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Updated: Dec 7, 2025
Three-Dimensional Bone Extracellular Matrix Model for Osteosarcoma
Published on: April 12, 2019
Identification of Potential Therapeutic Targets and Immune Cell Infiltration Characteristics in Osteosarcoma Using
Jianfang Niu1,2, Taiqiang Yan1,2, Wei Guo1,2
1Musculoskeletal Tumor Center, Peking University People's Hospital, Peking University, Beijing, China.
Abstract:
Osteosarcoma is one of the most aggressive malignant bone tumors worldwide. Although great advancements have been made in its treatment owing to the advent of neoadjuvant chemotherapy, the problem of lung metastasis is a major obstacle in the improvement of survival outcomes. Thus, the aim of the present study is to screen novel and key biomarkers, which may act as potential prognostic markers and therapeutic targets in osteosarcoma. We utilized the robust rank aggregation (RRA) method to integrate three osteosarcoma microarray datasets downloaded from the Gene Expression Omnibus (GEO) database, and we identified the robust differentially expressed genes (DEGs) between primary and metastatic osteosarcoma tissues. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to explore the functions of robust DEGs. The results of enrichment analysis showed that the robust DEGs were closely associated with osteosarcoma development and progression. Immune cell infiltration analysis was also conducted by CIBERSORT algorithm, and we found that macrophages are the most principal infiltrating immune cells in osteosarcoma, especially macrophages M0 and M2. Then, the protein-protein interaction network and key modules were constructed by Cytoscape, and 10 hub genes were selected by plugin cytoHubba from the whole network. The survival analysis of hub genes was also carried out based on the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database. The integrated bioinformatics analysis was utilized to provide new insight into osteosarcoma development and metastasis and identified EGR1, CXCL10, MYC, and CXCR4 as potential biomarkers for prognosis of osteosarcoma.
Insights
This study identifies key gene biomarkers for osteosarcoma metastasis. EGR1, CXCL10, MYC, and CXCR4 show potential for improving patient prognosis and guiding new therapeutic strategies.
Area of Science:
- Oncology
- Genomics
- Bioinformatics
Background:
- Osteosarcoma is an aggressive bone cancer with poor survival due to lung metastasis.
- Neoadjuvant chemotherapy has improved outcomes, but metastasis remains a significant challenge.
Purpose of the Study:
- To identify novel biomarkers for osteosarcoma prognosis and potential therapeutic targets.
- To analyze differentially expressed genes (DEGs) between primary and metastatic osteosarcoma.
Main Methods:
- Integrated three osteosarcoma microarray datasets using robust rank aggregation (RRA).
- Performed Gene Ontology (GO) and KEGG pathway analyses for DEGs.
- Utilized CIBERSORT for immune cell infiltration analysis and Cytoscape for protein-protein interaction network construction.
- Validated hub genes using the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database.
Main Results:
- Identified robust DEGs associated with osteosarcoma development and progression.
- Macrophages (M0 and M2) were the predominant infiltrating immune cells.
- Constructed a protein-protein interaction network and identified 10 hub genes.
- EGR1, CXCL10, MYC, and CXCR4 emerged as significant prognostic biomarkers.
Conclusions:
- Integrated bioinformatics analysis provides insights into osteosarcoma metastasis.
- EGR1, CXCL10, MYC, and CXCR4 are promising biomarkers for osteosarcoma prognosis.
- These biomarkers may serve as potential therapeutic targets for osteosarcoma treatment.
