Prognostic alternative mRNA splicing signature and immune infiltration in prostate cancer

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Abstract

Background Prostate cancer (PCa) is among the most prevalent malignancies in males across the globe. Alternative splicing (AS), a post-transcriptional modification, has been associated with several malignancies. This research focused on genome-wide analyses of AS events in PCa. Methods Using gap analysis, we detected remarkable differential AS events (DASEs) related to PCa. Cox analysis was conducted to identify DASEs that prognostically affect the disease-free interval (DFI) and overall survival (OS) in PCa patients. Unsupervised cluster analysis was utilized to identify differential AS clusters and AS networks. We investigated whether patients with PCa who had a higher or lower risk of OS responded to chemotherapeutic and immunotherapeutic treatments. Results In the analysis of PCa, 296 DASEs were identified as clinically significant. The prognostic values for DFI and OS were used to construct a prognostic model. Using unsupervised cluster analysis, we determined the AS clusters related to OS. According to our findings, high- and low-risk groups have different outcomes for cisplatin and gemcitabine chemotherapy. Conclusion We conducted a detailed investigation of AS events in PCa by performing a genome-wide analysis. According to the data presented here, DASEs and splicing factors tend to influence the survival rates of PCa patients as well as their susceptibility to chemotherapeutic medications. This could offer innovative perspectives for the treatment of PCa.

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