DDPC: Dragon Database of Genes associated with Prostate Cancer

Maqungo, Monique; Kaur, Mandeep; Kwofie, Samuel K.; Radovanović, Aleksandar; Schaefer, Ulf; Schmeier, Sebastian; Oppon, Ekow; Christoffels, Alan; Bajic, Vladimir B.

doi:10.1093/nar/gkq849

Cited by 40 publications

(26 citation statements)

References 33 publications

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“…DDPC serves as a comprehensive repository that integrates data about prostate cancer from other biological research areas including molecular interactions, pathways, gene ontologies, and gene regulation at the molecular level (Maqungo et al, 2011). All the genes implicated in prostate cancer by DDPC were downloaded.…”

Section: Genes Implicated In Ddpcmentioning

confidence: 99%

HNF1b is involved in prostate cancer risk via modulating androgenic hormone effects and coordination with other genes

Zhong²,

Pang³

et al. 2013

Genet. Mol. Res.

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Section: Genes Implicated In Ddpcmentioning

confidence: 99%

HNF1b is involved in prostate cancer risk via modulating androgenic hormone effects and coordination with other genes

Zhong²,

Pang³

et al. 2013

Genet. Mol. Res.

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“…Variants categorized as pathogenic by at least one tolerance predictor were defined as pathogenic. In addition, minor allele frequencies (MAF) were obtained from the dbSNP database and information on known PrCa-associated genes was retrieved from the COSMIC 16 and DDPC 17 databases. Pathway data were gathered from Pathway Commons, 18 KEGG 19 and WikiPathways 20 and Gene Ontology data were retrieved from Ensembl BioMart v.65.…”

Section: Methodsmentioning

confidence: 99%

Fine‐mapping the 2q37 and 17q11.2‐q22 loci for novel genes and sequence variants associated with a genetic predisposition to prostate cancer

Laitinen

Rantapero

Fischer

et al. 2014

Intl Journal of Cancer

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The 2q37 and 17q12-q22 loci are linked to an increased prostate cancer (PrCa) risk. No candidate gene has been localized at 2q37 and the HOXB13 variant G84E only partially explains the linkage to 17q21-q22 observed in Finland. We screened these regions by targeted DNA sequencing to search for cancer-associated variants. Altogether, four novel susceptibility alleles were identified. Two ZNF652 (17q21.3) variants, rs116890317 and rs79670217, increased the risk of both sporadic and hereditary PrCa (rs116890317: OR = 3.3 – 7.8, P = 0.003 – 3.3 × 10−5; rs79670217: OR = 1.6 – 1.9, P = 0.002 – 0.009). The HDAC4 (2q37.2) variant rs73000144 (OR = 14.6, P = 0.018) and the EFCAB13 (17q21.3) variant rs118004742 (OR = 1.8, P = 0.048) were overrepresented in patients with familial PrCa. To map the variants within 2q37 and 17q11.2-q22 that may regulate PrCa-associated genes, we combined DNA sequencing results with transcriptome data obtained by RNA sequencing. This expression quantitative trait locus (eQTL) analysis identified 272 SNPs possibly regulating six genes that were differentially expressed between cases and controls. In a modified approach, pre-filtered PrCa-associated SNPs were exploited and interestingly, a novel eQTL targeting ZNF652 was identified. The novel variants identified in this study could be utilized for PrCa risk assessment, and they further validate the suggested role of ZNF652 as a PrCa candidate gene. The regulatory regions discovered by eQTL mapping increase our understanding of the relationship between regulation of gene expression and susceptibility to PrCa and provide a valuable starting point for future functional research.

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“…It also provides absorption, distribution, metabolism, excretion and toxicity (ADMET) properties of compounds that are important for new drug development. This drugrelated information will help researchers and clinicians in the discovery of targets for new drugs, computational designing of drugs, in silico docking of drugs, and identification of ADMET properties of concordants of these drugs molecules 21 . Scientists are exploring new anticancer compounds from plants to reduce undesirable side effects associated with chemotherapy drugs.…”

Section: Analysis and Significance Of Gicdbmentioning

confidence: 99%