ArticleFrontiers in cell and developmental biology2021
Tumor Immune Microenvironment Landscape in Glioma Identifies a Prognostic and Immunotherapeutic Signature.
Article in Frontiers in cell and developmental biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 9 citations in OpenAlex.
- UCP2 Identifies Immunosuppressive Tumor-Associated Macrophages and Is Associated with Predicted Immunotherapy Resistance in Glioma.Oncology research · 2026Article
- Can tissue immune states shape the risk of hyperprogressive disease?Frontiers in immunology · 2026Review
- Next-generation anti-PD-L1/IL-15 immunocytokine elicits superior antitumor immunity in cold tumors with minimal toxicity.Cell reports. Medicine · 2024Article
- Fundamentals and Applications of Focused Ultrasound-Assisted Cancer Immune Checkpoint Inhibition for Solid Tumors.Pharmaceutics · 2024Review
- Identification of two robust subclasses of sepsis with both prognostic and therapeutic values based on machine learning analysis.Frontiers in immunology · 2022Article
- Construction and validation of an angiogenesis-related gene expression signature associated with clinical outcome and tumor immune microenvironment in glioma.Frontiers in genetics · 2022Article
- Global Characterization of Metabolic Genes Regulating Survival and Immune Infiltration in Osteosarcoma.Frontiers in genetics · 2021Article
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Authors and funding
12 authors at 7 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The tumor immune microenvironment (TIME) has been recognized to be associated with sensitivity to immunotherapy and patient prognosis. Recent research demonstrates that assessing the TIME patterns on large-scale samples will expand insights into TIME and will provide guidance to formulate immunotherapy strategies for tumors. However, until now, thorough research has not yet been reported on the immune infiltration landscape of glioma. Herein, the CIBERSORT algorithm was used to unveil the TIME landscape of 1,975 glioma observations. Three TIME subtypes were established, and the TIMEscore was calculated by least absolute shrinkage and selection operator (LASSO)-Cox analysis. The high TIMEscore was distinguished by an elevated tumor mutation burden (TMB) and activation of immune-related biological process, such as IL6-JAK-STAT3 signaling and interferon gamma (IFN-γ) response, which may demonstrate that the patients with high TIMEscore were more sensitive to immunotherapy. Multivariate analysis revealed that the TIMEscore could strongly and independently predict the prognosis of gliomas [Chinese Glioma Genome Atlas (CGGA) cohort: hazard ratio (HR): 2.134,
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