RE: Elevated Bladder Cancer in Northern New England: The Role of Drinking Water and Arsenic

RE: Elevated Bladder Cancer in Northern New England: The Role of Drinking Water and Arsenic In a large, population-based case–control study in New England, we recently reported a positive exposure-response relationship between cumulative arsenic intake from drinking water and bladder cancer risk (odds ratio [OR] for quartile 4 vs quartile 1 = 1.32, 95% confidence interval [CI] = 1.02 to 1.72; OR = 1.37, 95% CI = 1.03 to 1.82, for exposure lagged 40 years) (Supplementary Table 1, available online) (1). The mechanism by which arsenic induces bladder cancer is not well understood, although several studies have suggested arsenic may target important tumor-suppresser genes (p16, Rb) and disrupt cell cycle control (2). Here, we show heterogeneity in the arsenic–bladder cancer risk relationship by tumor expression of these cell cycle proteins. Tumor tissues from bladder cancer cases enrolled in the Maine and Vermont components of the New England bladder cancer case–control study were assembled as tissue microarrays and examined for expression of p16 and Rb. Cases (n = 424) were compared with controls (n = 1287) from all study states (ME, VT, NH), as distributions of cumulative arsenic from drinking water, as well as covariates, were similar across states. Data on cumulative arsenic from drinking water were used to evaluate the relationship between arsenic and bladder cancer risk by immunophenotype (p16-/p16+ and Rb-/Rb+) using polytomous logistic regression. Tissue microarray construction, immunohistochemistry (IHC), scoring, and definitions for immunophenotype have been published in detail previously (3). Tests for linear trend and Pheterogeneity values were calculated using the Wald test. Statistical tests were two-sided, with a type I error α of .05. Our results show that increasing arsenic intake from drinking water was associated with bladder cancer risk only when comparing patients with p16+ or Rb+ tumors with controls (representing 72.8% and 74.0% of tumors, respectively), with a strong monotonic association with increasing intake (compared with lowest unlagged exposure, ORp16+ = 1.36, 95% CI = 1.47 to 1.85, Ptrend = .004; ORRb+ = 1.51, 95% CI = 1.56 to 1.94, Ptrend = .007) (Table 1). There was no association between arsenic and p16- or Rb- bladder tumors (Pheterogeneity by subtype = .03 for p16 and .06 for Rb). This heterogeneity was not evident across subtypes defined by stage or grade (Supplementary Table 1, available online) despite the relationship of these markers with stage and grade of bladder cancer (4). Table 1. Association between cumulative arsenic exposure and bladder cancer risk by tumor immunophenotype Cumulative arsenic quartiles Case negative Case positive Control Immunophenotype* OR (95% CI)† Pheterogeneity‡ p16 IHC (-) p16 IHC (+) Unlagged, mg  0–15.70 29 53 327 Ref Ref  >15.70–34.50 31 74 321 1.03 (0.59 to 1.79) 1.36 (0.91 to 2.03)  >34.50–77.04 27 80 321 0.88 (0.50 to 1.55) 1.47 (0.99 to 2.19)  >77.04 28 102 318 0.88 (0.50 to 1.56) 1.85 (1.25 to 2.72) .03  Ptrend§ .60 .005 Lagged–40 y, mg  0–3.52 33 56 313 Ref Ref  >3.52–8.77 28 69 308 0.80 (0.46 to 1.41) 1.18 (0.78 