis was performed on the final set of selected genes. All statistical tests were two-sided.RESULTS: Eight predictive genes associated with HER2 (ERBB2, c17orf37, GRB7) or ER (ESR1, NAT1, GATA3, CA12, IGF1R) were selected for model building. Three-dimensional subset treatment effect pattern plot using two principal components of these genes was used to identify a subset with no benefit from trastuzumab, characterized by intermediate-level ERBB2 and high-level ESR1 mRNA expression. In the confirmation set, the predefined cut points for this model classified patients into three subsets with differential benefit from trastuzumab with hazard ratios of 1.58 (95% confidence interval [CI] = 0.67 to 3.69; P = .29; n = 100), 0.60 (95% CI = 0.41 to 0.89; P = .01; n = 449), and 0.28 (95% CI = 0.20 to 0.41; P < .001; n = 442; P(interaction) between the model and trastuzumab < .001).CONCLUSIONS: We developed a gene expression-based predictive model for degree of benefit from trastuzumab and demonstrated that HER2-negative tumors belong to the moderate benefit group, thus providing justification for testing trastuzumab in HER2-negative patients (NSABP B-47).

KW - Antibodies, Monoclonal, Humanized

KW - Antineoplastic Agents

KW - Breast Neoplasms

KW - Chemotherapy, Adjuvant

KW - Cohort Studies

KW - Estrogen Receptor alpha

KW - Female

KW - Gene Expression Profiling

KW - Gene Expression Regulation, Neoplastic

KW - Humans

KW - Odds Ratio

KW - Predictive Value of Tests

KW - Principal Component Analysis

KW - Proportional Hazards Models

KW - RNA, Messenger

KW - Receptor, ErbB-2

KW - Treatment Outcome

U2 - 10.1093/jnci/djt321

DO - 10.1093/jnci/djt321

M3 - SCORING: Journal article

C2 - 24262440

VL - 105

SP - 1782

EP - 1788

JO - JNCI-J NATL CANCER I

JF - JNCI-J NATL CANCER I

SN - 0027-8874

IS - 23

ER -