Gao Ziwei, Chen Siqi, Ye Wei
Hangzhou TCM Hospital of Zhejiang Chinese Medical University (Hangzhou Hospital of Traditional Chinese Medicine), Hangzhou, Zhejiang, China.
Department of Gastroenterology, Hangzhou TCM Hospital of Zhejiang Chinese Medical University (Hangzhou Hospital of Traditional Chinese Medicine), Hangzhou, Zhejiang, China.
Sci Rep. 2025 Jan 2;15(1):221. doi: 10.1038/s41598-024-84024-9.
Osteosarcoma is one of the most common malignant bone tumours in children. In this study, we aimed to construct a cuproptosis-related lncRNAs signature to predict the prognosis and immune landscape of osteosarcoma patients. Databases from TARGET were used to acquire osteosarcoma patient datasets, which included clinical information and RNA sequencing data. Cuproptosis-related lncRNAs was obtained by correlation analysis. Through univariate Cox regression analysis, prognosis-related lncRNAs were obtained. We used nonnegative matrix factorization clustering to identify potential molecular subgroups with different cuproptosis-related lncRNA expression patterns. The least absolute shrinkage and selection operator algorithm and multivariate Cox regression analysis were used to construct the prognostic signature. The ESTIMATE algorithm, Gene Ontology and Kyoto Encyclopaedia of Genes and Genomes were applied to explore the underlying mechanisms in the immune landscape of osteosarcoma. We used gene set enrichment analysis to compare the different enrichments in the high-risk group and the low-risk group. Furthermore, we predicted the response to targeted drugs in patients with different risk groups. Using multivariable analysis, we developed a risk scoring model based on 7 long noncoding RNAs and calculated two molecular subgroups from osteosarcoma patients from the database. There is a better immune microenvironment in the low-risk group compared to the high-risk group. At the same time, the gene functional enrichment analysis based on the differently expressed genes obtained by grouping showed they were mainly related to immunity, indicating that cuproptosis-related lncRNAs may affect the prognosis of osteosarcoma by regulating immunity. Moreover, these patients in high-risk group were more susceptible to targeted drugs than the low-risk group. We identified a cuproptosis-related lncRNA prognostic signature for osteosarcoma and showed a close connection in terms of immunity. Moreover, we provided some potential targeted drugs for the treatment of osteosarcoma.
骨肉瘤是儿童最常见的恶性骨肿瘤之一。在本研究中,我们旨在构建一种与铜死亡相关的长链非编码RNA特征,以预测骨肉瘤患者的预后和免疫格局。使用来自TARGET的数据库获取骨肉瘤患者数据集,其中包括临床信息和RNA测序数据。通过相关性分析获得与铜死亡相关的长链非编码RNA。通过单因素Cox回归分析,获得与预后相关的长链非编码RNA。我们使用非负矩阵分解聚类来识别具有不同铜死亡相关长链非编码RNA表达模式的潜在分子亚组。使用最小绝对收缩和选择算子算法以及多因素Cox回归分析来构建预后特征。应用ESTIMATE算法、基因本体论和京都基因与基因组百科全书来探索骨肉瘤免疫格局的潜在机制。我们使用基因集富集分析来比较高风险组和低风险组的不同富集情况。此外,我们预测了不同风险组患者对靶向药物的反应。通过多变量分析,我们基于7个长链非编码RNA开发了一个风险评分模型,并从数据库中的骨肉瘤患者中计算出两个分子亚组。与高风险组相比,低风险组有更好的免疫微环境。同时,基于分组获得的差异表达基因进行的基因功能富集分析表明,它们主要与免疫相关,这表明与铜死亡相关的长链非编码RNA可能通过调节免疫来影响骨肉瘤的预后。此外,高风险组的这些患者比低风险组更容易对靶向药物敏感。我们确定了一种骨肉瘤的与铜死亡相关长链非编码RNA预后特征,并显示出在免疫方面的密切联系。此外,我们为骨肉瘤的治疗提供了一些潜在的靶向药物。