Establishment of a predictive classifier of node-positive breast cancer patients treated by FEC100 chemotherapy using gene expression profiling

13004 Background: In breast cancer treatment, biomarkers providing information about chemotherapy sensitivity are needed. FEC100 combination, frequently prescribed in Europe, is still applied empirically to patients. Our study’s goal was to establish a classifier of sensitivity to this regimen using gene expression data and classical clinicopathologic parameters. Methods: The study retrospectively included 151 patients belonging to the FEC100 arms of two multicentric phase III clinical trials: PACS01 (n = 128) and PEGASE01 (n = 23) (FNCLCC). Patients had unilateral breast cancer, showed no evidence of distant metastasis, were node-positive, aged less than 65-year-old. Median follow-up was 5 years. The number of relapses were respectively 23 and 10. We used cDNA nylon microarrays containing 7,000 genes to analyze gene expression profiles of tumor. Patients were split into a training set and a test set. A 3-step analysis based on Cox regression was applied: 1) elimination of non discriminant genes, 2) robust (resampling) univariate selection of discriminant genes and 3) development of multivariate models combining the discriminant genes, the Nottingham Prognostic Index (NPI) (developed in 2 binary variables) and the hormonal receptors. As a final step, after dichotomization of the retained genes, a risk score was built and applied first on the test set, and then on the whole cohort. Kaplan-Meier curves and logrank tests were performed to assess the new risk score. Results: The new risk score (one gene [G6224] and NPI) permitted to separate patients from the test set in 3 significantly different groups; it was also an improvement on NPI (test set: NPI, p = 0.0005; risk score p = 0.0001 - whole cohort: NPI, p = 2.10−5; risk score, p = 1.10−10). Conclusions: We identified G6224 whose expression combined with NPI showed a good capacity for classifying breast cancer patients who received FEC100 chemotherapy. Our results strengthen the interest of G6224 since it was previously described in various solid tumors as a prognostic biomarker with a tumor-suppressor activity. No significant financial relationships to disclose.