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

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Citation: Journal of the National Cancer Institute. 105(23):1782-8, 2013 Dec 4.PMID: 24262440Institution: Washington Cancer InstituteForm of publication: Journal ArticleMedline article type(s): Journal Article | Randomized Controlled Trial | Research Support, N.I.H., Extramural | Research Support, Non-U.S. Gov'tSubject headings: *Antibodies, Monoclonal, Humanized/tu [Therapeutic Use] | *Antineoplastic Agents/tu [Therapeutic Use] | *Breast Neoplasms/dt [Drug Therapy] | *Breast Neoplasms/me [Metabolism] | *Estrogen Receptor alpha/ge [Genetics] | *Gene Expression Regulation, Neoplastic | *Receptor, erbB-2/ge [Genetics] | Chemotherapy, Adjuvant | Cohort Studies | Female | Gene Expression Profiling | Humans | Odds Ratio | Predictive Value of Tests | Principal Component Analysis | Proportional Hazards Models | RNA, Messenger/me [Metabolism] | Treatment OutcomeYear: 2013Local holdings: Available online from MWHC library: 1996 - present (after 1 year), Available in print through MWHC library: 1999 - 2006ISSN:
  • 0027-8874
Name of journal: Journal of the National Cancer InstituteAbstract: 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.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).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).All authors: Bandos H, Blackmon NL, Bohn OL, Burandt E, Costantino JP, Fehrenbacher L, Fumagalli D, Gavin PG, Geyer CE Jr, Goldstein LC, Horne ZD, Jeong JH, Kim C, Kim SI, Kim SR, Lee A, Mamounas EP, Paik S, Pogue-Geile KL, Rastogi P, Reilly ML, Remillard MY, Romond EH, Sneige N, Swain SM, Tanaka N, Taniyama Y, Wickerham DL, Wolmark NFiscal year: FY2014Digital Object Identifier: Date added to catalog: 2014-02-24
Holdings
Item type Current library Collection Call number Status Date due Barcode
Journal Article MedStar Authors Catalog Article 24262440 Available 24262440

Available online from MWHC library: 1996 - present (after 1 year), Available in print through MWHC library: 1999 - 2006

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.

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).

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).

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