Gene Expression Profiles Predict Complete Pathologic Response to Neoadjuvant Paclitaxel and Fluorouracil, Doxorubicin, and Cyclophosphamide Chemotherapy in Breast Cancer

Abstract

Purpose The goal of this study was to examine the feasibility of developing a multigene predictor of pathologic complete response (pCR) to sequential weekly paclitaxel and fluorouracil + doxorubicin + cyclophosphamide (T/FAC) neoadjuvant chemotherapy regimen for breast cancer. Patients and Methods All patients underwent one-time pretreatment fine-needle aspiration to obtain RNA from the cancer for transcriptional profiling using cDNA arrays containing 30,721 human sequence clones. Analysis was performed after profiling, and 42 patients' clinical results were available, 24 of which were used for predictive marker discovery; 18 patients' results were used as an independent validation set. Results Thirty-one percent of patients had pCR (six discovery and seven validation), defined as disappearance of all invasive cancer in the breast after completion of chemotherapy. We could identify no single marker that was sufficiently associated with pCR to be used as an individual predictor. A multigene model with 74 markers (P ≤ .09) was built using data from the discovery samples and tested on the validation samples. Overall, a 78% (14 of 18) predictive accuracy was observed, with a 100% (three of three) positive predictive value for pCR, a 73% (11 of 15) negative predictive value, a sensitivity of 43% (three of seven), and a specificity of 100% (11 of 11). The expected response rate to T/FAC neoadjuvant therapy in unselected patients is 28%. Conclusion Our results suggest that transcriptional profiling has the potential to identify a gene expression pattern in breast cancer that may lead to clinically useful predictors of pCR to T/FAC neoadjuvant therapy.