Severi, Gianluca

Abstract Background: Observational evidence has shown that smoking is a risk factor for breast and colorectal cancer. We used Mendelian randomization (MR) to examine causal associations between smoking and risks of breast and colorectal cancer. Methods: Genome-Wide Association Study summary data were used to identify genetic variants associated with lifetime amount of smoking (n = 126 variants) and ever having smoked regularly (n = 112 variants). Using two-sample MR, we examined these variants in relation to incident breast (122,977 cases/105,974 controls) and colorectal cancer (52,775 cases/45,940 controls). Results: In inverse-variance weighted models, a genetic predisposition to higher lifetime amount of smoking was positively associated with breast cancer risk [OR per 1-SD increment: 1.13; 95% confidence interval (CI): 1.00–1.26; P = 0.04]; although heterogeneity was observed. Similar associations were found for estrogen receptor–positive and estrogen receptor–negative tumors. Higher lifetime amount of smoking was positively associated with colorectal cancer (OR per 1-SD increment, 1.21; 95% CI, 1.04–1.40; P = 0.01), colon cancer (OR, 1.31; 95% CI, 1.11–1.55; P < 0.01), and rectal cancer (OR, 1.36; 95% CI, 1.07–1.73; P = 0.01). Ever having smoked regularly was not associated with risks of breast (OR, 1.01; 95% CI, 0.90–1.14; P = 0.85) or colorectal cancer (OR, 0.97; 95% CI, 0.86–1.10; P = 0.68). Conclusions: These findings are consistent with prior observational evidence and support a causal role of higher lifetime smoking amount in the development of breast and colorectal cancer. Impact: The results from this comprehensive MR analysis indicate that lifetime smoking is a causal risk factor for these common malignancies.

Objective Determinants of the increased risk of diffuse large B-cell lymphoma (DLBCL) in SLE are unclear. Using data from a recent lymphoma genome-wide association study (GWAS), we assessed whether certain lupus-related single nucleotide polymorphisms (SNPs) were also associated with DLBCL. Methods GWAS data on European Caucasians from the International Lymphoma Epidemiology Consortium (InterLymph) provided a total of 3857 DLBCL cases and 7666 general-population controls. Data were pooled in a random-effects meta-analysis. Results Among the 28 SLE-related SNPs investigated, the two most convincingly associated with risk of DLBCL included the CD40 SLE risk allele rs4810485 on chromosome 20q13 (OR per risk allele=1.09, 95% CI 1.02 to 1.16, p=0.0134), and the HLA SLE risk allele rs1270942 on chromosome 6p21.33 (OR per risk allele=1.17, 95% CI 1.01 to 1.36, p=0.0362). Of additional possible interest were rs2205960 and rs12537284. The rs2205960 SNP, related to a cytokine of the tumour necrosis factor superfamily TNFSF4, was associated with an OR per risk allele of 1.07, 95% CI 1.00 to 1.16, p=0.0549. The OR for the rs12537284 (chromosome 7q32, IRF5 gene) risk allele was 1.08, 95% CI 0.99 to 1.18, p=0.0765. Conclusions These data suggest several plausible genetic links between DLBCL and SLE.

