4.4 Article

Identification of prognostic alternative splicing signature in gastric cancer

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ARCHIVES OF PUBLIC HEALTH
卷 80, 期 1, 页码 -

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BMC
DOI: 10.1186/s13690-022-00894-3

关键词

Gastric carcinoma; Alternative splicing; Splicing factor; Prognosis

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This study identified prognostic AS events in gastric cancer (GC) and constructed multi-AS-based signatures using RNA-Seq data. The study found that these AS events served as prognostic biomarkers and were correlated with the expression of splicing factors. The findings provide valuable evidence for understanding the prognosis and potential therapeutic targets in GC.
Background Aberrant alternative splicing (AS) events could be viewed as prognostic indicators in a large number of malignancies. This study aims to identify prognostic AS events, illuminate the function of the splicing variants biomarkers and provide reliable evidence for formulating public health strategies for gastric cancer (GC) surveillance. Methods RNA-Seq data, clinical information and percent spliced in (PSI) values were available in The cancer genome atlas (TCGA) and TCGA SpliceSeq data portal. A three-step regression method was conducted to identify prognostic AS events and construct multi-AS-based signatures. The associations between prognostic AS events and splicing factors were also investigated. Results We identified a total of 1,318 survival-related AS events in GC, parent genes of which were implicated in numerous oncogenic pathways. The final prognostic signatures stratified by seven types of AS events or not stratified performed well in risk prediction for GC patients. Moreover, five signatures based on AA, AD, AT, ES and RI events function as independent prognostic indicators after multivariate adjustment of other clinical variables. Splicing network also showed marked correlation between the expression of splicing factors and PSI value of AS events in GC patients. Conclusion Our findings provide a landscape of AS events and regulatory network in GC, indicating that AS events might serve as prognostic biomarkers and therapeutic targets for GC.

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