非小细胞肺癌转移预测指标的研究

目的 :研究非小细胞肺癌 (NSCLC)淋巴结和远处转移的预测指标 ,并建立Logistic回归模型。　 方法 :通过免疫组化、ELISA、酶谱电泳等方法 ,对NSCLC肿瘤病理标本、血清、尿液和骨髓等进行检查 ,并通过Logistic回归分析建立预测概率模型。　结果 :免疫组化指标肿瘤组织内微血管密度 (IMVD)、血管内皮细胞生长因子(VEGF)、碱性成纤维细胞生长因子 (b FGF)、白细胞分化抗原变异型 (CD4 4v6 )、基质金属蛋白酶 2 (MMP 2 )与NSCLC淋巴结转移危险有关 (P <0 .0 5 ) ,组织金属蛋白酶抑制物 (TIMP 2 )、上皮型钙粘素 (E cad)与NSCLC淋巴结转移危险下降有关 (P <0 .0 5 )。血清MMP 2、MMP 9,尿液MMP 2、MMP 9及骨髓上皮膜抗原 (EMA)阳性细胞与NSCLC远处转移危险有关 (P <0 .0 5 )。其中免疫组化指标CD4 4v6、IMVD、E cad及尿液MMP 2、骨髓EMA阳性细胞对NSCLC转移有显著回归效果而分别被选入概率模型 1和 2 ,其预测准确率分别为 81.1%和 72 .7%。　结论 :组织标本中CD4 4v6、IMVD、E cad以及尿液中MMP 2及骨髓EMA阳性细胞检查 ,可预测绝大多数NSCLC的淋巴结转移和远处转移状况 ,为NSCLC转移的早期诊断提供重要信息 ,有助于NSCLC的个体化治疗和改善预后

Study on prediction of metastasis in human non-small cell lung cancer

Objectives: To study variables in predicting the metastasis of human non small cell lung cancer (NSCLC),and to establish Logistic regression equations. Methods: Expression of factors including intratumor micro vesseldensity(IMVD),VEGF,CD44v6,b FGF,E cad,MMP 2,MMP 9 and TIMP 2 in tumor of NSCLC were examined using immunohistochemical methods (SP).The levels of MMP 2 and MMP 9 in serum and urine from patients with NSCLC were detected by ELISA and zymography methods,respectively.The bone marrow epithelial membrane antigen(EMA) positive cells were measured by immunocytochemical assay. Logistic regressions were used to analyze the influence of variates on metastasis of NSCLC. Results:The expression of VEGF,b FGF,CD44v6,MMP 2,TIMP 2, E cad was related to lymph node metastasis in NSCLC, and the levels of MMP 2 and MMP 9 in serum and positive rates of MMPs in urine and EMA in bone marrow were related to remote metastasis of NSCLC. According to the results of stepwise regression analysis,IMVD,CD44v6 and E cad were selected into equation 1 predicting lymph node metastasis ,and positive rates of MMPs in urine and EMA cells in bone marrow were selected into equation 2 predicting remote metastasis of NSCLC ,respectively. Conclusions:Expression of CD44v6,E cad and IMVD in tumor tissues and detection of urine MMPs and bone marrow EMA positive cells are highly valuable for prediction of NSCLC metastasis.