Abstract Background: Diffuse large B-cell lymphoma (DLBCL) is the most common lymphoma subtype and is clinically aggressive. Relatives of DLBCL patients are at elevated risk for DLBCL. In small genome-wide association studies (GWAS) in which all NHL subtypes were combined, no conclusive loci for DLBCL have been previously identified in individuals of European background, whereas a recent study conducted in East Asia identified a locus at 3q27. Methods: To identify genetic susceptibility loci for DLBCL, we conducted a meta-analysis of three new GWAS and one prior scan, totaling 3,857 DLBCL cases and 7,666 controls of European ancestry. Imputation was used to combine all the data using the 1000 Genomes Project release v3 and IMPUTE2. Based on these findings, we selected 6 promising SNPs for genotyping in an additional 202 cases and 3,431 controls, which were then included in a second meta-analysis. SNPTEST was used to estimate odds ratios (ORs), using the additive model and adjusting for age, gender and significant eigenvectors. Results: In our multi-stage analysis, five independent SNPs in four loci achieved genome-wide significance marked by rs116446171 at 6p25.3 (EXOC2; OR=2.33, P=1.60x10-20), rs13255292 and rs4733601 at 8q24.21 (PVT1; OR=1.23, P=4.86x10-12 and OR=1.18, P=1.63x10-8, respectively), rs2523607 at 6p21.33 (HLA-B; OR=1.34, 3.35x10-9) and rs2681416 at 3q13.33 (CD86; OR=1.20, P=6.04x10-9). The two 8q24.21 SNPs displayed minimal linkage disequilibrium (r2=0.03) and conditional analysis supported their independence. We did not observe a notable signal for a locus previously reported for DLBCL on 3q27 in East Asia, rs6773854 (OR=1.06, P=0.81). We estimated that common SNPs, including but not limited to the loci discovered in this study, explain approximately 16% of the variance for DLBCL risk overall. Discussion: The susceptibility locus at 6p25.3 maps near a plausible DLBCL candidate gene, EXOC2 (exocyst complex component 2), which interacts with Ral proteins, and disruption of the Ral-exocyst regulatory node impacts cellular and developmental processes associated with malignant transformation and progression. The two 8q24.21 variants are approximately 1Mb telomeric to the 8q24 region linked with multiple cancers including CLL. Both variants are positioned in close proximity to PVT1, which is a non-coding RNA implicated in the MYC activation, and MYC is known to be deregulated in some DLBCLs. The locus at 3q13.33 maps to CD86 (B7-2), a B-7 family member that along with CD80 (B7-1) is essential in cognate interactions between T- and B-lymphocytes; both play key roles in immunodeficiency, autoimmune diseases, and in anti-tumor immunity. Finally, we had multiple signals in the HLA region, the strongest of which was at 6p21.33 near HLA-B. HLA-B encodes the HLA class I heavy chain paralogue, which heterodimerizes with a light chain (β2 microglobulin) and plays a central role in presenting intracellularly processed self or foreign antigens to CD8+ cytotoxic T lymphocytes. Class I molecules have been extensively linked to the risk of a variety of immune-mediated diseases and cancers including DLBCL. Conclusions: These data provide substantial new evidence for genetic susceptibility to this B-cell malignancy, and point towards pathways involved in immune recognition and immune function in the pathogenesis of DLBCL. Citation Format: James R. Cerhan, Sonja I. Berndt, Joseph Vijai, Hervé Ghesquières, James McKay, Sophia S. Wang, Zhaoming Wang, Meredith Yeager, Alexandra Nieters, David Cox, Alain Monnereau, Christopher Flowers, Anneclaire J. De Roos, Angela R. Brooks-Wilson, Qing Lan, Gianluca Severi, Mads Melbye, Rebecca D. Jackson, Lauren R. Teras, Mark Purdue, Claire Vajdic, Demetrius Albanes, Kimberly A. Bertrand, Anne Zeleniuch-Jacquotte, Simon Crouch, Yawei Zhang, Paolo Vineis, Susan L. Slager, Karin E. Smedby, Gilles Salles, Christine F. Skibola, Nathaniel Rothman, Stephen J. Chanock, on behalf of the NHL GWAS Project. Genome-wide association study identifies multiple susceptibility loci for diffuse large B-cell lymphoma. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr LB-272. doi:10.1158/1538-7445.AM2014-LB-272

