Abstract
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 immunohistochemistryin 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. © 2011 Japanese Cancer Association.
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CITATION STYLE
Chen, X., Wu, J., Lu, H., Huang, O., & Shen, K. (2012). Measuring β-tubulin III, Bcl-2, and ERCC1 improves pathological complete remission predictive accuracy in breast cancer. Cancer Science, 103(2), 262–268. https://doi.org/10.1111/j.1349-7006.2011.02135.x
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