Tumor Cell-Microenvironment Interaction Models Coupled with Clinical Validation Reveal CCL2 and SNCG as Two Predictors of Colorectal Cancer Hepatic Metastasis
Tumor Cell-Microenvironment Interaction Models Coupled with Clinical Validation Reveal CCL2 and SNCG as Two Predictors of Colorectal Cancer Hepatic Metastasis
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DOI：
10.1158/1078-0432.ccr-08-2491
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发表时间：
2009-09-01
影响因子：
11.5
通讯作者：
Ran, Yuliang
中科院分区：
文献类型：
--
作者：
Hu, Hai;Sun, Lichao;Ran, Yuliang
目的：本研究旨在确定用于预测结直肠癌肝转移的新型生物学标志物。
实验设计：我们建立了两个模拟结直肠肿瘤细胞与肝脏微环境相互作用的模型。从这些模型中我们建立了向肝脏转移能力增强的亚细胞系。通过微阵列筛选与肝转移相关的基因。通过免疫组织化学检测候选标志物，并通过交叉验证法和独立测试集评估其预测准确性。
结果：从肿瘤细胞 - 微环境相互作用模型中建立了高转移性结肠癌细胞亚系SW1116p21和SW1116v3。从亚系中上调的基因中选择了7个作为预测转移潜能的候选标志物。将总共245例结直肠癌样本分为包含117例的训练集和包含128例的测试集。在训练集中，免疫组织化学分析显示CCL2和SNCG在肝转移组中的表达高于非转移组，且与不良生存相关。逻辑回归分析表明，原发肿瘤中的CCL2和SNCG水平、血清癌胚抗原水平以及淋巴结转移状态是检测肝转移的唯一显著（P < 0.05）参数。在留一法交叉验证中，这两种标志物与临床病理特征相结合，对肝转移检测的敏感性为90.5%，特异性为90.7%。在独立测试集中，该组合对预测结直肠癌未来肝转移的敏感性为87.5%，特异性为82%。
结论：我们的结果表明这些模型能够模拟结直肠癌细胞与肝脏微环境之间的相互作用，并可能是一种确定转移相关基因的有前景的策略。CCL2和SNCG与临床病理特征相结合，可作为结直肠癌肝转移的准确预测因子。（《临床癌症研究》2009年；15(17):5485 - 93）
Purpose: This study aimed to identify novel biological markers for the prediction of colorectal cancer liver metastasis.Experimental Design: We established two models that mimicked the interactions between colorectal tumor cells and the liver microenvironment. From these models we established subcell lines that had an enhanced ability to metastasize to the liver. Genes that related to hepatic metastasis were screened by microarray. The candidate markers were tested by immunohistochemistry, and their predictive accuracy was assessed by the cross-validation method and an independent test set.Results: Highly metastatic colon cancer cell sublines SW1116p21 and SW1116v3 were established from the tumor cell-microenvironment interaction models. Seven of the up-regulated genes in the sublines were selected as candidate markers for predicting metastatic potential. A total of 245 colorectal cancer samples were divided into a training set containing 117 cases and a test set containing 128 cases. In the training set, immunohistochemical analysis showed CCL2 and SNCG expression was higher in the hepatic metastasis group than in the nonmetastasis group, and was correlated with poor survival. Logistic regression analysis revealed that CCL2 and SNCG levels in primary tumors, serum carcinoembryonic antigen level, and lymph node metastasis status were the only significant (P < 0.05) parameters for detecting liver metastasis. In leave-one-out-cross-validation, the two markers, when combined with clinicopathologic features, resulted in 90.5% sensitivity and 90.7% specificity for hepatic metastasis detection. In an independent test set, the combination achieved 87.5% sensitivity and 82% specificity for predicting the future hepatic metastasis of colorectal cancer.Conclusion: Our results suggest that these models are able to mimic the interactions between colorectal cancer cells and the liver microenvironment, and may represent a promising strategy to identify metastasis-related genes. CCL2 and SNCG, combined with clinicopathologic features, may be used as accurate predictors of liver metastasis in colorectal cancer. (Clin Cancer Res 2009;15(17):5485-93)