A risk stratification framework based on ammonia-induced cell death signatures for prognostic assessment and therapeutic insights in colorectal cancer

BACKGROUND: Ammonia, which was traditionally regarded as a metabolic by-product, has more recently emerged as a crucial regulator of tumor metabolism and immune dysfunction. Nevertheless, the prognostic implications and therapeutic significance of ammonia-related genes in colorectal cancer (CRC) are still largely uncharted territory. This lack of exploration means that there is a significant gap in our understanding of how these genes may impact the prognosis of CRC patients and potentially serve as targets for new therapeutic strategies. METHODS: Transcriptomic and clinical data from the TCGA-COAD dataset were analyzed to pinpoint ammonia-related genes that showed differential expression. A prognostic risk signature was then developed by employing univariate Cox, LASSO, and multivariate Cox regression analyses. To assess the immune landscape characteristics and pathway alterations, techniques such as CIBERSORT, GSVA, TIDE, and TCIA were utilized. External validation of the gene expression patterns across different cell types was carried out using single-cell RNA-seq data from the GSE132465 dataset. The exploration of potential therapeutic targets was further advanced through artificial intelligence-based virtual screening on the DrugCLIP platform. Finally, the key genes were experimentally verified using RT-qPCR. This comprehensive approach aimed to understand the role of ammonia-related genes in CRC, from their identification to their potential as therapeutic targets, while validating findings at multiple levels. RESULTS: A three-gene signature consisting of PMM2, CLK2, and UCHL1, which is associated with ammonia-induced cellular stress, was identified. This signature was then utilized to construct a prognostic risk model. This model successfully classified CRC patients into high- and low- risk groups, with these groups showing significantly disparate survival outcomes. Through functional analyses, it was discovered that the high-risk group had an enrichment of pathways related to mitochondrial metabolism, proteostasis regulation, and oxidative stress responses. Immune analyses indicated that in the high-risk group, there was an increased infiltration of regulatory T cells and enhanced interferon - related signaling. This suggests the presence of an "inflamed but immunosuppressed" tumor microenvironment. Single-cell RNA-seq analysis further confirmed the celltype-specific expression patterns of the three genes within the tumor microenvironment. Additionally, artificial intelligence (AI)-based virtual screening identified candidate small molecules that are predicted to bind to the catalytic pocket of CLK2. This finding indicates that CLK2 has the potential to be a druggable metabolic target. Overall, these results provide valuable insights into the role of ammonia-related genes in CRC and offer potential avenues for prognostic assessment and therapeutic intervention. CONCLUSIONS: This gene signature associated with ammonia offers a new paradigm for prognostic stratification in CRC. It mirrors the metabolic stress responses triggered by ammonia accumulation within the tumor microenvironment. These discoveries emphasize that metabolic adaptation related to ammonia could serve as a rich source of potential biomarkers. Moreover, they propose CLK2 as a highly promising therapeutic target, opening up new possibilities for more effective treatment strategies in CRC management.