Abstract
BackgroundAlternative splicing (AS), one of the main post-transcriptional biological regulation mechanisms, plays a key role in the progression of glioblastoma (GBM). Systematic AS profiling in GBM is limited and urgently needed.MethodsTCGA SpliceSeq data and the corresponding clinical data were downloaded from the TCGA data portal. Survival-related AS events were identified through Kaplan–Meier survival analysis and univariate Cox analysis. Then, splicing correlation network was constructed based on these AS events and associated splicing factors. LASSO regression followed by multivariate Cox analysis was performed to validate independent AS biomarkers and to construct a risk prediction model. Enrichment analysis was subsequently conducted to explore potential signaling pathways of these AS events.ResultsA total of 132 TCGA GBM samples and 45,610 AS events were included in our study, among which 416 survival-related AS events were identified. An AS correlation network, including 54 AS events and 94 splicing factors, was constructed, and further functional enrichment was performed. Moreover, the novel risk prediction model we constructed displayed moderate performance (the area under the curves were > 0.7) at both one, two and three years.ConclusionsSurvival-related AS events may be vital factors of both biological function and prognosis. Our findings in this study can deepen the understanding of the complicated mechanisms of AS in GBM and provide novel insights for further study. Moreover, our risk prediction model is ready for preliminary clinical applications. Further verification is required.
Highlights
Alternative splicing (AS), one of the main post-transcriptional biological regulation mechanisms, plays a key role in the progression of glioblastoma (GBM)
Around 20,000 protein-coding genes have been found in the human genome, but the number of mature Message RNAs (mRNA) in transcriptomics vastly exceeds the number of protein-coding genes (the current version of GENCODE (GENCODE 31) identified 82,141 different mature mRNA sequences) [15, 16]
Of note is that missing values of Percent Spliced In (PSI) were frequent or the variation or dispersion of the PSI value was small in the unfiltered samples
Summary
Alternative splicing (AS), one of the main post-transcriptional biological regulation mechanisms, plays a key role in the progression of glioblastoma (GBM). As a vital part of the post-transcriptional biological regulation mechanism, AS plays a key role in promoting protein polymorphism by altering functional domains and modification of proteins [17, 18]. For the same coding gene, its corresponding protein isoforms can perform different or even completely opposite functions, playing a vital role in regulating complex biological functions [19]. Splicing isoforms caused by exon skipping of C-CBL can lead to tumor growth whereas C-CBL itself can serve as an inhibitor of cell proliferation in normal tissues [20]. The upregulation of MYO1B-fl caused by splice-switching promotes cell proliferation and changes of the cytoskeleton, promoting the growth of GBM [21]. Cancer-specific splicing variants may be used as diagnostic, prognostic and predictive biomarkers as well as therapeutic targets
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