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Article Abstract
The limited understanding of the prognostic implications of immune checkpoint molecules in osteosarcoma (OS) poses significant challenges for improving patient outcomes. There is a gap in the identification of reliable biomarkers that can predict treatment response and prognosis in OS patients. This study focused on investigating the prognostic value of immune checkpoints, specifically BTN3A1, SIRPA, and TDO2, using data from the TARGET database and clinical follow-up data from our hospitals. By conducting univariate Cox regression and least absolute shrinkage and selection operator (LASSO) analyses, we identified these immune checkpoints as significant prognostic indicators. A three-immune-checkpoint genetic prognostic risk model was developed, which demonstrated different prognostic implications across different clinical subgroups. Drug sensitivity analysis revealed that BTN3A1, SIRPA, and TDO2 were correlated with the efficacy of several antineoplastic agents, including hydroxyurea and docetaxel. Validation in our clinical cohort highlighted the significant prognostic value of SIRPA, suggesting its potential as a target for immunotherapy. These findings established a framework for using immune checkpoints as prognostic biomarkers, highlighting their important role in enhancing personalized treatment strategies for OS patients.
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| http://dx.doi.org/10.1186/s13018-025-06171-7 | DOI Listing |
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