非小细胞肺癌淋巴转移血清蛋白指纹图谱分析

目的 应用表面增强激光解析离子化-飞行时间-质谱(SELDI-TOF-MS)技术获得区分非小细胞肺癌患者淋巴结转移的诊断模型及血清特异性蛋白.方法 应用弱阳离子蛋白芯片CM10及SELDI-TOF-MS技术检测84例肺癌患者血清中蛋白的相对含量(其中N0、N1、N2患者分别为35例、19例和30例),从淋巴结转移(N0组对比N1+N2组)和纵隔淋巴结转移(N0+N1组对比N2组)两方面进行分析,分别建立诊断模型.结果 在随机抽取50例构建的模型中,诊断淋巴结转移组病例的灵敏度和特异度分别为96.3%(26/27)和95.7%(22/23),同时进行盲法验证;随后将15例病理确认第10至14站淋巴结均无转移的N0病例与49例出现淋巴结转移患者(N1+N2)对比构建模型,预测转移的灵敏度和特异度别为77.6%和93.3%,其中相对分子质量6682等6个蛋白峰有显著差异;而诊断纵隔淋巴结转移模型的灵敏度为80.0%(24/30),特异度为77.8%(42/54).结论 SELDI-TOF-MS技术在预测非小细胞肺癌患者淋巴结转移方面具有应用价值,而该诊断模型以及与转移相关的蛋白需进一步研究证实.

Analysis of serum protein fingerprints on non-small cell lung cancer lymphatic metastasis

Objective To establish a classification model and serum proteomic patterns in non-small cell lung cancer (NSCLC) patients with lymph node metastasis by surface enhanced laser desorption/ionization time of flight mass spectrometry (SELDI-TOF-MS). Methods The relative contents of serum proteins of 84 NSCLC patients with different N stages (35 NO cases, 19 N1 and 30 N2 respectively) were detected by CM10 chip and SELDI-TOF-MS; two decision trees were generated to distinguish lymph nodes metastasis (N0 versus NI + N2) and mediastinal lymph nodes metastasis (N0 + N1 versus N2) respectively. Results The model in which 50 patients were randomly chosen differentiated patients with lymph nodes metastasis from NO patients with a sensitivity of 96.3% (26/27) and a specificity of 95.7% (22/23) in the training set, a following blind test was taken. Subsequently, compared with 49 patients with lymph node metastasis (N1 + N2), 15 patients with total negative lymph nodes (including lobar, segmental and subsegmental nodes necessarily) were defined as "true" NO and were chosen to form a better predictive model with a 77.6% (38/49) sensitivity and a 93.3% (14/15) specificity respectively. And 6682.0Da, together with other five proteins, hod significant difference between two groups; the result of this model for distinguishing the mediastinal lymph nodes metastasis is more accurate than thoracic CT analyses by Alongi F and many other clinical centers. It had a sensitivity of 80.0% (24/30) and a specificity of 77.8% (42/54) respectively. Conclusion SELDI-TOF-MS showed a potential value for predicting lymph nodes metastasis in NSCLC patients. And further studies are required to confirm the models and identify the related proteins.