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Measuring β‐tubulin III, Bcl‐2, and ERCC1 improves pathological complete remission predictive accuracy in breast cancer

机译:测量β-微管蛋白III,Bcl-2和ERCC1可提高乳腺癌的病理完全缓解预测准确性

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AbstractWeekly 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. (Cancer Sci 2012; 103: 262–268)
机译:摘要乳腺癌新辅助化疗(NCT)中的PCb(紫杉醇+卡铂)每周具有较高的病理完全缓解(pCR)率。本研究旨在鉴定pCR预测生物标记,并测试整合候选分子生物标记是否可以提高pCR预测准确性。回顾性分析每周PCb NCT治疗的91例乳腺癌患者。在NCT前核心穿刺活检样本中通过免疫组织化学检测了11种候选分子生物标志物(Tau,β-微管蛋白III,PTEN,MAP4,硫氧还蛋白,多药耐药性1,Ki67,p53,Bcl-2,BAX和ERCC1)。我们分析了这些生物标志物与pCR之间的关系。单因素分析表明,雌激素受体,孕激素受体,分子分类(临床病理标志物),Tau,β-微管蛋白III,p53,Bcl-2,ERCC1(候选分子生物标志物)的表达与pCR率相关。但是,多变量分析显示,只有β-微管蛋白III,Bcl-2和ERCC1是独立的pCR预测因子。 β-微管蛋白III阴性,Bcl-2阴性或ERCC1阴性的患者与更高的pCR率相关,OR(比值比)6.03(95%置信区间[CI],1.44–25.24,P = 0.014),7.54 (95%CI,1.52–37.40,P = 0.013)和4.09(95%CI,1.17–14.30,P = 0.028)。为了比较使用这些变量的不同组合构建的不同逻辑回归模型,我们发现包含常规临床和病理变量以及β-微管蛋白III,Bcl-2,ERCC1分子生物标记物的模型具有最高的pCR预测能力。该模型的ROC曲线下面积为0.900(95%CI,0.831-0.968),表明它值得进一步研究。试验名称:每周紫杉醇加卡铂用于乳腺癌的术前治疗。 (Cancer Sci 2012; 103:262-268)

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