JNCI J Natl Cancer Inst (2015) 107(11): djv223 doi:10.1093/jnci/djv223 First published online September 14, 2015 Brief Communication
brief communication
Modification of Occupational Exposures on Bladder Cancer Risk by Common Genetic Polymorphisms Jonine D. Figueroa*, Stella Koutros*, Joanne S. Colt, Manolis Kogevinas, Montserrat Garcia-Closas, Francisco X. Real, Melissa C. Friesen, Dalsu Baris, Patricia Stewart, Molly Schwenn, Alison Johnson, Margaret R. Karagas, Karla R. Armenti, Lee E. Moore, Alan Schned, Petra Lenz, Ludmila ProkuninaOlsson, A. Rouf Banday, Ashley Paquin, Kris Ylaya, Joon-Yong Chung, Stephen M. Hewitt, Michael L. Nickerson, Adonina Tardón, Consol Serra, Alfredo Carrato, Reina García-Closas, Josep Lloreta, Núria Malats, Joseph F. Fraumeni Jr., Stephen J. Chanock, Nilanjan Chatterjee†, Nathaniel Rothman†, Debra T. Silverman† Affiliations of authors: Division of Cancer Epidemiology and Genetics (JDF, SK, JSC, MGC, MCF, DB, PS, LEM, LPO, ARB, AP, JFFJr, SJC, NC, NR, DTS), Experimental Pathology Laboratory, Laboratory of Pathology, Center for Cancer Research (KY, JYC, SMH), and Cancer and Inflammation Program (MLN), National Cancer Institute, Bethesda, MD; Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh Medical School, Edinburgh UK (JDF); CIBERESP, CIBER Epidemiologia y Salud Publica, Madrid, Spain (MK, AT, JL); Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain (MK); Municipal Institute of Medical Research (IMIMHospital del Mar), Barcelona, Spain (MK); Division of Genetics and Epidemiology, Institute of Cancer Research, London, UK (MGC); Spanish National Cancer Research Centre (CNIO), Madrid, Spain (FXR, NM); Departament de Ciències Experimentals i de la Salut, Universitat Pompeu Fabra, Barcelona, Spain (FXR, CS); Maine Cancer Registry, Augusta, ME (MS); Vermont Cancer Registry, Burlington, VT (AJ); Geisel School of Medicine at Dartmouth, Hanover, NH (MRK, AS); New Hampshire Department of Health and Human Services, Concord, NH (KRA); Clinical Research Directorate/Clinical Monitoring Research Program, Leidos Biomedical Research, Inc. (formerly SAIC-Frederick, Inc.), Frederick National Laboratory for Cancer Research, Frederick, MD (PL); Molecular Epidemiology Group, Instituto Universitario de Oncologia, Universidad de Oviedo, Oviedo, Asturias, Spain (AT); Hospital Ramón y Cajal, Elche, Madrid, Spain (AC); Unidad de Investigación, Hospital Universitario de Canarias, La Laguna, Spain (RGC). *Authors contributed equally to this work. † Authors contributed equally to this work. Correspondence to: Jonine D. Figueroa, PhD, Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh Medical School, Teviot Place, Edinburgh EH8 9A8, UK (e-mail:
[email protected]).
Few studies have demonstrated gene/environment interactions in cancer research. Using data on high-risk occupations for 2258 case patients and 2410 control patients from two bladder cancer studies, we observed that three of 16 known or candidate bladder cancer susceptibility variants displayed statistically significant and consistent evidence of additive interactions; specifically, the GSTM1 deletion polymorphism (Pinteraction ≤ .001), rs11892031 (UGT1A, Pinteraction = .01), and rs798766 (TMEM129-TACC3-FGFR3, Pinteraction = .03). There was limited evidence for multiplicative interactions. When we examined detailed data on a prevalent occupational exposure associated with increased bladder cancer risk, straight metalworking fluids, we also observed statistically significant additive interaction for rs798766 (TMEM129-TACC3-FGFR3, Pinteraction = .02), with the interaction more apparent in patients with tumors positive for FGFR3 expression. All statistical tests were two-sided. The interaction we observed for rs798766 (TMEM129-TACC3-FGFR3) with specific exposure to straight metalworking fluids illustrates the value of integrating germline genetic variation, environmental exposures, and tumor marker data to provide insight into the mechanisms of bladder carcinogenesis.
Received: May 22, 2014; Revised: April 22, 2015; Accepted: July 16, 2015 Published by Oxford University Press 2015. This work is written by (a) US Government employee(s) and is in the public domain in the US.
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Abstract
2 of 5 | JNCI J Natl Cancer Inst, 2015, Vol. 107, No. 11
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Occupational exposures are a leading cause of bladder cancer, second only to smoking (1). Over 40 high-risk occupations for bladder cancer have been identified (1–3), yet few studies have examined whether the occupational risk is modified by genetic factors. We have demonstrated that the effect of smoking on absolute risk of bladder cancer, quantified using risk difference (RD) parameters, can vary by genetic susceptibility loci for bladder cancer (4–5). To further explore gene/environment interactions, we examined whether common single-nucleotide polymorphisms (SNPs) modify the association between employment in high-risk occupations and bladder cancer risk using data from 2258 case patients and 2410 control patients who participated in the New England Bladder Cancer Study (NEBCS) and the Spanish Bladder Cancer Study (6–7). All subjects gave informed consent, and each study was approved by the host institution’s internal review board. Lifetime occupational histories were obtained and exposureoriented questionnaire modules were administered to elicit information on selected exposures (2–3). High-risk occupations were identified separately by sex in each study (2–3), defined as those with bladder cancer odds ratios (ORs) of 1.5 or greater and with 10 or more employed individuals (Supplementary Table 1, available online), and were analyzed as a group hypothesizing a common mechanism of action from exposure to a mixture of putative carcinogens. We also assessed interactions with an a priori suspect occupational exposure, straight metalworking fluids (composed of mineral oils plus additives), which is common among the more prevalent high-risk occupations in both New England and Spain (Supplementary Table 1, available online). Based on detailed exposure data to quantify exposure to straight metalworking fluids in the NEBCS, we have shown a statistically significant association with increased bladder cancer risk (8). We used data on 16 SNPs identified as susceptibility variants for bladder cancer (4,9–17) to evaluate multiplicative and additive interactions. The Supplementary Materials (available online) contain additional details on genotyping, genome-wide interaction analysis, and the statistical methods used to assess interaction (5,18). All statistical tests were two-sided, and a P value of less than .05 was considered statistically significant. For five loci we observed a statistically significant interaction with employment in a high-risk occupation (Pinteraction < .05) (Table 1). Four loci had statistically significant differences in the RD for high-risk occupation by genotype (Padditive interaction < .05) (Table 1), the GSTM1 deletion polymorphism (Pinteraction ≤ .001), rs11892031 (UGT1A, Pinteraction = .01), rs907611 (LSP1- miRNA4298, Pinteraction = .01), and rs798766 (TMEM129-TACC3-FGFR3, Pinteraction = .03). In sensitivity analyses based on higher odds ratio cutpoints to define high-risk occupation (OR ≥ 1.7 or ≥ 2.0), three of these four SNPs showed consistent evidence for differences in RD for high-risk occupation by genotype, specifically rs11892031 (UGT1A), rs798766 (TMEM129-TACC3-FGFR3), and GSTM1 present/null genotype (Supplementary Table 2, available online). Evidence of additive interactions for rs798766 (TMEM129-TACC3FGFR3) and GSTM1 present/null genotype were also present when the genotypes were modeled as a three-level categorical variable rather than as a binary variable assuming a dominant model (Supplementary Table 3, available online). The evidence for additive interaction was strongest for GSTM1. We estimated that the difference in the 30-year absolute risk for men age 50 years living in the United States with and without a highrisk occupation was 3.0% for carriers of GSTM1-null and 1.9% GSTM1-present genotypes (Supplementary Table 4, available online) (5,19). There was limited evidence of multiplicative interaction, with only rs401681 (TERT-CPTML) showing statistically
significant differences in the relative risk for high-risk occupation by genotype (Pmultiplicative interaction = .03) (Table 1; Supplementary Table 2, available online). Recognizing that employment in high-risk occupations reflects heterogeneous exposures, we further explored interactions using detailed data on a specific exposure, straight metalworking fluids. We observed statistically significant differences in the RD for straight metalworking fluids by rs798766 genotype (Padditive interaction = .02) (Table 2; Supplementary Table 4, available online). Because rs798766 is located within the FGFR3 region and somatic changes in FGFR3 have been described in bladder tumors, we explored the relationship between tumor FGFR3 expression, the rs798766 genotypes, and straight metalworking fluids exposure (see the Supplementary Material, available online). Using FGFR3 immunohistochemistry data on 483 tumors from New England, we observed a statistically significant association between increased FGFR3 expression and the rs798766 risk allele (P = .01) (see the Supplementary Materials and Supplementary Figures 1–3, available online), consistent with a previous report (10). Data on mRNA expression from 197 bladder tumors also showed a trend of higher levels of FGFR3 expression with the rs798766 risk allele (Supplementary Figure 4, available online). Interestingly, the interaction between straight metalworking fluids and rs798766 was more apparent in the subset of patients with tumors displaying strong/intermediate FGFR3 expression (Padditive interaction = .02) compared with those with weak/no FGFR3 expression (Padditive interaction = .80) (Supplementary Table 5, available online). We found no association between the rs798766 and exposure to straight metalworking fluids in control patients, confirming that these factors are independent. Cumulatively, these data provide support that FGFR3 expression may play a role in defining the underlying mechanistic interaction between the rs798766 and straight metalworking fluid exposure. It is of interest to note that the three polymorphisms with consistent statistically significant additive interactions with high-risk occupation (GSTM1 null, rs11892031 [UGT1A], rs798766 [TMEM129-TACC3-FGFR3]) have also been observed to have statistically significant additive interactions with exposure to tobacco smoke (4,5,20). Given that GSTM1 and UGT1A are known carcinogen-metabolizing genes, our findings suggest that these genes may be important in the detoxification of one or more bladder chemical carcinogens in both tobacco and some highrisk occupations. Interestingly, a German study also found evidence of interaction among case patients who were both carriers of the GSTM1-null genotype and were employed in occupations exposed to known bladder carcinogens (21,22). Further, we present evidence linking exposure to straight metalworking fluids with bladder cancer risk using FGFR3 tumor expression data. Given that rs798766 also interacts with tobacco smoke (4), these data support the hypothesis that there may be pathways that are common to genotoxic exposures in tobacco smoke and straight metalworking fluids. Lastly, our data support the rs798766 (TMEM129-TACC3-FGFR3) results to be a biologically plausible interaction and also add to the weight of the evidence linking exposure to straight metalworking fluids to bladder cancer risk. Strengths of our study include high-quality detailed occupational exposure data in two large, well-designed case-control studies. Limitations of our study include limited power to broadly explore gene/environment interactions using the entire genome-wide association study data. Larger studies are needed to replicate and extend the observed findings. Only the P value of less than .001 for the additive interaction test of GSTM1and
rs4510656
rs6104690
rs907611
rs10936599
null vs present
170 117 70 51 721 565 185 182 416 337 318 248 311 255 476 393 98 76 39 28 319 284 457 364 44 46 474 358 162 149 227 176
Yes No Yes No Yes No Yes No Yes No Yes No Yes No Yes No Yes No Yes No Yes No Yes No Yes No Yes
Case patients, No.
No Yes No Yes No
Employed in a high-risk occupation* (Yes/No)
188 777 311 78 31 706 277 275 104 318 128
421 322 122 631 258 470 201 443 198 731 258 176 67 79 28 485
280 97 123 43 1025
Control patients, No.
2.47 (1.93 to 3.16) Ref 2.11 (1.72 to 2.58) Ref 2.61 (1.35 to 5.06) Ref 2.13 (1.73 to 2.63) Ref 2.77 (1.96 to 3.90) Ref 2.21 (1.63 to 2.99)
2.09 (1.77 to 2.48) Ref 2.96 (2.16 to 4.06) Ref 2.09 (1.68 to 2.59) Ref 1.96 (1.53 to 2.51) Ref 2.08 (1.62 to 2.67) Ref 2.52 (2.05 to 3.10) Ref 2.46 (1.57 to 3.86) Ref 1.67 (0.78 to 3.59) Ref
Ref 2.14 (1.50 to 3.05) Ref 2.81 (1.59 to 4.96) Ref
OR† (95% CI)
No risk allele
3.23×10-7
6.63×10-9
8.18×10-13
4.36×10-3
7.10×10-13
5.85×10-13
1.85×10-1
8.74×10-5
3.24×10-18
1.18×10-8
8.59×10-8
2.20×10-11
1.61×10-11
5.31×10-18
3.91×10-4
2.76×10-5
P 1272 518 1397 556 530 196 1208 478 922 358 1057 398 1104 415 822 359 1377 550 1473 585 1066 427 894 351 1443 564 794 309 1237 488 1204 467
979 813 1060 860 426 366 949 729 733 595 815 661 836 676 674 540 1052 857 1105 903 827 647 735 624 1086 859 643 533 967 751 904 729
Case Control patients patients
2.16 (1.83 to 2.53) Ref 2.36 (1.99 to 2.81) Ref 2.19 (1.91 to 2.52) Ref 2.31 (1.92 to 2.78) Ref 2.11 (1.82 to 2.45) Ref 2.23 (1.91 to 2.60)
2.48 (1.98 to 3.11) Ref 2.09 (1.80 to 2.43) Ref 2.31 (1.94 to 2.74) Ref 2.36 (2.00 to 2.77) Ref 2.32 (1.98 to 2.72) Ref 2.02 (1.70 to 2.41) Ref 2.19 (1.90 to 2.52) Ref 2.23 (1.95 to 2.56) Ref
Ref 2.20 (1.90 to 2.54) Ref 2.19 (1.90 to 2.52) Ref
OR† (95% CI)
One or two risk alleles
6.80×10-25
9.17×10-23
4.37×10-19
1.99×10-28
7.66×10-23
8.46×10-21
1.53×10-30
1.10×10-27
5.13×10-15
7.58×10-25
7.22×10-25
1.98×10-21
9.81×10-22
4.37×10-15
6.97×10-28
2.69×10-26
P
.28
.81
.01
.46
