Citations

Abstract Introduction The 2-3 fold excess risk of multiple myeloma (MM) among family members of cases suggests a heritable contribution to risk. Recently, a genome-wide association study (GWAS) identified two genome-wide significant and one promising novel loci associated with multiple myeloma risk. To confirm these associations and identify additional novel risk loci, we performed a four-center, genome-wide association meta-analysis. Methods A fixed effects model was used for the meta-analysis which included a total of 1248 cases and 1485 controls, all of European descent, genotyped and analyzed at four separate centers with samples contributed by 10 studies. After quality control and imputation using the 1000 Genomes Project, the analysis included ∼9.5 million variants (λ=1.024). Associations between (single nucleotide polymorphisms) SNP genotypes and MM risk were evaluated under a log-additive model of inheritance, with each study adjusting for age, sex, and up to 10 principal components to control for population stratification. Promising results were replicated in an independent set of 1587 cases and 1770 controls using TaqMan, for a total of 2835 and 3255 cases and controls, respectively, in a combined meta-analysis. Results The discovery meta-analysis did not reveal any genome-wide significant associations (defined as p<5 x 10-8). We used a novel pruning algorithm to identify the top 35 most promising single nucleotide polymorphisms (SNPs) to advance to replication. We successfully genotyped 22 SNPs in the replication set. In the combined discovery and replication meta-analysis, rs1345359 at 12q23.1 was the most strongly associated SNP (P=9 x 10-8, Table 1). The variant allele C was associated with reduced risk (odds ratio discovery set [OR]= 0.69, OR replication set = 0.78, OR combined = 0.74). A second locus at 20q13.2 (rs150220835), was associated with a two-fold increased risk (P=1.22 x 10-6), a borderline increased risk (P=0.0900) and 45% increased risk (P=2.44 X 10-5) in the discovery, replication, and combined analysis sets respectively (Table 1). We also confirmed the association between MM risk and two previously published SNPs (rs4487645, p=0.0007and rs105251, p=0.0044) (Broderick et al., Nat. Genet., 2011). The third previously suggested SNP (rs6746082) was of nominal significance (p=0.0517) in the meta-analysis. Discussion We confirmed the association between MM risk and two previously published SNPs and identified a possible association with a novel SNP in chromosome 12q23.1 (rs1345359). This SNP is not located in a gene nor associated with biofeatures in ENCODE, thus further examination of correlated SNPs is necessary to identify a functional SNP linked to this locus. We also found suggestive evidence for a second locus at 20q13.2 requiring additional replication. Larger studies would improve risk variant discovery for this rare hematologic malignancy. Disclosures: Wolf: Celgene: Honoraria, Research Funding; Millenium: Honoraria; Onyx: Honoraria. Anderson:Celgene, Millennium, BMS, Onyx: Membership on an entity’s Board of Directors or advisory committees; Acetylon, Oncopep: Scientific Founder , Scientific Founder Other.

Abstract We previously identified five single nucleotide polymorphisms (SNPs) at four susceptibility loci for diffuse large B-cell lymphoma (DLBCL) in individuals of European ancestry through a large genome-wide association study (GWAS). To further elucidate genetic susceptibility to DLBCL, we sought to validate two loci at 3q13.33 and 3p24.1 that were suggestive in the original GWAS with additional genotyping. In the meta-analysis (5662 cases and 9237 controls) of the four original GWAS discovery scans and three replication studies, the 3q13.33 locus (rs9831894; minor allele frequency [MAF] = 0.40) was associated with DLBCL risk [odds ratio (OR) = 0.83, P = 3.62 × 10−13]. rs9831894 is in linkage disequilibrium (LD) with additional variants that are part of a super-enhancer that physically interacts with promoters of CD86 and ILDR1. In the meta-analysis (5510 cases and 12 817 controls) of the four GWAS discovery scans and four replication studies, the 3p24.1 locus (rs6773363; MAF = 0.45) was also associated with DLBCL risk (OR = 1.20, P = 2.31 × 10−12). This SNP is 29 426-bp upstream of the nearest gene EOMES and in LD with additional SNPs that are part of a highly lineage-specific and tumor-acquired super-enhancer that shows long-range interaction with AZI2 promoter. These loci provide additional evidence for the role of immune function in the etiology of DLBCL, the most common lymphoma subtype.

