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Comprehensive Analysis of Prognostic Alternative Splicing Signatures in Endometrial Cancer.


ABSTRACT: Background:Alternative splicing (AS) is one of the critical post-transcriptional regulatory mechanisms of various cancers and also plays a crucial role in the development of cancers, including endometrial cancer (EC). Methods:The splicing data and gene expression profiles of EC were obtained from The Cancer Genome Atlas. The corresponding clinical data were extracted from TCGA-CDR. With univariate Cox regression analysis, least absolute shrinkage and selection operator model, and multivariate Cox regression analysis, the survival-related AS events were selected. Functional enrichment analysis was also performed to investigate the functions of these AS events. Splicing factors and AS regulation network were constructed to understand the correlation among these AS events. Result:A total of 1826 AS events were identified as survival-related events. Functional enrichment analysis showed that these AS events were associated with several immune system-related processes. Then, the prognostic signatures were developed based on these survival-related events and acted as an independent prognostic factor for EC. Splicing factors and AS regulation network were also constructed to understand the regulatory mechanisms of AS events in EC. Conclusion:This study systematically analyzed the role of AS events in EC and developed the prognostic model for EC.

SUBMITTER: Chen P 

PROVIDER: S-EPMC7272712 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Comprehensive Analysis of Prognostic Alternative Splicing Signatures in Endometrial Cancer.

Chen Peigen P   He Junxian J   Ye Huixia H   Jiang Senwei S   Li Yunhui Y   Li Xiaomao X   Wan Jing J  

Frontiers in genetics 20200529


<h4>Background</h4>Alternative splicing (AS) is one of the critical post-transcriptional regulatory mechanisms of various cancers and also plays a crucial role in the development of cancers, including endometrial cancer (EC).<h4>Methods</h4>The splicing data and gene expression profiles of EC were obtained from The Cancer Genome Atlas. The corresponding clinical data were extracted from TCGA-CDR. With univariate Cox regression analysis, least absolute shrinkage and selection operator model, and  ...[more]

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