Kelemen, Linda E.

Abstract 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.

Abstract Epithelial ovarian cancer (EOC) is a rare but deadly disease for which there is notably poorer survival in women of African Ancestry (AA) compared to women of European Ancestry (EA). Previous EA-based genome-wide association studies (GWAS) have identified 30 common, low penetrant EOC susceptibility alleles. Using the custom-designed 533,631 SNP Illumina OncoArray and imputation to ~12 million genetic variants in the 1000 Genomes Phase 3, we conducted a GWAS in 755 AA EOC cases, including 537 high-grade serous ovarian cancer (HGSOC) cases, and 1,235 AA controls from the Ovarian Cancer Association Consortium (OCAC). We identified novel susceptibility loci with suggestive evidence of association with EOC, based on a threshold of P<1x10-6, at three distinct loci including 10p15.1 (lead SNP rs4525119, intronic to AKR1C3, P=4.9 x 10-7, minor allele frequency [MAF]=0.33), 3p25.3 (lead SNP rs7643459, intronic to LOC101927394, P=8.4 x 10-7, MAF=0.36), and 4q13.3 (lead SNP rs4286604, 15 kb 3’ of UGT2A1, P=8.5x10-7, MAF=0.27). In analysis of HGSOC, we identified suggestive evidence of association at six distinct loci including 5q11.2 (lead SNP rs37792, 132 kb 5’ of FST, P=6.0x10-8, MAF=0.34), Xq27.2 (lead SNP rs57403204, 81 kb 3' of MAGEC1, P=1.7x10-7, MAF=0.06), 10p15.1 (lead SNP rs79079890, LOC105376360 intronic, P=3.0x10-7, MAF=0.03), 17p25.1 (lead SNP rs66459581, 5 kb 5’ of PRPSAP1, P=5.1x10-7, MAF=0.23), 15p12 (lead SNP rs116046250, GABRG3 intronic, P=8.7x10-7, MAF=0.05), and 4q21.21 (lead SNP rs192876988, 30 kb 3’ of GK2, P=9.2x10-7, MAF=0.05). These SNPs showed no evidence of association with risk in the OCAC EA GWAS including up to 23,543 EOC cases and 29,444 controls. Of the SNPs identified with suggestive evidence of association in our GWAS, two are located near genes known to regulate hormones and previously reported in relation to diseases of the ovary (AKR1C3 and FST), two have been linked to cancer (AKR1C3 and MAGEC1) and one represents testis-specific expression (GK2). Of the 30 SNPs identified previously in a EA EOC GWAS, we observed nominally significant associations (P<0.05) with consistent direction of effect for eight SNPs in AA women. Our investigation presents evidence of (1) variants for EOC shared among EA and AA women and (2) novel EOC risk loci of importance for AA women. Citation Format: Ani Manichaikul, Lauren C. Peres, Xin-Qun Wang, Kate Lawrenson, Sarah Abbott, Ann G. Schwartz, Anna H. Wu, Edward Peters, Patricia G. Moorman, Michele L. Cote, Melissa Bondy, Linda Kelemen, Ellen L. Goode, Jill Barnholtz-Sloan, Simon A. Gather, Andrew Berchuck, Jennifer A. Doherty, Paul Pharoah, Joellen Schildkraut. Identification of novel epithelial ovarian cancer loci in women of African ancestry from the Ovarian Cancer Association Consortium [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1307. doi:10.1158/1538-7445.AM2017-1307

