ArticleFrontiers in immunology2024
Single-cell RNA-seq reveals T cell exhaustion and immune response landscape in osteosarcoma.
Article in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
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Who cites it
30 citing papers in PubMed, 25 citations in OpenAlex.
- Tumor microenvironment-rearranging Nanoassemblies overcome angiogenesis-immunotherapy resistance to potentiate osteosarcoma treatment.Materials today. Bio · 2026Article
- The Osteosarcoma Tumor Microenvironment: From Cellular Interactions to Advanced Preclinical Models.Cancers · 2026Review
- Dissecting T-cell exhaustion heterogeneity and immune ecosystem dynamics in colorectal cancer through multi-omics machine learning.BMC cancer · 2026Article
- 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
- Aging reshapes the osteosarcoma ecosystem through immune dysfunction and tumor cell reprogramming.Cellular oncology (Dordrecht, Netherlands) · 2026Article
- AI-Based Prediction of Gene Expression in Single-Cell and Multiscale Genomics and Transcriptomics.International journal of molecular sciences · 2026Review
- Mapping Current Research Status and Emerging Frontiers of T-Cell Exhaustion: A Comprehensive Data-Mining-Based Study.Annals of surgical oncology · 2026Article
- Immunotherapy and postoperative bone defect repair strategies based on osteosarcoma tumor microenvironment characteristics: balancing antitumor effects and promotion of bone regeneration.Regenerative biomaterials · 2026Review
- Immune exclusion as a recurrent immune-escape state driving treatment resistance in osteosarcoma: insights from single-cell, spatial, and multi-omics studies.Frontiers in immunology · 2026Review
- Dynamic immune state transitions and metastatic niche remodelling drive osteosarcoma evolution as a barrier-restricted immune-cold ecosystem.Frontiers in immunology · 2026Review
- The regulatory networks and mechanisms of bone microenvironment in tumorigenesis and metastasis.Journal of bone oncology · 2025Review
- Single-cell RNA sequencing in osteosarcoma: applications in diagnosis, prognosis, and treatment.Medical oncology (Northwood, London, England) · 2025Review
- Osteosarcoma: A Comprehensive Morphological and Molecular Review with Prognostic Implications.Biology · 2025Review
- Current status of chimeric antigen receptor T cell therapy and its exhaustion mechanism.Immunotherapy · 2025Review
- Article
- The RNA-Binding Protein RBMX Mediates the Immunosuppressive Microenvironment of Osteosarcoma by Regulating CD8Cancers · 2025Article
- Activation of HTR2B Suppresses Osteosarcoma Progression through the STAT1-NLRP3 Inflammasome Pathway and Promotes OASL1+ Macrophage Production to Enhance Antitumor Immunity.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- SAC3 domain containing 1 intervention in energy metabolism reprogramming assists in the progression of hepatocellular carcinoma.World journal of gastrointestinal oncology · 2025Article
- Identifying PSIP1 as a critical R-loop regulator in osteosarcoma via machine-learning and multi-omics analysis.Cancer cell international · 2025Article
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: T cell exhaustion in the tumor microenvironment has been demonstrated as a substantial contributor to tumor immunosuppression and progression. However, the correlation between T cell exhaustion and osteosarcoma (OS) remains unclear. Methods: In our present study, single-cell RNA-seq data for OS from the GEO database was analysed to identify CD8+ T cells and discern CD8+ T cell subsets objectively. Subgroup differentiation trajectory was then used to pinpoint genes altered in response to T cell exhaustion. Subsequently, six machine learning algorithms were applied to develop a prognostic model linked with T cell exhaustion. This model was subsequently validated in the TARGETs and Meta cohorts. Finally, we examined disparities in immune cell infiltration, immune checkpoints, immune-related pathways, and the efficacy of immunotherapy between high and low TEX score groups. Results: The findings unveiled differential exhaustion in CD8+ T cells within the OS microenvironment. Three genes related to T cell exhaustion (RAD23A, SAC3D1, PSIP1) were identified and employed to formulate a T cell exhaustion model. This model exhibited robust predictive capabilities for OS prognosis, with patients in the low TEX score group demonstrating a more favorable prognosis, increased immune cell infiltration, and heightened responsiveness to treatment compared to those in the high TEX score group. Conclusion: In summary, our research elucidates the role of T cell exhaustion in the immunotherapy and progression of OS, the prognostic model constructed based on T cell exhaustion-related genes holds promise as a potential method for prognostication in the management and treatment of OS patients.
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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.