Abstract Background. Follicular lymphoma (FL) is an indolent B-cell malignancy with a variable clinical course that may transform to more aggressive forms of lymphoma. Previous modestly powered GWAS have reported multiple FL susceptibility loci in the HLA class I and II regions at 6p21.32-33, but novel non-HLA susceptibility loci and the genetic architecture of FL associations in the HLA region remain to be elucidated. Methods. We conducted the largest GWAS of FL to date consisting of 2,142 cases and 6,221 controls of European ancestry from 22 studies scanned on the Illumina OmniExpress. After imputation of common SNPs using IMPUTE2 and 1,000 Genomes Project v3 data, we conducted a meta-analysis of these data with two previous FL GWAS (n=586 cases, 1,537 controls) and replicated top hits in an additional 629 cases and 4,283 controls. Expression quantitative trait loci (eQTL) analyses were performed to evaluate the effects of associated variants on gene expression. Classical HLA allele imputations and stepwise regression analyses are underway to further characterize the HLA associations. Results. In the joint meta-analysis, the strongest association with FL risk was observed in the HLA region, where a large number of SNPs showed genome-wide significance (P<5x10-8 to P= 1.84x10-84), particularly in HLA class II at 6p21.32 where several HLA eQTLs were identified (P < 0.05). Outside HLA, we identified four novel loci associated with FL at 11q23.3 (CXCR5, rs4938573; P=3.14x10-15), 11q24.3 (ETS1, rs4937362; P=3.33x10-9), 3q13.33 (CD86, rs2681416; P=9.79x10-11) and 3q28 (LPP, rs6444305, P=2.55x10-8). These novel susceptibility loci were located in four biologically relevant genes involved in immune regulation: CXCR5 and its ligand, CXCL13, are involved in guiding B-cells into the B-cell zones of secondary lymphoid organs as well as T-cell migration. ETS1 is expressed in lymphoid cells and regulates immune cell function including differentiation, survival, and proliferation. CD86 and CD80 are classic members of the B7 costimulatory pathway that is important in maintaining immune function, suppression of autoimmunity and antitumor surveillance. LPP encodes a LIM domain-containing protein of the zyxin family and participates in cell adhesion, cell migration, proliferation and transcription dynamics. Conclusions. This large GWAS provides further support for the important role of common genetic variation in non-HLA genes and further evidence of the key role that HLA immune-regulatory genes play in the pathogenesis of FL. Citation Format: Christine F. Skibola, Sonja I. Berndt, James R. Cerhan, Zhaoming Wang, Joseph Vijai, Lucia Conde, Paul de Bakker, Sophia S. Wang, Claire M. Vajdic, Brenda M. Birmann, Susan L. Slager, James McKay, Paige M. Bracci, Alexandra Nieters, Qing Lan, Angela R. Brooks-Wilson, Martha S. Linet, Demetrius Albanes, John J. Spinelli, Roel C.H. Vermeulen, Mark P. Purdue, Meredith Yaeger, Lauren R. Teras, Silvia de Sanjose, Alain Monnereau, Simon Crouch, Jia Nee Foo, Henrik Hjalgrim, Gianluca Severi, Brian K. Link, Kimberly A. Bertrand, Yawei Zhang, Karin E. Smedby, Stephen J. Chanock, Nathaniel Rothman, NHL GWAS Consortium. Meta-analysis of genome-wide association studies identifies novel susceptibility loci for follicular lymphoma. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 5072. doi:10.1158/1538-7445.AM2014-5072

