RNA-seq of 4 colorectal cancer cases

<b>Abstract</b><b>Background:</b> Colorectal cancer (CRC) is associated with a high recurrence rate and late-stage diagnosis, leading to poor prognosis, thus urgent need for reliable prognostic biomarkers. Existing polygenic prognostic models mostly overlook individual molecular heterogeneity and neuromodulatory pathways. However, the nervous system is involved in tumor progression via pathways such as Axon Guidance, whose prognostic value in CRC remains unestablished.<b>M</b><b>ethod</b>：Based on transcriptomic and clinical data of CRC patients from the TCGA database, this study screened key genes through survival and differential expression analyses. Combined with stepwise Cox regression and machine learning, we constructed the OPISV prognostic model that integrates individual heterogeneity and neuromodulatory pathways, including four variables: age, M stage, EPHB2, and ZNF346. The model was validated using external datasets via Kaplan–Meier survival analysis and ROC curve evaluation; LASSO and logistic regression further confirmed its significant association with patient survival.<b>R</b><b>esult</b>: Notably, the Axon Guidance pathway was significantly enriched between the high-risk and low-risk OPISV groups. We further explored the biological role and underlying mechanisms of this pathway in CRC. Immune cell infiltration and mutational profiles were also compared between OPISV groups, and functional enrichment analyses were performed across Axon Guidance-related subtypes.<b>conclusion</b><b>:</b> the OPISV model is a reliable and practical tool for predicting patient prognosis. It may also provide mechanistic insights into the role of Axon Guidance in CRC progression.