Research Paper Volume 12, Issue 13 pp 13684—13700

Genome-wide analyses of the prognosis-related mRNA alternative splicing landscape and novel splicing factors based on large-scale low grade glioma cohort

Wang-Rui Liu1,2, *, , Chuan-Yu Li1,2, *, , Wen-Hao Xu3,4, *, , Xiao-Juan Liu5, , Hai-Dan Tang6, , Hai-Neng Huang1,2, ,

  • 1 Department of Neurosurgery, Affiliated Hospital of Youjiang Medical University for Nationalities, Guangxi 533000, China
  • 2 Clinical College of Youjiang Medical University for Nationalities, Baise 533000, China
  • 3 Department of Urology, Fudan University Shanghai Cancer Center, Shanghai 200032, China
  • 4 Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 20032, China
  • 5 Department of Pathogenic Biology, Medical College, Nantong University, Nantong 226001, Jiangsu, China
  • 6 Department of Neurology, Affiliated Hospital of Youjiang Medical College for Nationalities, Guangxi 533000, China
* Equal contribution

Received: March 24, 2020       Accepted: June 4, 2020       Published: July 13, 2020
How to Cite

Copyright © 2020 Liu et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


Alternative splicing (AS) changes are considered to be critical in predicting treatment response. Our study aimed to investigate differential splicing patterns and to elucidate the role of splicing factor (SF) as prognostic markers of low-grade glioma (LGG). We downloaded RNA-seq data from a cohort of 516 LGG tumors in The Cancer Genome Atlas and analyzed independent prognostic factors using LASSO regression and Cox proportional regression to build a network based on the correlation between SF-related survival AS events. We collected 100 patients from our center for immunohistochemistry and analyzed survival using χ2 test and Cox and Kaplan-Meier analyses. A total of 9,616 AS events related to LGG were screened and identified as well as established related models. Through analyzing specific splicing patterns in LGG, we screened 16 genes to construct a prognostic model to stratify the risk of LGG patients. Validation revealed that the expression level of the prognostic model in LGG tissue was increased, and patients with high expression showed worse prognosis. In summary, we demonstrated the role of SFs and AS events in the progression of LGG, which may provide insights into the clinical significance and aid the future exploration of LGG-associated AS.


AA: alternate acceptor site; AD: alternate donor site; AHYMUN: Affiliated Hospital of YouJiang Medical University for Nationalities; AP: alternate promotor; AS: alternative splicing; AT: alternate terminator; CI: confidence interval; DFS: disease-free survival; ES: exon skip; GO: Gene Ontology; HGG: high grade glioma; HR: hazard ratio; IHC: immunohistochemistry; KEGG: Kyoto Encyclopedia of Genes and Genomes; LGG: low grade glioma; ME: mutually exclusive exons; OS: overall survival; PPI: Protein-protein interaction; PSI: Percent spliced in index; RI: retained intron; SF gene: splicing factor gene; SFs: splicing factors; TCGA: the Cancer Genome Atlas.