Alternative Splicing Events and Subtype Analysis of Esophageal Cancer

Abstract

Aim: Alternative splicing (AS) has been widely demonstrated in the occurrence and progression of many cancers. Nevertheless, the involvement of cancer-associated splicing in the development of esophageal carcinoma (ESCA) is still ambiguous.Method: RNA-Seq data and the corresponding clinical information of the ESCA cohort was downloaded from The Cancer Genome Atlas database. The splicing percentage value was calculated using a Java application called SpliceSeq, and differently expressed AS (DEAS) events and their splicing network were further analyzed using bioinformatics methods. Kaplan–Meier, Cox regression, and unsupervised cluster analyses were used to assess the association between AS events and clinical characteristics of ESCA patients.Results: A total of 50,342 AS events were identified, of which 3,988 were DEAS events; 46 of these were associated with overall survival (OS) of ESCA patients, and the 5-year OS rate was 0.941. By constructing a network of AS events with survival-related splicing factors and variable-shear events associated with prognosis, the regulatory relationship was further predicted. Four clusters with different survival patterns were revealed using unsupervised cluster analysis.Conclusion: ESCA-associated AS events and splicing networks are of great value in deciphering the underlying mechanisms of AS in ESCA and providing clues for therapeutic goals for further validation.