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BMC Cancer

, 10:599

Genetics, genomics and epigenetics

Abstract

BackgroundThe genetic control of prostate cancer development is poorly understood. Large numbers of gene-expression datasets on different aspects of prostate tumorigenesis are available. We used these data to identify and prioritize candidate genes associated with the development of prostate cancer and bone metastases. Our working hypothesis was that combining meta-analyses on different but overlapping steps of prostate tumorigenesis will improve identification of genes associated with prostate cancer development.

MethodsA Z score-based meta-analysis of gene-expression data was used to identify candidate genes associated with prostate cancer development. To put together different datasets, we conducted a meta-analysis on 3 levels that follow the natural history of prostate cancer development. For experimental verification of candidates, we used in silico validation as well as in-house gene-expression data.

ResultsGenes with experimental evidence of an association with prostate cancer development were overrepresented among our top candidates. The meta-analysis also identified a considerable number of novel candidate genes with no published evidence of a role in prostate cancer development. Functional annotation identified cytoskeleton, cell adhesion, extracellular matrix, and cell motility as the top functions associated with prostate cancer development. We identified 10 genes-CDC2, CCNA2, IGF1, EGR1, SRF, CTGF, CCL2, CAV1, SMAD4, and AURKA-that form hubs of the interaction network and therefore are likely to be primary drivers of prostate cancer development.

ConclusionsBy using this large 3-level meta-analysis of the gene-expression data to identify candidate genes associated with prostate cancer development, we have generated a list of candidate genes that may be a useful resource for researchers studying the molecular mechanisms underlying prostate cancer development.

Abbreviations and acronymsGEOGene Expression Omnibus database

GOGene Ontology database

TGF-βtransforming growth factor beta

CAPCclinically advanced prostate cancer

BPHbenign prostatic hypertrophy

Electronic supplementary materialThe online version of this article doi:10.1186-1471-2407-10-599 contains supplementary material, which is available to authorized users.

Kanishka Sircar, Hongya Zhao contributed equally to this work.

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Autor: Ivan P Gorlov - Kanishka Sircar - Hongya Zhao - Sankar N Maity - Nora M Navone - Olga Y Gorlova - Patricia Troncoso - C

Fuente: https://link.springer.com/







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