ArticleBMC genomics2013
Post genome-wide association studies functional characterization of prostate cancer risk loci.
Article in BMC genomics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 24 citations in OpenAlex.
- Combined SNPs sequencing and allele specific proteomics capture reveal functional causality underpinning the 2p25 prostate cancer susceptibility locus.Nature communications · 2025Article
- Racial disparity in prostate cancer: an outlook in genetic and molecular landscape.Cancer metastasis reviews · 2024Review
- Unveiling the Genomic Symphony: Identification Cultivar-Specific Genes and Enhanced Insights on Sweet Sorghum Genomes Through Comprehensive superTranscriptomic Analysis.Journal of molecular evolution · 2024Article
- Data-driven translational prostate cancer research: from biomarker discovery to clinical decision.Journal of translational medicine · 2020Review
- Post-GWAS in prostate cancer: from genetic association to biological contribution.Nature reviews. Cancer · 2019Review
- Enrichment of putative PAX8 target genes at serous epithelial ovarian cancer susceptibility loci.British journal of cancer · 2017Article
- An Integrative Genomics Approach for Associating Genome-Wide Association Studies Information With Localized and Metastatic Prostate Cancer Phenotypes.Biomarker insights · 2017Article
- eQTL analysis links inflammatory bowel disease associated 1q21 locus to ECM1 gene.Journal of applied genetics · 2016Article
- Screening key microRNAs for castration-resistant prostate cancer based on miRNA/mRNA functional synergistic network.Oncotarget · 2015Article
- An analysis of the association between prostate cancer risk loci, PSA levels, disease aggressiveness and disease-specific mortality.British journal of cancer · 2015Article
- Discovery and characterization of long intergenic non-coding RNAs (lincRNA) module biomarkers in prostate cancer: an integrative analysis of RNA-Seq data.BMC genomics · 2015Article
- Identification of candidate miRNA biomarkers from miRNA regulatory network with application to prostate cancer.Journal of translational medicine · 2014Article
- Integrative analysis reveals disease-associated genes and biomarkers for prostate cancer progression.BMC medical genomics · 2014Article
- Interdisciplinary dialogue for education, collaboration, and innovation: intelligent Biology and Medicine in and beyond 2013.BMC genomics · 2013Article
- Genome-wide association analysis reveals regulation of at-risk loci by DNA methylation in prostate cancer.Asian journal of andrologyArticle
- Comparative Analysis of Prostate Cancer Gene Regulatory Networks via Hub Type Variation.Avicenna journal of medical biotechnologyArticle
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundOver the last decade, genome-wide association studies (GWAS) have discovered many risk associated single nucleotide polymorphisms (SNPs) of prostate cancer (PCa). However, the majority of the associated PCa SNPs, including those in linkage disequilibrium (LD) blocks, are generally not located in protein coding regions. The systematical investigation of the functional roles of these SNPs, especially the non-coding SNPs, becomes very necessary and helpful to the understanding of the molecular mechanism of PCa.
resultsIn this work, we proposed a comprehensive framework at network level to integrate the SNP annotation, target gene assignment, gene ontology (GO) classification, pathway enrichment analysis and regulatory network reconstruction to illustrate the molecular functions of PCa associated SNPs. By LD expansion, we first identified 1828 LD SNPs using 49 reported GWAS SNPs as a start. We carefully annotated these 1828 LD SNPs via either UCSC known genes, UCSC regulation elements, or expression Quantitative Trait Loci (eQTL) data. As a result, we found 1154 SNPs were functionally annotated and obtained 205 unique PCa genes for further enrichment analysis. The enriched GO biological processes and pathways were found mainly related to regulation of cell death, apoptosis, cell proliferation, and metabolic process, which have been proved essential to cancer development. We constructed PCa genes specific transcription regulatory networks, finding several important genetic regulators for PCa, such as IGF-1/IGF-2 receptors, SP1, CREB1, and androgen receptor (AR).
conclusionsA comprehensive framework was proposed for integrative and systematic analysis of PCa SNPs, the analysis can provide essential information for the understanding of the regulatory function of GWAS SNPs in PCa, and will facilitate the discovery of novel candidate biomarkers for diagnosis and prognosis of PCa.
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