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Fulltext Interactions Between Genome-Wide Significant Genetic Variants and Circulating Concentrations of 25-Hydroxyvitamin D in Relation to Prostate Cancer Risk in the National Cancer Institute BPC3

Dimitrakopoulou VI, Travis RC, Shui IM, Mondul A, Albanes D, Virtamo J, et al.

Am J Epidemiol, 2017 Mar 15;185(6):452-464.
PMID: 28399564 DOI: 10.1093/aje/kww143

Genome-wide association studies (GWAS) have identified over 100 single nucleotide polymorphisms (SNPs) associated with prostate cancer. However, information on the mechanistic basis for some associations is limited. Recent research has been directed towards the potential association of vitamin D concentrations and prostate cancer, but little is known about whether the aforementioned genetic associations are modified by vitamin D. We investigated the associations of 46 GWAS-identified SNPs, circulating concentrations of 25-hydroxyvitamin D (25(OH)D), and prostate cancer (3,811 cases, 511 of whom died from the disease, compared with 2,980 controls-from 5 cohort studies that recruited participants over several periods beginning in the 1980s). We used logistic regression models with data from the National Cancer Institute Breast and Prostate Cancer Cohort Consortium (BPC3) to evaluate interactions on the multiplicative and additive scales. After allowing for multiple testing, none of the SNPs examined was significantly associated with 25(OH)D concentration, and the SNP-prostate cancer associations did not differ by these concentrations. A statistically significant interaction was observed for each of 2 SNPs in the 8q24 region (rs620861 and rs16902094), 25(OH)D concentration, and fatal prostate cancer on both multiplicative and additive scales (P ≤ 0.001). We did not find strong evidence that associations between GWAS-identified SNPs and prostate cancer are modified by circulating concentrations of 25(OH)D. The intriguing interactions between rs620861 and rs16902094, 25(OH)D concentration, and fatal prostate cancer warrant replication.
Fulltext A genome-wide pleiotropy scan for prostate cancer risk

Panagiotou OA, Travis RC, Campa D, Berndt SI, Lindstrom S, Kraft P, et al.

Eur Urol, 2015 Apr;67(4):649-57.
PMID: 25277271 DOI: 10.1016/j.eururo.2014.09.020

BACKGROUND: No single-nucleotide polymorphisms (SNPs) specific for aggressive prostate cancer have been identified in genome-wide association studies (GWAS).
OBJECTIVE: To test if SNPs associated with other traits may also affect the risk of aggressive prostate cancer.
DESIGN, SETTING, AND PARTICIPANTS: SNPs implicated in any phenotype other than prostate cancer (p≤10(-7)) were identified through the catalog of published GWAS and tested in 2891 aggressive prostate cancer cases and 4592 controls from the Breast and Prostate Cancer Cohort Consortium (BPC3). The 40 most significant SNPs were followed up in 4872 aggressive prostate cancer cases and 24,534 controls from the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium.
OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Odds ratios (ORs) and 95% confidence intervals (CIs) for aggressive prostate cancer were estimated.
RESULTS AND LIMITATIONS: A total of 4666 SNPs were evaluated by the BPC3. Two signals were seen in regions already reported for prostate cancer risk. rs7014346 at 8q24.21 was marginally associated with aggressive prostate cancer in the BPC3 trial (p=1.6×10(-6)), whereas after meta-analysis by PRACTICAL the summary OR was 1.21 (95% CI 1.16-1.27; p=3.22×10(-18)). rs9900242 at 17q24.3 was also marginally associated with aggressive disease in the meta-analysis (OR 0.90, 95% CI 0.86-0.94; p=2.5×10(-6)). Neither of these SNPs remained statistically significant when conditioning on correlated known prostate cancer SNPs. The meta-analysis by BPC3 and PRACTICAL identified a third promising signal, marked by rs16844874 at 2q34, independent of known prostate cancer loci (OR 1.12, 95% CI 1.06-1.19; p=4.67×10(-5)); it has been shown that SNPs correlated with this signal affect glycine concentrations. The main limitation is the heterogeneity in the definition of aggressive prostate cancer between BPC3 and PRACTICAL.
CONCLUSIONS: We did not identify new SNPs for aggressive prostate cancer. However, rs16844874 may provide preliminary genetic evidence on the role of the glycine pathway in prostate cancer etiology.
PATIENT SUMMARY: We evaluated whether genetic variants associated with several traits are linked to the risk of aggressive prostate cancer. No new such variants were identified.
Fulltext ABO blood group alleles and prostate cancer risk: Results from the breast and prostate cancer cohort consortium (BPC3)

Markt SC, Shui IM, Unger RH, Urun Y, Berg CD, Black A, et al.

