An Apoptosis-Related Gene Prognostic Index for Colon Cancer.

Hanmin Tang,Qi Wang,Jie Chen,Xinyue Zhang,Xuehui Luo,Suxia Han,Jing Wang,Chengyi Gao,Yuesen Li,Qiuting Li

doi:10.3389/fcell.2021.790878

Abstract

Purpose: To construct an apoptosis-related gene prognostic index (ARGPI) for colon cancer, and clarify the molecular and immune characteristics of the risk subgroup as defined by the prognostic index and the benefits of adjuvant chemotherapy. Integrating the prognostic index and clinicopathological risk factors to better evaluate the prognosis of patients with colon cancer. Methods: Based on the colon adenocarcinoma data in the TCGA database, 20 apoptosis-related hub genes were screened by weighted gene co-expression network analysis (WGCNA). Five genes constituting the prognosis model were determined by Cox regression and verified by the Gene Expression Omnibus (GEO) dataset. Then the molecular and immune characteristics of risk subgroups defined by the prognostic index and the benefits of adjuvant chemotherapy were analyzed. Finally, nomograms integrating ARGPI and four clinicopathological risk factors were used to evaluate the prognosis of patients with colon cancer. Results: The ARGPI was constructed based on the FAS, VWA5A, SPTBN2, PCK1, and TIMP1 genes. In the TCGA cohort, patients in the low-risk subgroup had a longer progression-free interval (PFI) than patients in the high-risk subgroup, which coincided with the results of the GEO cohort. The comprehensive results showed that the high-risk score was related to the enrichment of the cell cycle pathway, high mutation rate of TP53 and KRAS, high infiltration of T regulatory cells (Tregs), immunosuppressive state, and less chemotherapeutic benefit. However, low-risk scores are related to drug metabolism-related pathways, low TP53 and KRAS mutation rates, high infiltration of plasma cells, more resting CD4 memory cells and eosinophils, active immune function, and better chemotherapeutic benefits. Receiver operating characteristic curve of two-year progress prediction evaluation showed that the ARGPI had higher prognostic accuracy than TNM staging. Nomograms integrating ARGPI and clinicopathological risk factors can better evaluate the prognosis of patients with colon cancer. Conclusions: The ARGPI is a promising biomarker for determining risk of colon cancer progression, molecular and immune characteristics, and chemotherapeutic benefit. This is a reliable method to predict the prognosis of colon cancer patients. It also can assist doctors in formulating more effective treatment strategies.

Highlights

Colorectal cancer is the third most common malignant tumor and second most common cause of death due to malignant tumors (Bray et al, 2018)
The Apoptosis Related Hub Gene was Identified by weighted gene co-expression network analysis (WGCNA) Analysis
A total of 7,859 differentially expressed genes (DEGs) were obtained by comparing colon adenocarcinoma samples with normal tissue samples, of which 5,432 genes were upregulated and 2,427 genes were downregulated (Figure 1A)

Summary

Introduction

Colorectal cancer is the third most common malignant tumor and second most common cause of death due to malignant tumors (Bray et al, 2018). To better tumor control, it is essential to predict tumor recurrence and death due to colon cancer. Prognosis evaluation and treatment plan formulation of colon cancer patients largely depend on the TNM staging system (Kehoe and Khatri, 2006). Due to tumor heterogeneity, even with the same tumor stage, there are still huge differences in disease progression and clinical results. This suggests the limitation of the TNM staging system in predicting the prognosis of patients with colon cancer. It is necessary to develop new and reliable biomarkers to accurately predict the prognosis of patients with colon cancer

Methods

Results

Conclusion