线粒体能量代谢途径相关特征可预测骨肉瘤的预后，并提示免疫微环境浸润。
The mitochondrial energy metabolism pathway-related signature predicts prognosis and indicates immune microenvironment infiltration in osteosarcoma.
机构信息
Department of Orthopedics, The Peace Hospital of Changzhi City, The First Clinical Hospital of Changzhi Medical University, Changzhi, Shanxi Province, China.
Department of General Medical, The People's Hospital of Changzhi City, The Third Clinical Hospital of Changzhi Medical University, Changzhi, Shanxi Province, China.
出版信息
Medicine (Baltimore). 2023 Nov 17;102(46):e36046. doi: 10.1097/MD.0000000000036046.
BACKGROUND
Abnormalities in the mitochondrial energy metabolism pathways are closely related to the occurrence and development of many cancers. Furthermore, abnormal genes in mitochondrial energy metabolism pathways may be novel targets and biomarkers for the diagnosis and treatment of osteosarcoma. In this study, we aimed to establish a mitochondrial energy metabolism-related gene signature for osteosarcoma prognosis.
METHODS
We first obtained differentially expressed genes based on the metastatic status of 84 patients with osteosarcoma from the TARGET database. After Venn analysis of differentially expressed genes and mitochondrial energy metabolism pathway-related genes (MMRGs), 2 key genes were obtained using univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analysis. Next, we used these 2 genes to establish a prognostic signature. Subsequent analyses elucidated the correlation between these 2 key genes with clinical features and 28 types of immune cells. Pathway changes in osteosarcoma pathogenesis under different metastatic states were clarified using gene set enrichment analysis (GSEA) of differentially expressed genes.
RESULTS
A gene signature composed of 2 key prognosis-related genes (KCNJ5 and PFKFB2) was identified. A risk score was calculated based on the gene signature, which divided osteosarcoma patients into low- or high-risk groups that showed good and poor prognosis, respectively. High expression of these 2 key genes is associated with low-risk group in patients with osteosarcoma. We constructed an accurate nomogram to help clinicians assess the survival time of patients with osteosarcoma. The results of immune cell infiltration level showed that the high-risk group had lower levels of immune cell infiltration. GSEA revealed changes in immune regulation and hypoxia stress pathways in osteosarcoma under different metastatic states.
CONCLUSION
Our study identified an excellent gene signature that could be helpful in improving the prognosis of patients with osteosarcoma.
背景
线粒体能量代谢途径的异常与许多癌症的发生和发展密切相关。此外，线粒体能量代谢途径中的异常基因可能是骨肉瘤诊断和治疗的新靶点和生物标志物。在这项研究中，我们旨在建立一个与骨肉瘤预后相关的线粒体能量代谢相关基因特征。
方法
我们首先从 TARGET 数据库中获得了 84 例骨肉瘤患者转移状态的差异表达基因。在差异表达基因和线粒体能量代谢途径相关基因（MMRGs）的 Venn 分析后，使用单变量 Cox 回归和最小绝对值收缩和选择算子（LASSO）回归分析获得了 2 个关键基因。接下来，我们使用这 2 个基因建立一个预后特征。随后的分析阐明了这 2 个关键基因与临床特征和 28 种免疫细胞的相关性。通过差异表达基因的基因集富集分析（GSEA）阐明了不同转移状态下骨肉瘤发病机制中的通路变化。
结果
确定了由 2 个关键预后相关基因（KCNJ5 和 PFKFB2）组成的基因特征。根据基因特征计算风险评分，将骨肉瘤患者分为低风险或高风险组，分别显示良好和较差的预后。这 2 个关键基因的高表达与骨肉瘤患者的低风险组相关。我们构建了一个准确的列线图，以帮助临床医生评估骨肉瘤患者的生存时间。免疫细胞浸润水平的结果表明，高风险组的免疫细胞浸润水平较低。GSEA 显示不同转移状态下骨肉瘤中免疫调节和缺氧应激通路的变化。
结论
我们的研究确定了一个优秀的基因特征，有助于改善骨肉瘤患者的预后。
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