Unraveling the PANoptosis Landscape in Osteosarcoma: A Single-Cell Sequencing and Machine Learning Approach to Prognostic Modeling and Tumor Microenvironment Analysis
Conclusion: This study provides novel insights into the PANoptosis landscape in OS and presents a validated prognostic model for risk stratification. The integration of scRNA-seq data with machine learning approaches enhances our understanding of OS heterogeneity and its impact on patient prognosis,...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-01-01
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| Series: | International Journal of Genomics |
| Online Access: | http://dx.doi.org/10.1155/ijog/6915258 |
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| Summary: | Conclusion: This study provides novel insights into the PANoptosis landscape in OS and presents a validated prognostic model for risk stratification. The integration of scRNA-seq data with machine learning approaches enhances our understanding of OS heterogeneity and its impact on patient prognosis, offering potential avenues for targeted therapeutic strategies. Further validation in clinical settings is warranted to confirm the model’s utility in guiding personalized treatment for OS patients. |
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| ISSN: | 2314-4378 |