Dataset Information

Bioinformatics analysis of Ewing's sarcoma: Seeking key candidate genes and pathways.

ABSTRACT: Ewing's sarcoma (ES) is the second most common bone tumor among children and adolescents worldwide. However, the genes and signaling pathways involved in ES tumorigenesis and progression remain unclear. The present study used two gene-expression profile datasets (GSE17674 and GSE31215) to elucidate key potential candidate genes and pathways in ES. Differentially expressed genes (DEGs) were identified and a functional enrichment analysis was performed. A protein-protein interaction (PPI) network was constructed, and the most significant module in the PPI network was selected from the Search Tool for the Retrieval of Interacting Genes/Proteins database. A total of 278 genes were identified by comparing the tumor samples with non-cancerous samples; these included 272 upregulated and 6 downregulated genes. The pathway analysis demonstrated significant enrichment in the positive regulation of transcription in the DEGs coding for RNA polymerase II promoter, plasma membrane and chromatin binding pathways in cancer in general. There were 269 nodes and 292 edges in the PPI network. Finally, MYC, IGF1, OAS1, EZH2 and ISG15 were identified as the hub genes according to the degree levels. The survival analysis revealed that EZH2 is associated with a poor prognosis in patients with ES. In conclusion, the DEGs, associated pathways and hub genes identified in the present study help elucidate the underlying molecular mechanisms of ES carcinogenesis and progression, and provide potential molecular targets and biomarkers for ES.

SUBMITTER: Zhang J

PROVIDER: S-EPMC6865160 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Bioinformatics analysis of Ewing's sarcoma: Seeking key candidate genes and pathways.

Zhang Jinming J Zhang Yao Y Li Ze Z Wu Hongzeng H Xun Jianjun J Feng Helin H

Oncology letters 20190930 6

Ewing's sarcoma (ES) is the second most common bone tumor among children and adolescents worldwide. However, the genes and signaling pathways involved in ES tumorigenesis and progression remain unclear. The present study used two gene-expression profile datasets (GSE17674 and GSE31215) to elucidate key potential candidate genes and pathways in ES. Differentially expressed genes (DEGs) were identified and a functional enrichment analysis was performed. A protein-protein interaction (PPI) network ...[more]

PMID: 31788075

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Project description:Breast cancer (BC) is the leading malignancy in women worldwide, yet relatively little is known about the genes and signaling pathways involved in BC tumorigenesis and progression. The present study aimed to elucidate potential key candidate genes and pathways in BC. Five gene expression profile data sets (GSE22035, GSE3744, GSE5764, GSE21422 and GSE26910) were downloaded from the Gene Expression Omnibus (GEO) database, which included data from 113 tumorous and 38 adjacent non?tumorous tissue samples. Differentially expressed genes (DEGs) were identified using t?tests in the limma R package. These DEGs were subsequently investigated by pathway enrichment analysis and a protein?protein interaction (PPI) network was constructed. The most significant module from the PPI network was selected for pathway enrichment analysis. In total, 227 DEGs were identified, of which 82 were upregulated and 145 were downregulated. Pathway enrichment analysis results revealed that the upregulated DEGs were mainly enriched in 'cell division', the 'proteinaceous extracellular matrix (ECM)', 'ECM structural constituents' and 'ECM?receptor interaction', whereas downregulated genes were mainly enriched in 'response to drugs', 'extracellular space', 'transcriptional activator activity' and the 'peroxisome proliferator?activated receptor signaling pathway'. The PPI network contained 174 nodes and 1,257 edges. DNA topoisomerase 2?a, baculoviral inhibitor of apoptosis repeat?containing protein 5, cyclin?dependent kinase 1, G2/mitotic?specific cyclin?B1 and kinetochore protein NDC80 homolog were identified as the top 5 hub genes. Furthermore, the genes in the most significant module were predominantly involved in 'mitotic nuclear division', 'mid?body', 'protein binding' and 'cell cycle'. In conclusion, the DEGs, relative pathways and hub genes identified in the present study may aid in understanding of the molecular mechanisms underlying BC progression and provide potential molecular targets and biomarkers for BC.

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Dataset Information

Bioinformatics analysis of Ewing's sarcoma: Seeking key candidate genes and pathways.

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Bioinformatics analysis of Ewing's sarcoma: Seeking key candidate genes and pathways.

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