AbstractEpidemiologic studies show an increased risk of non‐Hodgkin lymphoma (NHL) in patients with autoimmune disease (AD), due to a combination of shared environmental factors and/or genetic factors, or a causative cascade: chronic inflammation/antigen‐stimulation in one disease leads to another. Here we assess shared genetic risk in genome‐wide‐association‐studies (GWAS).Secondary analysis of GWAS of NHL subtypes (chronic lymphocytic leukemia, diffuse large B‐cell lymphoma, follicular lymphoma, and marginal zone lymphoma) and ADs (rheumatoid arthritis, systemic lupus erythematosus, and multiple sclerosis). Shared genetic risk was assessed by (a) description of regional genetic of overlap, (b) polygenic risk score (PRS), (c)"diseasome", (d)meta‐analysis.Descriptive analysis revealed few shared genetic factors between each AD and each NHL subtype. The PRS of ADs were not increased in NHL patients (nor vice versa). In the diseasome, NHLs shared more genetic etiology with ADs than solid cancers (p = .0041). A meta‐analysis (combing AD with NHL) implicated genes of apoptosis and telomere length.This GWAS‐based analysis four NHL subtypes and three ADs revealed few weakly‐associated shared loci, explaining little total risk. This suggests common genetic variation, as assessed by GWAS in these sample sizes, may not be the primary explanation for the link between these ADs and NHLs.

AbstractAn association between genetic variants in the vitamin D receptor (VDR) gene and epithelial ovarian cancer (EOC) was previously reported in women of African ancestry (AA). We sought to examine associations between genetic variants in VDR and additional genes from vitamin D biosynthesis and pathway targets (EGFR, UGT1A, UGT2A1/2, UGT2B, CYP3A4/5, CYP2R1, CYP27B1, CYP24A1, CYP11A1, and GC). Genotyping was performed using the custom‐designed 533,631 SNP Illumina OncoArray with imputation to the 1,000 Genomes Phase 3 v5 reference set in 755 EOC cases, including 537 high‐grade serous (HGSOC), and 1,235 controls. All subjects are of African ancestry (AA). Logistic regression was performed to estimate odds ratios (OR) and 95% confidence intervals (CI). We further evaluated statistical significance of selected SNPs using the Bayesian False Discovery Probability (BFDP). A significant association with EOC was identified in the UGT2A1/2 region for the SNP rs10017134 (per allele OR = 1.4, 95% CI = 1.2‐1.7, P = 1.2 × 10−6, BFDP = 0.02); and an association with HGSOC was identified in the EGFR region for the SNP rs114972508 (per allele OR = 2.3, 95% CI = 1.6‐3.4, P = 1.6 × 10−5, BFDP = 0.29) and in the UGT2A1/2 region again for rs1017134 (per allele OR = 1.4, 95% CI = 1.2‐1.7, P = 2.3 × 10−5, BFDP = 0.23). Genetic variants in the EGFR and UGT2A1/2 may increase susceptibility of EOC in AA women. Future studies to validate these findings are warranted. Alterations in EGFR and UGT2A1/2 could perturb enzyme efficacy, proliferation in ovaries, impact and mark susceptibility to EOC.

As a follow‐up to genome‐wide association analysis of common variants associated with ovarian carcinoma (cancer), our study considers seven well‐known ovarian cancer risk factors and their interactions with 28 genome‐wide significant common genetic variants. The interaction analyses were based on data from 9971 ovarian cancer cases and 15,566 controls from 17 case–control studies. Likelihood ratio and Wald tests for multiplicative interaction and for relative excess risk due to additive interaction were used. The top multiplicative interaction was noted between oral contraceptive pill (OCP) use (ever vs. never) and rs13255292 (p value = 3.48 × 10−4). Among women with the TT genotype for this variant, the odds ratio for OCP use was 0.53 (95% CI = 0.46–0.60) compared to 0.71 (95%CI = 0.66–0.77) for women with the CC genotype. When stratified by duration of OCP use, women with 1–5 years of OCP use exhibited differential protective benefit across genotypes. However, no interaction on either the multiplicative or additive scale was found to be statistically significant after multiple testing correction. The results suggest that OCP use may offer increased benefit for women who are carriers of the T allele in rs13255292. On the other hand, for women carrying the C allele in this variant, longer (5+ years) use of OCP may reduce the impact of carrying the risk allele of this SNP. Replication of this finding is needed. The study presents a comprehensive analytic framework for conducting gene–environment analysis in ovarian cancer.