Prostate, 2015 Nov;75(15):1677-81.
PMID: 26268879 DOI: 10.1002/pros.23035

BACKGROUND: ABO blood group has been associated with risk of cancers of the pancreas, stomach, ovary, kidney, and skin, but has not been evaluated in relation to risk of aggressive prostate cancer.
METHODS: We used three single nucleotide polymorphisms (SNPs) (rs8176746, rs505922, and rs8176704) to determine ABO genotype in 2,774 aggressive prostate cancer cases and 4,443 controls from the Breast and Prostate Cancer Cohort Consortium (BPC3). Unconditional logistic regression was used to calculate age and study-adjusted odds ratios and 95% confidence intervals for the association between blood type, genotype, and risk of aggressive prostate cancer (Gleason score ≥8 or locally advanced/metastatic disease (stage T3/T4/N1/M1).
RESULTS: We found no association between ABO blood type and risk of aggressive prostate cancer (Type A: OR = 0.97, 95%CI = 0.87-1.08; Type B: OR = 0.92, 95%CI =n0.77-1.09; Type AB: OR = 1.25, 95%CI = 0.98-1.59, compared to Type O, respectively). Similarly, there was no association between "dose" of A or B alleles and aggressive prostate cancer risk.
CONCLUSIONS: ABO blood type was not associated with risk of aggressive prostate cancer.
Fulltext A Meta-analysis of Individual Participant Data Reveals an Association between Circulating Levels of IGF-I and Prostate Cancer Risk

Travis RC, Appleby PN, Martin RM, Holly JMP, Albanes D, Black A, et al.

Cancer Res, 2016 04 15;76(8):2288-2300.
PMID: 26921328 DOI: 10.1158/0008-5472.CAN-15-1551

The role of insulin-like growth factors (IGF) in prostate cancer development is not fully understood. To investigate the association between circulating concentrations of IGFs (IGF-I, IGF-II, IGFBP-1, IGFBP-2, and IGFBP-3) and prostate cancer risk, we pooled individual participant data from 17 prospective and two cross-sectional studies, including up to 10,554 prostate cancer cases and 13,618 control participants. Conditional logistic regression was used to estimate the ORs for prostate cancer based on the study-specific fifth of each analyte. Overall, IGF-I, IGF-II, IGFBP-2, and IGFBP-3 concentrations were positively associated with prostate cancer risk (Ptrend all ≤ 0.005), and IGFBP-1 was inversely associated weakly with risk (Ptrend = 0.05). However, heterogeneity between the prospective and cross-sectional studies was evident (Pheterogeneity = 0.03), unless the analyses were restricted to prospective studies (with the exception of IGF-II, Pheterogeneity = 0.02). For prospective studies, the OR for men in the highest versus the lowest fifth of each analyte was 1.29 (95% confidence interval, 1.16-1.43) for IGF-I, 0.81 (0.68-0.96) for IGFBP-1, and 1.25 (1.12-1.40) for IGFBP-3. These associations did not differ significantly by time-to-diagnosis or tumor stage or grade. After mutual adjustment for each of the other analytes, only IGF-I remained associated with risk. Our collaborative study represents the largest pooled analysis of the relationship between prostate cancer risk and circulating concentrations of IGF-I, providing strong evidence that IGF-I is highly likely to be involved in prostate cancer development. Cancer Res; 76(8); 2288-300. ©2016 AACR.
Fulltext Mendelian Randomization Analysis of n-6 Polyunsaturated Fatty Acid Levels and Pancreatic Cancer Risk

Ghoneim DH, Zhu J, Zheng W, Long J, Murff HJ, Ye F, et al.

