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Identification of prognostic splicing factors and exploration of their potential regulatory mechanisms in pancreatic adenocarcinoma
Author(s) -
Minhua Rong,
Zhan-Hui Zhu,
Ying Guan,
Meiwei Li,
Jiashuo Zheng,
Yue-Qi Huang,
DanMing Wei,
Yingmei Li,
Xiao-ju Wu,
Hui-Ping Bu,
Hui-Liu Peng,
Xiaolin Wei,
Guosheng Li,
Mingxuan Li,
Minghui Chen,
SuNing Huang
Publication year - 2020
Publication title -
peerj
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.927
H-Index - 70
ISSN - 2167-8359
DOI - 10.7717/peerj.8380
Subject(s) - rna splicing , univariate , lasso (programming language) , pancreatic cancer , alternative splicing , adenocarcinoma , proportional hazards model , computational biology , biology , bioinformatics , medicine , oncology , cancer , gene , rna , messenger rna , computer science , genetics , multivariate statistics , machine learning , world wide web
Pancreatic adenocarcinoma (PAAD), the most common subtype of pancreatic cancer, is a highly lethal disease. In this study, we integrated the expression profiles of splicing factors (SFs) of PAAD from RNA-sequencing data to provide a comprehensive view of the clinical significance of SFs. A prognostic index (PI) based on SFs was developed using the least absolute shrinkage and selection operator (LASSO) COX analysis. The PI exhibited excellent performance in predicting the status of overall survival of PAAD patients. We also used the percent spliced in (PSI) value obtained from SpliceSeq software to quantify different types of alternative splicing (AS). The prognostic value of AS events was explored using univariate COX and LASSO COX analyses; AS-based PIs were also proposed. The integration of prognosis-associated SFs and AS events suggested the potential regulatory mechanisms of splicing processes in PAAD. This study defined the markedly clinical significance of SFs and provided novel insight into their potential regulatory mechanisms.

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