Comparative Bioinformatics Analysis of Ewing’s Sarcoma and Femoral Head Necrosis

Objective: To screen and analyze the differentially expressed genes (DEGs) in Ewing’s sarcoma (ES) and osteonecrosis of the femoral head (ONFH) using bioinformatics. Methods: Using the GEO gene chip public database in NCBI for data retrieval, select chip data GSE17674 and GSE74089 as analysis objects. Using the R language limma toolkit to screen for DEmRNAs, and standardizing the data, a Venn diagram was used to screen for common differentially expressed genes between the two; Perform GO functional and KEGG pathway enrichment analysis on common differentially expressed genes using the R language clusterProfiler package. Select String database for PPI analysis, import the results into Cytoscape software to obtain PPI mapping, core modules, and Hub genes. Download the known genes of ES and ONFH from the OMIM database, intersect them with the core module genes screened by MOCDE, and obtain the COL11A1 gene; Intersect the genes downloaded from the OMIM database with the screened differentially expressed genes to obtain four genes: COL11A1, KIT, KRAS, and MSH2. Then intersect the genes obtained from both to obtain the COL11A1 gene. Conclusion: The differentially expressed genes and related signaling pathways identified can help understand the molecular mechanisms underlying the pathogenesis of ES and ONFH, providing a basis for early diagnosis of ES combined with ONFH; The drug prediction results can provide second-line drugs for the clinical treatment of ES combined with ONFH, and provide new ideas for clinical drug treatment research.

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Publication Details

Journal
Journal of Biosciences and Medicines
Published
2025-01-01
DOI
https://doi.org/10.4236/jbm.2025.137007
Primary Topic
Bone and Joint Diseases
Type
article
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article

Comparative Bioinformatics Analysis of Ewing’s Sarcoma and Femoral Head Necrosis

Pengyuan He, Wen Huang, Jianbin Xu, Yongfu Chen et al.
Journal of Biosciences and Medicines
Bone and Joint Diseases
article

Comparative Bioinformatics Analysis of Ewing’s Sarcoma and Femoral Head Necrosis

Pengyuan He, Wen Huang, Jianbin Xu, Yongfu Chen, Huan Zhang, Fang Liao, Jialong Huang, Yanlin He, Junxiu Zhou, Mingxuan Liu
article en

Abstract

Objective: To screen and analyze the differentially expressed genes (DEGs) in Ewing’s sarcoma (ES) and osteonecrosis of the femoral head (ONFH) using bioinformatics. Methods: Using the GEO gene chip public database in NCBI for data retrieval, select chip data GSE17674 and GSE74089 as analysis objects. Using the R language limma toolkit to screen for DEmRNAs, and standardizing the data, a Venn diagram was used to screen for common differentially expressed genes between the two; Perform GO functional and KEGG pathway enrichment analysis on common differentially expressed genes using the R language clusterProfiler package. Select String database for PPI analysis, import the results into Cytoscape software to obtain PPI mapping, core modules, and Hub genes. Download the known genes of ES and ONFH from the OMIM database, intersect them with the core module genes screened by MOCDE, and obtain the COL11A1 gene; Intersect the genes downloaded from the OMIM database with the screened differentially expressed genes to obtain four genes: COL11A1, KIT, KRAS, and MSH2. Then intersect the genes obtained from both to obtain the COL11A1 gene. Conclusion: The differentially expressed genes and related signaling pathways identified can help understand the molecular mechanisms underlying the pathogenesis of ES and ONFH, providing a basis for early diagnosis of ES combined with ONFH; The drug prediction results can provide second-line drugs for the clinical treatment of ES combined with ONFH, and provide new ideas for clinical drug treatment research.

Journal of Biosciences and MedicinesVol. 13(07)
Zero hunger
Openalex Percentile: Top 78%
Bone and Joint Diseases
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Comparative Bioinformatics Analysis of Ewing’s Sarcoma and Femoral Head Necrosis — Pengyuan He, Wen Huang, et al. · Journal of Biosciences and Medicines (2025) | TGRS Research Map | TGRS