to 1.77)  >8.77–22.42 20 73 311 0.61 (0.33 to 1.15) 1.43 (0.95 to 2.16)  >22.42 32 107 305 0.98 (0.55 to 1.75) 2.12 (1.39 to 3.22) .06  Ptrend§ .75 <.001 Unlagged, mg Rb IHC (-) Rb IHC (+)  0–15.70 29 46 327 Ref Ref  >15.70–34.50 23 72 321 0.79 (0.44 to 1.42) 1.51 (1.00 to 2.30)  >34.50–77.04 18 76 321 0.60 (0.32 to 1.13) 1.56 (1.03 to 2.37)  >77.04 30 93 318 0.95 (0.54 to 1.67) 1.94 (1.29 to 2.92) .19  Ptrend§ .78 .007 Lagged–40 y, mg  0–3.52 25 56 313 Ref Ref  >3.52–8.77 24 63 308 0.95 (0.51 to 1.76) 1.13 (0.74 to 1.73)  >8.77–22.42 23 64 311 0.93 (0.49 to 1.77) 1.24 (0.80 to 1.92)  >22.42 27 101 305 1.03 (0.54 to 1.95) 2.00 (1.30 to 3.05) .06  Ptrend§ .83 <.001 Cumulative arsenic quartiles Case negative Case positive Control Immunophenotype* OR (95% CI)† Pheterogeneity‡ p16 IHC (-) p16 IHC (+) Unlagged, mg  0–15.70 29 53 327 Ref Ref  >15.70–34.50 31 74 321 1.03 (0.59 to 1.79) 1.36 (0.91 to 2.03)  >34.50–77.04 27 80 321 0.88 (0.50 to 1.55) 1.47 (0.99 to 2.19)  >77.04 28 102 318 0.88 (0.50 to 1.56) 1.85 (1.25 to 2.72) .03  Ptrend§ .60 .005 Lagged–40 y, mg  0–3.52 33 56 313 Ref Ref  >3.52–8.77 28 69 308 0.80 (0.46 to 1.41) 1.18 (0.78 to 1.77)  >8.77–22.42 20 73 311 0.61 (0.33 to 1.15) 1.43 (0.95 to 2.16)  >22.42 32 107 305 0.98 (0.55 to 1.75) 2.12 (1.39 to 3.22) .06  Ptrend§ .75 <.001 Unlagged, mg Rb IHC (-) Rb IHC (+)  0–15.70 29 46 327 Ref Ref  >15.70–34.50 23 72 321 0.79 (0.44 to 1.42) 1.51 (1.00 to 2.30)  >34.50–77.04 18 76 321 0.60 (0.32 to 1.13) 1.56 (1.03 to 2.37)  >77.04 30 93 318 0.95 (0.54 to 1.67) 1.94 (1.29 to 2.92) .19  Ptrend§ .78 .007 Lagged–40 y, mg  0–3.52 25 56 313 Ref Ref  >3.52–8.77 24 63 308 0.95 (0.51 to 1.76) 1.13 (0.74 to 1.73)  >8.77–22.42 23 64 311 0.93 (0.49 to 1.77) 1.24 (0.80 to 1.92)  >22.42 27 101 305 1.03 (0.54 to 1.95) 2.00 (1.30 to 3.05) .06  Ptrend§ .83 <.001 * Cutoff values used to define negative and positive staining for each marker were based on the distribution of the percentage of positive cells among all cases (30% for both markers). Spearman correlation among markers was .24 (P < .05, two-sided P value computed using t distribution with n = 2 degrees of freedom). CI = confidence interval; HR = hazard ratio; IHC = immunohistochemistry. † Odds ratios and 95% confidence intervals from polytomous logistic regression are adjusted for age, sex, ethnicity, smoking, disinfection by products, and high-risk occupation. ‡ Pheterogeneity based on a two-sided Wald test. § Ptrend based on a two-sided Wald test for linear trend. Table 1. Association between cumulative arsenic exposure and bladder cancer risk by tumor immunophenotype Cumulative arsenic quartiles Case negative Case positive Control Immunophenotype* OR (95% CI)† Pheterogeneity‡ p16 IHC (-) p16 IHC (+) Unlagged, mg  0–15.70 29 53 327 Ref Ref  >15.70–34.50 31 74 321 1.03 (0.59 to 1.79) 1.36 (0.91 to 2.03)  >34.50–77.04 27 80 321 0.88 (0.50 to 1.55) 1.47 (0.99 to 2.19)  >77.04 28 102 318 0.88 (0.50 to 1.56) 1.85 (1.25 to 2.72) .03  Ptrend§ .60 .005 Lagged–40 y, mg  0–3.52 33 56 313 Ref Ref  >3.52–8.77 28 69 308 0.80 (0.46 to 1.41) 1.18 (0.78 to 1.77)  >8.77–22.42 20 73 311 0.61 (0.33 to 1.15) 1.43 (0.95 to 2.16)  >22.42 32 107 305 0.98 (0.55 to 1.75) 2.12 (1.39 to 3.22) .06  Ptrend§ .75 <.001 Unlagged, mg Rb IHC (-) Rb IHC (+)  0–15.70 29 46 327 Ref Ref  >15.70–34.50 23 72 321 0.79 (0.44 to 1.42) 1.51 (1.00 to 2.30)  >34.50–77.04 18 76 321 0.60 (0.32 to 1.13) 1.56 (1.03 to 2.37)  >77.04 30 93 318 0.95 (0.54 to 1.67) 1.94 (1.29 to 2.92) .19  Ptrend§ .78 .007 Lagged–40 y, mg  0–3.52 25 56 313 Ref Ref  >3.52–8.77 24 63 308 0.95 (0.51 to 1.76) 1.13 (0.74 to 1.73)  >8.77–22.42 23 64 311 0.93 (0.49 to 1.77) 1.24 (0.80 to 1.92)  >22.42 27 101 305 1.03 (0.54 to 1.95) 2.00 (1.30 to 3.05) .06  Ptrend§ .83 <.001 Cumulative arsenic quartiles Case negative Case positive Control Immunophenotype* OR (95% CI)† Pheterogeneity‡ p16 IHC (-) p16 IHC (+) Unlagged, mg  0–15.70 29 53 327 Ref Ref  >15.70–34.50 31 74 321 1.03 (0.59 to 1.79) 1.36 (0.91 to 2.03)  >34.50–77.04 27 80 321 0.88 (0.50 to 1.55) 1.47 (0.99 to 2.19)  >77.04 28 102 318 0.88 (0.50 to 1.56) 1.85 (1.25 to 2.72) .03  Ptrend§ .60 .005 Lagged–40 y, mg  0–3.52 33 56 313 Ref Ref  >3.52–8.77 28 69 308 0.80 (0.46 to 1.41) 1.18 (0.78 to 1.77)  >8.77–22.42 20 73 311 0.61 (0.33 to 1.15) 1.43 (0.95 to 2.16)  >22.42 32 107 305 0.98 (0.55 to 1.75) 2.12 (1.39 to 3.22) .06  Ptrend§ .75 <.001 Unlagged, mg Rb IHC (-) Rb IHC (+)  0–15.70 29 46 327 Ref Ref  >15.70–34.50 23 72 321 0.79 (0.44 to 1.42) 1.51 (1.00 to 2.30)  >34.50–77.04 18 76 321 0.60 (0.32 to 1.13) 1.56 (1.03 to 2.37)  >77.04 30 93 318 0.95 (0.54 to 1.67) 1.94 (1.29 to 2.92) .19  Ptrend§ .78 .007 Lagged–40 y, mg  0–3.52 25 56 313 Ref Ref  >3.52–8.77 24 63 308 0.95 (0.51 to 1.76) 1.13 (0.74 to 1.73)  >8.77–22.42 23 64 311 0.93 (0.49 to 1.77) 1.24 (0.80 to 1.92)  >22.42 27 101 305 1.03 (0.54 to 1.95) 2.00 (1.30 to 3.05) .06  Ptrend§ .83 <.001 * Cutoff values used to define negative and positive staining for each marker were based on the distribution of the percentage of positive cells among all cases (30% for both markers). Spearman correlation among markers was .24 (P < .05, two-sided P value computed using t distribution with n = 2 degrees of freedom). CI = confidence interval; HR = hazard ratio; IHC = immunohistochemistry. † Odds ratios and 95% confidence intervals from polytomous logistic regression are adjusted for age, sex, ethnicity, smoking, disinfection by products, and high-risk occupation. ‡ Pheterogeneity based on a two-sided Wald test. § Ptrend based on a two-sided Wald test for linear trend. The p16/Rb axis critically regulates G1 to S phase progression of the cell cycle, and alterations of this pathway have been identified as a mechanism of bladder carcinogenesis (5). Notably, homozygous deletion of CDKN2A (the gene that encodes p16), as well as inactivating mutations of RB1, occur commonly in bladder tumors and result in a loss of function of these important tumor suppressor genes (4). Our data suggest a low frequency of these mutations in arsenic-induced bladder cancer, pointing to an alternate mechanism. The role of arsenic on changes in DNA methylation and subsequent gene regulation has been one of the most intensively studied mechanisms by which arsenic mediates carcinogenesis (6). In addition, the silencing of tumor suppressors by arsenic, including hypermethylation of CDKN2A, has been evaluated in several studies (reviewed in [6]). Our data provide