Cancer Epidemiol Biomarkers Prev, 2020 Dec;29(12):2735-2739.
PMID: 32967863 DOI: 10.1158/1055-9965.EPI-20-0651

BACKGROUND: Whether circulating polyunsaturated fatty acid (PUFA) levels are associated with pancreatic cancer risk is uncertain. Mendelian randomization (MR) represents a study design using genetic instruments to better characterize the relationship between exposure and outcome.
METHODS: We utilized data from genome-wide association studies within the Pancreatic Cancer Cohort Consortium and Pancreatic Cancer Case-Control Consortium, involving approximately 9,269 cases and 12,530 controls of European descent, to evaluate associations between pancreatic cancer risk and genetically predicted plasma n-6 PUFA levels. Conventional MR analyses were performed using individual-level and summary-level data.
RESULTS: Using genetic instruments, we did not find evidence of associations between genetically predicted plasma n-6 PUFA levels and pancreatic cancer risk [estimates per one SD increase in each PUFA-specific weighted genetic score using summary statistics: linoleic acid odds ratio (OR) = 1.00, 95% confidence interval (CI) = 0.98-1.02; arachidonic acid OR = 1.00, 95% CI = 0.99-1.01; and dihomo-gamma-linolenic acid OR = 0.95, 95% CI = 0.87-1.02]. The OR estimates remained virtually unchanged after adjustment for covariates, using individual-level data or summary statistics, or stratification by age and sex.
CONCLUSIONS: Our results suggest that variations of genetically determined plasma n-6 PUFA levels are not associated with pancreatic cancer risk.
IMPACT: These results suggest that modifying n-6 PUFA levels through food sources or supplementation may not influence risk of pancreatic cancer.
Fulltext Smoking Modifies Pancreatic Cancer Risk Loci on 2q21.3

Mocci E, Kundu P, Wheeler W, Arslan AA, Beane-Freeman LE, Bracci PM, et al.

Cancer Res, 2021 Jun 01;81(11):3134-3143.
PMID: 33574088 DOI: 10.1158/0008-5472.CAN-20-3267

Germline variation and smoking are independently associated with pancreatic ductal adenocarcinoma (PDAC). We conducted genome-wide smoking interaction analysis of PDAC using genotype data from four previous genome-wide association studies in individuals of European ancestry (7,937 cases and 11,774 controls). Examination of expression quantitative trait loci data from the Genotype-Tissue Expression Project followed by colocalization analysis was conducted to determine whether there was support for common SNP(s) underlying the observed associations. Statistical tests were two sided and P < 5 × 10-8 was considered statistically significant. Genome-wide significant evidence of qualitative interaction was identified on chr2q21.3 in intron 5 of the transmembrane protein 163 (TMEM163) and upstream of the cyclin T2 (CCNT2). The most significant SNP using the Empirical Bayes method, in this region that included 45 significantly associated SNPs, was rs1818613 [per allele OR in never smokers 0.87, 95% confidence interval (CI), 0.82-0.93; former smokers 1.00, 95% CI, 0.91-1.07; current smokers 1.25, 95% CI 1.12-1.40, P interaction = 3.08 × 10-9). Examination of the Genotype-Tissue Expression Project data demonstrated an expression quantitative trait locus in this region for TMEM163 and CCNT2 in several tissue types. Colocalization analysis supported a shared SNP, rs842357, in high linkage disequilibrium with rs1818613 (r 2 = 0. 94) driving both the observed interaction and the expression quantitative trait loci signals. Future studies are needed to confirm and understand the differential biologic mechanisms by smoking status that contribute to our PDAC findings. SIGNIFICANCE: This large genome-wide interaction study identifies a susceptibility locus on 2q21.3 that significantly modified PDAC risk by smoking status, providing insight into smoking-associated PDAC, with implications for prevention.
Fulltext Genome-Wide Association Study Data Reveal Genetic Susceptibility to Chronic Inflammatory Intestinal Diseases and Pancreatic Ductal Adenocarcinoma Risk

Yuan F, Hung RJ, Walsh N, Zhang H, Platz EA, Wheeler W, et al.

