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Variants at IRX4 as prostate cancer expression quantitative trait loci.

ABSTRACT: Genome-wide association studies (GWAS) have identified numerous prostate cancer-associated risk loci. Some variants at these loci may be regulatory and influence expression of nearby genes. Such loci are known as cis-expression quantitative trait loci (cis-eQTL). As cis-eQTLs are highly tissue-specific, we asked if GWAS-identified prostate cancer risk loci are cis-eQTLs in human prostate tumor tissues. We investigated 50 prostate cancer samples for their genotype at 59 prostate cancer risk-associated single-nucleotide polymorphisms (SNPs) and performed cis-eQTL analysis of transcripts from paired primary tumors within two megabase windows. We tested 586 transcript-genotype associations, of which 27 were significant (false discovery rate ?10%). An equivalent eQTL analysis of the same prostate cancer risk loci in lymphoblastoid cell lines did not result in any significant associations. The top-ranked cis-eQTL involved the IRX4 (Iroquois homeobox protein 4) transcript and rs12653946, tagged by rs10866528 in our study (P=4.91 × 10(-5)). Replication studies, linkage disequilibrium, and imputation analyses highlight population specificity at this locus. We independently validated IRX4 as a potential prostate cancer risk gene through cis-eQTL analysis of prostate cancer risk variants. Cis-eQTL analysis in relevant tissues, even with a small sample size, can be a powerful method to expedite functional follow-up of GWAS.

SUBMITTER: Xu X

PROVIDER: S-EPMC3953920 | biostudies-literature | 2014 Apr

REPOSITORIES: biostudies-literature

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Variants at IRX4 as prostate cancer expression quantitative trait loci.

Xu Xing X Hussain Wasay M WM Vijai Joseph J Offit Kenneth K Rubin Mark A MA Demichelis Francesca F Klein Robert J RJ

European journal of human genetics : EJHG 20130911 4

Genome-wide association studies (GWAS) have identified numerous prostate cancer-associated risk loci. Some variants at these loci may be regulatory and influence expression of nearby genes. Such loci are known as cis-expression quantitative trait loci (cis-eQTL). As cis-eQTLs are highly tissue-specific, we asked if GWAS-identified prostate cancer risk loci are cis-eQTLs in human prostate tumor tissues. We investigated 50 prostate cancer samples for their genotype at 59 prostate cancer risk-assoc ...[more]

PMID: 24022300

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Project description:BACKGROUND:Prostate cancer (PCa) shows a substantial clinical heterogeneity. The existing risk classification for PCa prognosis based on clinical factors is not sufficient. Although some biomarkers for PCa aggressiveness have been identified, their underlying functional mechanisms are still unclear. We previously reported a gene-gene interaction network associated with PCa aggressiveness based on single nucleotide polymorphism (SNP)-SNP interactions in the angiogenesis pathway. The goal of this study is to investigate potential functional evidence of the involvement of the genes in this gene-gene interaction network. METHODS:A total of 11 angiogenesis genes were evaluated. The crosstalks among genes were examined through coexpression and expression quantitative trait loci (eQTL) analyses. The study population is 352 Caucasian PCa patients in the Cancer Genome Atlas (TCGA) study. The pairwise coexpressions among the genes of interest were evaluated using the Spearman coefficient. The eQTL analyses were tested using the Kruskal-Wallis test. RESULTS:Among all within gene and 55 possible pairwise gene evaluations, 12 gene pairs and one gene (MMP16) showed strong coexpression or significant eQTL evidence. There are nine gene pairs with a strong correlation (Spearman correlation ?0.6, P<1×10-13). The top coexpressed gene pairs are EGFR-SP1 (r=0.73), ITGB3-HSPG2 (r=0.71), ITGB3-CSF1 (r=0.70), MMP16-FBLN5 (r=0.68), ITGB3-MMP16 (r=0.65), ITGB3-ROBO1 (r=0.62), CSF1-HSPG2 (r=0.61), CSF1-FBLN5 (r=0.6), and CSF1-ROBO1 (r=0.60). One cis-eQTL in MMP16 and five trans-eQTLs (MMP16-ESR1, ESR1-ROBO1, CSF1-ROBO1, HSPG2-ROBO1, and FBLN5-CSF1) are significant with a false discovery rate q value less than 0.2. CONCLUSIONS:These findings provide potential biological evidence for the gene-gene interactions in this angiogenesis network. These identified interactions between the angiogenesis genes not only provide information for PCa etiology mechanism but also may serve as integrated biomarkers for building a risk prediction model for PCa aggressiveness.

Project description:Genetic dissection of the S rat genome has provided strong evidence for the presence of two interacting blood pressure (BP) quantitative trait loci (QTLs), termed QTL1 and QTL2, on rat chromosome 5. However, the identities of the underlying interacting genetic factors remain unknown. Further experiments targeted to identify the interacting genetic factors by the substitution mapping approach alone are difficult because of the interdependency of natural recombinations to occur at the two QTLs. We hypothesized that the interacting genetic factors underlying these two QTLs may interact at the level of gene transcription and thereby represent expression QTLs (eQTLs). To detect these interacting eQTLs, a custom QTL chip containing the annotated genes within QTL1 and QTL2 was developed and used to conduct a transcriptional profiling study of S and two congenic strains that retain either one or both the QTLs. The results uncovered an interaction between two transcription factors, DMRTA2 and NFIA. Further, the âbiological signatureâ elicited by these two transcription factors was differential between the congenic strain that retained LEW alleles at both QTL1 and 2 compared to the congenic strain that retained LEW alleles at QTL1 alone. A network of transcription factors potentially affecting BP could be traced, lending support to our hypothesis. Pairs of Cy5 and Cy3 labeled targets were co-hybridized onto either a custom long oligonucleotide microarray for the interrogation of 231 genes encompassed by QTL1 and QTL2, or a TIGR rat cDNA array consisting of 26,401 probe elements representing 20,465 unique non-QTL genes. A âflip-dyeâ or âbalanced blockâ design was used as the experimental method of choice to account for potential dye-bias labeling effects. Six âbalanced blockâ normalized files are submitted for the long oligonucleotide array interrogating the hearts from S versus S.LEW(5)x6x9 animals, fourteen âflip-dyeâ hybridizations are submitted for the cDNA array interrogating the hearts from S versus S.LEW(5)x6x9 animals, and twelve âflip-dyeâ hybridizations are submitted for the cDNA array interrogating the hearts from S versus S.LEW(5)x6x11 animals. GPR and MEV files cannot be located.

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Variants at IRX4 as prostate cancer expression quantitative trait loci.

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Variants at IRX4 as prostate cancer expression quantitative trait loci.

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