Absence of truncating BRIP1 mutations in chromosome 17q-linked hereditary prostate cancer families

Background:In a genome-wide scan (GWS) of 175 multiplex prostate cancer (PCa) families from the University of Michigan Prostate Cancer Genetics Project (PCGP), linkage was observed to markers on chromosome 17q21–24, a region that includes two breast cancer susceptibility genes, BRCA1 and BRIP1. BRIP1 is a Fanconi anaemia gene (FANCJ) that interacts with the BRCT domain of BRCA1 and has a role in DNA damage repair. Protein truncating mutations in BRIP1 have been identified in hereditary breast and ovarian cancer families, and a recent report suggested that a recurrent truncating mutation (R798X) may have a role in PCa susceptibility.Methods:We examined the role of BRIP1 mutations in hereditary PCa through sequence analysis of 94 individuals from PCGP families showing linkage to 17q.Results:A total of 24 single-nucleotide polymorphisms, including 7 missense variants but no protein truncating mutations, were observed.Conclusion:The data presented here suggest that BRIP1 truncating mutations are uncommon in PCa cases and do not account for the linkage to chromosome 17q observed in our GWS. Additional investigation is needed to determine the significance, if any, of the observed BRIP1 missense variants in hereditary PCa

Replication and Fine Mapping for Association of the C2orf43, FOXP4, GPRC6A and RFX6 Genes with Prostate Cancer in the Chinese Population

Prostate cancer represents the leading cause of male death across the world. A recent genome-wide association study (GWAS) identified five novel susceptibility loci for prostate cancer in the Japanese population. This study is to replicate and fine map the potential association of these five loci with prostate cancer in the Chinese Han population.In Phase I of the study, we tested the five single nucleotide polymorphisms (SNPs) which showed the strongest association evidence in the original GWAS in Japanese. The study sample consists of 1,169 Chinese Hans, comprising 483 patients and 686 healthy controls. Then in phase II, flanking SNPs of the successfully replicated SNPs in Phase I were genotyped and tested for association with prostate cancer to fine map those significant association signals.We successfully replicated the association of rs13385191 (located in the C2orf43 gene, P = 8.60×10(-5)), rs12653946 (P = 1.33×10(-6)), rs1983891 (FOXP4, P = 6.22×10(-5)), and rs339331 (GPRC6A/RFX6, P = 1.42×10(-5)) with prostate cancer. The most significant odds ratio (OR) was recorded as 1.41 (95% confidence interval 1.18-1.68) for rs12653946. Rs9600079 did not show significant association (P = 8.07×10(-2)) with prostate cancer in this study. The Phase II study refined these association signals, and identified several SNPs showing more significant association with prostate cancer than the very SNPs tested in Phase I.Our results provide further support for association of the C2orf43, FOXP4, GPRC6A and RFX6 genes with prostate cancer in Eastern Asian populations. This study also characterized the novel loci reported in the original GWAS with more details. Further work is still required to determine the functional variations and finally clarify the underlying biological mechanisms

Incompatibilities Involving Yeast Mismatch Repair Genes: A Role for Genetic Modifiers and Implications for Disease Penetrance and Variation in Genomic Mutation Rates

Genetic background effects underlie the penetrance of most genetically determined phenotypes, including human diseases. To explore how such effects can modify a mutant phenotype in a genetically tractable system, we examined an incompatibility involving the MLH1 and PMS1 mismatch repair genes using a large population sample of geographically and ecologically diverse Saccharomyces cerevisiae strains. The mismatch repair incompatibility segregates into naturally occurring yeast strains, with no strain bearing the deleterious combination. In assays measuring the mutator phenotype conferred by different combinations of MLH1 and PMS1 from these strains, we observed a mutator phenotype only in combinations predicted to be incompatible. Surprisingly, intragenic modifiers could be mapped that specifically altered the strength of the incompatibility over a 20-fold range. Together, these observations provide a powerful model in which to understand the basis of disease penetrance and how such genetic variation, created through mating, could result in new mutations that could be the raw material of adaptive evolution in yeast populations

