Affiliations of authors: Cancer Prevention Studies Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD (CCA, PRT, SMD); Experimental Facilities Division, Argonne National Laboratory, Argonne, IL (BL, SV); Department of Cancer Epidemiology, Cancer Institute, Chinese Academy of Medical Sciences, Beijing, People's Republic of China (YLQ, XML, ZWD); Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD (SDM)
Correspondence to: Christian Abnet, PhD, MPH, Cancer Prevention Studies Branch, National Cancer Institute, National Institutes of Health, 6116 Executive Blvd., Rm. 705, Bethesda, MD 20892 (e-mail: abnetc{at}mail.nih.gov); You-Lin Qiao, MD, PhD, Department of Cancer Epidemiology, Cancer Institute, Chinese Academy of Medical Sciences, Beijing 100021, People's Republic of China (e-mail: qiaoy{at}public.bta.net.cn).
![]() |
ABSTRACT |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
![]() |
INTRODUCTION |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Because x-ray fluorescence spectroscopy directly measures actual tissues levels of elements, it has advantages over other methods of measuring zinc levels, such as quantifying serum zinc levels or estimating dietary zinc intake. Serum zinc concentrations are maintained homeostatically, and thus, serum zinc is a weak marker of zinc status in humans (8). Estimating zinc intake on the basis of nutrient density in diet is complicated by the dramatic differences in zinc bioavailability created by other dietary constituents. For example, phytate in whole grain efficiently prohibits dietary zinc uptake (9).
People who consume relatively little meat and large quantities of whole grain are more likely to be zinc deficient than those who eat more meat and more refined grains (9). This dietary pattern (low meat, high whole grain) is seen in residents of Linzhou (formerly Linxian), People's Republic of China. Previous studies in Linxian found that zinc levels in patients with esophageal squamous cell cancers are lower than those in control subjects, in both serum (81 and 91 µg/dL, respectively) and esophageal tissue (81 and 97 µg/g [dry weight], respectively) (10,11). Residents of Linzhou have some of the highest rates of esophageal squamous cell cancer and gastric cardia adenocarcinoma in the world, with more than 100 cases per 100 000 people per year (12). Two trials, the Nutrition Intervention Trials, were carried out in Linzhou (13), and a subset of the subjects enrolled in the Dysplasia Trial (13) underwent endoscopy with biopsy at the study baseline in 1985. These subjects have been followed through 2001.
In a prospective observational study, we used x-ray fluorescence to measure zinc, copper, iron, nickel, and sulfur levels in esophageal biopsy specimens from 60 subjects who developed esophageal squamous cell carcinoma during 16 years of follow-up and from 72 subjects, matched on worst baseline histology, who did not develop esophageal cancer.
![]() |
SUBJECTS AND METHODS |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
In 1985, as part of the baseline evaluation for the Dysplasia Trial (13), 3318 subjects completed a demographic questionnaire and a subset of 440 individuals had endoscopy and biopsy. All subjects provided oral informed consent, and the study was approved by the Institutional Review Boards of the U.S. National Cancer Institute and the Cancer Institute, Chinese Academy of Medical Sciences. Esophageal biopsy specimens contained only esophageal epithelium without lamina propria. All trial subjects were followed to ascertain vital status and incidence of cancer through May 31, 2001. Case ascertainment (13) and cancer definition (14) were as described previously, and all cases were verified by an international panel of experts. Among the participants who received endoscopy, 88 subjects developed esophageal squamous cell carcinoma, 60 of whom had sufficient tissue remaining in their biopsy specimens for x-ray fluorescence analysis. From the other 352 subjects who had endoscopy, we selected a group of 88 subjects who had not developed esophageal squamous cell carcinoma as of May 31, 2001 and matched them to the case subjects on worst baseline histology. Of the 88 control subjects, 72 had sufficient tissue remaining in their biopsy material for analysis. X-ray fluorescence measurements were therefore completed on a total of 132 samples.
X-Ray Fluorescence Measurements of the Tissue Concentration of the Elements
A single 5-µm-thick section was cut from each tissue block and mounted on 3525 Ultralene XRF film (SPEX CertiPrep, Metuchen, NJ). X-ray fluorescence measurements were carried out at beamline 2-BM of the Advanced Photon Source (Argonne National Laboratory, Argonne, IL). X-rays of 10.5 keV energy were focused to a 100-micron-diameter spot on the specimen. X-ray fluorescence emission was collected by an energy-dispersive silicon drift detector. Each experimental tissue was measured at two randomly selected sites within the tissue and at a single spot within the embedding wax outside the tissue. X-ray fluorescence emission spectra were collected for 200 seconds. In addition to measuring the experimental tissues, we measured a single section on five separate occasions in the same spots to assess the coefficient of variation for these measurements. Finally, we measured NIST standards NBS 1832 and NBS 1833 (National Institute of Standards, Gaithersburg, MD) to allow quantitative estimates of element concentrations.
The intensity of the x-ray fluorescence for each of the different elements was determined by fitting the elemental peaks in the x-ray fluorescence spectra to modified Gaussian functions (7). The measured sample intensities were converted to element concentrations (nanograms/cm2) by comparison with a calibration curve. The calibration curve was calculated from measurement of the NIST 1832 and 1833 standard reference materials by taking into account, for each chemical element of interest, the corresponding photoelectric absorption cross sections (15) based on fluorescence yield, absorption by the Beryllium window of the energy-dispersive fluorescence detector, and absorption by a dead layer on the detector. Individual experimental tissue concentrations for each element were derived by averaging the two tissue measurements and then subtracting the measurement in the embedding wax. After graphing the data, we found that the distribution of the tissue concentrations had a long right tail (i.e., the data were not normally distributed); we then log transformed the data, after which the distribution of the concentrations was approximately normal. Therefore, all analyses used log-transformed data. Of the 660 experimental sample measurements, only five measurements (one zinc, two nickel, one copper, and one iron) were more than 4 standard deviations from the geometric mean and had no other values nearby. We classified these measurements as outliers and excluded them from further analyses.
