Weekly PCb (
paclitaxel +
carboplatin) in
neoadjuvant chemotherapy (NCT) for
breast cancer has a high pathological complete remission (pCR) rate. The present study was to identify pCR predictive
biomarkers and to test whether integrating candidate molecular
biomarkers can improve the pCR predictive accuracy. Ninety-one
breast cancer patients treated with weekly PCb NCT were retrospectively analyzed. Eleven candidate molecular
biomarkers (Tau, β-
tubulin III, PTEN,
MAP4,
thioredoxin, multidrug resistance-1, Ki67, p53, Bcl-2, BAX, and ERCC1) were detected by immunohistochemistry in pre-NCT core needle biopsy specimens. We analyzed the relationship between these
biomarkers and pCR. Univariate analysis showed that
estrogen receptor,
progesterone receptor, molecular classification (clinicopathological markers), and Tau, β-
tubulin III, p53, Bcl-2, ERCC1 (candidate molecular
biomarkers) expression were associated with pCR rate; however, multivariate analysis revealed that only β-
tubulin III, Bcl-2, and ERCC1 were independent pCR predictive factors. Patients with β-
tubulin III negative, Bcl-2 negative, or ERCC1 negative
tumors were associated with higher pCR rate, with OR (odds ratios) 6.03 (95% confidence interval [CI], 1.44-25.24, P = 0.014), 7.54 (95% CI, 1.52-37.40, P = 0.013), and 4.09 (95% CI, 1.17-14.30, P = 0.028), respectively. To compare different logistic regression models, built with different combinations of these variables, we found that the model integrating routine clinical and pathological variables, as well as the β-
tubulin III, Bcl-2, ERCC1 molecular
biomarkers had the highest pCR predictive power. The area under the ROC curve for this model was 0.900 (95% CI, 0.831-0.968), indicating that it deserves further investigation. Trial name: Weekly
Paclitaxel Plus
Carboplatin in Preoperative Treatment of
Breast Cancer.