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目的:分析肾癌患者手术前后及免疫治疗前后的血清蛋白指纹图谱,构建并评估血清差异蛋白诊断模型。方法:首先应用弱阳离子磁珠技术富集肾癌患者手术前后、免疫治疗后及健康对照组的血清蛋白,其次用基质辅助激光解离-飞行时间质谱(MALDI-TOF-MS)技术构建肾癌患者不同时期的蛋白指纹图谱,再应用有监督以及无监督的化学计量学模式识别方法对构建的指纹图谱进行效力评价,最后应用受试者工作特征曲线(ROC)寻求区别各个时期肾癌患者血清中的差异蛋白。结果:在无监督模式识别方法(主成分分析,PCA)结果不理想的情况下,对比了不同有监督模式识别方法构建的指纹图谱模型,结果表明遗传算法(GA)对各个时期的肾癌患者均有较高的识别率,达到了97.7%;术前和术后差异蛋白只有一个,而术前和免疫治疗后、术后和免疫治疗后存在较多的差异蛋白。结论:肾癌患者经过免疫治疗后,血清蛋白质和术前及术后存在明显差异,肾癌应用遗传算法构建的血清蛋白指纹图谱可有效识别术前、术后、免疫治疗后以及正常对照组的血清差异蛋白。
Objective: To analyze the serum protein fingerprints of patients with renal cell carcinoma before and after operation and before and after immunotherapy, and to construct and evaluate the diagnostic model of serum differential proteins. Methods: We first enriched the serum proteins of renal cell carcinoma patients before and after operation, after immunotherapy and in the healthy control group by using weak cation magnetic bead technique. Secondly, we constructed the renal carcinoma with matrix-assisted laser desorption-time of flight mass spectrometry (MALDI-TOF-MS) The protein fingerprints of patients at different periods were evaluated by using supervised and unsupervised chemometric pattern recognition methods. Finally, the receiver operating characteristic curve (ROC) The difference in protein. Results: Under the condition of unsupervised pattern recognition (PCA), the results of different PCA-based fingerprinting models were compared. The results showed that genetic algorithm (GA) All had a higher recognition rate, reaching 97.7%. There was only one differential protein before and after surgery, but there were more differential proteins after surgery and after immunotherapy. Conclusion: After immunotherapy, the protein in serum of patients with renal cell carcinoma is obviously different from preoperative and postoperative. Serum protein fingerprints constructed by genetic algorithm in renal cell carcinoma can be used to identify preoperative, postoperative, immunotherapy and normal control group Serum differential proteins.