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Identification of Prognostic Signatures of Alternative Splicing in Glioma

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Abstract

Alternative splicing (AS) is a ubiquitous mechanism in which pre-mRNA can be spliced into divergent variants and involved in carcinogenesis and progression in several cancers. In the present study, we systematically profiled prognostic AS signatures involving both low grade glioma (LGG) and glioblastoma (GBM) and investigated the association of AS signatures with tumor grade and IDH1 status in glioma. Percent spliced in (PSI) values and corresponding clinical data were obtained from TCGA SpliceSeq and TCGA data portal, respectively. Prognostic AS signatures were identified using univariate and stepwise multivariate Cox regression. Heatmap analysis was performed based on prognostic AS signatures. A prognostic signature was established with 69 and 88 AS events, including specific splicing events of MUTYH, STEAP3, and CTNNB1, in LGG and GBM cohorts, respectively. The area under the curve (AUC) of the prediction model was 0.968 at 2000 days of overall survival (OS) in the LGG cohort and 0.966 at 450 days of OS in the GBM cohort. In addition, these prognostic AS signatures could complement current molecular classification, such as IDH1 mutation, 1p/19q codeletion, and ATRX loss, of glioma and further identify potential subgroups of glioma with the same molecular features. In conclusion, our study systematically profiled prognostic AS events involving both low grade glioma and glioblastoma for the first time, which also shed light on the crosstalk between AS signatures and molecular features of glioma.

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Funding

This study was supported by the National Nature Science Fund of China (No. 81872064), Natural Science Fund of Guangdong Province, China (No. 2016A030313549), Natural Science Fund of Tibet Autonomous Region (No.XZ2017ZR-ZYZ27), Science and Technology Program of Guangzhou, China (No.201607010350), Outstanding Youths Development Scheme of Nanfang Hospital, Southern Medical University (No.2016 J008).

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Correspondence to Liang Gao or Ye Song.

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The authors declare that they have no competing interests.

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Zeng, Y., Zhang, P., Wang, X. et al. Identification of Prognostic Signatures of Alternative Splicing in Glioma. J Mol Neurosci 70, 1484–1492 (2020). https://doi.org/10.1007/s12031-020-01581-0

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  • DOI: https://doi.org/10.1007/s12031-020-01581-0

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