Abstract
Alternative splicing (AS) events play a crucial role in the tumorigenesis and progression of cancer. Transcriptome data and Percent Spliced In (PSI) values of ovarian cancer patients were downloaded from TCGA database and TCGA SpliceSeq. Totally we identified 1472 AS events that were associated with survival of ovarian serous cystadenocarcinoma (OC) and exon skipping (ES) was the most important type. Univariate and multivariate Cox regression analysis were performed to identify survival-associated AS events and developed the prognostic model based on 11-AS events. The immune cells and different response to cytotoxic T lymphocyte associated antigen 4 (CTLA-4) and programmed cell death protein 1 (PD-1) blockers in low-risk and high-risk group of OC patients were analyzed. Ten kinds of immune cells were found up-regulated in low-risk group. Activated B cell, natural killer T cell, natural killer cell and regulatory T cell were associated with survival of OC. The patients in low-risk group had good response to CTLA-4 and PD-1 blockers treatment. Moreover, a regulatory network was established according to the correlation between AS events and splicing factors (SFs). The present study provided valuable insights into the underlying mechanisms of OC. AS events that were correlated with the immune system might be potential therapeutic targets.
Highlights
Alternative splicing (AS) events play a crucial role in the tumorigenesis and progression of cancer
The results showed that exon skipping (ES) was the main splicing pattern, while mutually exclusive exon (ME) was the least frequent event among the seven types of AS events in ovarian serous cystadenocarcinoma (OC)
Just as many other cellular processes are modified during cellular growth, differentiation, and tissue development, AS events are affected[32]
Summary
Alternative splicing (AS) events play a crucial role in the tumorigenesis and progression of cancer. A new study on AS events in ovarian cancer demonstrated that AS events can act as an independent prognostic signature for predicting ovarian cancer patients’ survival outcome[10] These findings suggest that AS events are valuable targets for cancer diagnosis, treatment, and prognosis prediction. With the development of next-generation sequencing technologies and the construction of The Cancer Genome Atlas (TCGA) database, the integrative analysis of RNA-sequencing data and prognosis information of patients makes it possible to systematically analyze the survival-related AS events in several types of c ancers[17]. We aimed to analyze the prognosis of AS events in OC through bioinformatics analysis, and explore the potential relationship between risk scores of patients and immune cells regulating OC comprehensively.
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