Ling-Yu Wu, Yan Shao, Yang Gao, Xun-Jie Li, Xing-Xing Kang, Guo-Ping Zhao, Peng-Bo Wen
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引用次数: 0
Abstract
Radiotherapy (RT) plays a crucial role in tumor treatment, but reliable prognostic biomarkers for patient survival remain limited. To address this gap, we constructed a comprehensive database, RadSpliceDB (https://radsplicedb.com.cn), focusing on splicing isoforms, aiming to identify potential prognostic markers from this perspective. We integrated transcriptome data from patients treated with RT across 24 tumor types in The Cancer Genome Atlas to identify splicing isoforms associated with RT prognosis. We constructed effective prognostic models to validate the potential of the selected isoforms as reliable biomarkers. The database provides comprehensive annotations and functional analyses of these isoforms. RadSpliceDB contains a total of 49,587 splicing events associated with RT prognosis, covering 180,149 splicing isoforms and encompassing various common splicing patterns, such as exon skipping, 3' splice site, and 5' splice site. We further evaluated the potential of these splicing isoforms as tumor antigens using VaxiJen v2.0, identifying several candidates with high antigenicity scores. This database not only provides systematic annotations of splicing isoforms to elucidate the mechanisms of RT response but also serves as a valuable resource for identifying potential biomarkers for personalized RT. RadSpliceDB provides essential data support for optimizing RT strategies in cancer treatment.
期刊介绍:
Journal of Computational Biology is the leading peer-reviewed journal in computational biology and bioinformatics, publishing in-depth statistical, mathematical, and computational analysis of methods, as well as their practical impact. Available only online, this is an essential journal for scientists and students who want to keep abreast of developments in bioinformatics.
Journal of Computational Biology coverage includes:
-Genomics
-Mathematical modeling and simulation
-Distributed and parallel biological computing
-Designing biological databases
-Pattern matching and pattern detection
-Linking disparate databases and data
-New tools for computational biology
-Relational and object-oriented database technology for bioinformatics
-Biological expert system design and use
-Reasoning by analogy, hypothesis formation, and testing by machine
-Management of biological databases