血清蛋白质指纹图谱对紫杉类联合蒽环类化疗一线治疗乳腺癌的预测作用

Serum protein pattern in predicting the response to taxane-anthracycline chemotherapy in patients with metastatic breast cancer

目的寻找能预测紫杉类联合蒽环类(AT)一线治疗转移性乳腺癌疗效的潜在蛋白质标志物。方法以2015年8月至2018年7月浙江大学医学院附属第二医院经AT一线化疗的转移性三阴性乳腺癌的26例患者为对象,使用实体瘤疗效评价标准(RICIST)区分经过2个疗程治疗后的化疗受益者和化疗无效者,使用血清蛋白质指纹图谱技术分析比较化疗受益者和化疗无效者的血清蛋白质谱的差异,并构建预测模型。结果经AT一线化疗,26例患者中17例有效,9例无效。表面增强激光解吸/电离飞行时间质谱(SELDI-TOF-MS)和人工神经网络(ANN)分析发现,两组患者间5个蛋白质峰存在差异。基于血清蛋白质指纹图谱构建的乳腺癌患者AT方案化疗疗效的潜在预测模型可有效区分化疗受益者与化疗无效者,灵敏度达1.000,特异度达0.889。结论血清蛋白质指纹图谱模型可有效筛选出可能从AT方案化疗中受益的转移性乳腺癌患者。

Objective To investigate serum protein profile in predicting the response to first-line chemotherapy with taxane-anthracycline(AT)in patients with metastatic breast cancer.Methods Twenty-six patients with metastatic tripleegative breast cancer admitted in Department of Medical Oncology of the Second Affiliated Hospital,Zhejiang University School of Medicine were enrolled in the study.All patients received first-line chemotherapy with AT regimen.After 2 cycles of treatment,response evaluation criteria in solid tumors(RICIST)criteria were used to define the responders(n=17)and nonresponders(n=9).Serum samples before chemotherapy were collected.The serum protein profile was determined with surface-enhanced laser desorption/ionization time-of-flight mass spectrometry(SELDI-TOF-MS)and artificial neural networks(ANN)analysis,and the difference of proteomic spectra was compared between responders and non-responders.Results Five differentially expressed protein peaks were identified between the responders and non-responders.A predictive model was established based on the serum protein pattern,the sensitivity and specificity for distinguishing responder and nonresponder was 1.000 and 0.889,respectively.Conclusion The established model in the study based on serum protein pattern may be used for predicting response to AT chemotherapy in patients with metastatic breast cancer.