Displaying publications 1 - 20 of 21 in total

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  1. Lujan-Barroso L, Zhang W, Olson SH, Gao YT, Yu H, Baghurst PA, et al.
    Pancreas, 2016 11;45(10):1401-1410.
    PMID: 27088489
    OBJECTIVES: We aimed to evaluate the relation between menstrual and reproductive factors, exogenous hormones, and risk of pancreatic cancer (PC).

    METHODS: Eleven case-control studies within the International Pancreatic Cancer Case-control Consortium took part in the present study, including in total 2838 case and 4748 control women. Pooled estimates of odds ratios (ORs) and their 95% confidence intervals (CIs) were calculated using a 2-step logistic regression model and adjusting for relevant covariates.

    RESULTS: An inverse OR was observed in women who reported having had hysterectomy (ORyesvs.no, 0.78; 95% CI, 0.67-0.91), remaining significant in postmenopausal women and never-smoking women, adjusted for potential PC confounders. A mutually adjusted model with the joint effect for hormone replacement therapy (HRT) and hysterectomy showed significant inverse associations with PC in women who reported having had hysterectomy with HRT use (OR, 0.64; 95% CI, 0.48-0.84).

    CONCLUSIONS: Our large pooled analysis suggests that women who have had a hysterectomy may have reduced risk of PC. However, we cannot rule out that the reduced risk could be due to factors or indications for having had a hysterectomy. Further investigation of risk according to HRT use and reason for hysterectomy may be necessary.