Cancer Res, 2020 Sep 15;80(18):4004-4013.
PMID: 32641412 DOI: 10.1158/0008-5472.CAN-20-0447

Registry-based epidemiologic studies suggest associations between chronic inflammatory intestinal diseases and pancreatic ductal adenocarcinoma (PDAC). As genetic susceptibility contributes to a large proportion of chronic inflammatory intestinal diseases, we hypothesize that the genomic regions surrounding established genome-wide associated variants for these chronic inflammatory diseases are associated with PDAC. We examined the association between PDAC and genomic regions (±500 kb) surrounding established common susceptibility variants for ulcerative colitis, Crohn's disease, inflammatory bowel disease, celiac disease, chronic pancreatitis, and primary sclerosing cholangitis. We analyzed summary statistics from genome-wide association studies data for 8,384 cases and 11,955 controls of European descent from two large consortium studies using the summary data-based adaptive rank truncated product method to examine the overall association of combined genomic regions for each inflammatory disease group. Combined genomic susceptibility regions for ulcerative colitis, Crohn disease, inflammatory bowel disease, and chronic pancreatitis were associated with PDAC at P values < 0.05 (0.0040, 0.0057, 0.011, and 3.4 × 10-6, respectively). After excluding the 20 PDAC susceptibility regions (±500 kb) previously identified by GWAS, the genomic regions for ulcerative colitis, Crohn disease, and inflammatory bowel disease remained associated with PDAC (P = 0.0029, 0.0057, and 0.0098, respectively). Genomic regions for celiac disease (P = 0.22) and primary sclerosing cholangitis (P = 0.078) were not associated with PDAC. Our results support the hypothesis that genomic regions surrounding variants associated with inflammatory intestinal diseases, particularly, ulcerative colitis, Crohn disease, inflammatory bowel disease, and chronic pancreatitis are associated with PDAC. SIGNIFICANCE: The joint effects of common variants in genomic regions containing susceptibility loci for inflammatory bowel disease and chronic pancreatitis are associated with PDAC and may provide insights to understanding pancreatic cancer etiology.
Fulltext Common variation at 2p13.3, 3q29, 7p13 and 17q25.1 associated with susceptibility to pancreatic cancer

Childs EJ, Mocci E, Campa D, Bracci PM, Gallinger S, Goggins M, et al.

Nat Genet, 2015 Aug;47(8):911-6.
PMID: 26098869 DOI: 10.1038/ng.3341

Pancreatic cancer is the fourth leading cause of cancer death in the developed world. Both inherited high-penetrance mutations in BRCA2 (ref. 2), ATM, PALB2 (ref. 4), BRCA1 (ref. 5), STK11 (ref. 6), CDKN2A and mismatch-repair genes and low-penetrance loci are associated with increased risk. To identify new risk loci, we performed a genome-wide association study on 9,925 pancreatic cancer cases and 11,569 controls, including 4,164 newly genotyped cases and 3,792 controls in 9 studies from North America, Central Europe and Australia. We identified three newly associated regions: 17q25.1 (LINC00673, rs11655237, odds ratio (OR) = 1.26, 95% confidence interval (CI) = 1.19-1.34, P = 1.42 × 10(-14)), 7p13 (SUGCT, rs17688601, OR = 0.88, 95% CI = 0.84-0.92, P = 1.41 × 10(-8)) and 3q29 (TP63, rs9854771, OR = 0.89, 95% CI = 0.85-0.93, P = 2.35 × 10(-8)). We detected significant association at 2p13.3 (ETAA1, rs1486134, OR = 1.14, 95% CI = 1.09-1.19, P = 3.36 × 10(-9)), a region with previous suggestive evidence in Han Chinese. We replicated previously reported associations at 9q34.2 (ABO), 13q22.1 (KLF5), 5p15.33 (TERT and CLPTM1), 13q12.2 (PDX1), 1q32.1 (NR5A2), 7q32.3 (LINC-PINT), 16q23.1 (BCAR1) and 22q12.1 (ZNRF3). Our study identifies new loci associated with pancreatic cancer risk.
Fulltext Genome-Wide Gene-Diabetes and Gene-Obesity Interaction Scan in 8,255 Cases and 11,900 Controls from PanScan and PanC4 Consortia

Tang H, Jiang L, Stolzenberg-Solomon RZ, Arslan AA, Beane Freeman LE, Bracci PM, et al.