additional evidence linking arsenic exposure and bladder cancer risk and point to alterations of the cell cycle as the relevant pathway, although the precise mechanisms need further evaluation in additional experimental and human studies. Funding This work was supported by the Intramural Research Program of the National Institutes of Health, National Cancer Institute, Division of Cancer Epidemiology and Genetics (Z01 CP010125-22). This project has been funded in whole or in part with federal funds from the National Cancer Institute, National Institutes of Health, under Contract No. HHSN261200800001E. Notes Affiliations of authors: Division of Cancer Epidemiology and Genetics (SK, DB, RP, MGC, NR, LEM, DTS) and Laboratory of Pathology, Center for Cancer Research (SMH), National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, MD; Clinical Research Directorate/Clinical Monitoring Research Program, Leidos Biomedical Research Inc., Frederick National Laboratory of Cancer Research, Frederick, MD (PL); Department of Pathology, University of Vermont College of Medicine, Burlington, VT (MK); Department of Pathology, Maine Medical Center, Portland, ME (MJ); Department of Pathology, Dartmouth Medical School, Hanover, NH (ARS); Maine Cancer Registry, Augusta, ME (MS); Vermont Department of Health, Burlington, VT (AJ); Department of Epidemiology, Geisel School of Medicine at Dartmouth, Hanover, NH (MRK). None of the authors has conflicts of interest that are relevant to the subject matter or materials discussed in the manuscript. The authors had full responsibility for the design of the study, the collection of the data, the analysis and interpretation of the data, the decision to submit the manuscript for publication, and the writing of the manuscript. References 1 Baris D , Waddell R , Beane Freeman LE , et al. . Elevated bladder cancer in northern New England: The role of drinking water and arsenic . J Natl Cancer Inst. 2016 ; 108 ( 9 ):djw099. 2 IARC . Arsenic, metals, fibers and dusts . IARC Monogr Eval Carcinog Risks Hum . 2012 ; 100 ( Pt C ): 11 – 465 . PubMed 3 Lenz P , Pfeiffer R , Baris D , et al. . Cell-cycle control in urothelial carcinoma: Large-scale tissue array analysis of tumor tissue from Maine and Vermont . Cancer Epidemiol Biomarkers Prev. 2012 ; 21 ( 9 ): 1555 – 1564 . Google Scholar Crossref Search ADS PubMed 4 Knowles MA , Hurst CD. Molecular biology of bladder cancer: New insights into pathogenesis and clinical diversity . Nat Rev Cancer. 2015 ; 15 ( 1 ): 25 – 41 . Google Scholar Crossref Search ADS PubMed 5 The Cancer Genome Atlas Research Network. Comprehensive molecular characterization of urothelial bladder carcinoma . Nature. 2014 ; 507 ( 7492 ): 315 – 322 . Crossref Search ADS PubMed 6 Reichard JF , Puga A. Effects of arsenic exposure on DNA methylation and epigenetic gene regulation . Epigenomics. 2010 ; 2 ( 1 ): 87 – 104 . Google Scholar Crossref Search ADS PubMed Published by Oxford University Press 2018. This work is written by US Government employees and is in the public domain in the US. This work is written by (a) US Government employee(s) and is in the public domain in the US. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png JNCI: Journal of the National Cancer Institute Oxford University Press