  2. Martinez S, Sullivan A, Hagan E, Goley J, Epstein JH, Olival KJ, et al.
    Glob Health Sci Pract, 2022 Dec 21;10(6).
    PMID: 36951282 DOI: 10.9745/GHSP-D-22-00106
    As part of a public health behavior change and communication strategy related to the identification of a novel ebolavirus in bats in Sierra Leone in 2016, a consortium of experts launched an effort to create a widely accessible resource for community awareness and education on reducing disease risk. The resulting picture book, Living Safely With Bats, includes technical content developed by a consortium of experts in public health, animal health, conservation, bats, and disease ecology from 30 countries. The book has now been adapted, translated, and used in more than 20 countries in Africa and Asia. We review the processes used to integrate feedback from local stakeholders and multidisciplinary experts. We also provide recommendations for One Health and other practitioners who choose to pursue the development and evaluation of this or similar zoonotic disease risk mitigation tools.
  3. Campa D, Rizzato C, Stolzenberg-Solomon R, Pacetti P, Vodicka P, Cleary SP, et al.
    Int J Cancer, 2015 Nov 01;137(9):2175-83.
    PMID: 25940397 DOI: 10.1002/ijc.29590
    A small number of common susceptibility loci have been identified for pancreatic cancer, one of which is marked by rs401681 in the TERT-CLPTM1L gene region on chromosome 5p15.33. Because this region is characterized by low linkage disequilibrium, we sought to identify whether additional single nucleotide polymorphisms (SNPs) could be related to pancreatic cancer risk, independently of rs401681. We performed an in-depth analysis of genetic variability of the telomerase reverse transcriptase (TERT) and the telomerase RNA component (TERC) genes, in 5,550 subjects with pancreatic cancer and 7,585 controls from the PANcreatic Disease ReseArch (PANDoRA) and the PanScan consortia. We identified a significant association between a variant in TERT and pancreatic cancer risk (rs2853677, odds ratio = 0.85; 95% confidence interval = 0.80-0.90, p = 8.3 × 10(-8)). Additional analysis adjusting rs2853677 for rs401681 indicated that the two SNPs are independently associated with pancreatic cancer risk, as suggested by the low linkage disequilibrium between them (r(2) = 0.07, D' = 0.28). Three additional SNPs in TERT reached statistical significance after correction for multiple testing: rs2736100 (p = 3.0 × 10(-5) ), rs4583925 (p = 4.0 × 10(-5) ) and rs2735948 (p = 5.0 × 10(-5) ). In conclusion, we confirmed that the TERT locus is associated with pancreatic cancer risk, possibly through several independent variants.
  4. 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.
  5. Klein AP, Wolpin BM, Risch HA, Stolzenberg-Solomon RZ, Mocci E, Zhang M, et al.
    Nat Commun, 2018 02 08;9(1):556.
    PMID: 29422604 DOI: 10.1038/s41467-018-02942-5
    In 2020, 146,063 deaths due to pancreatic cancer are estimated to occur in Europe and the United States combined. To identify common susceptibility alleles, we performed the largest pancreatic cancer GWAS to date, including 9040 patients and 12,496 controls of European ancestry from the Pancreatic Cancer Cohort Consortium (PanScan) and the Pancreatic Cancer Case-Control Consortium (PanC4). Here, we find significant evidence of a novel association at rs78417682 (7p12/TNS3, P = 4.35 × 10-8). Replication of 10 promising signals in up to 2737 patients and 4752 controls from the PANcreatic Disease ReseArch (PANDoRA) consortium yields new genome-wide significant loci: rs13303010 at 1p36.33 (NOC2L, P = 8.36 × 10-14), rs2941471 at 8q21.11 (HNF4G, P = 6.60 × 10-10), rs4795218 at 17q12 (HNF1B, P = 1.32 × 10-8), and rs1517037 at 18q21.32 (GRP, P = 3.28 × 10-8). rs78417682 is not statistically significantly associated with pancreatic cancer in PANDoRA. Expression quantitative trait locus analysis in three independent pancreatic data sets provides molecular support of NOC2L as a pancreatic cancer susceptibility gene.
  6. Zhang M, Wang Z, Obazee O, Jia J, Childs EJ, Hoskins J, et al.
    Oncotarget, 2016 Oct 11;7(41):66328-66343.
    PMID: 27579533 DOI: 10.18632/oncotarget.11041
    Genome-wide association studies (GWAS) have identified common pancreatic cancer susceptibility variants at 13 chromosomal loci in individuals of European descent. To identify new susceptibility variants, we performed imputation based on 1000 Genomes (1000G) Project data and association analysis using 5,107 case and 8,845 control subjects from 27 cohort and case-control studies that participated in the PanScan I-III GWAS. This analysis, in combination with a two-staged replication in an additional 6,076 case and 7,555 control subjects from the PANcreatic Disease ReseArch (PANDoRA) and Pancreatic Cancer Case-Control (PanC4) Consortia uncovered 3 new pancreatic cancer risk signals marked by single nucleotide polymorphisms (SNPs) rs2816938 at chromosome 1q32.1 (per allele odds ratio (OR) = 1.20, P = 4.88x10 -15), rs10094872 at 8q24.21 (OR = 1.15, P = 3.22x10 -9) and rs35226131 at 5p15.33 (OR = 0.71, P = 1.70x10 -8). These SNPs represent independent risk variants at previously identified pancreatic cancer risk loci on chr1q32.1 ( NR5A2), chr8q24.21 ( MYC) and chr5p15.33 ( CLPTM1L- TERT) as per analyses conditioned on previously reported susceptibility variants. We assessed expression of candidate genes at the three risk loci in histologically normal ( n = 10) and tumor ( n = 8) derived pancreatic tissue samples and observed a marked reduction of NR5A2 expression (chr1q32.1) in the tumors (fold change -7.6, P = 5.7x10 -8). This finding was validated in a second set of paired ( n = 20) histologically normal and tumor derived pancreatic tissue samples (average fold change for three NR5A2 isoforms -31.3 to -95.7, P = 7.5x10 -4-2.0x10 -3). Our study has identified new susceptibility variants independently conferring pancreatic cancer risk that merit functional follow-up to identify target genes and explain the underlying biology.
  7. Walsh N, Zhang H, Hyland PL, Yang Q, Mocci E, Zhang M, et al.
    J Natl Cancer Inst, 2019 Jun 01;111(6):557-567.
    PMID: 30541042 DOI: 10.1093/jnci/djy155
    BACKGROUND: Genome-wide association studies (GWAS) identify associations of individual single-nucleotide polymorphisms (SNPs) with cancer risk but usually only explain a fraction of the inherited variability. Pathway analysis of genetic variants is a powerful tool to identify networks of susceptibility genes.

