Yang Sha, Zhao Ying, Tan Ying, Zheng Chao
Guizhou University Medical College, Guiyang, 550025, Guizhou Province, PR China.
Department of Orthopedics, GuiQian International General Hospital, GuiYang, PR China.
Heliyon. 2024 May 23;10(11):e31853. doi: 10.1016/j.heliyon.2024.e31853. eCollection 2024 Jun 15.
This study aims to explore the microtubule-associated gene signatures and molecular processes shared by osteonecrosis of the femoral head (ONFH) and osteosarcoma (OS).
Datasets from the TARGET and GEO databases were subjected to bioinformatics analysis, including the functional enrichment analysis of genes shared by ONFH and OS. Prognostic genes were identified using univariate and multivariate Cox regression analyses to develop a risk score model for predicting overall survival and immune characteristics. Furthermore, LASSO and SVM-RFE algorithms identified biomarkers for ONFH, which were validated in OS. Function prediction, ceRNA network analysis, and gene-drug interaction network construction were subsequently conducted. Biomarker expression was then validated on clinical samples by using qPCR.
A total of 14 microtubule-associated disease genes were detected in ONFH and OS. Subsequently, risk score model based on four genes was then created, revealing that patients with low-risk exhibited superior survival outcomes compared with those with high-risk. Notably, ONFH with low-risk profiles may manifest an antitumor immune microenvironment. Moreover, by utilizing LASSO and SVM-RFE algorithms, four diagnostic biomarkers were pinpointed, enabling effective discrimination between patients with ONFH and healthy individuals as well as between OS and normal tissues. Additionally, 21 drugs targeting these biomarkers were predicted, and a comprehensive ceRNA network comprising four mRNAs, 71 miRNAs, and 98 lncRNAs was established. The validation of biomarker expression in clinical samples through qPCR affirmed consistency with the results of bioinformatics analysis.
Microtubule-associated genes may play pivotal roles in OS and ONFH. Additionally, a prognostic model was constructed, and four genes were identified as potential biomarkers and therapeutic targets for both diseases.
本研究旨在探索股骨头坏死（ONFH）和骨肉瘤（OS）共有的微管相关基因特征及分子过程。
对来自TARGET和GEO数据库的数据集进行生物信息学分析，包括对ONFH和OS共有的基因进行功能富集分析。使用单变量和多变量Cox回归分析鉴定预后基因，以建立预测总生存期和免疫特征的风险评分模型。此外，LASSO和SVM-RFE算法鉴定出ONFH的生物标志物，并在OS中进行验证。随后进行功能预测、ceRNA网络分析和基因-药物相互作用网络构建。然后通过qPCR在临床样本上验证生物标志物的表达。
在ONFH和OS中总共检测到14个微管相关疾病基因。随后，基于四个基因创建了风险评分模型，结果显示低风险患者的生存结果优于高风险患者。值得注意的是，低风险的ONFH可能表现出抗肿瘤免疫微环境。此外，通过使用LASSO和SVM-RFE算法，确定了四个诊断生物标志物，能够有效区分ONFH患者与健康个体以及OS与正常组织。此外，预测了21种靶向这些生物标志物的药物，并建立了一个包含四个mRNA、71个miRNA和98个lncRNA的综合ceRNA网络。通过qPCR对临床样本中生物标志物表达的验证证实了与生物信息学分析结果的一致性。
微管相关基因可能在OS和ONFH中起关键作用。此外，构建了一个预后模型，并确定了四个基因作为这两种疾病的潜在生物标志物和治疗靶点。