Abstract Genome-wide association studies have identified 40 ovarian cancer risk loci. However, the mechanisms underlying these associations remain elusive. In this study, we conducted a two-pronged approach to identify candidate causal SNPs and assess underlying biological mechanisms at chromosome 9p22.2, the first and most statistically significant associated locus for ovarian cancer susceptibility. Three transcriptional regulatory elements with allele-specific effects and a scaffold/matrix attachment region were characterized and, through physical DNA interactions, BNC2 was established as the most likely target gene. We determined the consensus binding sequence for BNC2 in vitro, verified its enrichment in BNC2 ChIP-seq regions, and validated a set of its downstream target genes. Fine-mapping by dense regional genotyping in over 15,000 ovarian cancer cases and 30,000 controls identified SNPs in the scaffold/matrix attachment region as among the most likely causal variants. This study reveals a comprehensive regulatory landscape at 9p22.2 and proposes a likely mechanism of susceptibility to ovarian cancer. Significance: Mapping the 9p22.2 ovarian cancer risk locus identifies BNC2 as an ovarian cancer risk gene. See related commentary by Choi and Brown, p. 439

Thymidylate synthase (TYMS) is a crucial enzyme for DNA synthesis. TYMS expression is regulated by its antisense mRNA, ENOSF1. Disrupted regulation may promote uncontrolled DNA synthesis and tumor growth. We sought to replicate our previously reported association between rs495139 in the TYMS-ENOSF1 3′ gene region and increased risk of mucinous ovarian carcinoma (MOC) in an independent sample. Genotypes from 24,351 controls to 15,000 women with invasive OC, including 665 MOC, were available. We estimated per-allele odds ratios (OR) and 95% confidence intervals (CI) using unconditional logistic regression, and meta-analysis when combining these data with our previous report. The association between rs495139 and MOC was not significant in the independent sample (OR = 1.09; 95% CI = 0.97–1.22; p = 0.15; N = 665 cases). Meta-analysis suggested a weak association (OR = 1.13; 95% CI = 1.03–1.24; p = 0.01; N = 1019 cases). No significant association with risk of other OC histologic types was observed (p = 0.05 for tumor heterogeneity). In expression quantitative trait locus (eQTL) analysis, the rs495139 allele was positively associated with ENOSF1 mRNA expression in normal tissues of the gastrointestinal system, particularly esophageal mucosa (r = 0.51, p = 1.7 × 10−28), and nonsignificantly in five MOC tumors. The association results, along with inconclusive tumor eQTL findings, suggest that a true effect of rs495139 might be small.

