ArticleInternational journal of general medicine2022
Construction of a Risk Model to Predict the Prognosis and Immunotherapy of Low-Grade Glioma Ground on 7 Ferroptosis-Related Genes.
Article in International journal of general medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 6 citations in OpenAlex.
- Bioinformatics-based identification of key genes for Olaparib resistance in breast cancer: prognostic implications and therapeutic relevance.Discover oncology · 2025Article
- Glioma stem cells remodel immunotolerant microenvironment in GBM and are associated with therapeutic advancements.Cancer biomarkers : section A of Disease markers · 2024Review
- Prognosis Individualized: Survival predictions for WHO grade II and III gliomas with a machine learning-based web application.NPJ digital medicine · 2023Article
- Construction of a prognostic risk model based on apoptosis-related genes to assess tumor immune microenvironment and predict prognosis in hepatocellular carcinoma.BMC gastroenterology · 2022Article
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: Ferroptosis is closely associated with tumors. The purpose of this study was to investigate the correlation between ferroptosis and prognosis of low grade glioma (LGG) via construction and verification of a risk model. Patients and Methods: The data of LGG were downloaded from public databases. Through LASSO analysis of characteristic genes, a gene signature was constructed. Patients into were divided two groups based on risk score. Subsequently, survival, clinical phenotype, functional enrichment, immune cell infiltration and somatic mutation analysis were performed. In addition, whether ferroptosis-related genes (FRGs) signature can predict the patient's response to anti-PD-1/PD-L1 immunotherapy was also investigated. Results: FRGs signature had strong prognostic assessment ability, and high risk score was associated with poor overall survival (OS) of LGG. The high risk score group had higher degree of immune cell infiltration, stronger stromal activity, higher immune score, and high expression of immune checkpoint. In low risk score group anti-PD-1/PD-L1 immunotherapy has significant therapeutic advantages and clinical response. Genes and frequency of somatic mutations and clinical phenotypes in the high and low risk score groups were significantly different. Conclusion: A prognostic model based on 7 FRGs can be used to predict the prognosis and immunotherapeutic response of LGG.
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