Earticle

초록

영어

Background: Sarcomas are rare mesenchymal malignancies originating from connective tissues and are generally associated with poor prognosis. Previous bioinformatics studies have often relied on a single database, limiting generalizability. This study aimed to identify novel hub genes associated with sarcoma using integrative analysis of GEO (Gene Expression Omnibus) and TCGA (The Cancer Genome Atlas) datasets. Methods: Differential gene expression (DEG) analysis was performed using integrated data from TCGA and GEO. Functional enrichment analyses and protein–protein interaction (PPI) network construction were conducted, and hub genes were identified based on node connectivity. Survival analysis was performed using the Kaplan–Meier method. Results: After identifying 47 overlapping DEGs from the analysis of 261 TCGA samples and 149 GEO samples, the GO (Gene Ontology) enrichment analysis revealed associations with cell adhesion, plasma membrane components, and calcium ion binding. Moreover, the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analysis showed that target genes were mainly involved in the chemical carcinogenesis-receptor activation. Then, 29 genes were screened through the PPI network. With calculating protein nodes, eight genes (BCL2, EMCN, CLDN5, LYVE1, CD36, CD93, VWF, and CDH5) were screened from TCGA and GEO datasets. Comparing survival analysis outcomes among these eight genes, highly expressed CD36 (HR=0.627, log-rank p value=0.0202) was identified as being associated with improved survival outcomes in sarcoma patients. Conclusions: CD36 may serve as a candidate prognostic biomarker or survival-associated hub gene in patients with sarcoma. However, further validation is required to clarify its clinical relevance.

목차

ABSTRACT
Materials and Methods
Preparation and analysis of datasets
Differential expression analysis
Functional enrichment analysis of DEGs correlated with GO and KEGG
Analysis of the PPI network and identification of genes
Survival analysis of the selected hub genes of sarcoma
Results
Analysis of GEO and TCGA datasets
Screening of DEGs
GO and KEGG functional enrichment analysis
PPI network and gene selection
Validation of the hub genes and overall survival analysis
Discussion
Conclusion
Conflict of Interest
References

키워드

저자

• Yunjeong Kim [ Center for Advanced Clinical Education, Inje University, Gimhae 50843, Republic of Korea ]
• Jongwon Han [ College of Pharmacy, Inje University/Inje Institute of Pharmaceutical Sciences and Research, Inje University, Gimhae 50843, Republic of Korea ]
• Heeyoung Lee [ Center for Advanced Clinical Education, Inje University/College of Pharmacy, Inje University/Inje Institute of Pharmaceutical Sciences and Research, Inje University, Gimhae 50843, Republic of Korea ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  한국임상약학회지 [Korean Journal of Clinical Pharmacy]

• 간기

  계간

• pISSN

  1226-6051

• 수록기간

  1991~2026

• 등재여부

  KCI 등재

• 십진분류

  KDC 518 DDC 615