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BMC Medical Genetics

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Open Access 01-12-2014 | Research article

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

Authors: Zuozhang Yang, Yongbin Chen, Yu Fu, Yihao Yang, Ya Zhang, Yanjin Chen, Dongqi Li

Published in: BMC Medical Genetics | Issue 1/2014

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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The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2350/15/80/prepub

Title: Meta-analysis of differentially expressed genes in osteosarcoma based on gene expression data
Authors: Zuozhang Yang
Yongbin Chen
Yu Fu
Yihao Yang
Ya Zhang
Yanjin Chen
Dongqi Li
Publication date: 01-12-2014
Publisher: BioMed Central
Published in: BMC Medical Genetics / Issue 1/2014
Electronic ISSN: 1471-2350
DOI: https://doi.org/10.1186/1471-2350-15-80

Keynote webinar | Spotlight on medication adherence

Springer Medicine

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

Abstract

Background

Methods

Results

Conclusions

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Background

Methods

Results

Conclusions

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