Dataset Information

Identification of key genes in osteosarcoma by meta?analysis of gene expression microarray.

ABSTRACT: Osteosarcoma (OS) is one of the most malignant tumors in children and young adults. To better understand the underlying mechanism, five related datasets deposited in the Gene Expression Omnibus were included in the present study. The Bioconductor 'limma' package was used to identify differentially expressed genes (DEGs) and the 'Weighted Gene Co?expression Network Analysis' package was used to construct a weighted gene co?expression network to identify key modules and hub genes, associated with OS. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes overrepresentation analyses were used for functional annotation. The results indicated that 1,405 genes were dysregulated in OS, including 927 upregulated and 478 downregulated genes, when the cut off value was set at a ?2 fold?change and an adjusted P?value of P<0.01 was used. Functional annotation of DEGs indicated that these genes were involved in the extracellular matrix (ECM) and that they function in several processes, including biological adhesion, ECM organization, cell migration and leukocyte migration. These findings suggested that dysregulation of the ECM shaped the tumor microenvironment and modulated the OS hallmark. Genes assigned to the yellow module were positively associated with OS and could contribute to the development of OS. In conclusion, the present study has identified several key genes that are potentially druggable genes or therapeutics targets in OS. Functional annotations revealed that the dysregulation of the ECM may contribute to OS development and, therefore, provided new insights to improve our understanding of the mechanisms underlying OS.

SUBMITTER: Sun J

PROVIDER: S-EPMC6755242 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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Identification of key genes in osteosarcoma by meta‑analysis of gene expression microarray.

Sun Junkui J Xu Hongen H Qi Muge M Zhang Chi C Shi Jianxiang J

Molecular medicine reports 20190731 4

Osteosarcoma (OS) is one of the most malignant tumors in children and young adults. To better understand the underlying mechanism, five related datasets deposited in the Gene Expression Omnibus were included in the present study. The Bioconductor 'limma' package was used to identify differentially expressed genes (DEGs) and the 'Weighted Gene Co‑expression Network Analysis' package was used to construct a weighted gene co‑expression network to identify key modules and hub genes, associated with ...[more]

PMID: 31432118

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Project description:Osteosarcoma (OS) is an invasive malignant neoplasm of the bones. The present study identified and analyzed key genes associated with OS. Expression profiling of the dataset GSE49003, which included 6 metastatic and 6 non-metastatic OS cell lines and was obtained from the Gene Expression Omnibus, was performed. Following data preprocessing, the differentially expressed genes (DEGs) were selected using the limma package in R. Subsequently, bidirectional hierarchical clustering using the pheatmap package in R and an unpaired Students' t-test was performed for the DEGs. Based on the Search Tool for the Retrieval of Interacting Genes database and Cytoscape software, a protein-protein interaction (PPI) network for the DEGs was constructed. Using Database for Annotation, Visualization and Integrated Discovery software and the Kyoto Encyclopedia of Genes and Genomes Orthology Based Annotation System server, functional and pathway enrichment analyses were performed for the DEGs corresponding to the proteins of the network. In addition, the transcription factors (TFs) and CpG islands of the gene promoter were searched for using the TRANSFAC database and CpG Island Searcher software, respectively. A total of 323 DEGs were identified between the metastatic and non-metastatic samples. In the PPI network, upregulated epidermal growth factor receptor (EGFR) exhibits a high degree and was therefore highly interconnected with other proteins. Enrichment analysis revealed that EGFR was enriched in cytoskeleton organization, organic substance response and the signaling pathway of focal adhesion. The TFs early growth response 1, nuclear factor-?B complex subunits, peroxisome proliferator activated receptor ?, signal transducer and activator of transcription 3 and MYC proto-oncogene were identified in the EGFR promoter region. Furthermore, multiple CpG islands, starting from the 400 bp of the EGFR promoter sequence, were predicted. Methylated modification of the CpG islands in the EGFR promoter may help to regulate EGFR expression. The TFs identified in the EGFR promoter may function in the progression of OS.

Dataset Information

Identification of key genes in osteosarcoma by meta?analysis of gene expression microarray.

Publications

Identification of key genes in osteosarcoma by meta‑analysis of gene expression microarray.

Similar Datasets

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