Cancer Epidemiol Biomarkers Prev, 2020 Sep;29(9):1784-1791.
PMID: 32546605 DOI: 10.1158/1055-9965.EPI-20-0275

BACKGROUND: Obesity and diabetes are major modifiable risk factors for pancreatic cancer. Interactions between genetic variants and diabetes/obesity have not previously been comprehensively investigated in pancreatic cancer at the genome-wide level.
METHODS: We conducted a gene-environment interaction (GxE) analysis including 8,255 cases and 11,900 controls from four pancreatic cancer genome-wide association study (GWAS) datasets (Pancreatic Cancer Cohort Consortium I-III and Pancreatic Cancer Case Control Consortium). Obesity (body mass index ≥30 kg/m2) and diabetes (duration ≥3 years) were the environmental variables of interest. Approximately 870,000 SNPs (minor allele frequency ≥0.005, genotyped in at least one dataset) were analyzed. Case-control (CC), case-only (CO), and joint-effect test methods were used for SNP-level GxE analysis. As a complementary approach, gene-based GxE analysis was also performed. Age, sex, study site, and principal components accounting for population substructure were included as covariates. Meta-analysis was applied to combine individual GWAS summary statistics.
RESULTS: No genome-wide significant interactions (departures from a log-additive odds model) with diabetes or obesity were detected at the SNP level by the CC or CO approaches. The joint-effect test detected numerous genome-wide significant GxE signals in the GWAS main effects top hit regions, but the significance diminished after adjusting for the GWAS top hits. In the gene-based analysis, a significant interaction of diabetes with variants in the FAM63A (family with sequence similarity 63 member A) gene (significance threshold P < 1.25 × 10-6) was observed in the meta-analysis (P GxE = 1.2 ×10-6, P Joint = 4.2 ×10-7).
CONCLUSIONS: This analysis did not find significant GxE interactions at the SNP level but found one significant interaction with diabetes at the gene level. A larger sample size might unveil additional genetic factors via GxE scans.
IMPACT: This study may contribute to discovering the mechanism of diabetes-associated pancreatic cancer.
Fulltext Female chromosome X mosaicism is age-related and preferentially affects the inactivated X chromosome

Machiela MJ, Zhou W, Karlins E, Sampson JN, Freedman ND, Yang Q, et al.

Nat Commun, 2016 06 13;7:11843.
PMID: 27291797 DOI: 10.1038/ncomms11843

To investigate large structural clonal mosaicism of chromosome X, we analysed the SNP microarray intensity data of 38,303 women from cancer genome-wide association studies (20,878 cases and 17,425 controls) and detected 124 mosaic X events >2 Mb in 97 (0.25%) women. Here we show rates for X-chromosome mosaicism are four times higher than mean autosomal rates; X mosaic events more often include the entire chromosome and participants with X events more likely harbour autosomal mosaic events. X mosaicism frequency increases with age (0.11% in 50-year olds; 0.45% in 75-year olds), as reported for Y and autosomes. Methylation array analyses of 33 women with X mosaicism indicate events preferentially involve the inactive X chromosome. Our results provide further evidence that the sex chromosomes undergo mosaic events more frequently than autosomes, which could have implications for understanding the underlying mechanisms of mosaic events and their possible contribution to risk for chronic diseases.
Fulltext Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants

Dadaev T, Saunders EJ, Newcombe PJ, Anokian E, Leongamornlert DA, Brook MN, et al.

Nat Commun, 2018 06 11;9(1):2256.
PMID: 29892050 DOI: 10.1038/s41467-018-04109-8

Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling.
Fulltext Association analyses of more than 140,000 men identify 63 new prostate cancer susceptibility loci

Schumacher FR, Al Olama AA, Berndt SI, Benlloch S, Ahmed M, Saunders EJ, et al.

Nat Genet, 2018 07;50(7):928-936.
PMID: 29892016 DOI: 10.1038/s41588-018-0142-8

Genome-wide association studies (GWAS) and fine-mapping efforts to date have identified more than 100 prostate cancer (PrCa)-susceptibility loci. We meta-analyzed genotype data from a custom high-density array of 46,939 PrCa cases and 27,910 controls of European ancestry with previously genotyped data of 32,255 PrCa cases and 33,202 controls of European ancestry. Our analysis identified 62 novel loci associated (P C, p.Pro1054Arg) in ATM and rs2066827 (OR = 1.06; P = 2.3 × 10-9; T>G, p.Val109Gly) in CDKN1B. The combination of all loci captured 28.4% of the PrCa familial relative risk, and a polygenic risk score conferred an elevated PrCa risk for men in the ninetieth to ninety-ninth percentiles (relative risk = 2.69; 95% confidence interval (CI): 2.55-2.82) and first percentile (relative risk = 5.71; 95% CI: 5.04-6.48) risk stratum compared with the population average. These findings improve risk prediction, enhance fine-mapping, and provide insight into the underlying biology of PrCa1.
Author Correction: Association analyses of more than 140,000 men identify 63 new prostate cancer susceptibility loci

Schumacher FR, Olama AAA, Berndt SI, Benlloch S, Ahmed M, Saunders EJ, et al.

