Establishment and evaluation of module-based immune-associated gene signature to predict overall survival in patients of colon adenocarcinoma

Background: Patients with colon adenocarcinoma (COAD) exhibit significant heterogeneity in overall survival. The current tumor-node-metastasis staging system is insufficient to provide a precise prediction for prognosis. Identification and evaluation of new risk models by using big cancer data may provide a good way to identify prognosis-related signature. Methods: We integrated different datasets and applied bioinformatic and statistical methods to construct a robust immune-associated risk model for COAD prognosis. Furthermore, a nomogram was constructed based on the gene signature and clinicopathological features to improve risk stratification and quantify risk assessment for individual patients. Results: The immune-associated risk model discriminated high-risk patients in our investigated and validated cohorts. Survival analyses demonstrated that our gene signature served as an independent risk factor for overall survival and the nomogram exhibited high accuracy. Functional analysis interpreted the correlation between our risk model and its role in prognosis by classifying groups with different immune activities. Remarkably, patients in the low-risk group showed higher immune activity, while those in the high-risk group displayed a lower immune activity. Conclusions: Our study provides a novel tool that may contribute to the optimization of risk stratification for survival and personalized management of COAD.