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Abstract

In a large, population-based case–control study in New England, we recently reported a positive exposure-response relationship between cumulative arsenic intake from drinking water and bladder cancer risk (odds ratio [OR] for quartile 4 vs quartile 1 = 1.32, 95% confidence interval [CI] = 1.02 to 1.72; OR = 1.37, 95% CI = 1.03 to 1.82, for exposure lagged 40 years) (Supplementary Table 1, available online) (1). The mechanism by which arsenic induces bladder cancer is not well understood, although several studies have suggested arsenic may target important tumor-suppresser genes (p16, Rb) and disrupt cell cycle control (2). Here, we show heterogeneity in the arsenic–bladder cancer risk relationship by tumor expression of these cell cycle proteins. Tumor tissues from bladder cancer cases enrolled in the Maine and Vermont components of the New England bladder cancer case–control study were assembled as tissue microarrays and examined for expression of p16 and Rb. Cases (n = 424) were compared with controls (n = 1287) from all study states (ME, VT, NH), as distributions of cumulative arsenic from drinking water, as well as covariates, were similar across states. Data on cumulative arsenic from drinking water were used to evaluate the relationship between arsenic and bladder cancer risk by immunophenotype (p16-/p16+ and Rb-/Rb+) using polytomous logistic regression. Tissue microarray construction, immunohistochemistry (IHC), scoring, and definitions for immunophenotype have been published in detail previously (3). Tests for linear trend and Pheterogeneity values were calculated using the Wald test. Statistical tests were two-sided, with a type I error α of .05. Our results show that increasing arsenic intake from drinking water was associated with bladder cancer risk only when comparing patients with p16+ or Rb+ tumors with controls (representing 72.8% and 74.0% of tumors, respectively), with a strong monotonic association with increasing intake (compared with lowest unlagged exposure, ORp16+ = 1.36, 95% CI = 1.47 to 1.85, Ptrend = .004; ORRb+ = 1.51, 95% CI = 1.56 to 1.94, Ptrend = .007) (Table 1). There was no association between arsenic and p16- or Rb- bladder tumors (Pheterogeneity by subtype = .03 for p16 and .06 for Rb). This heterogeneity was not evident across subtypes defined by stage or grade (Supplementary Table 1, available online) despite the relationship of these markers with stage and grade of bladder cancer (4). Table 1. Association between cumulative arsenic exposure and bladder cancer risk by tumor immunophenotype Cumulative arsenic quartiles Case negative Case positive Control Immunophenotype* OR (95% CI)† Pheterogeneity‡ p16 IHC (-) p16 IHC (+) Unlagged, mg  0–15.70 29 53 327 Ref Ref  >15.70–34.50 31 74 321 1.03 (0.59 to 1.79) 1.36 (0.91 to 2.03)  >34.50–77.04 27 80 321 0.88 (0.50 to 1.55) 1.47 (0.99 to 2.19)  >77.04 28 102 318 0.88 (0.50 to 1.56) 1.85 (1.25 to 2.72) .03  Ptrend§ .60 .005 Lagged–40 y, mg  0–3.52 33 56 313 Ref Ref  >3.52–8.77 28 69 308 0.80 (0.46 to 1.41) 1.18 (0.78 to 1.77)  >8.77–22.42 20 73 311 0.61 (0.33 to 1.15) 1.43 (0.95 to 2.16)  >22.42 32 107 305 0.98 (0.55 to 1.75) 2.12 (1.39 to 3.22) .06  Ptrend§ .75 <.001 Unlagged, mg Rb IHC (-) Rb IHC (+)  0–15.70 29 46 327 Ref Ref  >15.70–34.50 23 72 321 0.79 (0.44 to 1.42) 1.51 (1.00 to 2.30)  >34.50–77.04 18 76 321 0.60 (0.32 to 1.13) 1.56 (1.03 to 2.37)  >77.04 30 93 318 0.95 (0.54 to 1.67) 1.94 (1.29 to 2.92) .19  Ptrend§ .78 .007 Lagged–40 y, mg  0–3.52 25 56 313 Ref Ref  >3.52–8.77 24 63 308 0.95 (0.51 to 1.76) 1.13 (0.74 to 1.73)  >8.77–22.42 23 64 311 0.93 (0.49 to 1.77) 1.24 (0.80 to 1.92)  >22.42 27 101 305 1.03 (0.54 to 1.95) 2.00 (1.30 to 3.05) .06  Ptrend§ .83 <.001 Cumulative arsenic quartiles Case negative Case positive Control Immunophenotype* OR (95% CI)† Pheterogeneity‡ p16 IHC (-) p16 IHC (+) Unlagged, mg  0–15.70 29 53 327 Ref Ref  >15.70–34.50 31 74 321 1.03 (0.59 to 1.79) 1.36 (0.91 to 2.03)  >34.50–77.04 27 80 321 0.88 (0.50 to 1.55) 1.47 (0.99 to 2.19)  >77.04 28 102 318 0.88 (0.50 to 1.56) 1.85 (1.25 to 2.72) .03  Ptrend§ .60 .005 Lagged–40 y, mg  0–3.52 33 56 313 Ref Ref  >3.52–8.77 28 69 308 0.80 (0.46 to 1.41) 1.18 (0.78 to 1.77)  >8.77–22.42 20 73 311 0.61 (0.33 to 1.15) 1.43 (0.95 to 2.16)  >22.42 32 107 305 0.98 (0.55 to 1.75) 2.12 (1.39 to 3.22) .06  Ptrend§ .75 <.001 Unlagged, mg Rb IHC (-) Rb IHC (+)  0–15.70 29 46 327 Ref Ref  >15.70–34.50 23 72 321 0.79 (0.44 to 1.42) 1.51 (1.00 to 2.30)  >34.50–77.04 18 76 321 0.60 (0.32 to 1.13) 1.56 (1.03 to 2.37)  >77.04 30 93 318 0.95 (0.54 to 1.67) 1.94 (1.29 to 2.92) .19  Ptrend§ .78 .007 Lagged–40 y, mg  0–3.52 25 56 313 Ref Ref  >3.52–8.77 24 63 308 0.95 (0.51 to 1.76) 1.13 (0.74 to 1.73)  >8.77–22.42 23 64 311 0.93 (0.49 to 1.77) 1.24 (0.80 to 1.92)  >22.42 27 101 305 1.03 (0.54 to 1.95) 2.00 (1.30 to 3.05) .06  Ptrend§ .83 <.001 * Cutoff values used to define negative and positive staining for each marker were based on the distribution of the percentage of positive cells among all cases (30% for both markers). Spearman correlation among markers was .24 (P < .05, two-sided P value computed using t distribution with n = 2 degrees of freedom). CI = confidence interval; HR = hazard ratio; IHC = immunohistochemistry. † Odds ratios and 95% confidence intervals from polytomous logistic regression are adjusted for age, sex, ethnicity, smoking, disinfection by products, and high-risk occupation. ‡ Pheterogeneity based on a two-sided Wald test. § Ptrend based on a two-sided Wald test for linear trend. Table 1. Association between cumulative arsenic exposure and bladder cancer risk by tumor immunophenotype Cumulative arsenic quartiles Case negative Case positive Control Immunophenotype* OR (95% CI)† Pheterogeneity‡ p16 IHC (-) p16 IHC (+) Unlagged, mg  0–15.70 29 53 327 Ref Ref  >15.70–34.50 31 74 321 1.03 (0.59 to 1.79) 1.36 (0.91 to 2.03)  >34.50–77.04 27 80 321 0.88 (0.50 to 1.55) 1.47 (0.99 to 2.19)  >77.04 28 102 318 0.88 (0.50 to 1.56) 1.85 (1.25 to 2.72) .03  Ptrend§ .60 .005 Lagged–40 y, mg  0–3.52 33 56 313 Ref Ref  >3.52–8.77 28 69 308 0.80 (0.46 to 1.41) 1.18 (0.78 to 1.77)  >8.77–22.42 20 73 311 0.61 (0.33 to 1.15) 1.43 (0.95 to 2.16)  >22.42 32 107 305 0.98 (0.55 to 1.75) 2.12 (1.39 to 3.22) .06  Ptrend§ .75 <.001 Unlagged, mg Rb IHC (-) Rb IHC (+)  0–15.70 29 46 327 