Emerging science: Prospective validation of gene expression profiling-based prediction of complete pathologic response to neoadjuvant paclitaxel/FAC chemotherapy in breast cancer

Emerging science: Prospective validation of gene expression profiling-based prediction of complete pathologic response to neoadjuvant paclitaxel/FAC chemotherapy in breast cancer. L. Pusztai, M. Ayers, F. W. Simmans, A. Damokosh, K. Hess, V. Valero, E. Clark, J. Ross, G. N. Hortobagyi, J. Stec; MD Anderson Cancer Ctr, Houston, TX; Millennium Pharmaceuticals, Cambridge, MA Several different adjuvant chemotherapy regimens are used in the treatment of breast cancer. Not all regimens may be equally effective for all patients. Currently it is not possible to select the most effective regimen for a particular individual. One accepted surrogate of prolonged recurrencefree survival after chemotherapy in breast cancer is complete pathologic response (pCR) to neoadjuvant therapy. We report the discovery of a gene expression profile that predicts pCR after neoadjuvant weekly paclitaxel followed by FAC sequential chemotherapy (T/FAC). Our predictive markers were generated from fine needle aspirates of 24 early stage breast cancers. Six of the 24 patients achieved pCR (25%). RNA from each sample were profiled on cDNA microarrays of 30,000 human transcripts. Differentially expressed genes between the pCR and residual disease (RD) groups were selected by signal-to-noise-ratio. Several supervised learning methods were evaluated to define the best class prediction algorithm and the optimal number of genes needed for outcome prediction using leave-one out cross validation. Support vector machine using 5 genes (3 ESTs, nuclear factor 1/A, and histone acetyltransferase) yielded the greatest estimated accuracy. This predictive marker set was tested on independent cases receiving T/FAC neoadjuvant therapy. At the time of this submission, results are available on 21 patients included in the validation. The overall accuracy of our response prediction based on gene expression profile was 81%. The positive predictive value of our test for pCR was 75% (3 of the 4 predicted cases had pCR). The overall specificity was 93%. The sensitivity was 50% (3 of the 6 pCR were misclassified as RD). Updates with additional patients will be presented. In conclusion, patients predicted to have pCR to T/FAC preoperative chemotherapy had a 75% chance of experiencing pCR compared to 25–30% that is expected in unselected patients. This finding may help physicians to select individual patients who are most likely to benefit from T/FAC adjuvant chemotherapy.