AUTHOR=Sun Jian-Rong , Kong Chen-Fan , Lou Yan-Ni , Yu Ran , Qu Xiang-Ke , Jia Li-Qun 

TITLE=Genome-Wide Profiling of Alternative Splicing Signature Reveals Prognostic Predictor for Esophageal Carcinoma

JOURNAL=Frontiers in Genetics

VOLUME=Volume 11 - 2020

YEAR=2020

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2020.00796

DOI=10.3389/fgene.2020.00796

ISSN=1664-8021

ABSTRACT=Background: Alternative splicing (AS) provides a vital mechanism by which one mRNA could generate multiple isoforms to drive protein diversity. Growing evidence demonstrates that dysregulation of AS is connected with tumorigenesis. However, an integrated analysis of exploring the AS biomarkers for esophageal carcinoma (ESCA) is largely unstudied. 
Methods: AS percent-splice-in (PSI) data were obtained from the TCGA SpliceSeq database. Univariate and multivariate Cox regression analysis was successively performed to identify the overall survival (OS)-associated AS events and construct the AS predictor by different splicing patterns. Then a nomogram combining the final AS predictor and clinicopathological characteristics was established. Furthermore, a splicing regulatory network was created according to the correlation between the AS events and splicing factors (SF). 
Results: We detected a total of 2389 AS events connected with the OS of ESCA patients, which could serve as candidates for prognostic markers. Subsequently, we built eight AS predictors by splicing patterns that presented great ability in distinguishing high- and low-risk patients and predicting ESCA prognosis. Notably, the area under curve (AUC) value for the exon skip (ES) prognostic predictor could reach 0.885, which showed the ES predictor possesses the most powerful predictive ability for ESCA prognosis. Besides, a nomogram consisting of the pathological stage and risk group presented a powerful predictive ability for survival possibility of ESCA patients. Moreover, the splicing correlation network revealed the opposite roles of splicing factors (SFs) in ESCA.
Conclusion: In this study, the AS events may provide reliable biomarkers for the prognosis of ESCA and the splicing correlation networks could provide a new insight for the potential regulatory mechanisms in ESCA development.