A Metabolic Plasticity-Based Signature for Molecular Classification and Prognosis of Lower-Grade Glioma.

ABSTRACT:

Background

Glioma is one of the major health problems worldwide. Biomarkers for predicting the prognosis of Glioma are still needed.

Methods

The transcriptome data and clinic information on Glioma were obtained from the CGGA, TCGA, GDC, and GEO databases. The immune infiltration status in the clusters was compared. The genes with differential expression were identified, and a prognostic model was developed. Several assays were used to detect RPH3A's role in Glioma cells, including CCK-8, colony formation, wound healing, and transwell migration assay.

Results

Lower Grade Glioma (LGG) was divided into two clusters. The immune infiltration difference was observed between the two clusters. We screened for genes that differed between the two groups. WGCNA was used to const

SUBMITTER: Yang MC 

PROVIDER: S-EPMC9497112 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature