Chatterjee, Nilanjan

Telomeres cap chromosome ends, protecting them from degradation, double‐strand breaks, and end‐to‐end fusions. Telomeres are maintained by telomerase, a reverse transcriptase encoded by TERT, and an RNA template encoded by TERC. Loci in the TERT and adjoining CLPTM1L region are associated with risk of multiple cancers. We therefore investigated associations between variants in 22 telomere structure and maintenance gene regions and colorectal, breast, prostate, ovarian, and lung cancer risk. We performed subset‐based meta‐analyses of 204,993 directly‐measured and imputed SNPs among 61,851 cancer cases and 74,457 controls of European descent. Independent associations for SNP minor alleles were identified using sequential conditional analysis (with gene‐level p value cutoffs ≤3.08 × 10−5). Of the thirteen independent SNPs observed to be associated with cancer risk, novel findings were observed for seven loci. Across the DCLRE1B region, rs974494 and rs12144215 were inversely associated with prostate and lung cancers, and colorectal, breast, and prostate cancers, respectively. Across the TERC region, rs75316749 was positively associated with colorectal, breast, ovarian, and lung cancers. Across the DCLRE1B region, rs974404 and rs12144215 were inversely associated with prostate and lung cancers, and colorectal, breast, and prostate cancers, respectively. Near POT1, rs116895242 was inversely associated with colorectal, ovarian, and lung cancers, and RTEL1 rs34978822 was inversely associated with prostate and lung cancers. The complex association patterns in telomere‐related genes across cancer types may provide insight into mechanisms through which telomere dysfunction in different tissues influences cancer risk.

Abstract Identifying genetic variants with pleiotropic associations can uncover common pathways influencing multiple cancers. We took a two-stage approach to conduct genome-wide association studies for lung, ovary, breast, prostate, and colorectal cancer from the GAME-ON/GECCO Network (61,851 cases, 61,820 controls) to identify pleiotropic loci. Findings were replicated in independent association studies (55,789 cases, 330,490 controls). We identified a novel pleiotropic association at 1q22 involving breast and lung squamous cell carcinoma, with eQTL analysis showing an association with ADAM15/THBS3 gene expression in lung. We also identified a known breast cancer locus CASP8/ALS2CR12 associated with prostate cancer, a known cancer locus at CDKN2B-AS1 with different variants associated with lung adenocarcinoma and prostate cancer, and confirmed the associations of a breast BRCA2 locus with lung and serous ovarian cancer. This is the largest study to date examining pleiotropy across multiple cancer-associated loci, identifying common mechanisms of cancer development and progression. Cancer Res; 76(17); 5103–14. ©2016 AACR.

Abstract Telomeres are complex structures that cap chromosome ends, protecting them from degradation, double strand breaks and end-to-end fusions. Telomeres are maintained by the enzyme telomerase, which is made up of a reverse transcriptase encoded by TERT, and an RNA template encoded by TERC. The telomere structure itself is composed of proteins encoded by ACD, ACYP2, BICD1, DKC1, DCLRE1B, MPHOSPH6, NAF1, NOLA1, NOLA2, NOLA3, OBFC1, PIK3C3, POT1, RTEL1, TEP1, TERF1, TERF2, TERF21P, TINF2, TNKS/PINX1, TPP1 and ZNF208. Several single nucleotide polymorphisms (SNPs) in the TERT and adjoining CLPTM1L gene region are associated with multiple cancer types, and some are associated with both increased and decreased risks across different cancer types. We systematically characterized the patterns of association between variants in these 25 telomere structure and maintenance genes and risk across five cancer types in the Genetic Association and Mechanisms in Oncology (GAME-ON) consortium. We performed a subset-based meta-analysis (ASSET) of 209,367 directly measured and imputed SNPs, one megabase up- and downstream of these genes, across genome-wide association studies of colorectal (5,100 cases, 4,831 controls), lung (12,160 cases, 16,838 controls), breast (15,748 cases, 18,084 controls), ovarian (4,369 cases, 9,123 controls) and prostate (14,160 cases, 12,724 controls) cancers. Correlations (r2) between SNPs were examined in Haploview using the 1000 Genomes Project CEU population. A total of 87 TERT, 123 TERC and 26 DCLRE1B SNPs were associated with cancer risk at gene-level Bonferroni-corrected p-values of 4.2-7.8×10−6. Patterns of association were similar for prostate and colorectal cancers in DCLRE1B. Much stronger associations were observed in TERT and TERC, with 63 and 24 SNPs reaching genome-wide significance (p<5.0×10−8), respectively. Of these, 9 TERT and 9 TERC SNPs were correlated at r2<0.75. The most strongly associated SNPs in TERT (rs37004, p = 2.6×10−11) and TERC (rs76925190, p = 1.5×10−15) are in regions containing documented risk loci for lung and prostate cancers, respectively. TERT rs37004 (p = 1.2×10−13) and 6 of the other 9 SNPs in TERT were associated only with lung cancer risk. For the other 2 SNPs, there was a suggestion that patterns of risk were opposite for lung and prostate cancers. While TERC rs76925190 was strongly associated with prostate cancer risk (p = 5.4 x10−17), it was also suggestively associated with colorectal cancer risk (p<0.005). This pattern was similar for another 2 of the 9 SNPs, while for the rest, associations were limited to prostate cancer. The complex patterns of association in telomere structure and maintenance genes observed across cancer types may provide insight about the mechanisms through which telomere dysfunction in different tissues influences cancer risk. Citation Format: Sara Karami, Younghun Han, Fredrick R. Schumacher, Zsofia Kote-Jarai, Sara Lindstrom, John S. Witte, Iona Cheng, Shenying Fang, Jiali Han, Peter Kraft, Fengju Song, Rayjean J. Hung, James McKay, Stephen J. Chanock, Mala Pande, Angela Risch, Hongbing Shen, Christopher A. Haiman, Lisa Boardman, Cornelia M. Ulrich, Graham Casey, Ulrike Peters, Nilanjan Chatterjee, Brandon Pierce, Wei Zheng, Christopher I. Amos, Jennifer A. Doherty. Risk loci in telomere structure and maintenance genes across five cancer types: GAME-ON Consortium. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4609. doi:10.1158/1538-7445.AM2015-4609

Abstract Background: Genetic and environmental factors influence colorectal cancer (CRC) risk. Previous studies have provided additional etiologic insight by examining multiplicative gene-environment interactions for individual susceptibility loci. However, individual loci confer only modest risks, which may limit statistical power and clinical significance. A genetic risk score comprising known CRC loci may provide a more comprehensive assessment of risk. Further, there is a paucity of data on the role of additive gene-environment interactions, which may have greater public health implications than multiplicative interactions. We thus evaluated both additive and multiplicative interactions between a genetic risk score and 15 key environmental factors on risk of CRC. Methods: We conducted an analysis of 10,491 CRC cases and 10,725 controls of European ancestry in 7 cohort and 6 case-control studies participating in the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO) or Colon Cancer Family Registry (CCFR). To provide a global measure of genetic predisposition, information across multiple risk variants was combined by calculating a genetic risk score based on 24 polymorphisms near 21 genetic loci identified in previous genome-wide association studies. For the genetic score and environmental factors, the reference category corresponded to that associated with lower CRC risk. We tested for additive interactions by estimating relative excess risk due to interactions (RERIs) using logistic regression; for multiplicative interactions we used an empirical-Bayes approach. Nominal P values ≤ 0.05 were considered statistically significant. Results: After adjustment for age, sex, center, study, principal components, and total energy, as appropriate, we observed super-additive gene-environment interactions for CRC risk between the genetic risk score and body mass index (RERI=0.15; 95% CI: 0.00-0.31), ever smoking (RERI=0.14; 95% CI: 0.00-0.28), pack-years of smoking (RERI=0.23; 95% CI: 0.05-0.41), postmenopausal hormone therapy use (RERI=0.38; 95% CI: 0.17-0.59), and intake of processed meat (RERI=0.23; 95% CI: 0.06-0.40). Of the 15 environmental risk factors, 12 showed RERIs > 0 – suggesting an overall trend toward super-additive interactions for these factors. In addition, we observed evidence of sub-multiplicative interactions for use of aspirin and non-steroidal anti-inflammatory drugs. There were no other statistically significant multiplicative interactions. Conclusions: We observed evidence for super-additive effects of genetic predisposition and environmental risk factors on risk of CRC. Our findings suggest that certain environmental risk factors have stronger effects on absolute risk among individuals with higher genetic risk of CRC. If confirmed in future studies, these results may have implications for targeted prevention strategies. Citation Format: Mengmeng Du, Sonja I. Berndt, Hermann Brenner, Bette J. Caan, Peter T. Campbell, Graham Casey, Andrew Chan, Jenny Chang-Claude, Stephen J. Chanock, Nilanjan Chatterjee, David V. Conti, David Duggan, Jane C. Figueiredo, Steven Gallinger, Jian Gong, Robert W. Haile, Tabitha A. Harrison, Richard B. Hayes, Michael Hoffmeister, John L. Hopper, Li Hsu, Thomas J. Hudson, Carolyn M. Hutter, Eric J. Jacobs, Mark A. Jenkins, Shuo Jiao, Laurence N. Kolonel, Peter Kraft, Loic Le Marchand, Mathieu Lemire, Yi Lin, Noralane M. Lindor, Polly A. Newcomb, John D. Potter, Robert E. Schoen, Fredrick R. Schumacher, Daniela Seminara, Martha L. Slattery, Stephen N. Thibodeau, Cornelia M. Ulrich, Aung Ko Win, Emily White, Brent W. Zanke, Ulrike Peters. Additive and multiplicative gene-environment interactions for colorectal cancer risk. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 4831. doi:10.1158/1538-7445.AM2013-4831

AbstractOver the past several years, genome‐wide association studies (GWAS) have succeeded in identifying hundreds of genetic markers associated with common diseases. However, most of these markers confer relatively small increments of risk and explain only a small proportion of familial clustering. To identify obstacles to future progress in genetic epidemiology research and provide recommendations to NIH for overcoming these barriers, the National Cancer Institute sponsored a workshop entitled “Next Generation Analytic Tools for Large‐Scale Genetic Epidemiology Studies of Complex Diseases” on September 15–16, 2010. The goal of the workshop was to facilitate discussions on (1) statistical strategies and methods to efficiently identify genetic and environmental factors contributing to the risk of complex disease; and (2) how to develop, apply, and evaluate these strategies for the design, analysis, and interpretation of large‐scale complex disease association studies in order to guide NIH in setting the future agenda in this area of research. The workshop was organized as a series of short presentations covering scientific (gene‐gene and gene‐environment interaction, complex phenotypes, and rare variants and next generation sequencing) and methodological (simulation modeling and computational resources and data management) topic areas. Specific needs to advance the field were identified during each session and are summarized.Genet. Epidemiol. 36 : 22–35, 2012. © 2011 Wiley Periodicals, Inc.

Abstract Caspases play a critical role in regulation of apoptosis, cell differentiation, inflammation, and innate immunity, and several are mutated or have altered expression in non-Hodgkin lymphoma (NHL). To study the impact of genetic variation in caspases on NHL risk, we analyzed tag single nucleotide polymorphisms (SNPs) in 12 caspase and related genes in 3 population-based case-control studies (1946 cases and 1808 controls). Gene-based analysis, adjusting for the number of tagSNPs genotyped in each gene, showed significant associations for CASP8, CASP9, and CASP1. SNP-based analysis showed that CASP8 rs6736233 (odds ratio (OR) CG = 1.21; ORCC = 2.13; P trend = .011); CASP9 rs4661636 (ORCT = 0.89; ORTT = 0.77; P trend = .011); and CASP1 rs1785882 (ORAT = 1.12; ORAA = 1.30; P trend = .0054) were significantly associated with NHL risk and consistent across studies. It is noteworthy that genetic variants in CASP8 were associated with risk of all major NHL subtypes. Our findings suggest that genetic variation in caspases may play an important role in lymphomagenesis.

