Identification and drug sensitivity analysis of key molecular markers in mesenchymal cell-derived osteosarcoma

doi:10.12307/2025.009

Abstract

Abstract: BACKGROUND: Osteosarcoma has a complex pathogenesis and a poor prognosis. While advancements in medical technology have led to some improvements in the 5-year survival rate, substantial progress in its treatment has not yet been achieved.
OBJECTIVE: To screen key molecular markers in osteosarcoma, analyze their relationship with osteosarcoma treatment drugs, and explore the potential disease mechanisms of osteosarcoma at the molecular level.
METHODS: GSE99671 and GSE284259 (miRNA) datasets were obtained from the Gene Expression Omnibus database. Differential gene expression analysis and Weighted Gene Co-expression Network Analysis (WGCNA) on GSE99671 were performed. Functional enrichment analysis was conducted using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes separately for the differentially expressed genes and the module genes with the highest positive correlation to the disease. The intersection of these module genes and differentially expressed genes was taken as key genes. A Protein-Protein Interaction network was constructed, and correlation analysis on the key genes was performed using CytoScape software, and hub genes were identified. Hub genes were externally validated using the GSE28425 dataset and text validation was conducted. The drug sensitivity of hub genes was analyzed using the CellMiner database, with a threshold of absolute value of correlation coefficient |R| > 0.3 and P < 0.05.
RESULTS AND CONCLUSION: (1) Differential gene expression analysis identified 529 differentially expressed genes, comprising 177 upregulated and 352 downregulated genes. WGCNA analysis yielded a total of 592 genes with the highest correlation to osteosarcoma. (2) Gene Ontology enrichment results indicated that the development of osteosarcoma may be associated with extracellular matrix, bone cell differentiation and development, human immune regulation, and collagen synthesis and degradation. Kyoto Encyclopedia of Genes and Genomes enrichment results showed the involvement of pathways such as PI3K-Akt signaling pathway, focal adhesion signaling pathway, and immune response in the onset of osteosarcoma. (3) The intersection analysis revealed a total of 59 key genes. Through Protein-Protein Interaction network analysis, 8 hub genes were selected, which were LUM, PLOD1, PLOD2, MMP14, COL11A1, THBS2, LEPRE1, and TGFB1, all of which were upregulated. (4) External validation revealed significantly downregulated miRNAs that regulate the hub genes, with hsa-miR-144-3p and hsa-miR-150-5p showing the most significant downregulation. Text validation results demonstrated that the expression of hub genes was consistent with previous research. (5) Drug sensitivity analysis indicated a negative correlation between the activity of methotrexate, 6-mercaptopurine, and pazopanib with the mRNA expression of PLOD1, PLOD2, and MMP14. Moreover, zoledronic acid and lapatinib showed a positive correlation with the mRNA expression of PLOD1, LUM, MMP14, PLOD2, and TGFB1. This suggests that zoledronic acid and lapatinib may be potential therapeutic drugs for osteosarcoma, but further validation is required through additional basic experiments and clinical studies.

Key words: osteosarcoma, molecular marker, signaling pathway, drug prediction, WGCNA, drug sensitivity, bioinformatics

CLC Number:

Zhang Haojun, Li Hongyi, Zhang Hui, Chen Haoran, Zhang Lizhong, Geng Jie, Hou Chuandong, Yu Qi, He Peifeng, Jia Jinpeng, Lu Xuechun. Identification and drug sensitivity analysis of key molecular markers in mesenchymal cell-derived osteosarcoma[J]. Chinese Journal of Tissue Engineering Research, 2025, 29(7): 1448-1456.

Figures/Tables 6

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