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

Abstract:

: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.

journal_name

Aging (Albany NY)

journal_title

Aging

authors

Liu WR,Li CY,Xu WH,Liu XJ,Tang HD,Huang HN

doi

10.18632/aging.103491

subject

Has Abstract

pub_date

2020-07-13 00:00:00

pages

13684-13700

issue

13

issn

1945-4589

pii

103491

journal_volume

12

pub_type

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