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目的分析原发性肝癌患者经导管肝动脉化疗栓塞(TACE)治疗后血清蛋白质指纹图谱的变化。方法应用SELDI-TOF/MS技术和IMAC 30蛋白质芯片采集50例肝癌患者TACE治疗前后肝癌患者的血清蛋白质质谱,Biomarker Wizard软件分析差异表达蛋白质峰,应用支持向量机(support vector machine,SVM)建立TACE治疗前后分类模型,ROC评价各差异蛋白质峰和SVM分类模型的分类效率。结果在0~20 000m/z质荷比范围内,共采集到199个蛋白质峰,Biomarker Wizard软件鉴定出13个差异表达蛋白质峰(P<0.05),包括TACE治疗24 h后7个高表达蛋白质峰和6个低表达蛋白质峰。2 883、11 535和11 687等3个蛋白质峰区分TACE治疗前后HCC的敏感性和特异性分别为80%、76%、62%和80%、60%、62%,AUC为0.8;SVM分类模型区分TACE治疗前后HCC的敏感性和特异性均为100%。结论应用SELDI-TOF/MS技术可分析TACE治疗后血清差异表达蛋白质谱,SVM分类模型能有效区分TACE治疗前后HCC。
Objective To analyze the changes of serum protein fingerprints after transcatheter arterial chemoembolization (TACE) in patients with primary liver cancer. Methods Serum protein profiles of patients with hepatocellular carcinoma (HCC) before and after TACE treatment were collected by SELDI-TOF / MS and IMAC 30 protein chip. The protein peaks were differentially expressed by Biomarker Wizard software. TACE was established using support vector machine (SVM) Before and after treatment classification model, ROC evaluation of the differential protein peaks and SVM classification model classification efficiency. Results A total of 199 protein peaks were collected in the mass-to-charge ratio range of 0-20 000 m / z. Biomarker Wizard software identified 13 differentially expressed protein peaks (P <0.05), including seven highly expressed proteins Peaks and 6 low-expression protein peaks. 2 883, 11 535 and 11 687, respectively. The sensitivity and specificity of differentiating HCC before and after TACE were 80%, 76%, 62% and 80%, 60% and 62%, respectively. The AUC was 0.8. The sensitivity and specificity of the model to distinguish HCC before and after TACE treatment were 100%. Conclusion SELDI-TOF / MS technique can be used to analyze differentially expressed protein profiles of serum after TACE treatment. The SVM classification model can effectively distinguish HCC before and after TACE treatment.