    METHODS: We conducted a large agnostic pathway-based meta-analysis of GWAS data using the summary-based adaptive rank truncated product method to identify gene sets and pathways associated with pancreatic ductal adenocarcinoma (PDAC) in 9040 cases and 12 496 controls. We performed expression quantitative trait loci (eQTL) analysis and functional annotation of the top SNPs in genes contributing to the top associated pathways and gene sets. All statistical tests were two-sided.

    RESULTS: We identified 14 pathways and gene sets associated with PDAC at a false discovery rate of less than 0.05. After Bonferroni correction (P ≤ 1.3 × 10-5), the strongest associations were detected in five pathways and gene sets, including maturity-onset diabetes of the young, regulation of beta-cell development, role of epidermal growth factor (EGF) receptor transactivation by G protein-coupled receptors in cardiac hypertrophy pathways, and the Nikolsky breast cancer chr17q11-q21 amplicon and Pujana ATM Pearson correlation coefficient (PCC) network gene sets. We identified and validated rs876493 and three correlating SNPs (PGAP3) and rs3124737 (CASP7) from the Pujana ATM PCC gene set as eQTLs in two normal derived pancreas tissue datasets.

    CONCLUSION: Our agnostic pathway and gene set analysis integrated with functional annotation and eQTL analysis provides insight into genes and pathways that may be biologically relevant for risk of PDAC, including those not previously identified.

  8. Amankwah EK, Lin HY, Tyrer JP, Lawrenson K, Dennis J, Chornokur G, et al.
    Genet Epidemiol, 2015 Dec;39(8):689-97.
    PMID: 26399219 DOI: 10.1002/gepi.21921
    Epithelial-mesenchymal transition (EMT) is a process whereby epithelial cells assume mesenchymal characteristics to facilitate cancer metastasis. However, EMT also contributes to the initiation and development of primary tumors. Prior studies that explored the hypothesis that EMT gene variants contribute to epithelial ovarian carcinoma (EOC) risk have been based on small sample sizes and none have sought replication in an independent population. We screened 15,816 single-nucleotide polymorphisms (SNPs) in 296 genes in a discovery phase using data from a genome-wide association study of EOC among women of European ancestry (1,947 cases and 2,009 controls) and identified 793 variants in 278 EMT-related genes that were nominally (P < 0.05) associated with invasive EOC. These SNPs were then genotyped in a larger study of 14,525 invasive-cancer patients and 23,447 controls. A P-value <0.05 and a false discovery rate (FDR) <0.2 were considered statistically significant. In the larger dataset, GPC6/GPC5 rs17702471 was associated with the endometrioid subtype among Caucasians (odds ratio (OR) = 1.16, 95% CI = 1.07-1.25, P = 0.0003, FDR = 0.19), whereas F8 rs7053448 (OR = 1.69, 95% CI = 1.27-2.24, P = 0.0003, FDR = 0.12), F8 rs7058826 (OR = 1.69, 95% CI = 1.27-2.24, P = 0.0003, FDR = 0.12), and CAPN13 rs1983383 (OR = 0.79, 95% CI = 0.69-0.90, P = 0.0005, FDR = 0.12) were associated with combined invasive EOC among Asians. In silico functional analyses revealed that GPC6/GPC5 rs17702471 coincided with DNA regulatory elements. These results suggest that EMT gene variants do not appear to play a significant role in the susceptibility to EOC.
  9. Jim HS, Lin HY, Tyrer JP, Lawrenson K, Dennis J, Chornokur G, et al.
    J Genet Genome Res, 2015 09 15;2(2).
    PMID: 26807442
    Disruption in circadian gene expression, whether due to genetic variation or environmental factors (e.g., light at night, shiftwork), is associated with increased incidence of breast, prostate, gastrointestinal and hematologic cancers and gliomas. Circadian genes are highly expressed in the ovaries where they regulate ovulation; circadian disruption is associated with several ovarian cancer risk factors (e.g., endometriosis). However, no studies have examined variation in germline circadian genes as predictors of ovarian cancer risk and invasiveness. The goal of the current study was to examine single nucleotide polymorphisms (SNPs) in circadian genes BMAL1, CRY2, CSNK1E, NPAS2, PER3, REV1 and TIMELESS and downstream transcription factors KLF10 and SENP3 as predictors of risk of epithelial ovarian cancer (EOC) and histopathologic subtypes. The study included a test set of 3,761 EOC cases and 2,722 controls and a validation set of 44,308 samples including 18,174 (10,316 serous) cases and 26,134 controls from 43 studies participating in the Ovarian Cancer Association Consortium (OCAC). Analysis of genotype data from 36 genotyped SNPs and 4600 imputed SNPs indicated that the most significant association was rs117104877 in BMAL1 (OR = 0.79, 95% CI = 0.68-0.90, p = 5.59 × 10-4]. Functional analysis revealed a significant down regulation of BMAL1 expression following cMYC overexpression and increasing transformation in ovarian surface epithelial (OSE) cells as well as alternative splicing of BMAL1 exons in ovarian and granulosa cells. These results suggest that variation in circadian genes, and specifically BMAL1, may be associated with risk of ovarian cancer, likely through disruption of hormonal pathways.
  10. Chornokur G, Lin HY, Tyrer JP, Lawrenson K, Dennis J, Amankwah EK, et al.
    PLoS One, 2015;10(6):e0128106.
    PMID: 26091520 DOI: 10.1371/journal.pone.0128106
    BACKGROUND: Defective cellular transport processes can lead to aberrant accumulation of trace elements, iron, small molecules and hormones in the cell, which in turn may promote the formation of reactive oxygen species, promoting DNA damage and aberrant expression of key regulatory cancer genes. As DNA damage and uncontrolled proliferation are hallmarks of cancer, including epithelial ovarian cancer (EOC), we hypothesized that inherited variation in the cellular transport genes contributes to EOC risk.