Abstract Recent studies have shown that associations between common genetic variation and gene expression in breast tumors provide insight into the functional mechanisms underlying breast cancer risk loci. However, the relationship between genetic variation, gene expression, and risk of triple negative (TN) breast cancer remains largely unexplored. We performed a genome-wide expression quantitative trait locus (eQTL) analysis of TN breast cancer using 668 formalin-fixed paraffin embedded TN tumors from the Triple Negative Breast Cancer Consortium (TNBCC) to identify novel genes relevant to TN breast cancer risk and to further explore the biology underlying known TN risk loci. Cis-eQTLs were defined as correlations between single nucleotide polymorphisms (SNP) and expression of genes within 1Mb, and trans-eQTLs were defined as the remainder of all SNP-gene correlations. In a genome-wide analysis, we identified 68,012 cis-eQTLs, representing correlations between 42,193 SNPs and 2,092 genes that were significant at a 10% false discovery rate (FDR). We also identified 70 trans-eQTLs across two unique genes at the same FDR threshold. Five cis-eQTLs involved SNPs previously associated with TN breast cancer risk (p<5.0x10-5) in 3,700 TN cases and 4,700 controls from the TNBCC. Three of these, located on chromosomes 5p (cis-eQTL p=4.8x10-34; risk p=1.1x10-7), 7p (cis-eQTL p=6.1x10-10; risk p=1.3x10-7), and 17q (cis-eQTL p=1.8x10-15; risk p=2.9x10-7), have previously been reported in public databases of normal tissue. The remaining two TN breast cancer cis-eQTLs, located on chromosomes 8q (cis-eQTL p=6.3x10-6, risk p=8.3x10-6) and 14q (cis-eQTL p=3.1x10-6, risk p=1.2x10-5), have not been reported as eQTLs in other tissues. In addition, 12 of 25 known TN breast cancer risk loci (PEX14, MDM4, 2q31.1, ESR1, 11q13.1, 11q24.3, 12p13.1, PTHLH, NTN4, 12q24, 19p13.1, MLK1), contained at least one significant cis-eQTL. In summary, we have identified five cis-eQTLs that may identify novel risk loci for TN breast cancer. Citation Format: Kristen S. Purrington, Drakoulis Yannoukakos, Jane Carpenter, Heli Nevanlinna, Angela Cox, Gianluca Severi, Christine Ambrosone, Amanda Ewart Toland, Andrew K. Godwin, Hiltrud Brauch, Peter A. Fasching, Penelope Miron, Jenny Chang-Claude, Nicholas G. Martin, Grant W. Montgomery, Vessela Kristensen, Hoda Anton-Culver, Paul Goodfellow, Janet E. Olson, Hugues Sicotte, Naresh Prodduturi, Daniel W. Visscher, Jeanette E. Eckel-Passow, S. Keith Anderson, Seth Slettedahl, Curtis Olswold, Xianshu Wang, V. Shane Pankratz, Susan Slager, Wei Zheng, Arto Mannermaa, Ute Hamann, Diana M. Eccles, Celine M. Vachon, Fergus J. Couch. Expression quantitative trait locus analysis of triple negative breast cancer. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 3266. doi:10.1158/1538-7445.AM2014-3266

Abstract Background: Genome-wide association studies have identified multiple genetic variants associated with prostate cancer risk which explain a substantial proportion of familial relative risk. These variants can be used to stratify individuals by their risk of prostate cancer. Methods: We genotyped 25 prostate cancer susceptibility loci in 40,414 individuals and derived a polygenic risk score (PRS). We estimated empirical odds ratios (OR) for prostate cancer associated with different risk strata defined by PRS and derived age-specific absolute risks of developing prostate cancer by PRS stratum and family history. Results: The prostate cancer risk for men in the top 1% of the PRS distribution was 30.6 (95% CI, 16.4–57.3) fold compared with men in the bottom 1%, and 4.2 (95% CI, 3.2–5.5) fold compared with the median risk. The absolute risk of prostate cancer by age of 85 years was 65.8% for a man with family history in the top 1% of the PRS distribution, compared with 3.7% for a man in the bottom 1%. The PRS was only weakly correlated with serum PSA level (correlation = 0.09). Conclusions: Risk profiling can identify men at substantially increased or reduced risk of prostate cancer. The effect size, measured by OR per unit PRS, was higher in men at younger ages and in men with family history of prostate cancer. Incorporating additional newly identified loci into a PRS should improve the predictive value of risk profiles. Impact: We demonstrate that the risk profiling based on SNPs can identify men at substantially increased or reduced risk that could have useful implications for targeted prevention and screening programs. Cancer Epidemiol Biomarkers Prev; 24(7); 1121–9. ©2015 AACR.