Ref Ref  >15.70–34.50 23 72 321 0.79 (0.44 to 1.42) 1.51 (1.00 to 2.30)  >34.50–77.04 18 76 321 0.60 (0.32 to 1.13) 1.56 (1.03 to 2.37)  >77.04 30 93 318 0.95 (0.54 to 1.67) 1.94 (1.29 to 2.92) .19  Ptrend§ .78 .007 Lagged–40 y, mg  0–3.52 25 56 313 Ref Ref  >3.52–8.77 24 63 308 0.95 (0.51 to 1.76) 1.13 (0.74 to 1.73)  >8.77–22.42 23 64 311 0.93 (0.49 to 1.77) 1.24 (0.80 to 1.92)  >22.42 27 101 305 1.03 (0.54 to 1.95) 2.00 (1.30 to 3.05) .06  Ptrend§ .83 <.001 Cumulative arsenic quartiles Case negative Case positive Control Immunophenotype* OR (95% CI)† Pheterogeneity‡ p16 IHC (-) p16 IHC (+) Unlagged, mg  0–15.70 29 53 327 Ref Ref  >15.70–34.50 31 74 321 1.03 (0.59 to 1.79) 1.36 (0.91 to 2.03)  >34.50–77.04 27 80 321 0.88 (0.50 to 1.55) 1.47 (0.99 to 2.19)  >77.04 28 102 318 0.88 (0.50 to 1.56) 1.85 (1.25 to 2.72) .03  Ptrend§ .60 .005 Lagged–40 y, mg  0–3.52 33 56 313 Ref Ref  >3.52–8.77 28 69 308 0.80 (0.46 to 1.41) 1.18 (0.78 to 1.77)  >8.77–22.42 20 73 311 0.61 (0.33 to 1.15) 1.43 (0.95 to 2.16)  >22.42 32 107 305 0.98 (0.55 to 1.75) 2.12 (1.39 to 3.22) .06  Ptrend§ .75 <.001 Unlagged, mg Rb IHC (-) Rb IHC (+)  0–15.70 29 46 327 Ref Ref  >15.70–34.50 23 72 321 0.79 (0.44 to 1.42) 1.51 (1.00 to 2.30)  >34.50–77.04 18 76 321 0.60 (0.32 to 1.13) 1.56 (1.03 to 2.37)  >77.04 30 93 318 0.95 (0.54 to 1.67) 1.94 (1.29 to 2.92) .19  Ptrend§ .78 .007 Lagged–40 y, mg  0–3.52 25 56 313 Ref Ref  >3.52–8.77 24 63 308 0.95 (0.51 to 1.76) 1.13 (0.74 to 1.73)  >8.77–22.42 23 64 311 0.93 (0.49 to 1.77) 1.24 (0.80 to 1.92)  >22.42 27 101 305 1.03 (0.54 to 1.95) 2.00 (1.30 to 3.05) .06  Ptrend§ .83 <.001 * Cutoff values used to define negative and positive staining for each marker were based on the distribution of the percentage of positive cells among all cases (30% for both markers). Spearman correlation among markers was .24 (P < .05, two-sided P value computed using t distribution with n = 2 degrees of freedom). CI = confidence interval; HR = hazard ratio; IHC = immunohistochemistry. † Odds ratios and 95% confidence intervals from polytomous logistic regression are adjusted for age, sex, ethnicity, smoking, disinfection by products, and high-risk occupation. ‡ Pheterogeneity based on a two-sided Wald test. § Ptrend based on a two-sided Wald test for linear trend. The p16/Rb axis critically regulates G1 to S phase progression of the cell cycle, and alterations of this pathway have been identified as a mechanism of bladder carcinogenesis (5). Notably, homozygous deletion of CDKN2A (the gene that encodes p16), as well as inactivating mutations of RB1, occur commonly in bladder tumors and result in a loss of function of these important tumor suppressor genes (4). Our data suggest a low frequency of these mutations in arsenic-induced bladder cancer, pointing to an alternate mechanism. The role of arsenic on changes in DNA methylation and subsequent gene regulation has been one of the most intensively studied mechanisms by which arsenic mediates carcinogenesis (6). In addition, the silencing of tumor suppressors by arsenic, including hypermethylation of CDKN2A, has been evaluated in several studies (reviewed in [6]). Our data provide additional evidence linking arsenic exposure and bladder