    METHODS: In total, DNA samples were obtained from 14,525 case subjects with invasive EOC and from 23,447 controls from 43 sites in the Ovarian Cancer Association Consortium (OCAC). Two hundred seventy nine SNPs, representing 131 genes, were genotyped using an Illumina Infinium iSelect BeadChip as part of the Collaborative Oncological Gene-environment Study (COGS). SNP analyses were conducted using unconditional logistic regression under a log-additive model, and the FDR q<0.2 was applied to adjust for multiple comparisons.

    RESULTS: The most significant evidence of an association for all invasive cancers combined and for the serous subtype was observed for SNP rs17216603 in the iron transporter gene HEPH (invasive: OR = 0.85, P = 0.00026; serous: OR = 0.81, P = 0.00020); this SNP was also associated with the borderline/low malignant potential (LMP) tumors (P = 0.021). Other genes significantly associated with EOC histological subtypes (p<0.05) included the UGT1A (endometrioid), SLC25A45 (mucinous), SLC39A11 (low malignant potential), and SERPINA7 (clear cell carcinoma). In addition, 1785 SNPs in six genes (HEPH, MGST1, SERPINA, SLC25A45, SLC39A11 and UGT1A) were imputed from the 1000 Genomes Project and examined for association with INV EOC in white-European subjects. The most significant imputed SNP was rs117729793 in SLC39A11 (per allele, OR = 2.55, 95% CI = 1.5-4.35, p = 5.66x10-4).

    CONCLUSION: These results, generated on a large cohort of women, revealed associations between inherited cellular transport gene variants and risk of EOC histologic subtypes.