Abstract Background: Epigenetic disturbances are crucial in cancer initiation, potentially with pleiotropic effects, and may be influenced by the genetic background. Methods: In a subsets (ASSET) meta-analytic approach, we investigated associations of genetic variants related to epigenetic mechanisms with risks of breast, lung, colorectal, ovarian and prostate carcinomas using 51,724 cases and 52,001 controls. False discovery rate–corrected P values (q values < 0.05) were considered statistically significant. Results: Among 162,887 imputed or genotyped variants in 555 candidate genes, SNPs in eight genes were associated with risk of more than one cancer type. For example, variants in BABAM1 were confirmed as a susceptibility locus for squamous cell lung, overall breast, estrogen receptor (ER)–negative breast, and overall prostate, and overall serous ovarian cancer; the most significant variant was rs4808076 [OR = 1.14; 95% confidence interval (CI) = 1.10–1.19; q = 6.87 × 10−5]. DPF1 rs12611084 was inversely associated with ER-negative breast, endometrioid ovarian, and overall and aggressive prostate cancer risk (OR = 0.93; 95% CI = 0.91–0.96; q = 0.005). Variants in L3MBTL3 were associated with colorectal, overall breast, ER-negative breast, clear cell ovarian, and overall and aggressive prostate cancer risk (e.g., rs9388766: OR = 1.06; 95% CI = 1.03–1.08; q = 0.02). Variants in TET2 were significantly associated with overall breast, overall prostate, overall ovarian, and endometrioid ovarian cancer risk, with rs62331150 showing bidirectional effects. Analyses of subpathways did not reveal gene subsets that contributed disproportionately to susceptibility. Conclusions: Functional and correlative studies are now needed to elucidate the potential links between germline genotype, epigenetic function, and cancer etiology. Impact: This approach provides novel insight into possible pleiotropic effects of genes involved in epigenetic processes. Cancer Epidemiol Biomarkers Prev; 26(6); 816–25. ©2017 AACR.

Abstract 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.

Background The rarity of mutations in PALB2, CHEK2 and ATM make it difficult to estimate precisely associated cancer risks. Population-based family studies have provided evidence that at least some of these mutations are associated with breast cancer risk as high as those associated with rare BRCA2 mutations. We aimed to estimate the relative risks associated with specific rare variants in PALB2, CHEK2 and ATM via a multicentre case-control study. Methods We genotyped 10 rare mutations using the custom iCOGS array: PALB2 c.1592delT, c.2816T>G and c.3113G>A, CHEK2 c.349A>G, c.538C>T, c.715G>A, c.1036C>T, c.1312G>T, and c.1343T>G and ATM c.7271T>G. We assessed associations with breast cancer risk (42 671 cases and 42 164 controls), as well as prostate (22 301 cases and 22 320 controls) and ovarian (14 542 cases and 23 491 controls) cancer risk, for each variant. Results For European women, strong evidence of association with breast cancer risk was observed for PALB2 c.1592delT OR 3.44 (95% CI 1.39 to 8.52, p=7.1×10−5), PALB2 c.3113G>A OR 4.21 (95% CI 1.84 to 9.60, p=6.9×10−8) and ATM c.7271T>G OR 11.0 (95% CI 1.42 to 85.7, p=0.0012). We also found evidence of association with breast cancer risk for three variants in CHEK2, c.349A>G OR 2.26 (95% CI 1.29 to 3.95), c.1036C>T OR 5.06 (95% CI 1.09 to 23.5) and c.538C>T OR 1.33 (95% CI 1.05 to 1.67) (p≤0.017). Evidence for prostate cancer risk was observed for CHEK2 c.1343T>G OR 3.03 (95% CI 1.53 to 6.03, p=0.0006) for African men and CHEK2 c.1312G>T OR 2.21 (95% CI 1.06 to 4.63, p=0.030) for European men. No evidence of association with ovarian cancer was found for any of these variants. Conclusions This report adds to accumulating evidence that at least some variants in these genes are associated with an increased risk of breast cancer that is clinically important.

