Alternative splicing (AS) is a gene regulatory mechanism that drives protein diversity and dysregulation of AS plays a significant role in tumorigenesis. This study aimed to develop a prognostic signature based on AS and elucidate the role in tumor immune microenvironment (TIME) in clear cell renal cell carcinoma (ccRCC). The prognosis-related AS events were analyzed by univariate Cox regression analysis. Gene set enrichment analyses (GSEA) were performed for functional annotation. Prognostic signatures were identified and validated using univariate and multivariate Cox regression, LASSO regression, Kaplan-Meier survival analysis, and proportional hazards model. The context of TIME in ccRCC was also analyzed. Gene and protein expression data of C4orf19 were obtained from ONCOMINE website and Human Protein Altas. Splicing factors (SFs) regulatory networks were visualized. 4431 survival-related AS events in ccRCC were screened. Based on splicing subtypes, eight AS prognostic signatures were constructed. A nomogram with good prognostic prediction was generated. Furthermore, the prognostic signatures were significantly correlated with TIME diversity and immune checkpoint inhibitor (ICI)-related genes. C4orf19 was the only gene whose expression levels were downregulated among the prognostic AS-related genes, which is considered as a promising prognostic factor in ccRCC. Potential functions of SFs were determined by splicing regulatory networks. In our study, AS patterns of novel indicators for prognostic prediction of ccRCC were explored. The AS-SF networks provide information of regulatory mechanisms. Players of AS events related to TIME were investigated, which contribute to prognosis monitoring of ccRCC.
© 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.