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Meta-analysis of differentially expressed genes in osteosarcoma based on gene expression data.

Yang Z, Chen Y, Fu Y, Yang Y, Zhang Y, Chen Y, Li D - BMC Med. Genet. (2014)

Bottom Line: Furthermore, ECM-receptor interaction (P = 1.27E-13) and Cell cycle (P = 4.53E-11) are found to be highly enriched.PPI network analysis indicated that the significant hub proteins containing PTBP2 (Degree = 33), RGS4 (Degree = 15) and FXYD6 (Degree = 13).Our meta-analysis detected DEGs and biological functions associated with gene expression changes between OS and NC tissues, guiding further identification and treatment for OS.

View Article: PubMed Central - HTML - PubMed

Affiliation: Bone and Soft Tissue Tumors Research Center of Yunnan Province, Department of Orthopaedics, The Third Affiliated Hospital of Kunming Medical University (Tumor Hospital of Yunnan Province), Kunming, Yunnan 650118, PR China. yangzuozhangpre@163.com.

ABSTRACT

Background: To uncover the genes involved in the development of osteosarcoma (OS), we performed a meta-analysis of OS microarray data to identify differentially expressed genes (DEGs) and biological functions associated with gene expression changes between OS and normal control (NC) tissues.

Methods: We used publicly available GEO datasets of OS to perform a meta-analysis. We performed Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and Protein-Protein interaction (PPI) networks analysis.

Results: Eight GEO datasets, including 240 samples of OS and 35 samples of controls, were available for the meta-analysis. We identified 979 DEGs across the studies between OS and NC tissues (472 up-regulated and 507 down-regulated). We found GO terms for molecular functions significantly enriched in protein binding (GO: 0005515, P = 3.83E-60) and calcium ion binding (GO: 0005509, P = 3.79E-13), while for biological processes, the enriched GO terms were cell adhesion (GO:0007155, P = 2.26E-19) and negative regulation of apoptotic process (GO: 0043066, P = 3.24E-15), and for cellular component, the enriched GO terms were cytoplasm (GO: 0005737, P = 9.18E-63) and extracellular region (GO: 0005576, P = 2.28E-47). The most significant pathway in our KEGG analysis was Focal adhesion (P = 5.70E-15). Furthermore, ECM-receptor interaction (P = 1.27E-13) and Cell cycle (P = 4.53E-11) are found to be highly enriched. PPI network analysis indicated that the significant hub proteins containing PTBP2 (Degree = 33), RGS4 (Degree = 15) and FXYD6 (Degree = 13).

Conclusions: Our meta-analysis detected DEGs and biological functions associated with gene expression changes between OS and NC tissues, guiding further identification and treatment for OS.

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Flowchart of the selected process of microarray datasets for the meta-analysis.
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Figure 1: Flowchart of the selected process of microarray datasets for the meta-analysis.

Mentions: OS expression profiling studies were identified by searching PubMed database. The following key words and their combinations were used: “osteosarcoma, gene expression, microarray, genetics”. In addition, the Gene Expression Omnibus database (GEO, http://www.ncbi.nlm.nih.gov/geo) was also searched to ensure the relevant studies were not missed [17]. We only retained the original experimental articles that analyzed gene expression profiling between OS and normal control (NC) tissues. Non-human studies, review articles and integrated analysis of expression profiles were excluded (Figure 1). We conducted this meta-analysis in accordance with the guidelines provided in the PRISMA statement (Additional file 1: The PRISMA Checklist S1). Data were extracted from the original studies by 2 independent reviewers. Any discrepancies between reviewers were resolved by consensus or a third reviewer. The following information was extracted from each identified study: GEO accession number, sample type, platform, number of cases and controls, references, and gene expression data.


Meta-analysis of differentially expressed genes in osteosarcoma based on gene expression data.

Yang Z, Chen Y, Fu Y, Yang Y, Zhang Y, Chen Y, Li D - BMC Med. Genet. (2014)

Flowchart of the selected process of microarray datasets for the meta-analysis.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4109777&req=5

Figure 1: Flowchart of the selected process of microarray datasets for the meta-analysis.
Mentions: OS expression profiling studies were identified by searching PubMed database. The following key words and their combinations were used: “osteosarcoma, gene expression, microarray, genetics”. In addition, the Gene Expression Omnibus database (GEO, http://www.ncbi.nlm.nih.gov/geo) was also searched to ensure the relevant studies were not missed [17]. We only retained the original experimental articles that analyzed gene expression profiling between OS and normal control (NC) tissues. Non-human studies, review articles and integrated analysis of expression profiles were excluded (Figure 1). We conducted this meta-analysis in accordance with the guidelines provided in the PRISMA statement (Additional file 1: The PRISMA Checklist S1). Data were extracted from the original studies by 2 independent reviewers. Any discrepancies between reviewers were resolved by consensus or a third reviewer. The following information was extracted from each identified study: GEO accession number, sample type, platform, number of cases and controls, references, and gene expression data.

Bottom Line: Furthermore, ECM-receptor interaction (P = 1.27E-13) and Cell cycle (P = 4.53E-11) are found to be highly enriched.PPI network analysis indicated that the significant hub proteins containing PTBP2 (Degree = 33), RGS4 (Degree = 15) and FXYD6 (Degree = 13).Our meta-analysis detected DEGs and biological functions associated with gene expression changes between OS and NC tissues, guiding further identification and treatment for OS.

View Article: PubMed Central - HTML - PubMed

Affiliation: Bone and Soft Tissue Tumors Research Center of Yunnan Province, Department of Orthopaedics, The Third Affiliated Hospital of Kunming Medical University (Tumor Hospital of Yunnan Province), Kunming, Yunnan 650118, PR China. yangzuozhangpre@163.com.

ABSTRACT

Background: To uncover the genes involved in the development of osteosarcoma (OS), we performed a meta-analysis of OS microarray data to identify differentially expressed genes (DEGs) and biological functions associated with gene expression changes between OS and normal control (NC) tissues.

Methods: We used publicly available GEO datasets of OS to perform a meta-analysis. We performed Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and Protein-Protein interaction (PPI) networks analysis.

Results: Eight GEO datasets, including 240 samples of OS and 35 samples of controls, were available for the meta-analysis. We identified 979 DEGs across the studies between OS and NC tissues (472 up-regulated and 507 down-regulated). We found GO terms for molecular functions significantly enriched in protein binding (GO: 0005515, P = 3.83E-60) and calcium ion binding (GO: 0005509, P = 3.79E-13), while for biological processes, the enriched GO terms were cell adhesion (GO:0007155, P = 2.26E-19) and negative regulation of apoptotic process (GO: 0043066, P = 3.24E-15), and for cellular component, the enriched GO terms were cytoplasm (GO: 0005737, P = 9.18E-63) and extracellular region (GO: 0005576, P = 2.28E-47). The most significant pathway in our KEGG analysis was Focal adhesion (P = 5.70E-15). Furthermore, ECM-receptor interaction (P = 1.27E-13) and Cell cycle (P = 4.53E-11) are found to be highly enriched. PPI network analysis indicated that the significant hub proteins containing PTBP2 (Degree = 33), RGS4 (Degree = 15) and FXYD6 (Degree = 13).

Conclusions: Our meta-analysis detected DEGs and biological functions associated with gene expression changes between OS and NC tissues, guiding further identification and treatment for OS.

Show MeSH
Related in: MedlinePlus