Development of a risk model based on immune genes in patients with colon adenocarcinoma

Abstract

Abstract Background The rapidly increasing morbidity and the poor prognosis making the colon adenocarcinoma not only common but also highly malignant. On the other hand, immunotherapy emerges as a therapeutic modality of colon cancer recently. In this study, we developed a prognostic risk model that is based on immune genes, which could predict the overall survival (OS) of patients with colon adenocarcinoma. Methods The Cancer Genome Atlas (TCGA) database was used to download both transcriptomic and clinical data, and the ImmPort database was used to obtain immune genes. The least absolute shrinkage and selection operator (LASSO)‐Cox regression was adopted to further select the key genes with prognostic value. Then the key genes were inputted into stepwise regression to calculated each patient's immune‐related risk score (immune score). Survival, survminer packages and bilateral tests in R language were adopted to determine the optimal cut‐off value (cut‐off value) for the risk score. This threshold divides patients into immune‐score high‐risk and low‐risk groups. The differences in the levels of infiltrating immune cells and stromal cells in the high and low immune risk groups were then calculated and compared by the CIBERSORT algorithm. Results According to our results, a prognostic risk model was constructed based upon 26 immune‐related genes. High immune score was shown to be a poor prognostic factor for colon adenocarcinoma patients, such as overall survival, progress free survival for different therapies, and tumor stages. High immune score was also associated with the abundance of CD4+ T cells and CD8+ T cells. In addition, the high immune score group, the expression levels of LMTK3, LAG3 and PD‐L1 were higher than those in the low score group. Conclusion We developed a 26‐immune gene model of colon adenocarcinoma to predict patient's survival. This model might be used in clinical practice as a prognostic instrument for patients diagnosed with colon adenocarcinoma.

Keywords

• colon adenocarcinoma
• immune genes
• prognostic model
• TCGA