OBJECTIVE: Tumor gene expression signatures have been used to classify, prognosticate, and predict chemotherapy sensitivity in breast cancer, although almost all efforts have been focused on the unchallenged baseline tumor. Most cancer patients receive systemic therapy, and exposure to drug may modify the tumor's short-term and long-term outcomes. Drug-induced tumor gene signatures may thus be more predictive of treatment outcomes than the unperturbed tumor gene signatures. METHODS: Using a set of 47 breast cancer patients, we obtained paired prechemotherapy and postchemotherapy tumor biopsies and developed gene panels of baseline tumor (T1), postchemotherapy tumor (T2), and chemotherapy-induced relative change signatures (TDelta) to predict pathological response and progression-free survival (PFS). The signatures were validated in two independent test sets with paired prechemotherapy and postchemotherapy tumor samples, comprising of 18-20 patients each. RESULTS: T2 and TDelta were superior to T1 signatures in predicting for PFS (area under the curve of receiver operating characteristic 0.770 and 0.660 vs. 0.530) and pathological response (area under the curve of receiver operating characteristic 0.631 and 0.462 vs. 0.446) in the validation sets. In multivariate analysis for PFS with other clinical predictors, T2, but not T1, signatures remained as significant independent predictors. CONCLUSION: Postchemotherapy tumor gene signatures outperformed baseline signatures and clinical predictors in predicting for pathological response and PFS, independent of clinical and pathological response to chemotherapy. Drug-induced tumor gene signatures may be more informative than unchallenged signatures in predicting treatment outcomes. These findings challenge the current practice of relying only on the baseline tumor to predict outcome, which overlooks the contributions of therapeutic interventions.
RCT Entities:
OBJECTIVE:Tumor gene expression signatures have been used to classify, prognosticate, and predict chemotherapy sensitivity in breast cancer, although almost all efforts have been focused on the unchallenged baseline tumor. Most cancerpatients receive systemic therapy, and exposure to drug may modify the tumor's short-term and long-term outcomes. Drug-induced tumor gene signatures may thus be more predictive of treatment outcomes than the unperturbed tumor gene signatures. METHODS: Using a set of 47 breast cancerpatients, we obtained paired prechemotherapy and postchemotherapy tumor biopsies and developed gene panels of baseline tumor (T1), postchemotherapy tumor (T2), and chemotherapy-induced relative change signatures (TDelta) to predict pathological response and progression-free survival (PFS). The signatures were validated in two independent test sets with paired prechemotherapy and postchemotherapy tumor samples, comprising of 18-20 patients each. RESULTS: T2 and TDelta were superior to T1 signatures in predicting for PFS (area under the curve of receiver operating characteristic 0.770 and 0.660 vs. 0.530) and pathological response (area under the curve of receiver operating characteristic 0.631 and 0.462 vs. 0.446) in the validation sets. In multivariate analysis for PFS with other clinical predictors, T2, but not T1, signatures remained as significant independent predictors. CONCLUSION: Postchemotherapy tumor gene signatures outperformed baseline signatures and clinical predictors in predicting for pathological response and PFS, independent of clinical and pathological response to chemotherapy. Drug-induced tumor gene signatures may be more informative than unchallenged signatures in predicting treatment outcomes. These findings challenge the current practice of relying only on the baseline tumor to predict outcome, which overlooks the contributions of therapeutic interventions.
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