Identification and Validation of Immune Molecular Subtypes and Immune Landscape Based on Colon Cancer Cohort
1Department of Digestive, China-Japan Union Hospital, Jilin University, Changchun, China.
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.
Insights
This study identified three distinct immune subtypes in colon adenocarcinoma (COAD) with varying prognoses. Understanding these immune subtypes and their associated genes is crucial for developing effective colon cancer immunotherapy strategies.
Area of Science:
- Oncology
- Immunology
- Genomics
Background:
- Colon adenocarcinoma (COAD) is a prevalent cancer with high mortality.
- Immunotherapy shows promise for a subset of COAD patients, but efficacy varies.
- A deeper understanding of the tumor immune microenvironment in COAD is needed to optimize immunotherapy.
Purpose of the Study:
- To classify colon cancer into immune subtypes.
- To investigate the prognostic value of these immune subtypes.
- To identify key immune-related genes and modules influencing COAD prognosis and immunotherapy response.
Main Methods:
- Utilized The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) data.
- Employed ConsensusClusterPlus for immune subtype identification.
- Applied Cox regression, graph structure learning, and Weighted Gene Correlation Network Analysis (WGCNA).
- Verified gene expression patterns using western blotting.
Main Results:
- Identified three distinct immune subtypes in 424 COAD samples with significant prognostic differences.
- Discovered five immune-related gene modules with varying immune subtype distributions.
- Found significant differences in immune checkpoints and markers across subtypes.
- Identified four core prognostic genes: CD2, FGL2, LAT2, and SLAMF1.
Conclusions:
- This study provides a framework for understanding the tumor immune microenvironment in colon cancer.
- The identified immune subtypes and core genes offer potential targets for novel immunotherapy strategies.
- Further research into these subtypes could improve patient stratification and treatment outcomes.