cancer risk and point to alterations of the cell cycle as the relevant pathway, although the precise mechanisms need further evaluation in additional experimental and human studies. Funding This work was supported by the Intramural Research Program of the National Institutes of Health, National Cancer Institute, Division of Cancer Epidemiology and Genetics (Z01 CP010125-22). This project has been funded in whole or in part with federal funds from the National Cancer Institute, National Institutes of Health, under Contract No. HHSN261200800001E. Notes Affiliations of authors: Division of Cancer Epidemiology and Genetics (SK, DB, RP, MGC, NR, LEM, DTS) and Laboratory of Pathology, Center for Cancer Research (SMH), National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, MD; Clinical Research Directorate/Clinical Monitoring Research Program, Leidos Biomedical Research Inc., Frederick National Laboratory of Cancer Research, Frederick, MD (PL); Department of Pathology, University of Vermont College of Medicine, Burlington, VT (MK); Department of Pathology, Maine Medical Center, Portland, ME (MJ); Department of Pathology, Dartmouth Medical School, Hanover, NH (ARS); Maine Cancer Registry, Augusta, ME (MS); Vermont Department of Health, Burlington, VT (AJ); Department of Epidemiology, Geisel School of Medicine at Dartmouth, Hanover, NH (MRK). None of the authors has conflicts of interest that are relevant to the subject matter or materials discussed in the manuscript. The authors had full responsibility for the design of the study, the collection of the data, the analysis and interpretation of the data, the decision to submit the manuscript for publication, and the writing of the manuscript. References 1 Baris D , Waddell R , Beane Freeman LE , et al. . Elevated bladder cancer in northern New England: The role of drinking water and arsenic . J Natl Cancer Inst. 2016 ; 108 ( 9 ):djw099. 2 IARC . Arsenic, metals, fibers and dusts . IARC Monogr Eval Carcinog Risks Hum . 2012 ; 100 ( Pt C ): 11 – 465 . PubMed 3 Lenz P , Pfeiffer R , Baris D , et al. . Cell-cycle control in urothelial carcinoma: Large-scale tissue array analysis of tumor tissue from Maine and Vermont . Cancer Epidemiol Biomarkers Prev. 2012 ; 21 ( 9 ): 1555 – 1564 . Google Scholar Crossref Search ADS PubMed 4 Knowles MA , Hurst CD. Molecular biology of bladder cancer: New insights into pathogenesis and clinical diversity . Nat Rev Cancer. 2015 ; 15 ( 1 ): 25 – 41 . Google Scholar Crossref Search ADS PubMed 5 The Cancer Genome Atlas Research Network. Comprehensive molecular characterization of urothelial bladder carcinoma . Nature. 2014 ; 507 ( 7492 ): 315 – 322 . Crossref Search ADS PubMed 6 Reichard JF , Puga A. Effects of arsenic exposure on DNA methylation and epigenetic gene regulation . Epigenomics. 2010 ; 2 ( 1 ): 87 – 104 . Google Scholar Crossref Search ADS PubMed Published by Oxford University Press 2018. This work is written by US Government employees and is in the public domain in the US. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Journal

JNCI: Journal of the National Cancer InstituteOxford University Press

Published: Nov 1, 2018

References

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