Identifying novel prostate cancer associated pathways based on integrative microarray data analysis
Wang Y.5; Chen J.5; Li Q.5; Wang H.6; Liu G.5; Jing Q.6; Shen B.5
Source PublicationComputational Biology and Chemistry
AbstractThe development and diverse application of microarray and next generation sequencing technologies has made the meta-analysis widely used in expression data analysis. Although it is commonly accepted that pathway, network and systemic level approaches are more reproducible than reductionism analyses, the meta-analysis of prostate cancer associated molecular signatures at the pathway level remains unexplored. In this article, we performed a meta-analysis of 10 prostate cancer microarray expression datasets to identify the common signatures at both the gene and pathway levels. As the enrichment analysis result of GeneGo's database and KEGG database, 97.8% and 66.7% of the signatures show higher similarity at pathway level than that at gene level, respectively. Analysis by using gene set enrichment analysis (GSEA) method also supported the hypothesis. Further analysis of PubMed citations verified that 207 out of 490 (42%) pathways from GeneGo and 48 out of 74 (65%) pathways from KEGG were related to prostate cancer. An overlap of 15 enriched pathways was observed in at least eight datasets. Eight of these pathways were first described as being associated with prostate cancer. In particular, endothelin-1/EDNRA transactivation of the EGFR pathway was found to be overlapped in nine datasets. The putative novel prostate cancer related pathways identified in this paper were indirectly supported by PubMed citations and would provide essential information for further development of network biomarkers and individualized therapy strategy for prostate cancer. © 2011 Elsevier Ltd.
KeywordGene set enrichment analysis GeneGo database KEGG database Meta-analysis Pathway enrichment analysis
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Cited Times [WOS]:32   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionUniversity of Macau
Affiliation1.University of Science and Technology of Suzhou
2.Shanghai Institute for Biological Sciences Chinese Academy of Sciences
3.University of Queensland
4.Second Military Medical University
5.Soochow University
6.Tongji University
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GB/T 7714
Wang Y.,Chen J.,Li Q.,et al. Identifying novel prostate cancer associated pathways based on integrative microarray data analysis[J]. Computational Biology and Chemistry,2011,35(3):151-158.
APA Wang Y..,Chen J..,Li Q..,Wang H..,Liu G..,...&Shen B..(2011).Identifying novel prostate cancer associated pathways based on integrative microarray data analysis.Computational Biology and Chemistry,35(3),151-158.
MLA Wang Y.,et al."Identifying novel prostate cancer associated pathways based on integrative microarray data analysis".Computational Biology and Chemistry 35.3(2011):151-158.
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