Abstract Background: We previously identified 5 SNPs at 4 susceptibility loci for diffuse large B-cell lymphoma (DLBCL) in individuals of European ancestry through a large genome-wide association study (Cerhan et al, Nat Gen 2014;46:1233-8); however, much of the heritability remains unexplained. To further elucidate genetic susceptibility to DLBCL, we sought to validate 2 loci at 3q13.33 and 3p24.1 that were suggestive in the original report. Methods: We selected two SNPs rs9831894 (3q13.33) and rs6773363 (3p24.1) for de novo replication from studies at the Mayo Clinic, MD Anderson, and Memorial Sloan Kettering. Logistic regression was used to estimate odds ratios (ORs), using a log-additive model, and adjusting for age, gender and significant eigenvectors for each genotyping center separately. For both SNPs, we then conducted a meta-analysis of all replication studies (n=3) and our original GWAS studies (n=4), encompassing in total 5662 cases and 9237 controls for rs9831894, and 5510 cases and 12,817 controls for rs6773363. Meta-analysis was conducted using the fixed-effects inverse variance method based on the β estimates and standard errors from each study. Results: In a meta-analysis of the 4 original GWAS scans (3856 cases and 7666 controls), rs9831894 (MAF=0.40) was associated with DLBCL risk (OR=0.84, P=4.52 x 10-9) and this replicated in a meta-analysis of the 3 studies with de novo genotyping (OR=0.80, P=4.17 x 10-5); the overall meta-analysis showed a strong association with DLBCL risk (OR=0.83, P=3.62 x 10-13). This locus maps near a plausible candidate gene, CD86, a protein coding gene and a member of the immunoglobulin superfamily that encodes a type I membrane protein. Binding of CD86 with cytotoxic T-lymphocyte-associated protein 4 negatively regulates T-cell activation and diminishes the immune response, while binding of CD86 with CD28 antigen is a costimulatory signal for activation of the T-cell. In a meta-analysis of the same 4 GWAS scans, rs6773363 (MAF=0.45) was tentatively associated with DLBCL risk (OR=1.17, P= 3.68 x 10-7) and this replicated in a meta-analysis of the studies with de novo genotyping (OR=1.27, P=3.78 x 10-7); the overall meta-analysis showed a strong association with DLBCL risk (OR=1.20, P=2.31 x 10-12). This locus also maps near a plausible candidate gene, eomesodermin (EOMES), a transcription factor crucial for embryonic development of the central nervous system and also putatively involved in T-cell differentiation in viral infection defense. Conclusion: In this follow-up analysis of our initial GWAS, we have identified two additional loci associated with risk of DLBCL, the most common lymphoma subtype. These loci provide additional evidence for the role of immune function in the etiology of DLBCL. Citation Format: Geffen Kleinstern, Michelle Hildebrand, Vijai Joseph, Sonja I. Berndt, Hervé Ghesquières, James McKay, Sophia S. Wang, Alexandra Nieters, David Cox, Alain Monnereau, Angela R. Brooks-Wilson, Qing Lan, Mads Melbye, Rebecca D. Jackson, Lauren R. Teras, Mark P. Purdue, Claire M. Vajdic, Demetrius Albanes, Anne Zeleniuch-Jacquotte, Simon Crouch, Yawei Zhang, Susan L. Slager, Xifeng Wu, Karin E. Smedby, Gilles Salles, Christine F. Skibola, Nathaniel Rothman, Stephen J. Chanock, James R. Cerhan. Inherited variants at 3q13.33 and 3p24.1 influences risk of diffuse large B-cell lymphoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 221.

Abstract A growing number of loci within the human leukocyte antigen (HLA) region have been implicated in non-Hodgkin lymphoma (NHL) etiology. Here, we test a complementary hypothesis of “heterozygote advantage” regarding the role of HLA and NHL, whereby HLA diversity is beneficial and homozygous HLA loci are associated with increased disease risk. HLA alleles at class I and II loci were imputed from genome-wide association studies (GWAS) using SNP2HLA for 3,617 diffuse large B-cell lymphomas (DLBCL), 2,686 follicular lymphomas (FL), 2,878 chronic lymphocytic leukemia/small lymphocytic lymphomas (CLL/SLL), 741 marginal zone lymphomas (MZL), and 8,753 controls of European descent. Both DLBCL and MZL risk were elevated with homozygosity at class I HLA-B and -C loci (OR DLBCL = 1.31, 95% CI = 1.06–1.60; OR MZL = 1.45, 95% CI = 1.12–1.89) and class II HLA-DRB1 locus (OR DLBCL = 2.10, 95% CI = 1.24–3.55; OR MZL = 2.10, 95% CI = 0.99–4.45). Increased FL risk was observed with the overall increase in number of homozygous HLA class II loci (P trend &lt; 0.0001, FDR = 0.0005). These results support a role for HLA zygosity in NHL etiology and suggests that distinct immune pathways may underly the etiology of the different NHL subtypes. Significance: HLA gene diversity reduces risk for non-Hodgkin lymphoma. Cancer Res; 78(14); 4086–96. ©2018 AACR.

Key Points PRS, based on the known CLL loci, predicts CLL risk with high discrimination. This PRS predicts risk of monoclonal B-cell lymphocytosis, a precursor to CLL and a condition that has clinical impact beyond risk for CLL.