Abstract Background: Overexpression of mitotic kinases has been associated with prognosis, histologic grade, and clinical stage in ovarian cancer, but the relationship between inherited variation in these genes and ovarian cancer risk has not been well defined. Methods: We measured associations between 397 single nucleotide polymorphisms (SNPs) from 67 mitotic kinases and invasive epithelial ovarian cancer risk in two case–control studies (n = 671 cases; n = 939 controls). Thirty-six candidate SNPs (P < 0.05) were assessed in a replication analysis consisting of three additional studies (n = 1,094 cases; n = 829 controls). Results: In initial analysis, thirty-six SNPs were suggestive of association with risk of serous ovarian cancer, all subtypes of ovarian cancer, or both (P < 0.05). Replication analyses suggested an association between rs2125846 in the Nemo-like kinase (NLK) gene and ovarian cancer (serous OR = 1.36, 95% CI: 1.11–1.67, P = 1.77 × 10−3; all subtypes OR = 1.30, 95% CI: 1.08–1.56, P = 2.97 × 10−3). Furthermore, rs2125846 was associated with risk in the combined discovery and replication sets (serous OR = 1.33, 95% CI: 1.15–1.54; all subtypes OR = 1.27, 95% CI: 1.12–1.45). Conclusions: Variation in NLK may be associated with risk of invasive epithelial ovarian cancer. Further studies are needed to confirm and understand the biologic relationship between this mitotic kinase and ovarian cancer risk. Impact: An association between SNPs in NLK and ovarian cancer may provide biologic insight into the development of this disease. Cancer Epidemiol Biomarkers Prev; 21(3); 523–8. ©2012 AACR.

AbstractUnderstanding patterns of etiologic commonality and heterogeneity for non-Hodgkin lymphomas may illuminate lymphomagenesis. We present the first systematic comparison of risks by lymphoma subtype for a broad range of putative risk factors in a population-based case-control study, including diffuse large B-cell (DLBCL; N = 416), follicular (N = 318), and marginal zone lymphomas (N = 106), and chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL; N = 133). We required at least 2 of 3 analyses to support differences in risk: (1) polytomous logistic regression, (2) homogeneity tests, or (3) dichotomous logistic regression, analyzing all 7 possible pairwise comparisons among the subtypes, corresponding to various groupings by clinical behavior, genetic features, and differentiation. Late birth order and high body mass index (≥ 35) kg/m2) increased risk for DLBCL alone. Autoimmune conditions increased risk for marginal zone lymphoma alone. The tumor necrosis factor G-308A polymorphism (rs1800629) increased risks for both DLBCL and marginal zone lymphoma. Exposure to certain dietary heterocyclic amines from meat consumption increased risk for CLL/SLL alone. We observed no significant risk factors for follicular lymphoma alone. These data clearly support both etiologic commonality and heterogeneity for lymphoma subtypes, suggesting that immune dysfunction is of greater etiologic importance for DLBCL and marginal zone lymphoma than for CLL/SLL and follicular lymphoma.

AbstractWe previously reported a lower risk of non-Hodgkin lymphoma (NHL) associated with high consumption of vitamin B6 and methionine, dietary determinants of one-carbon metabolism. Evidence has linked genetic variants involved in one-carbon metabolism to NHL. We investigated 30 polymorphisms in 18 genes for their main effect on NHL among 1141 incident cases and 949 population-based controls and examined gene-nutrient interactions in a subgroup of 386 cases and 319 controls who provided detailed food-frequency information. Odds ratios (ORs) and 95% confidence intervals (CIs) were adjusted for age, sex, and race. We observed a decreased risk of NHL overall with BHMT Ex8+453A>T and increased risk with CBS Ex13+41C>T, FPGS Ex15-263T>C, and SHMT1 Ex12+138C>T and Ex12+236C>T. Furthermore, significant gene-nutrient interactions limited the protective association comparing high versus low vitamin B6 to FPGS Ex15-263T>C CC (OR = 0.22; 95% CI = 0.10-0.52), MTHFS IVS2-1411T>G TT/TG (OR = 0.54; 95% CI = 0.36-0.81), and MTR Ex26-20A>G AA (OR = 0.55; 95% CI = 0.35-0.86) genotypes, and the protective association of methionine to FTHFD Ex10-40G>T GG (OR = 0.63; 95% CI = 0.44-0.91), MTHFR Ex8-62A>C CC (OR = 0.13; 95% CI = 0.04-0.39), and MTRR Ex5+136T>C TT (OR = 0.67; 95% CI = 0.47-0.97) genotypes. Warranting replication, our finding of gene-nutrient interactions in one-carbon metabolism supports their etiologic involvement in lymphomagenesis.