结肠癌淋巴结转移的风险基因及列线图预测模型的构建

目的 寻找结肠癌淋巴结转移的相关风险基因,并构建由基因组成的列线图（nomogram）预测模型。 方法 从TCGA和GEO数据库下载基因测序数据,利用差异分析和LASSO回归方法筛选基因。利用赤池信息准则确定最优的nomogram模型,ROC曲线、校准曲线及拟合优度检验评估模型预测的准确性,决策曲线分析评估临床应用价值。 结果 通过筛选得到11个有效预测结肠癌淋巴结转移的基因。由年龄、病理T分期、TH、CDH4、PNMA6A、TNNC1、KIR2DL4、STUM、SFTA2构成的nomogram模型具有最小的AIC值（440.4）。内部评估模型AUC值为0.800,外部验证AUC值为0.664,校准度及拟合优度均较佳。临床决策曲线分析法评估基于nomogram模型的风险判断可以带来临床获益。结论 共筛选出11个结肠癌淋巴结转移的风险基因。构建的nomogram预测模型的一致性和区分度良好,可帮助评估患者淋巴结转移状态。

Risk Genes and Nomogram Model for Lymph Node Metastasis of Colon Cancer

Objective To find out the risk genes related to lymph node metastasis of colon cancer and construct a nomogram model to predict lymph node metastasis. Methods Genome sequencing data were downloaded from TCGA and GEO databases, and candidate genes were screened by differential expressed gene analysis and LASSO regression. AIC was used to determine the optimal nomogram model. ROC curve, calibration curve and Hosmer-Lemeshow test were used to evaluate the accuracy of the model. Decision curve analysis was used to evaluate the clinical utility. Results Eleven genes which could effectively predict lymph node metastasis of colon cancer were obtained through LASSO regression. According to the results of stepwise regression, the model composed of age, pathological T stage, TH, CDH4, PNMA6A, TNNC1, KIR2DL4, STUM and SFTA2 had the minimum AIC value (440.4). The AUC value of internal evaluation was 0.800, and that of external verification was 0.664. In model evaluation, the calibration and Hosmer-Lemeshow test showed favorable performance. Decision curve analysis showed nomogram model could bring clinical benefits for predicting lymph nodes metastasis. Conclusion Eleven risk genes of lymph node metastasis of colon cancer are selected and a nomogram model is constructed. The model has favorable performance in discriminative and calibration abilities to help evaluate the status of lymph node metastasis of colon cancer patients.