Systematic exploration of prognostic alternative splicing events related to tumor immune microenvironment of Clear Cell Renal Cell Carcinoma

Abstract

Abstract Background Pathologically, clear cell renal cell carcinoma (ccRCC) is the most common type of renal carcinoma, with high heterogeneity and poor prognosis. There is increasing evidence that alternative splicing (AS) is involved in tumor evolution and tumor immune microenvironment (TIME). However, studies on the exploration of AS events and TIME in ccRCC are still few but needed. Methods The transcriptional data and clinicopathological information of patients with ccRCC in The Cancer Genome Atlas (TCGA) database were extracted completely. Patients were grouped according to the ESTIMATE algorithm and differentially expressed AS events (DEASs) were identified. The relationship between AS events and features of TIME were investigated by functional enrichment analysis and unsupervised consensus analysis. Finally, hub SF was identified by the regulatory network of survival-related AS events and intersection splicing factors (SFs), and its biological function was further verified in vitro. Results In total, the data of 515 patients with ccRCC were extracted and analyzed. Patients with low immune-score presented longer overall survival (OS) than high immune-score. 861 AS events were identified as DEASs, and they were enriched in immune-related pathways. 3 AS-based clusters were identified and found to have different prognoses and unique immune features. Finally, MBNL1 was identified as a hub SF, and it was shown to inhibit proliferation and metastasis, promote apoptosis, and block cells in G2/M phase in 786O and A498 cells. Conclusion The prognosticrisk model constructed base on immune-related AS events has good predictive ability for ccRCC, and the 3-clusters model based on immune-related AS events has potential for further clinical exploration. Thehub SF found in the present study, such as MBNL1, could affect the progression of ccRCC.