A Genome Screen of Families with Multiple Cases of Prostate Cancer: Evidence of Genetic Heterogeneity

Department of Health Research and Policy, Stanford University, Stanford, California, United States
The American Journal of Human Genetics (Impact Factor: 10.93). 08/2001; 69(1):148-58. DOI: 10.1086/321281
Source: PubMed


We conducted a genomewide screen for prostate cancer-susceptibility genes on the basis of data from 98 families from the United States and Canada that had three or more verified diagnoses of prostate cancer among first- and second-degree relatives. We found a statistically significant excess of markers for which affected relatives exhibited modest amounts of excess allele-sharing; however, no single chromosomal region contained markers with excess allele-sharing of sufficient magnitude to indicate unequivocal evidence of linkage. Positive linkage signals of nominal statistical significance were found in two regions (5p-q and 12p) that have been identified as weakly positive in other data sets and in region 19p, which has not been identified previously. All these signals were considerably stronger for analyses restricted to families with mean age at onset below the median than for analyses of families with mean age at onset above the median. The data provided little support for any of the putative prostate cancer-susceptibility genes identified in other linkage studies.

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    • "IL-8, VEGF, MMP9, vimentin, uPA and uPA receptor, further contribute to the development of aggressive PCA (Karin et al. 2002). On the other side, among multiple factors implicated in the initiation and progression of PC (Xu et al. 2002; Albany et al. 2011; Hsieh et al. 2001) tumor suppressor gene DLC1, a member of RhoGAP family of genes, stands out, as it has been shown to be down-regulated or absent not only in PC, but in various other solid tumors and hematological malignancies (Guan et al. 2006; Durkin et al. 2007; Ullmannova et al. 2009). Introduction of DLC1 in highly metastatic PCA cells suppressed proliferation , invasiveness and anchorage-independent growth and restored response to apoptotic signaling (Guan et al. 2008). "
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    ABSTRACT: DLC1 (Deleted in Liver Cancer 1) gene encodes a RhoGTPase-activating protein (RhoGAP), which exerts most of its tumor suppressor functions through suppression of small Rho GTPases proteins RhoA, RhoB, RhoC and to some degree Cdc42, but not Rac. RhoGTPases are implicated in NF-κB activation in highly invasive prostate carcinoma (PCA), with consequences on cell proliferation, survival and metastatic capacity. Here we demonstrate that DLC1 transduction in two androgen-independent (AI) and highly metastatic PCA cell lines negatively regulates NF-κB activity in a GAP- and α-catenin-dependent manner. Expressed DLC1 protein suppresses the phosphorylation of NF-κB inhibitor, IκBα, causes its relocation from membrane ruffles into cytoplasm and attenuates its ubiquitination and subsequent degradation. DLC1-mediated NF-kB suppression and its effects are comparable to NF-κB inhibition using either shRNA knockdown or peptide inhibitor. Expression of transduced DLC1 suppressed the expression of NF-κB mediated genes. Such effects were found to be reliant on presence of calcium, indicating that the observed modifications are dependent on, and enabled by DLC-mediated stabilization of adherens junctions. These results expand the multitude of DLC1 interactions with other genes that modulate its oncosuppressive function, and may have potential therapeutic implications.
    Full-text · Article · Jan 2014 · SpringerPlus
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    • "Jin et al. conducted a meta-analysis of two GWAS and a replication study through which they identified a novel PCa risk locus rs3787016 at 19p13 [26]. This chromosomal region was previously associated through linkage studies with familial type of PCa in several populations with various ancestral backgrounds , but its functional implication remained unknown [37] [38]. Since rs3787016 locates to an intron of POLR2E [26], functional genetic variants underlying reported association with PCa could also be located in the coding or noncoding regions of this gene, causing its abnormal structure and/or expression pattern with possible involvement in carcinogenesis. "
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    ABSTRACT: Recent study, which included meta-analysis of two genome-wide association studies (GWAS), followed by a replication, identified the association between single nucleotide polymorphism (SNP) rs3787016 at 19p13 and prostate cancer (PCa) risk. Considering possible genetic differences between populations, we conducted the study in order to evaluate the association of this polymorphism with prostate cancer risk in Serbian population. 261 samples of peripheral blood were obtained from the patients with PCa and 257 samples from patients with benign prostatic hyperplasia (BPH). 106 volunteers who gave samples of bucal swabs comprised the control group. For individuals diagnosed with PCa clinicopathological characteristics including serum prostate-specific antigen (PSA) level at diagnosis, Gleason score (GS) and clinical stage were determined. Genotypization of rs3787016 was performed by using Taqman(®) SNP Genotyping Assay. The differences in alelle and genotype frequencies between analyzed groups of subjects were performed by using PLINK, SPSS 17.0 for Windows and SNPStats statistical software. No significant association of rs3787016 with PCa risk was determined comparing allele and genotype frequencies among group of patients diagnosed with PCa and the control group, as well as among groups of patients with PCa and BPH. Also, no evidence of association of rs3787016 with PCa risk was shown using tests for association under dominant and recessive genetic models. SNP rs3787016 showed no significant association with standard prognostic parameters regarding PCa progression, nor with the risk of disease progression assessed according to two different risk classification systems.
    Full-text · Article · Jan 2013 · International Journal of Clinical and Experimental Medicine
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    • "This is particularly true when exploring for novel regions of linkage using genome-wide scans. Among a dozen genome-wide scans for prostate cancer susceptibility genes published to date, none of these have modeled gene–gene interactions (Smith et al. 1996; Witte et al. 2000; Hsieh et al. 2001; Cunningham et al. 2003; Edwards et al. 2003; Janer et al. 2003; Lange et al. 2003; Schleutker et al. 2003; Wiklund et al. 2003; Xu et al. 2003; Maier et al. 2005). This gap may be primarily due to a combination of factors, such as a lack of standard analytical methods to model interactions and sample sizes that are not large enough to investigate interac- tions. "
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    ABSTRACT: 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< or =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.
    Full-text · Article · Feb 2006 · Human Genetics
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