AbstractChromosomal translocations are the hallmark genetic aberration in non–Hodgkin lymphoma (NHL), with specific translocations often selectively associated with specific NHL subtypes. Because many NHL-associated translocations involve cell cycle, apoptosis, and lymphocyte development regulatory genes, we evaluated NHL risk associated with common genetic variation in 20 candidate genes in these pathways. Genotyping of 203 tag single nucleotide polymorphisms (SNP) was conducted in 1,946 NHL cases and 1,808 controls pooled from 3 independent population-based case-control studies. We used logistic regression to compute odds ratios (OR) and 95% confidence intervals (CI) for NHL and four major NHL subtypes in relation to tag SNP genotypes and haplotypes. We observed the most striking associations for tag SNPs in the proapoptotic gene BCL2L11 (BIM) and BCL7A, which is involved in a rare NHL-associated translocation. Variants in BCL2L11 were strongly related to follicular lymphoma only, particularly rs3789068 (ORAG, 1.41; 95% CI, 1.10-1.81; ORGG, 1.65; 95% CI, 1.25-2.19; Ptrend = 0.0004). Variants in BCL7A were strongly related to diffuse large B-cell lymphoma only, particularly rs1880030 (ORAG, 1.34; 95% CI, 1.08-1.68; ORAA, 1.60; 95% CI, 1.22-2.08; Ptrend = 0.0004). The associations for both variants were similar in all three studies and supported by haplotype analyses. We also observed notable associations for variants in BCL6, CCND1, and MYC. Our results support the role of common genetic variation in cell cycle, apoptosis, and lymphocyte development regulatory genes in lymphomagenesis, and suggest that effects may vary by NHL subtype. Replication of our findings and further study to identify functional SNPs are warranted. (Cancer Epidemiol Biomarkers Prev 2009;18(4):1259–70)

Organochlorine exposure was linked to non-Hodgkin lymphoma (NHL) risk. To determine whether this relation is modified by immune gene variation, we genotyped 61 polymorphisms in 36 immune genes in 1172 NHL cases and 982 controls from the National Cancer Institute–Surveillance, Epidemiology, and End Results (NCI-SEER) study. We examined 3 exposures with elevated risk in this study: PCB180 (plasma, dust measurements), the toxic equivalency quotient (an integrated functional measure of several organochlorines) in plasma, and α-chlordane (dust measurements, self-reported termiticide use). Plasma (100 cases, 100 controls) and dust (682 cases, 513 controls) levels were treated as natural log-transformed continuous variables. Unconditional logistic regression was used to calculate β coefficients and odds ratios, stratified by genotype. Associations between all 3 exposures and NHL risk were limited to the same genotypes for IFNG (C−1615T) TT and IL4 (5′-UTR, Ex1-168C>T) CC. Associations between PCB180 in plasma and dust and NHL risk were limited to the same genotypes for IL16 (3′-UTR, Ex22+871A>G) AA, IL8 (T−251A) TT, and IL10 (A−1082G) AG/GG. This shows that the relation between organochlorine exposure and NHL risk may be modified by particular variants in immune genes and provides one of the first examples of a potential gene-environment interaction for NHL.

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.

Abstract Profound disruption of immune function is an established risk factor for non-Hodgkin lymphoma. We report here a large-scale evaluation of common genetic variants in immune genes and their role in lymphoma. We genotyped 57 single nucleotide polymorphisms (SNP) from 36 candidate immune genes in 1,172 non-Hodgkin lymphoma cases and 982 population-based controls from a US multicenter study. We calculated odds ratios (OR) and 95% confidence intervals (95% CI) for the association between individual SNP and haplotypes with non-Hodgkin lymphoma overall and five well-defined subtypes. A haplotype comprising SNPs in two proinflammatory cytokines, tumor necrosis factor-α and lymphotoxin-α (rs1800629, rs361525, rs1799724, rs909253, and rs2239704), increased non-Hodgkin lymphoma risk overall (OR, 1.31; 95% CI, 1.06-1.63; P = 0.01) and notably for diffuse large B cell (OR, 1.64; 95% CI, 1.23-2.19; P = 0.0007). A functional nonsynonymous SNP in the innate immune gene Fcγ receptor 2A (FCGR2A; rs1801274) was also associated with non-Hodgkin lymphoma; AG and AA genotypes were associated with a 1.26-fold (95% CI, 1.01-1.56) and 1.41-fold (95% CI, 1.10-1.81) increased risk, respectively (Ptrend = 0.006). Among non-Hodgkin lymphoma subtypes, the association with FCGR2A was pronounced for follicular and small lymphocytic lymphomas. In conclusion, common variants in genes influencing proinflammatory and innate immune responses were associated with non-Hodgkin lymphoma risk overall and their effects could vary by subtype. Our results require replication but potentially provide important clues for investigating common genetic variants as susceptibility factors and in disease outcomes, treatment responses, and immunotherapy targets. (Cancer Res 2006; 66(19): 9771-80)