ArticleFrontiers in genetics2022
T cell exhaustion assessment algorism in tumor microenvironment predicted clinical outcomes and immunotherapy effects in glioma.
Article in Frontiers in genetics, 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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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed, 6 citations in OpenAlex.
- Crosstalk between immune and programmed cell death and their application in colorectal cancer risk stratification.Molecular and clinical oncology · 2026Article
- Overcoming resistance to immune checkpoint inhibitor therapy in acute myeloid leukemia.Frontiers in oncology · 2026Review
- Gut microbiota influences colorectal cancer through immune cell interactions: a Mendelian randomization study.Discover oncology · 2025Article
- The germinal center-tertiary lymphoid structure after neoadjuvant chemo-immunotherapy for locally advanced lung squamous cell carcinoma can predict the disease progression.Frontiers in immunology · 2025Article
- Role of Bioinformatics in Identifying Novel Biomarkers for Immune Cell Exhaustion and Tumor Microenvironment.Technology in cancer research & treatmentReview
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Despite the recent increase in the use of immune checkpoint blockade (ICB), no ICB medications have been approved or are undergoing large-scale clinical trials for glioma. T cells, the main mediators of adaptive immunity, are important components of the tumor immune microenvironment. Depletion of T cells in tumors plays a key role in assessing the sensitivity of patients to immunotherapy. In this study, the bioinformatics approach was applied to construct T cell depletion-related risk assessment to investigate the impact of T cell depletion on prognosis and ICB response in glioma patients. The Cancer Genome Atlas (TCGA) and GSE108474 glioma cohorts and IMvigor210 immunotherapy datasets were collected, including complete mRNA expression profiles and clinical information. We used cell lines to verify the gene expression and the R 3.6.3 tool and GraphPad for bioinformatics analysis and mapping. T cell depletion in glioma patients displayed significant heterogeneity. The T cell depletion-related prognostic model was developed based on seven prognostic genes (
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