Nat Genet, 2019 02;51(2):363.
PMID: 30622367 DOI: 10.1038/s41588-018-0330-6

In the version of this article initially published, the name of author Manuela Gago-Dominguez was misspelled as Manuela Gago Dominguez. The error has been corrected in the HTML and PDF version of the article.
Fulltext Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction

Conti DV, Darst BF, Moss LC, Saunders EJ, Sheng X, Chou A, et al.

Nat Genet, 2021 Jan;53(1):65-75.
PMID: 33398198 DOI: 10.1038/s41588-020-00748-0

Prostate cancer is a highly heritable disease with large disparities in incidence rates across ancestry populations. We conducted a multiancestry meta-analysis of prostate cancer genome-wide association studies (107,247 cases and 127,006 controls) and identified 86 new genetic risk variants independently associated with prostate cancer risk, bringing the total to 269 known risk variants. The top genetic risk score (GRS) decile was associated with odds ratios that ranged from 5.06 (95% confidence interval (CI), 4.84-5.29) for men of European ancestry to 3.74 (95% CI, 3.36-4.17) for men of African ancestry. Men of African ancestry were estimated to have a mean GRS that was 2.18-times higher (95% CI, 2.14-2.22), and men of East Asian ancestry 0.73-times lower (95% CI, 0.71-0.76), than men of European ancestry. These findings support the role of germline variation contributing to population differences in prostate cancer risk, with the GRS offering an approach for personalized risk prediction.
Fulltext Genome-Wide Meta-Analyses of Breast, Ovarian, and Prostate Cancer Association Studies Identify Multiple New Susceptibility Loci Shared by at Least Two Cancer Types

Kar SP, Beesley J, Amin Al Olama A, Michailidou K, Tyrer J, Kote-Jarai Z, et al.

Cancer Discov, 2016 Sep;6(9):1052-67.
PMID: 27432226 DOI: 10.1158/2159-8290.CD-15-1227

Breast, ovarian, and prostate cancers are hormone-related and may have a shared genetic basis, but this has not been investigated systematically by genome-wide association (GWA) studies. Meta-analyses combining the largest GWA meta-analysis data sets for these cancers totaling 112,349 cases and 116,421 controls of European ancestry, all together and in pairs, identified at P < 10(-8) seven new cross-cancer loci: three associated with susceptibility to all three cancers (rs17041869/2q13/BCL2L11; rs7937840/11q12/INCENP; rs1469713/19p13/GATAD2A), two breast and ovarian cancer risk loci (rs200182588/9q31/SMC2; rs8037137/15q26/RCCD1), and two breast and prostate cancer risk loci (rs5013329/1p34/NSUN4; rs9375701/6q23/L3MBTL3). Index variants in five additional regions previously associated with only one cancer also showed clear association with a second cancer type. Cell-type-specific expression quantitative trait locus and enhancer-gene interaction annotations suggested target genes with potential cross-cancer roles at the new loci. Pathway analysis revealed significant enrichment of death receptor signaling genes near loci with P < 10(-5) in the three-cancer meta-analysis.
SIGNIFICANCE: We demonstrate that combining large-scale GWA meta-analysis findings across cancer types can identify completely new risk loci common to breast, ovarian, and prostate cancers. We show that the identification of such cross-cancer risk loci has the potential to shed new light on the shared biology underlying these hormone-related cancers. Cancer Discov; 6(9); 1052-67. ©2016 AACR.This article is highlighted in the In This Issue feature, p. 932.
Fulltext Genome-wide association analysis of more than 120,000 individuals identifies 15 new susceptibility loci for breast cancer

Michailidou K, Beesley J, Lindstrom S, Canisius S, Dennis J, Lush MJ, et al.

