Identification and Validation of Novel Immune-Related Alternative Splicing Signatures as a Prognostic Model for Colon Cancer

Individual immune-related alternative splicing (AS) events have been found to be significant in immune regulation and cancer prognosis. However, a comprehensive analysis of AS events in cancer cells based on immune-related genes (IRGs) has not been performed, and its clinical value is unknown.

Colon cancer cases with AS data were obtained from TCGA, and then, we identified overall survival-related AS events (OS-ASEs) based on IRGs by univariate analyses. Using Lasso regression, multivariate Cox regression, Kaplan-Meier analysis and nomograms, we constructed an AS risk model based on the calculated risk score. Furthermore, associations of the risk score with clinical and immune features were confirmed through the Wilcoxon rank sum test, association analysis, etc. Finally, by qRT-PCR, cell coculture and CCK-8 analyses, we validated the significance of OS-ASEs in colon cancer cell lines and clinical samples.

A total of 3,119 immune-related AS events and 183 OS-ASEs were identified, and 9 OS-ASEs were ultimately used to construct a comprehensive risk model for colon cancer patients. Low-risk patients had better OS and DFS rates than high risk patients. Furthermore, a high risk score corresponded to high numbers of multiple tumour-infiltrating immune cells and high expression of HLA-D region genes and immune checkpoint genes. Notably, we identified for the first time that anti-PD-L1 or anti-CTLA-4 antibodies may decrease the OS of specific colon cancer patients in the low-risk group. Additionally, the in vitro experiment validated that CD46-9652-ES and PSMC5-43011-ES are positively correlated with the infiltration of immune cells and promote the growth of colon cancer cells. CD46-9652-ES can contribute to T cell-mediated tumour cell killing. PSMC5-43011-ES was observed to induce M2 polarization of macrophages.

This study identified and validated immune-related prognostic AS signatures that can be used as a novel AS prognostic model and provide a novel understanding of the relationship between the immune microenvironment and clinical outcomes.