Lajos Pusztai1, Keith Anderson, Kenneth R Hess. 1. Department of Breast Medical Oncology, the University of Texas MD Anderson Cancer Center, Houston, Texas 77230-1439, USA. lpusztai@mdanderson.org
Abstract
PURPOSE: We examined if supervised analysis of gene expression data from phase II studies could identify HER-2 overexpression as a predictor of response to trastuzumab. EXPERIMENTAL DESIGN: Gene expression data from 132 newly diagnosed breast cancers were used to simulate 50,000 single-agent phase II trastuzumab studies. True HER-2 amplification was assessed by fluorescence in situ hybridization. RESULTS: Only 3.67% of the simulated studies yielded HER-2 as the top predictor, >96% of the individual "studies" picked a different gene as the most predictive of trastuzumab response. HER-2 was included in the top 10 gene list 9.73% of the time. When HER-2 was a priori defined as a potential predictor, 99.6% of the simulated studies confirmed overexpression among responders. Candidate marker testing may be more efficient than de novo predictor discovery in phase II trials. We describe a tandem, two-step phase II trial design for rapid marker assessment that combines two optimal two-stage phase II trials into a single study. In the first stage, unselected patients are treated, and if insufficient responses are seen, the trial remains open for marker-positive patients only and a second two-stage trial commences. CONCLUSIONS: The probability of successful discovery of drug-specific pharmacogenomic response markers in a typical phase II study is small. The evaluation of predefined predictors using tandem two-step phase II design has the advantages of estimating response rates in both unselected and marker-selected patient populations and allows for simultaneous screening of multiple different predictors for the same drug and several distinct predictor-drug pairs in a single, parallel multiarm trial.
PURPOSE: We examined if supervised analysis of gene expression data from phase II studies could identify HER-2 overexpression as a predictor of response to trastuzumab. EXPERIMENTAL DESIGN: Gene expression data from 132 newly diagnosed breast cancers were used to simulate 50,000 single-agent phase II trastuzumab studies. True HER-2 amplification was assessed by fluorescence in situ hybridization. RESULTS: Only 3.67% of the simulated studies yielded HER-2 as the top predictor, >96% of the individual "studies" picked a different gene as the most predictive of trastuzumab response. HER-2 was included in the top 10 gene list 9.73% of the time. When HER-2 was a priori defined as a potential predictor, 99.6% of the simulated studies confirmed overexpression among responders. Candidate marker testing may be more efficient than de novo predictor discovery in phase II trials. We describe a tandem, two-step phase II trial design for rapid marker assessment that combines two optimal two-stage phase II trials into a single study. In the first stage, unselected patients are treated, and if insufficient responses are seen, the trial remains open for marker-positive patients only and a second two-stage trial commences. CONCLUSIONS: The probability of successful discovery of drug-specific pharmacogenomic response markers in a typical phase II study is small. The evaluation of predefined predictors using tandem two-step phase II design has the advantages of estimating response rates in both unselected and marker-selected patient populations and allows for simultaneous screening of multiple different predictors for the same drug and several distinct predictor-drug pairs in a single, parallel multiarm trial.
Authors: Larissa A Korde; Lara Lusa; Lisa McShane; Peter F Lebowitz; LuAnne Lukes; Kevin Camphausen; Joel S Parker; Sandra M Swain; Kent Hunter; Jo Anne Zujewski Journal: Breast Cancer Res Treat Date: 2010-02 Impact factor: 4.872
Authors: René Natowicz; Roberto Incitti; Euler Guimarães Horta; Benoît Charles; Philippe Guinot; Kai Yan; Charles Coutant; Fabrice Andre; Lajos Pusztai; Roman Rouzier Journal: BMC Bioinformatics Date: 2008-03-15 Impact factor: 3.169
Authors: Francisco J Esteva; Jing Wang; Feng Lin; Jaime A Mejia; Kai Yan; Kadri Altundag; Vicente Valero; Aman U Buzdar; Gabriel N Hortobagyi; W Fraser Symmans; Lajos Pusztai Journal: Breast Cancer Res Date: 2007 Impact factor: 6.466