ArticleFrontiers in immunology2022
Positive regulators of T cell functions as predictors of prognosis and microenvironment characteristics of low-grade gliomas.
Article in Frontiers in immunology, 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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5 citing papers in PubMed, 5 citations in OpenAlex.
- Integrated transcriptomic network analysis reveals shared immunogenomic regulators between glioma and type 2 diabetes, highlighting VCAN as a prominent marker.Scientific reports · 2026Article
- Mitochondrial electron transport chain gene-based prognostic model identifies SDHB as a key regulator of low-grade glioma progression and therapeutic target.Cancer cell international · 2025Article
- Discovering the Potential Role of the C2 DUSP2+ MCs Subgroup in Lung Adenocarcinoma.Translational oncology · 2025Article
- The characteristics and functional significance of disulfidptosis-related genes in head and neck squamous cell carcinoma.Discover oncology · 2024Article
- SPDYC serves as a prognostic biomarker related to lipid metabolism and the immune microenvironment in breast cancer.Immunologic research · 2024Article
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Authors and funding
5 authors at 1 institution in 1 country.
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Abstract
Background: Low-grade gliomas (LGG) are one of the most prevalent types of brain cancers. The efficacy of immunotherapy in LGG is limited compared to other cancers. Immunosuppression in the tumor microenvironment (TME) of LGG is one of the main reasons for the low efficacy of immunotherapy. Recent studies have identified 33 positive regulators of T cell functions (TPRs) that play a critical role in promoting the proliferation, activity, and functions of multiple immunocytes. However, their role in the TME of LGG has not been investigated. This study aimed to construct a risk model based on these TPRs and to detect the significance of immunotypes in predicting LGG prognosis and immunotherapy efficacy. Methods: A total of 688 LGGs and 202 normal brain tissues were extracted from The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), and Genotype-Tissue Expression (GTEx) databases. The NMF R package was used to identify TRP-related subtypes. The TPR prognostic model was established using the least absolute shrinkage and selection operator (LASSO) algorithm to predict the overall survival of LGG samples. Results: The Subtype 2 patients had worse survival outcomes, suppressed immune function, and higher immune cell infiltration. A risk regression model consisting of 14 TPRs was established, and its performance was validated in CGGA325 cohorts. The low-risk group exhibited better overall survival, immune microenvironment, and immunotherapy response, as determined Conclusions: Our study identified two distinct TPR subtypes and built a TPR signature to elucidate the characteristics of T cell proliferation in LGG and its association with immune status and prognosis. These findings shed light on possible immunotherapeutic strategies for LGGs.
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