ArticleCancer immunology, immunotherapy : CII2024
Unraveling T cell exhaustion in the immune microenvironment of osteosarcoma via single-cell RNA transcriptome.
Article in Cancer immunology, immunotherapy : CII, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 11 citations in OpenAlex.
- New biological insights into osteosarcoma-lessons from single cell sequencing studies.Cancer metastasis reviews · 2026Review
- Identification of Key Bioactive Compounds of Medicine-Food Homologous Substances and Their Multi-Target Intervention Effects in Osteosarcoma Treatment.International journal of molecular sciences · 2026Article
- Mapping Current Research Status and Emerging Frontiers of T-Cell Exhaustion: A Comprehensive Data-Mining-Based Study.Annals of surgical oncology · 2026Article
- Prognostic and biological significance of MRPL13 in multiple myeloma: evidence from multi-cohort, single-cell analyses.Frontiers in oncology · 2026Article
- Integrative Single-Cell and Bulk Transcriptomics Identifies a Proliferative Malignant State and Supports a Functional Contribution of TROAP in Osteosarcoma.International journal of genomics · 2026Article
- Androgenetic alopecia drugs and male infertility: Evidence from pharmacovigilance and testicular transcriptomics.PloS one · 2026Article
- Unveiling the role of the extracellular matrix in the osteosarcoma tumor microenvironment through integrated transcriptomics and experimental validation.Cancer gene therapy · 2025Article
- Engineering Osteosarcoma In Vitro: From Traditional Models to Biofabricated Platforms for Precision Medicine.ACS omega · 2025Review
- Comprehensive single-cell transcriptomic analysis reveals fibroblast subpopulations and the prognostic association of COMT in prostate cancer progression， COMT ， COMT.Scientific reports · 2025Article
- Emerging immunotherapies in osteosarcoma: from checkpoint blockade to cellular therapies.Frontiers in immunology · 2025Review
- Identification and functional characterization of T-cell exhaustion-associated lncRNA AL031775.1 in osteosarcoma: a novel therapeutic target.Frontiers in immunology · 2025Article
- Global research trends and hotspots in metabolomics of osteosarcoma: a decade-spanning bibliometric and visualized analysis.Frontiers in immunology · 2024Article
- Circulating immune cells and risk of osteosarcoma: a Mendelian randomization analysis.Frontiers in immunology · 2024Article
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
Abstract
Osteosarcoma (OS) represents a profoundly invasive malignancy of the skeletal system. T cell exhaustion (Tex) is known to facilitate immunosuppression and tumor progression, but its role in OS remains unclear. In this study, single-cell RNA sequencing data was employed to identify exhausted T cells within the tumor immune microenvironment (TIME) of OS. We found that exhausted T cells exhibited substantial infiltration in OS samples. Pseudotime trajectory analysis revealed a progressive increase in the expression of various Tex marker genes, including PDCD1, CTLA4, LAG3, ENTPD1, and HAVCR2 in OS. GSVA showed that apoptosis, fatty acid metabolism, xenobiotic metabolism, and the interferon pathway were significantly activated in exhausted T cells in OS. Subsequently, a prognostic model was constructed using two Tex-specific genes, MYC and FCGR2B, which exhibited exceptional prognostic accuracy in two independent cohorts. Drug sensitivity analysis revealed that OS patients with a low Tex risk were responsive to Dasatinib and Pazopanib. Finally, immunohistochemistry verified that MYC and FCGR2B were significantly upregulated in OS tissues compared with adjacent tissues. This study investigates the role of Tex within the TIME of OS, and offers novel insights into the mechanisms underlying disease progression as well as the potential treatment strategies for OS.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.