Two-locus genome-wide linkage scan for prostate cancer susceptibility genes with an interaction effect

Prostate cancer represents a significant worldwide public health burden. Epidemiological and genetic epidemiological studies have consistently provided data supporting the existence of inherited prostate cancer susceptibility genes. Segregation analyses of prostate cancer suggest that a multigene model may best explain familial clustering of this disease. Therefore, modeling gene–gene interactions in linkage analysis may improve the power to detect chromosomal regions harboring these disease susceptibility genes. In this study, we systematically screened for prostate cancer linkage by modeling two-locus gene–gene interactions for all possible pairs of loci across the genome in 426 prostate cancer families from Johns Hopkins Hospital, University of Michigan, University of Umeå, and University of Tampere. We found suggestive evidence for an epistatic interaction for six sets of loci (target chromosome-wide/reference marker-specific P ≤0.0001). Evidence for these interactions was found in two independent subsets from within the 426 families. While the validity of these results requires confirmation from independent studies and the identification of the specific genes underlying this linkage evidence, our approach of systematically assessing gene–gene interactions across the entire genome represents a promising alternative approach for gene identification for prostate cancer.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47598/1/439_2005_Article_99.pd

Novel pleiotropic risk loci for melanoma and nevus density implicate multiple biological pathways.

The total number of acquired melanocytic nevi on the skin is strongly correlated with melanoma risk. Here we report a meta-analysis of 11 nevus GWAS from Australia, Netherlands, UK, and USA comprising 52,506 individuals. We confirm known loci including MTAP, PLA2G6, and IRF4, and detect novel SNPs in KITLG and a region of 9q32. In a bivariate analysis combining the nevus results with a recent melanoma GWAS meta-analysis (12,874 cases, 23,203 controls), SNPs near GPRC5A, CYP1B1, PPARGC1B, HDAC4, FAM208B, DOCK8, and SYNE2 reached global significance, and other loci, including MIR146A and OBFC1, reached a suggestive level. Overall, we conclude that most nevus genes affect melanoma risk (KITLG an exception), while many melanoma risk loci do not alter nevus count. For example, variants in TERC and OBFC1 affect both traits, but other telomere length maintenance genes seem to affect melanoma risk only. Our findings implicate multiple pathways in nevogenesis

Cell-type–specific eQTL of primary melanocytes facilitates identification of melanoma susceptibility genes

Most expression quantitative trait locus (eQTL) studies to date have been performed in heterogeneous tissues as opposed to specific cell types. To better understand the cell-type–specific regulatory landscape of human melanocytes, which give rise to melanoma but account for <5% of typical human skin biopsies, we performed an eQTL analysis in primary melanocyte cultures from 106 newborn males. We identified 597,335 cis-eQTL SNPs prior to linkage disequilibrium (LD) pruning and 4997 eGenes (FDR < 0.05). Melanocyte eQTLs differed considerably from those identified in the 44 GTEx tissue types, including skin. Over a third of melanocyte eGenes, including key genes in melanin synthesis pathways, were unique to melanocytes compared to those of GTEx skin tissues or TCGA melanomas. The melanocyte data set also identified trans-eQTLs, including those connecting a pigmentation-associated functional SNP with four genes, likely through cis-regulation of IRF4. Melanocyte eQTLs are enriched in cis-regulatory signatures found in melanocytes as well as in melanoma-associated variants identified through genome-wide association studies. Melanocyte eQTLs also colocalized with melanoma GWAS variants in five known loci. Finally, a transcriptome-wide association study using melanocyte eQTLs uncovered four novel susceptibility loci, where imputed expression levels of five genes (ZFP90, HEBP1, MSC, CBWD1, and RP11-383H13.1) were associated with melanoma at genome-wide significant P-values. Our data highlight the utility of lineage-specific eQTL resources for annotating GWAS findings, and present a robust database for genomic research of melanoma risk and melanocyte biology