Identification of microtubule-associated biomarker using machine learning methods in osteonecrosis of the femoral head and osteosarcoma

Background: This study aims to explore the microtubule-associated gene signatures and molecular processes shared by osteonecrosis of the femoral head (ONFH) and osteosarcoma (OS). Methods: 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. Results: 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. Conclusion: 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.