ArticleBrain sciences2022
A Metabolic Plasticity-Based Signature for Molecular Classification and Prognosis of Lower-Grade Glioma.
Article in Brain sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Comprehensive machine learning-based integration develops a novel prognostic model for glioblastoma.Molecular therapy. Oncology · 2024Article
- PSMB2 plays an oncogenic role in glioma and correlates to the immune microenvironment.Scientific reports · 2024Article
- Identifying a novel cuproptosis-related necroptosis gene subtype-related signature for predicting the prognosis, tumor microenvironment, and immunotherapy of hepatocellular carcinoma.Frontiers in molecular biosciences · 2023Article
- Development of a Hallmark Pathway-Related Gene Signature Associated with Immune Response for Lower Grade Gliomas.International journal of molecular sciences · 2022Article
- Targeting GSTP1-dependent ferroptosis in lung cancer radiotherapy: Existing evidence and future directions.Frontiers in molecular biosciences · 2022Review
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5 authors.
Funding
Abstract
backgroundGlioma is one of the major health problems worldwide. Biomarkers for predicting the prognosis of Glioma are still needed.
methodsThe 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.
resultsLower 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 construct a co-expressed network using the DEGs, and four co-expressed modules were identified, which are blue, green, grey, and yellow modules. High-risk patients have a lower overall survival rate than low-risk patients. In addition, the risk score is associated with histological subtypes. Finally, the role of RPH3A was detected. The overexpression of RPH3A in LGG cells can significantly inhibit cell proliferation and migration and regulate EMT-regulated proteins.
conclusionOur study developed a metabolic-related model for the prognosis of Glioma cells. RPH3A is a potential therapeutic target for Glioma.
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