Lu Ying, Zhou Li, Yang Zhanyu
Department of Orthopaedics, Hunan Provincial People's Hospital (the First Affiliated Hospital of Hunan Normal University), Changsha, Hunan, China.
Hunan Emergency Center, Changsha, Hunan, China.
PLoS One. 2025 Jul 16;20(7):e0326876. doi: 10.1371/journal.pone.0326876. eCollection 2025.
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.
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.
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.
TMIEGs and TMIELs can reliably predict survival in patients with osteosarcoma, suggesting their potential as therapeutic biomarkers and the need for further research.
骨肉瘤是一种侵袭性骨癌,预后较差,尤其是在年轻个体中。本研究旨在鉴定影响患者预后的肿瘤微环境相关基因(TMIEGs)和相关长链非编码RNA(TMIELs)。
分析来自TARGET骨肉瘤数据集和GTEx肌肉数据集的数据,以计算基质和免疫评分,将患者分为高分和低分两组。评估差异基因表达,并通过回归分析鉴定预后性TMIELs和TMIEGs。通过Kaplan-Meier曲线、受试者工作特征(ROC)分析和Cox回归评估预后特征,同时通过CIBERSORT分析免疫细胞组成。
鉴定出三个预后性TMIELs(AC090559.1、LINC01549、SENCR)和三个TMIEGs(DOK2、RHBDL2、NPW)。高危患者的生存结果较差,免疫过程可能会降低骨肉瘤风险。预后特征可有效预测总生存期。
TMIEGs和TMIELs能够可靠地预测骨肉瘤患者的生存情况,表明它们作为治疗生物标志物的潜力以及进一步研究的必要性。