Nat Genet, 2015 Apr;47(4):373-80.
PMID: 25751625 DOI: 10.1038/ng.3242

Genome-wide association studies (GWAS) and large-scale replication studies have identified common variants in 79 loci associated with breast cancer, explaining ∼14% of the familial risk of the disease. To identify new susceptibility loci, we performed a meta-analysis of 11 GWAS, comprising 15,748 breast cancer cases and 18,084 controls together with 46,785 cases and 42,892 controls from 41 studies genotyped on a 211,155-marker custom array (iCOGS). Analyses were restricted to women of European ancestry. We generated genotypes for more than 11 million SNPs by imputation using the 1000 Genomes Project reference panel, and we identified 15 new loci associated with breast cancer at P < 5 × 10(-8). Combining association analysis with ChIP-seq chromatin binding data in mammary cell lines and ChIA-PET chromatin interaction data from ENCODE, we identified likely target genes in two regions: SETBP1 at 18q12.3 and RNF115 and PDZK1 at 1q21.1. One association appears to be driven by an amino acid substitution encoded in EXO1.
Publisher Correction: Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction

Conti DV, Darst BF, Moss LC, Saunders EJ, Sheng X, Chou A, et al.

Nat Genet, 2021 Mar;53(3):413.
PMID: 33473200 DOI: 10.1038/s41588-021-00786-2
Fulltext Genome-wide association study identifies 32 novel breast cancer susceptibility loci from overall and subtype-specific analyses

Zhang H, Ahearn TU, Lecarpentier J, Barnes D, Beesley J, Qi G, et al.

Nat Genet, 2020 06;52(6):572-581.
PMID: 32424353 DOI: 10.1038/s41588-020-0609-2

Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype1-3. To identify novel loci, we performed a genome-wide association study including 133,384 breast cancer cases and 113,789 controls, plus 18,908 BRCA1 mutation carriers (9,414 with breast cancer) of European ancestry, using both standard and novel methodologies that account for underlying tumor heterogeneity by estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 status and tumor grade. We identified 32 novel susceptibility loci (P
Fulltext Characterizing prostate cancer risk through multi-ancestry genome-wide discovery of 187 novel risk variants

Wang A, Shen J, Rodriguez AA, Saunders EJ, Chen F, Janivara R, et al.

Nat Genet, 2023 Dec;55(12):2065-2074.
PMID: 37945903 DOI: 10.1038/s41588-023-01534-4

The transferability and clinical value of genetic risk scores (GRSs) across populations remain limited due to an imbalance in genetic studies across ancestrally diverse populations. Here we conducted a multi-ancestry genome-wide association study of 156,319 prostate cancer cases and 788,443 controls of European, African, Asian and Hispanic men, reflecting a 57% increase in the number of non-European cases over previous prostate cancer genome-wide association studies. We identified 187 novel risk variants for prostate cancer, increasing the total number of risk variants to 451. An externally replicated multi-ancestry GRS was associated with risk that ranged from 1.8 (per standard deviation) in African ancestry men to 2.2 in European ancestry men. The GRS was associated with a greater risk of aggressive versus non-aggressive disease in men of African ancestry (P = 0.03). Our study presents novel prostate cancer susceptibility loci and a GRS with effective risk stratification across ancestry groups.
Fulltext Identification of four novel susceptibility loci for oestrogen receptor negative breast cancer

Couch FJ, Kuchenbaecker KB, Michailidou K, Mendoza-Fandino GA, Nord S, Lilyquist J, et al.

Nat Commun, 2016 Apr 27;7:11375.
PMID: 27117709 DOI: 10.1038/ncomms11375

Common variants in 94 loci have been associated with breast cancer including 15 loci with genome-wide significant associations (P<5 × 10(-8)) with oestrogen receptor (ER)-negative breast cancer and BRCA1-associated breast cancer risk. In this study, to identify new ER-negative susceptibility loci, we performed a meta-analysis of 11 genome-wide association studies (GWAS) consisting of 4,939 ER-negative cases and 14,352 controls, combined with 7,333 ER-negative cases and 42,468 controls and 15,252 BRCA1 mutation carriers genotyped on the iCOGS array. We identify four previously unidentified loci including two loci at 13q22 near KLF5, a 2p23.2 locus near WDR43 and a 2q33 locus near PPIL3 that display genome-wide significant associations with ER-negative breast cancer. In addition, 19 known breast cancer risk loci have genome-wide significant associations and 40 had moderate associations (P<0.05) with ER-negative disease. Using functional and eQTL studies we implicate TRMT61B and WDR43 at 2p23.2 and PPIL3 at 2q33 in ER-negative breast cancer aetiology. All ER-negative loci combined account for ∼11% of familial relative risk for ER-negative disease and may contribute to improved ER-negative and BRCA1 breast cancer risk prediction.

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