  11. Lawrenson K, Li Q, Kar S, Seo JH, Tyrer J, Spindler TJ, et al.
    Nat Commun, 2015 Sep 22;6:8234.
    PMID: 26391404 DOI: 10.1038/ncomms9234
    Genome-wide association studies have reported 11 regions conferring risk of high-grade serous epithelial ovarian cancer (HGSOC). Expression quantitative trait locus (eQTL) analyses can identify candidate susceptibility genes at risk loci. Here we evaluate cis-eQTL associations at 47 regions associated with HGSOC risk (P≤10(-5)). For three cis-eQTL associations (P<1.4 × 10(-3), FDR<0.05) at 1p36 (CDC42), 1p34 (CDCA8) and 2q31 (HOXD9), we evaluate the functional role of each candidate by perturbing expression of each gene in HGSOC precursor cells. Overexpression of HOXD9 increases anchorage-independent growth, shortens population-doubling time and reduces contact inhibition. Chromosome conformation capture identifies an interaction between rs2857532 and the HOXD9 promoter, suggesting this SNP is a leading causal variant. Transcriptomic profiling after HOXD9 overexpression reveals enrichment of HGSOC risk variants within HOXD9 target genes (P=6 × 10(-10) for risk variants (P<10(-4)) within 10 kb of a HOXD9 target gene in ovarian cells), suggesting a broader role for this network in genetic susceptibility to HGSOC.
  12. Earp M, Tyrer JP, Winham SJ, Lin HY, Chornokur G, Dennis J, et al.
    PLoS One, 2018;13(7):e0197561.
    PMID: 29979793 DOI: 10.1371/journal.pone.0197561
    Epithelial ovarian cancer (EOC) is the fifth leading cause of cancer mortality in American women. Normal ovarian physiology is intricately connected to small GTP binding proteins of the Ras superfamily (Ras, Rho, Rab, Arf, and Ran) which govern processes such as signal transduction, cell proliferation, cell motility, and vesicle transport. We hypothesized that common germline variation in genes encoding small GTPases is associated with EOC risk. We investigated 322 variants in 88 small GTPase genes in germline DNA of 18,736 EOC patients and 26,138 controls of European ancestry using a custom genotype array and logistic regression fitting log-additive models. Functional annotation was used to identify biofeatures and expression quantitative trait loci that intersect with risk variants. One variant, ARHGEF10L (Rho guanine nucleotide exchange factor 10 like) rs2256787, was associated with increased endometrioid EOC risk (OR = 1.33, p = 4.46 x 10-6). Other variants of interest included another in ARHGEF10L, rs10788679, which was associated with invasive serous EOC risk (OR = 1.07, p = 0.00026) and two variants in AKAP6 (A-kinase anchoring protein 6) which were associated with risk of invasive EOC (rs1955513, OR = 0.90, p = 0.00033; rs927062, OR = 0.94, p = 0.00059). Functional annotation revealed that the two ARHGEF10L variants were located in super-enhancer regions and that AKAP6 rs927062 was associated with expression of GTPase gene ARHGAP5 (Rho GTPase activating protein 5). Inherited variants in ARHGEF10L and AKAP6, with potential transcriptional regulatory function and association with EOC risk, warrant investigation in independent EOC study populations.
  13. Hampras SS, Sucheston-Campbell LE, Cannioto R, Chang-Claude J, Modugno F, Dörk T, et al.
    Oncotarget, 2016 10 25;7(43):69097-69110.
    PMID: 27533245 DOI: 10.18632/oncotarget.10215
    BACKGROUND: Regulatory T (Treg) cells, a subset of CD4+ T lymphocytes, are mediators of immunosuppression in cancer, and, thus, variants in genes encoding Treg cell immune molecules could be associated with ovarian cancer.

    METHODS: In a population of 15,596 epithelial ovarian cancer (EOC) cases and 23,236 controls, we measured genetic associations of 1,351 SNPs in Treg cell pathway genes with odds of ovarian cancer and tested pathway and gene-level associations, overall and by histotype, for the 25 genes, using the admixture likelihood (AML) method. The most significant single SNP associations were tested for correlation with expression levels in 44 ovarian cancer patients.

