Clinical relevance of immune microenvironment and gene-expression-based biomarkers in colorectal cancer

Background/Objectives: We explored genomic and immune landscape of colorectal cancer (CRC) compared to normal adjacent tissue (NCT). Starting from differentially expressed genes (DEGs) data, protein-protein interaction (PPI) network and deconvolution analysis were employed to unravel the intricate interplay between molecular alterations and immune cell CRC composition. Methods: The PPI network was constructed using the STRING database and Cytohubba MCC algorithm was applied to identify hub genes. Deconvolution analysis utilizing CIBERSORTx estimated the immune cells proportions between CRC and NCT. Statistical analyses, including the Wilcoxon signed rank test, effect size measurement and Cox regression, were applied to determine the magnitude of variations in cell populations and their correlation with overall survival. Results: The PPI network exploration revealed ten hub genes upregulated in CRC, showing significant enrichment (P < 1.0e-16). KEGG pathway analysis highlighted their involvement in critical cellular processes such as cell cycle, cell senescence, and p53 signaling pathways. Deconvolution analysis disclosed a distinct immune microenvironment, with fifteen cell types exhibiting significant differences in abundance and impact between CRC and NCT. Two correlated with a favorable and three with worse prognosis. Conclusion: We provided insight into the molecular and immune dynamics in CRC, identifying potential prognostic biomarkers and therapeutic targets. The intricate interplay between specific immune cell populations and clinical outcomes underscores the importance of genetic and immune factors in the management of CRC. These findings contribute to advancing our knowledge of cellular heterogeneity and CRC pathogenesis toward personalized patient treatment strategies.