(1) Gene expression profile of tumor samples obtained by a vacuum-assisted core biopsy before Paclitaxel-FEC was analyzed by DNA microarray in breast cancer patients to construct a classifier for predicting pathological complete response (pCR). The 70-probe classifier for predicting pCR to Paclitaxel-FEC was constructed successfully with a high sensitivity of 91% and a high negative predictive value of 93% (Fig. 1., Table 1).
(2) A diagnostic system comprising a 95-gene classifier was developed for predicting the prognosis of node-negative and ER-positive breast cancer patients by using already published DNA microarray (gene expression) data (n=549) as the training set and the DNA microarray data (n=105) obtained at our institute as the validation set. The 95-gene classifier could classify the 105 patients in the validation set into a high-risk (n=44) and a low-risk (n=61) group with 10-year recurrence-free survival rates of 93% and 53%, respectively (p=8.6e-7)(Fig. 2).