ArticleFrontiers in genetics2024
Prognostic value of four immune-related genes in lower-grade gliomas: a biomarker discovery study.
Article in Frontiers in genetics, 2024. 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.
- Immune infiltration differences underlying prognostic radiomics subtypes from matched MRI and RNA sequencing in patients with lower-grade gliomas.Discover oncology · 2026Article
- Revealing roles of PANoptosis-related genes in prognosis and molecular subtypes in lung squamous cell carcinoma by integrated bioinformatic analyses and experiments.Clinical and experimental medicine · 2025Article
- M6A methyltransferase METTL3 promotes glucose metabolism hub gene expression and induces metabolic dysfunction-associated steatotic liver disease (MASLD).BMC genomics · 2025Article
- Multi-omics analyses inform mechanisms of immunotherapy response in pancreatic cancer.Frontiers in immunology · 2025Article
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4 authors.
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Abstract
Introduction: The tumor microenvironment and IRGs are highly correlated with tumor occurrence, progression, and prognosis. However, their roles in grade II and III gliomas, termed LGGs in this study, remain to be fully elucidated. Our research aims to develop immune-related features for risk stratification and prognosis prediction in LGG. Methods: Using the ssGSEA method, we assessed the immune characteristics of the LGG population. We conducted differential analysis using LGG samples from the TCGA database and normal samples from GTEx, identifying 412 differentially expressed immune-related genes (DEIRGs). Subsequently, we utilized univariate Cox, LASSO, and multivariate Cox regression analyses to establish both a gene predictive model and a nomogram predictive model. Results: Here, we found that the ESTIMATE score, immune score and stromal score of high-immunity, high-grade and isocitrate dehydrogenase (IDH) wild-type glioma were higher than those of the corresponding group, and the tumor purity was lower. Higher ESTIMATE scores, stromal scores and immune scores indicated a poor prognosis in patients with LGG. Our four-gene prognostic model demonstrated superior accuracy compared to other molecular features. Validation using the CGGA as a testing set and the combined TCGA and CGGA cohort confirmed its robust prognostic value. Additionally, a nomogram integrating the prognostic model and clinical variables showed enhanced predictive capability. Discussion: Our study highlights the prognostic significance of the identified four DEIRGs (KLRC3, MR1, PDIA2, and RFXAP) in LGG patients. The predictive model and nomogram developed herein offer valuable tools for personalized treatment strategies in LGG. Future research should focus on further validating these findings and exploring the functional roles of these DEIRGs within the LGG tumor microenvironment.
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