    RESULTS: The most significant global associations for all genes in the pathway were seen in endometrioid ( p = 0.082) and clear cell ( p = 0.083), with the most significant gene level association seen with TGFBR2 ( p = 0.001) and clear cell EOC. Gene associations with histotypes at p < 0.05 included: IL12 ( p = 0.005 and p = 0.008, serous and high-grade serous, respectively), IL8RA ( p = 0.035, endometrioid and mucinous), LGALS1 ( p = 0.03, mucinous), STAT5B ( p = 0.022, clear cell), TGFBR1 ( p = 0.021 endometrioid) and TGFBR2 ( p = 0.017 and p = 0.025, endometrioid and mucinous, respectively).

    CONCLUSIONS: Common inherited gene variation in Treg cell pathways shows some evidence of germline genetic contribution to odds of EOC that varies by histologic subtype and may be associated with mRNA expression of immune-complex receptor in EOC patients.

  14. Lu Y, Beeghly-Fadiel A, Wu L, Guo X, Li B, Schildkraut JM, et al.
    Cancer Res, 2018 Sep 15;78(18):5419-5430.
    PMID: 30054336 DOI: 10.1158/0008-5472.CAN-18-0951
    Large-scale genome-wide association studies (GWAS) have identified approximately 35 loci associated with epithelial ovarian cancer (EOC) risk. The majority of GWAS-identified disease susceptibility variants are located in noncoding regions, and causal genes underlying these associations remain largely unknown. Here, we performed a transcriptome-wide association study to search for novel genetic loci and plausible causal genes at known GWAS loci. We used RNA sequencing data (68 normal ovarian tissue samples from 68 individuals and 6,124 cross-tissue samples from 369 individuals) and high-density genotyping data from European descendants of the Genotype-Tissue Expression (GTEx V6) project to build ovarian and cross-tissue models of genetically regulated expression using elastic net methods. We evaluated 17,121 genes for their cis-predicted gene expression in relation to EOC risk using summary statistics data from GWAS of 97,898 women, including 29,396 EOC cases. With a Bonferroni-corrected significance level of P < 2.2 × 10-6, we identified 35 genes, including FZD4 at 11q14.2 (Z = 5.08, P = 3.83 × 10-7, the cross-tissue model; 1 Mb away from any GWAS-identified EOC risk variant), a potential novel locus for EOC risk. All other 34 significantly associated genes were located within 1 Mb of known GWAS-identified loci, including 23 genes at 6 loci not previously linked to EOC risk. Upon conditioning on nearby known EOC GWAS-identified variants, the associations for 31 genes disappeared and three genes remained (P < 1.47 × 10-3). These data identify one novel locus (FZD4) and 34 genes at 13 known EOC risk loci associated with EOC risk, providing new insights into EOC carcinogenesis.Significance: Transcriptomic analysis of a large cohort confirms earlier GWAS loci and reveals FZD4 as a novel locus associated with EOC risk. Cancer Res; 78(18); 5419-30. ©2018 AACR.
  15. Lawrenson K, Iversen ES, Tyrer J, Weber RP, Concannon P, Hazelett DJ, et al.
    Carcinogenesis, 2015 Nov;36(11):1341-53.
    PMID: 26424751 DOI: 10.1093/carcin/bgv138
    Genome-wide association studies have identified 20 genomic regions associated with risk of epithelial ovarian cancer (EOC), but many additional risk variants may exist. Here, we evaluated associations between common genetic variants [single nucleotide polymorphisms (SNPs) and indels] in DNA repair genes and EOC risk. We genotyped 2896 common variants at 143 gene loci in DNA samples from 15 397 patients with invasive EOC and controls. We found evidence of associations with EOC risk for variants at FANCA, EXO1, E2F4, E2F2, CREB5 and CHEK2 genes (P ≤ 0.001). The strongest risk association was for CHEK2 SNP rs17507066 with serous EOC (P = 4.74 x 10(-7)). Additional genotyping and imputation of genotypes from the 1000 genomes project identified a slightly more significant association for CHEK2 SNP rs6005807 (r (2) with rs17507066 = 0.84, odds ratio (OR) 1.17, 95% CI 1.11-1.24, P = 1.1×10(-7)). We identified 293 variants in the region with likelihood ratios of less than 1:100 for representing the causal variant. Functional annotation identified 25 candidate SNPs that alter transcription factor binding sites within regulatory elements active in EOC precursor tissues. In The Cancer Genome Atlas dataset, CHEK2 gene expression was significantly higher in primary EOCs compared to normal fallopian tube tissues (P = 3.72×10(-8)). We also identified an association between genotypes of the candidate causal SNP rs12166475 (r (2) = 0.99 with rs6005807) and CHEK2 expression (P = 2.70×10(-8)). These data suggest that common variants at 22q12.1 are associated with risk of serous EOC and CHEK2 as a plausible target susceptibility gene.
  16. Kar SP, Tyrer JP, Li Q, Lawrenson K, Aben KK, Anton-Culver H, et al.
    Cancer Epidemiol Biomarkers Prev, 2015 Oct;24(10):1574-84.
    PMID: 26209509 DOI: 10.1158/1055-9965.EPI-14-1270
    BACKGROUND: Genome-wide association studies (GWAS) have so far reported 12 loci associated with serous epithelial ovarian cancer (EOC) risk. We hypothesized that some of these loci function through nearby transcription factor (TF) genes and that putative target genes of these TFs as identified by coexpression may also be enriched for additional EOC risk associations.

