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Systematic Profiling of mRNA Splicing Reveals the Prognostic Predictor and Potential Therapeutic Target for Glioblastoma Multiforme

Despite many changes in alternative splicing events (ASEs) are frequently involved in various cancers, prognosis-related ASEs and drug treatment targets in glioblastoma multiforme (GBM) have not been well explored. ASEs participate in many biological behaviors in the initiation and progression of tu...

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Detalles Bibliográficos
Autores principales: Zhang, Botao, Wu, Quanyou, Cheng, Shujun, Li, Wenbin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8277521/
https://www.ncbi.nlm.nih.gov/pubmed/34326872
http://dx.doi.org/10.1155/2021/4664955
Descripción
Sumario:Despite many changes in alternative splicing events (ASEs) are frequently involved in various cancers, prognosis-related ASEs and drug treatment targets in glioblastoma multiforme (GBM) have not been well explored. ASEs participate in many biological behaviors in the initiation and progression of tumors, the aberrant ASE has been considered another hallmark of cancer, and the systematic study of alternative splicing may provide potential biomarkers for malignancies. In this study, we carried out a systematic analysis to characterize the ASE signatures in GBM cohort. Through comparing GBM tissues and nontumor tissues, a total of 48,191 differently expressed ASEs from 10,727 genes were obtained, and these aberrant ASEs play an important role in the oncogenic process. Then, we identified 514 ASEs independently associated with patient survival in GBM by univariate and multivariate Cox regression, including exon skip in CD3D, alternate acceptor site in POLD2, and exon skip in DCN. Those prognostic models built on ASEs of each splice type can accurately predict the outcome of GBM patients, and values for the area under curve were 0.97 in the predictive model based on alternate acceptor site. In addition, the splicing-regulatory network revealed an interesting correlation between survival-associated splicing factors and prognostic ASE corresponding genes. Moreover, these three hub splicing factors in splicing regulation network are the potential targets of some drugs. In conclusion, a systematic analysis of ASE signatures in GBM could serve as an indicator for identifying novel prognostic biomarkers and guiding clinical treatment.