Signatures of tumor microenvironment-related genes and long noncoding RNAs predict poor prognosis in osteosarcoma

Ying Lu, Li Zhou and Zhanyu Yang

PLOS ONE, 2025, vol. 20, issue 7, 1-27

Abstract: Introduction: Osteosarcoma is an aggressive bone cancer with poor outcomes, especially in young individuals. This study sought to identify tumor microenvironment-related genes (TMIEGs) and associated long noncoding RNAs (TMIELs) that influence patient prognosis. Materials and methods: Data from the TARGET osteosarcoma and GTEx muscle datasets were analysed to calculate stromal and immune scores, dividing patients into high- and low-score groups. Differential gene expression was assessed, and prognostic TMIELs and TMIEGs were identified through regression analyses. Prognostic signatures were evaluated via Kaplan‒Meier curves, receiver operating characteristic (ROC) analysis, and Cox regression, while immune cell composition was analysed via CIBERSORT. Results: Three prognostic TMIELs (AC090559.1, LINC01549, SENCR) and three TMIEGs (DOK2, RHBDL2, NPW) were identified. High-risk patients have poorer survival outcomes, with immune processes possibly reducing the risk of osteosarcoma. Prognostic signatures effectively predict overall survival. Conclusion: TMIEGs and TMIELs can reliably predict survival in patients with osteosarcoma, suggesting their potential as therapeutic biomarkers and the need for further research.

Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0326876

DOI: 10.1371/journal.pone.0326876

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