Table_3_Identification and Validation of Immune Molecular Subtypes and Immune Landscape Based on Colon Cancer Cohort.DOCX

Background

The incidence and mortality rates of colon adenocarcinoma (COAD), which is the fourth most diagnosed cancer worldwide, are high. A subset of patients with COAD has shown promising responses to immunotherapy. However, the percentage of patients with COAD benefiting from immunotherapy is unclear. Therefore, gaining a better understanding of the immune milieu of colon cancer could aid in the development of immunotherapy and suitable combination strategies.

Methods

In this study, gene expression profiles and clinical follow-up data were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, and molecular subtypes were identified using the ConsensusClusterPlus package in R. Univariate and multivariate Cox regression analyses were performed to evaluate the prognostic value of immune subtypes. The graph structure learning method was used to reduce the dimension to reveal the internal structure of the immune system. Weighted correlation network analysis (WGCNA) was performed to identify immune-related gene modules. Finally, western blotting was performed to verify the gene expression patterns in COAD samples.

Results

The results showed that 424 COAD samples could be divided into three subtypes based on 1921 immune cell-related genes, with significant differences in prognosis between subtypes. Furthermore, immune-related genes could be divided into five functional modules, each with a different distribution pattern of immune subtypes. Immune subtypes and gene modules were highly reproducible across many data sets. There were significant differences in the distribution of immune checkpoints, molecular markers, and immune characteristics among immune subtypes. Four core genes, namely, CD2, FGL2, LAT2, and SLAMF1, with prognostic significance were identified by WGCNA and univariate Cox analysis.

Conclusion

Overall, this study provides a conceptual framework for understanding the tumor immune microenvironment of colon cancer.