Abstract A missense single-nucleotide polymorphism (SNP) in the immune modulatory gene IL1A has been associated with ovarian cancer risk (rs17561). Although the exact mechanism through which this SNP alters risk of ovarian cancer is not clearly understood, rs17561 has also been associated with risk of endometriosis, an epidemiologic risk factor for ovarian cancer. Interleukin-1α (IL1A) is both regulated by and able to activate NF-κB, a transcription factor family that induces transcription of many proinflammatory genes and may be an important mediator in carcinogenesis. We therefore tagged SNPs in more than 200 genes in the NF-κB pathway for a total of 2,282 SNPs (including rs17561) for genotype analysis of 15,604 cases of ovarian cancer in patients of European descent, including 6,179 of high-grade serous (HGS), 2,100 endometrioid, 1,591 mucinous, 1,034 clear cell, and 1,016 low-grade serous, including 23,235 control cases spanning 40 studies in the Ovarian Cancer Association Consortium. In this large population, we confirmed the association between rs17561 and clear cell ovarian cancer [OR, 0.84; 95% confidence interval (CI), 0.76–0.93; P = 0.00075], which remained intact even after excluding participants in the prior study (OR, 0.85; 95% CI, 0.75–0.95; P = 0.006). Considering a multiple-testing–corrected significance threshold of P < 2.5 × 10−5, only one other variant, the TNFSF10 SNP rs6785617, was associated significantly with a risk of ovarian cancer (low malignant potential tumors OR, 0.85; 95% CI, 0.79–0.91; P = 0.00002). Our results extend the evidence that borderline tumors may have a distinct genetic etiology. Further investigation of how these SNPs might modify ovarian cancer associations with other inflammation-related risk factors is warranted. Cancer Res; 74(3); 852–61. ©2013 AACR.

ABSTRACTGenes that alter disease risk only in combination with certain environmental exposures may not be detected in genetic association analysis. By using methods accounting for gene‐environment (G × E) interaction, we aimed to identify novel genetic loci associated with breast cancer risk. Up to 34,475 cases and 34,786 controls of European ancestry from up to 23 studies in the Breast Cancer Association Consortium were included. Overall, 71,527 single nucleotide polymorphisms (SNPs), enriched for association with breast cancer, were tested for interaction with 10 environmental risk factors using three recently proposed hybrid methods and a joint test of association and interaction. Analyses were adjusted for age, study, population stratification, and confounding factors as applicable. Three SNPs in two independent loci showed statistically significant association: SNPs rs10483028 and rs2242714 in perfect linkage disequilibrium on chromosome 21 and rs12197388 in ARID1B on chromosome 6. While rs12197388 was identified using the joint test with parity and with age at menarche (P‐values = 3 × 10−07), the variants on chromosome 21 q22.12, which showed interaction with adult body mass index (BMI) in 8,891 postmenopausal women, were identified by all methods applied. SNP rs10483028 was associated with breast cancer in women with a BMI below 25 kg/m2 (OR = 1.26, 95% CI 1.15–1.38) but not in women with a BMI of 30 kg/m2 or higher (OR = 0.89, 95% CI 0.72–1.11, P for interaction = 3.2 × 10−05). Our findings confirm comparable power of the recent methods for detecting G × E interaction and the utility of using G × E interaction analyses to identify new susceptibility loci.

Abstract Part of the substantial unexplained familial aggregation of breast cancer may be due to interactions between common variants, but few studies have had adequate statistical power to detect interactions of realistic magnitude. We aimed to assess all two-way interactions in breast cancer susceptibility between 70 917 single nucleotide polymorphisms (SNPs) selected primarily based on prior evidence of a marginal effect. Thirty-eight international studies contributed data for 46 450 breast cancer cases and 42 461 controls of European origin as part of a multi-consortium project (COGS). First, SNPs were preselected based on evidence (P < 0.01) of a per-allele main effect, and all two-way combinations of those were evaluated by a per-allele (1 d.f.) test for interaction using logistic regression. Second, all 2.5 billion possible two-SNP combinations were evaluated using Boolean operation-based screening and testing, and SNP pairs with the strongest evidence of interaction (P < 10−4) were selected for more careful assessment by logistic regression. Under the first approach, 3277 SNPs were preselected, but an evaluation of all possible two-SNP combinations (1 d.f.) identified no interactions at P < 10−8. Results from the second analytic approach were consistent with those from the first (P > 10−10). In summary, we observed little evidence of two-way SNP interactions in breast cancer susceptibility, despite the large number of SNPs with potential marginal effects considered and the very large sample size. This finding may have important implications for risk prediction, simplifying the modelling required. Further comprehensive, large-scale genome-wide interaction studies may identify novel interacting loci if the inherent logistic and computational challenges can be overcome.