Classification of glioma based on prognostic alternative splicing.

ABSTRACT:

Background

Previously developed classifications of glioma have provided enormous advantages for the diagnosis and treatment of glioma. Although the role of alternative splicing (AS) in cancer, especially in glioma, has been validated, a comprehensive analysis of AS in glioma has not yet been conducted. In this study, we aimed at classifying glioma based on prognostic AS.

Methods

Using the TCGA glioblastoma (GBM) and low-grade glioma (LGG) datasets, we analyzed prognostic splicing events. Consensus clustering analysis was conducted to classified glioma samples and correlation analysis was conducted to characterize regulatory network of splicing factors and splicing events.

Results

We analyzed prognostic splicing events and proposed novel splicing classifications across

SUBMITTER: Li Y 

PROVIDER: S-EPMC6858651 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature