Liesel M. FitzGerald

Association of TMPRSS2-ERG gene fusion with clinical characteristics and outcomes: results from a population-based study of prostate cancer

BackgroundThe presence of the TMPRSS2-ERG fusion gene in prostate tumors has recently been associated with an aggressive phenotype, as well as recurrence and death from prostate cancer. These associations suggest the hypothesis that the gene fusion may be used as a prognostic indicator for prostate cancer.MethodsIn this study, fluorescent in situ hybridization (FISH) assays were used to assess TMPRSS2-ERG fusion status in a group of 214 prostate cancer cases from two population-based studies. The FISH assays were designed to detect both fusion type (deletion vs. translocation) and the number of fusion copies (single vs. multiple). Genotyping of four ERG and one TMPRSS2 SNPs using germline DNA was also performed in a sample of the cases (n = 127).ResultsOf the 214 tumors scored for the TMPRSS2-ERG fusion, 64.5% were negative and 35.5% were positive for the fusion. Cases with the TMPRSS2-ERG fusion did not exhibit reduced prostate cancer survival (HR = 0.92, 95% CI = 0.22–3.93), nor was there a significant difference in cause-specific survival when stratifying by translocation or deletion (HR = 0.84, 95% CI = 0.23–3.12) or by the number of retained fusion copies (HR = 1.22, 95% CI = 0.45–3.34). However, evidence for reduced prostate cancer-specific survival was apparent in those cases whose tumor had multiple copies of the fusion. The variant T allele of the TMPRSS2 SNP, rs12329760, was positively associated with TMPRSS2-ERG fusion by translocation (p = 0.05) and with multiple copies of the gene fusion (p = 0.03).ConclusionIf replicated, the results presented here may provide insight into the mechanism by which the TMPRSS2-ERG gene fusion arises and also contribute to diagnostic evaluations for determining the subset of men who will go on to develop metastatic prostate cancer.

Testing the Circadian Gene Hypothesis in Prostate Cancer: A Population-Based Case-Control Study

Circadian genes are responsible for maintaining the ancient adaptation of a 24-hour circadian rhythm and influence a variety of cancer-related biological pathways, including the regulation of sex hormone levels. However, few studies have been undertaken to investigate the role of circadian genes in the development of prostate cancer, the most common cancer type among men (excluding nonmelanoma skin cancer). The current genetic association study tested the circadian gene hypothesis in relation to prostate cancer by genotyping a total of 41 tagging and amino acid-altering single nucleotide polymorphisms (SNP) in 10 circadian-related genes in a population-based case-control study of Caucasian men (n = 1,308 cases and 1,266 controls). Our results showed that at least one SNP in nine core circadian genes (rs885747 and rs2289591 in PER1; rs7602358 in PER2; rs1012477 in PER3; rs1534891 in CSNK1E; rs12315175 in CRY1; rs2292912 in CRY2; rs7950226 in ARNTL; rs11133373 in CLOCK; and rs1369481, rs895521, and rs17024926 in NPAS2) was significantly associated with susceptibility to prostate cancer (either overall risk or risk of aggressive disease), and the risk estimate for four SNPs in three genes (rs885747 and rs2289591 in PER1, rs1012477 in PER3, and rs11133373 in CLOCK) varied by disease aggressiveness. Further analyses of haplotypes were consistent with these genotyping results. Findings from this candidate gene association study support the hypothesis of a link between genetic variants in circadian genes and prostate cancer risk, warranting further confirmation and mechanistic investigation of circadian biomarkers in prostate tumorigenesis.

Clinical Utility of Five Genetic Variants for Predicting Prostate Cancer Risk and Mortality

A recent report suggests that the combination of five single‐nucleotide polymorphisms (SNPs) at 8q24, 17q12, 17q24.3 and a family history of the disease may predict risk of prostate cancer. The present study tests the performance of these factors in prediction models for prostate cancer risk and prostate cancer‐specific mortality.

Use of Aspirin and Other Nonsteroidal Antiinflammatory Medications in Relation to Prostate Cancer Risk

Recent interest has focused on the role that inflammation may play in the development of prostate cancer and whether use of aspirin or other nonsteroidal antiinflammatory drugs (NSAIDs) affects risk. In a population-based case-control study designed to investigate the relation between these medications and prostate cancer risk, detailed exposure data were analyzed from 1,001 cases diagnosed with prostate cancer between January 1, 2002, and December 31, 2005, and 942 age-matched controls from King County, Washington. A significant 21% reduction in the risk of prostate cancer was observed among current users of aspirin compared with nonusers (95% confidence interval (CI): 0.65, 0.96). Long-term use of aspirin (>5 years: odds ratio = 0.76, 95% CI: 0.61, 0.96) and daily use of low-dose aspirin (odds ratio = 0.71, 95% CI: 0.56, 0.90) were also associated with decreased risk. There was no evidence that the association with aspirin use varied by disease aggressiveness, but there was effect modification (P(interaction) = 0.02) with a genetic variant in prostaglandin-endoperoxide synthase 2 (PTGS2) (rs12042763). Prostate cancer risk was not related to use of either nonaspirin NSAIDs or acetaminophen. These results contribute further evidence that aspirin may have chemopreventive activity against prostate cancer and highlight the need for additional research.

Analysis of Recently Identified Prostate Cancer Susceptibility Loci in a Population-based Study: Associations with Family History and Clinical Features

Purpose: Two recent genome-wide association studies have highlighted several single nucleotide polymorphisms (SNPs) purported to be associated with prostate cancer risk. We investigated the significance of these SNPs in a population-based study of Caucasian men, testing the effects of each SNP in relation to family history of prostate cancer and the clinicopathologic features of the disease. Experimental Design: We genotyped 13 SNPs in 1,308 prostate cancer patients and 1,267 unaffected controls frequency matched to cases by five-year age groups. The association of each SNP with disease risk stratified by family history of prostate cancer and clinicopathologic features of the disease was calculated with the use of logistic and polytomous regression. Results: These results confirm the importance of multiple, previously reported SNPs in relation to prostate cancer susceptibility; 11 of the 13 SNPs were significantly associated with risk of developing prostate cancer. However, none of the SNP associations were of comparable magnitude with that associated with having a first-degree family history of the disease. Risk estimates associated with SNPs rs4242382 and rs2735839 varied by family history, whereas risk estimates for rs10993994 and rs5945619 varied by Gleason score. Conclusions: Our results confirm that several recently identified SNPs are associated with prostate cancer risk; however, the variant alleles only confer a low to moderate relative risk of disease and are generally not associated with more aggressive disease features.

Genetic Variants in the LEPR, CRY1, RNASEL, IL4, and ARVCF Genes Are Prognostic Markers of Prostate Cancer-Specific Mortality

Background: Prostate cancer is the second leading cause of cancer-related deaths in men, accounting for more than 30,000 deaths annually. The purpose of this study was to test whether variation in selected candidate genes in biological pathways of interest for prostate cancer progression could help distinguish patients at higher risk for fatal prostate cancer. Methods: In this hypothesis-driven study, we genotyped 937 single nucleotide polymorphisms (SNPs) in 156 candidate genes in a population-based cohort of 1,309 prostate cancer patients. We identified 22 top-ranking SNPs (P ≤ 0.01, FDR ≤ 0.70) associated with prostate cancer-specific mortality (PCSM). A subsequent validation study was completed in an independent population-based cohort of 2,875 prostate cancer patients. Results: Five SNPs were validated (P ≤ 0.05) as being significantly associated with PCSM, one each in the LEPR, CRY1, RNASEL, IL4, and ARVCF genes. Compared with patients with 0 to 2 of the at-risk genotypes those with 4 to 5 at-risk genotypes had a 50% (95% CI, 1.2–1.9) higher risk of PCSM and risk increased with the number of at-risk genotypes carried (Ptrend = 0.001), adjusting for clinicopathologic factors known to influence prognosis. Conclusion: Five genetic markers were validated to be associated with lethal prostate cancer. Impact: This is the first population-based study to show that germline genetic variants provide prognostic information for prostate cancer-specific survival. The clinical utility of this five-SNP panel to stratify patients at higher risk for adverse outcomes should be evaluated. Cancer Epidemiol Biomarkers Prev; 20(9); 1928–36. ©2011 AACR.

The OncoArray Consortium: a Network for Understanding the Genetic Architecture of Common Cancers.

Background: Common cancers develop through a multistep process often including inherited susceptibility. Collaboration among multiple institutions, and funding from multiple sources, has allowed the development of an inexpensive genotyping microarray, the OncoArray. The array includes a genome-wide backbone, comprising 230,000 SNPs tagging most common genetic variants, together with dense mapping of known susceptibility regions, rare variants from sequencing experiments, pharmacogenetic markers, and cancer-related traits. Methods: The OncoArray can be genotyped using a novel technology developed by Illumina to facilitate efficient genotyping. The consortium developed standard approaches for selecting SNPs for study, for quality control of markers, and for ancestry analysis. The array was genotyped at selected sites and with prespecified replicate samples to permit evaluation of genotyping accuracy among centers and by ethnic background. Results: The OncoArray consortium genotyped 447,705 samples. A total of 494,763 SNPs passed quality control steps with a sample success rate of 97% of the samples. Participating sites performed ancestry analysis using a common set of markers and a scoring algorithm based on principal components analysis. Conclusions: Results from these analyses will enable researchers to identify new susceptibility loci, perform fine-mapping of new or known loci associated with either single or multiple cancers, assess the degree of overlap in cancer causation and pleiotropic effects of loci that have been identified for disease-specific risk, and jointly model genetic, environmental, and lifestyle-related exposures. Impact: Ongoing analyses will shed light on etiology and risk assessment for many types of cancer. Cancer Epidemiol Biomarkers Prev; 26(1); 126–35. ©2016 AACR.

Mutations in the NDP gene: contribution to Norrie disease, familial exudative vitreoretinopathy and retinopathy of prematurity

Background:  To examine the contribution of mutations within the Norrie disease (NDP) gene to the clinically similar retinal diseases Norrie disease, X‐linked familial exudative vitreoretinopathy (FEVR), Coat’s disease and retinopathy of prematurity (ROP).

Genome-wide Association Study Identifies a Genetic Variant Associated with Risk for More Aggressive Prostate Cancer

Background: Of the 200,000 U.S. men annually diagnosed with prostate cancer, approximately 20% to 30% will have clinically aggressive disease. Although factors such as Gleason score and tumor stage are used to assess prognosis, there are no biomarkers to identify men at greater risk for developing aggressive prostate cancer. We therefore undertook a search for genetic variants associated with risk of more aggressive disease. Methods: A genome-wide scan was conducted in 202 prostate cancer cases with a more aggressive phenotype and 100 randomly sampled, age-matched prostate-specific antigen screened negative controls. Analysis of 387,384 autosomal single nucleotide polymorphisms (SNPs) was followed by validation testing in an independent set of 527 cases with more aggressive and 595 cases with less aggressive prostate cancer, and 1,167 age-matched controls. Results: A variant on 15q13, rs6497287, was confirmed to be most strongly associated with more aggressive (Pdiscovery = 5.20 × 10−5, Pvalidation = 0.004) than less aggressive disease (P = 0.14). Another SNP on 3q26, rs3774315, was found to be associated with prostate cancer risk; however, the association was not stronger for more aggressive disease. Conclusions: This study provides suggestive evidence for a genetic predisposition to more aggressive prostate cancer and highlights the fact that larger studies are warranted to confirm this supposition and identify further risk variants. Impact: These findings raise the possibility that assessment of genetic variation may one day be useful to discern men at higher risk for developing clinically significant prostate cancer. Cancer Epidemiol Biomarkers Prev; 20(6); 1196–203. ©2011 AACR.

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same region.