Comput Biol Chem - Identifying novel prostate cancer associated pathways based on integrative microarray data analysis.

Tópicos

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Resumo

The 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.

Resumo Limpo

develop divers applic microarray next generat sequenc technolog made metaanalysi wide use express data analysi although common accept pathway network system level approach reproduc reduction analys metaanalysi prostat cancer associ molecular signatur pathway level remain unexplor articl perform metaanalysi prostat cancer microarray express dataset identifi common signatur gene pathway level enrich analysi result genego databas kegg databas signatur show higher similar pathway level gene level respect analysi use gene set enrich analysi gsea method also support hypothesi analysi pubm citat verifi pathway genego pathway kegg relat prostat cancer overlap enrich pathway observ least eight dataset eight pathway first describ associ prostat cancer particular endothelinednra transactiv egfr pathway found overlap nine dataset putat novel prostat cancer relat pathway identifi paper indirect support pubm citat provid essenti inform develop network biomark individu therapi strategi prostat cancer

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