Predicting response to docetaxel neoadjuvant chemotherapy for advanced breast cancers through genome-wide gene expression profiling

Abstract

Neoadjuvant chemotherapy with docetaxel for advanced breast cancer can improve the radicality for a subset of patients, but some patients suffer from severe adverse drug reactions without any benefit. To establish a method for predicting responses to docetaxel, we analyzed gene expression profiles of biopsy materials from 29 advanced breast cancers using a cDNA microarray consisting of 36,864 genes or ESTs, after enrichment of cancer cell population by laser microbeam microdissection. Analyzing eight PR (partial response) patients and twelve patients with SD (stable disease) or PD (progressive disease) response, we identified dozens of genes that were expressed differently between the 'responder (PR)' and 'non-responder (SD or PD)' groups. We further selected the nine 'predictive' genes showing the most significant differences and established a numerical prediction scoring system that clearly separated the responder group from the non-responder group. This system accurately predicted the drug responses of all of nine additional test cases that were reserved from the original 29 cases. Moreover, we developed a quantitative PCR-based prediction system that could be feasible for routine clinical use. Our results suggest that the sensitivity of an advanced breast cancer to the neoadjuvant chemotherapy with docetaxel could be predicted by expression patterns in this set of genes.