Colorectal cancer prognosis: insights from the tumor immune microenvironment and gut microbiota.

BACKGROUND

Colorectal cancer (CRC) is the third most common cancer worldwide. Despite recent advancements in screening strategies and treatments, the prognosis of CRC patients remains poor. Emerging evidences suggest that tumor immune microenvironment (TIME) and gut microbiota play a pivotal role in CRC progression and treatment. However, the clinical utility of these findings remains limited due to the absence of robust biomarkers. We sought to establish a clinically actionable tool that could guide personalized treatment decisions and ultimately improve outcomes for CRC patients.

METHODS

We analyzed differentially expressed genes (DEGs) from the Gene Expression Omnibus (GEO) and identified the prognostic genes for CRC by integrating the TIME- and gut microbiota-related genes from GeneCards. Using Mendelian randomization (MR), we examined the causal relationships between the prognostic genes, gut microbiota, and CRC. We then developed a risk model and independently validated its predictive performance using The Cancer Genome Atlas-Colon Adenocarcinoma (TCGA-COADREAD) dataset as an external validation cohort.

RESULTS

We established a risk model comprising the six identified genes and found that the high-risk group had a significantly higher mortality rate than the low-risk group. Additionally, the high-risk group showed increased immune cell infiltration and a diminished response to immunotherapy. The two-step MR analysis revealed that and mediated the causal relationship between the prognostic genes and CRC. Further, the risk score was shown to be an independent prognostic factor for CRC survival, and the newly established nomogram demonstrated strong concordance between the predicted and observed clinical outcomes.

CONCLUSIONS

We developed a six-gene risk model and showed that gut microbes mediate the causal link between the prognostic genes and CRC. Further research on the regulation of the TIME and gut microbiota in CRC may provide valuable insights.