    METHODS: We selected TF genes within 1 Mb of the top signal at the 12 genome-wide significant risk loci. Mutual information, a form of correlation, was used to build networks of genes strongly coexpressed with each selected TF gene in the unified microarray dataset of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this dataset were subsequently ranked using a gene-level test based on results for germline SNPs from a serous EOC GWAS meta-analysis (2,196 cases/4,396 controls).

    RESULTS: Gene set enrichment analysis identified six networks centered on TF genes (HOXB2, HOXB5, HOXB6, HOXB7 at 17q21.32 and HOXD1, HOXD3 at 2q31) that were significantly enriched for genes from the risk-associated end of the ranked list (P < 0.05 and FDR < 0.05). These results were replicated (P < 0.05) using an independent association study (7,035 cases/21,693 controls). Genes underlying enrichment in the six networks were pooled into a combined network.

    CONCLUSION: We identified a HOX-centric network associated with serous EOC risk containing several genes with known or emerging roles in serous EOC development.

    IMPACT: Network analysis integrating large, context-specific datasets has the potential to offer mechanistic insights into cancer susceptibility and prioritize genes for experimental characterization.

  17. 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.
  18. 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.

  19. Kuchenbaecker KB, Ramus SJ, Tyrer J, Lee A, Shen HC, Beesley J, et al.
    Nat Genet, 2015 Feb;47(2):164-71.
    PMID: 25581431 DOI: 10.1038/ng.3185
    Genome-wide association studies (GWAS) have identified 12 epithelial ovarian cancer (EOC) susceptibility alleles. The pattern of association at these loci is consistent in BRCA1 and BRCA2 mutation carriers who are at high risk of EOC. After imputation to 1000 Genomes Project data, we assessed associations of 11 million genetic variants with EOC risk from 15,437 cases unselected for family history and 30,845 controls and from 15,252 BRCA1 mutation carriers and 8,211 BRCA2 mutation carriers (3,096 with ovarian cancer), and we combined the results in a meta-analysis. This new study design yielded increased statistical power, leading to the discovery of six new EOC susceptibility loci. Variants at 1p36 (nearest gene, WNT4), 4q26 (SYNPO2), 9q34.2 (ABO) and 17q11.2 (ATAD5) were associated with EOC risk, and at 1p34.3 (RSPO1) and 6p22.1 (GPX6) variants were specifically associated with the serous EOC subtype, all with P < 5 × 10(-8). Incorporating these variants into risk assessment tools will improve clinical risk predictions for BRCA1 and BRCA2 mutation carriers.
  20. Dareng EO, Tyrer JP, Barnes DR, Jones MR, Yang X, Aben KKH, et al.
    Eur J Hum Genet, 2022 Jan 14.
    PMID: 35027648 DOI: 10.1038/s41431-021-00987-7
    Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, "select and shrink for summary statistics" (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28-1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08-1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21-1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29-1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35-1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs.
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