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

Abstract

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.

Keywords

• colon cancer
• lymph nodes metastasis
• nomogram model
• decision curve analysis