Assay Reliability
Using the five repeated measurements of the same section, we estimated the coefficient of variations to be 0.5% for zinc, 6% for copper, 3% for iron, 29% for nickel, and 3% for sulfur. The coefficient of variation for the four elements other than nickel were excellent, and that for nickel was acceptable. The lower coefficient of variation for nickel may reflect its low absolute concentration in our tissue sections. We examined the distribution of the differences between the two measurements of each experimental sample and found these to be normally distributed, and the mean of the differences did not statistically significantly differ from zero. Because the median ratios of the tissue-to-wax concentrations (i.e., foreground to background) were 28 for zinc, four for copper, three for iron, six for nickel, and two for sulfur, we had sufficient element concentrations above the background level in the wax to be unconcerned about potential contamination.
Statistical Analysis
Demographic data for case and control subjects was compared using chi-square tests for categorical variables and the Wilcoxon rank-sum test for age. The Wilcoxon rank-sum test was also used to compare element concentrations between cases and control subjects. Pearson's correlation coefficient was used to examine the correlation between element concentrations.
In our other analyses, we examined associations between cancer risk and three different constructs for the tissue concentrations. First, we centered and standardized the continuous variable (i.e., the element concentration) by subtracting the median value and dividing by the average size of the two central quartiles of the control values (0.5 x interquartile range). Second, we created quartile variables on the basis of the actual distribution of the tissue element concentrations from the control subjects. Third, we created an ordinal quartile trend variable in which the value from each subject was 1, 2, 3, or 4 depending on the quartile in which the subjects' value was assigned. For each construct, we used linear regression to examine the association between the log-transformed element concentrations and potential confounding factors such as age, sex, smoking status, and consumption of alcohol. We used the Wilcoxon rank-sum test to test the univariate association between tissue element concentration and esophageal cancer. To estimate within-quartile nonparametric survival curves and hazard ratios (HRs) in the Cox proportional hazards model, we used the estimators of Mark (16,17) as implemented in the R-software (18) by Katki and Mark (19). These estimators are weighted versions of the usual Nelson-Aalen and maximum partial-likelihood estimators (20) of the cumulative hazard ratios and hazard ratios, respectively. The weights account for the outcome by baseline histology-specific sampling fractions and are required to produce unbiased estimators (16,17). The nonparametric estimates of survival curves were obtained from the cumulative hazards by exponentiating the negative of the cumulative hazard estimates (16,17,20). These estimates are asymptotically equivalent to Kaplan-Meier estimates and are hereafter referred to as Kaplan-Meier survival curves adjusted for sampling fractions. All estimates of hazard ratios come from Cox proportional hazards models adjusted for age (continuous variable) and with indicator variables for sex; ever smoking (regular use for 6 months); drinking (any alcohol in the preceding 12 months); and mild, moderate, and severe dysplasia at baseline. Using no variable or a single variable (i.e., any dysplasia) to correct for histology produced results essentially similar to those reported. To test for deviations from the proportional hazards assumption, we fit Cox proportional hazards models by using spline parameterizations of the hazard ratios that allowed them to vary flexibly with time. No time trends were detectable. All P-values were two-sided and derived from the Wald test. Tests for trend were the usual one-degree of freedom test for log-linearity and used the ordinal classifications of element concentration quartile.
![]() |
RESULTS |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Subject characteristics are presented in Table 1. Subjects were similar in all categories, with the exception of alcohol consumption, which was less frequent among case subjects. Less than 25% of the Linzhou population consumed any alcohol, and among users, the amount consumed was very low. This distribution of alcohol consumption is similar to the cohort from which the subjects were drawn.
|
The medians and interquartile ranges for baseline levels of each of the measured elements (for case and control subjects stratified by future cancer incidence) are given in Table 2. Subjects who later developed esophageal cancer had statistically significantly lower baseline esophageal tissue concentrations of zinc than those who did not develop this cancer (44 versus 57 ng/cm2, P = .008). Levels of copper (8.3 versus 9.5 ng/cm2, P = .22), iron (10.0 versus 9.3 ng/cm2, P = .78), nickel (0.92 versus 0.88 ng/cm2, P = .82), and sulfur (752 versus 815 ng/cm2, P = .13) did not differ statistically significantly between case and control subjects, respectively.
|
Tissue Element Concentrations and Cancer Risk
We examined the relationship between incident esophageal squamous cell carcinoma for study participants stratified by quartile of tissue zinc concentration (Fig. 1). Approximately 90% of individuals in the highest zinc quartile were alive without esophageal cancer after 16 years (i.e., at the end of follow-up). By contrast, only 65% of individuals in the lowest zinc quartile were alive without esophageal cancer after 16 years. The individuals in the second and third quartile of zinc concentration show intermediary disease-free survival rates of 85% and 80%, respectively.
|
|
![]() |
DISCUSSION |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Our results are different from those obtained from an intervention trial conducted in the same subjects, in which they received zinc as part of a multivitamin supplement and in the companion General Population Trial, in which one group of subjects received zinc and retinol supplements (14,21). None of these trials showed protective effects of zinc supplements against esophageal squamous cell carcinoma incidence. In this observational study, by contrast, in which we examined zinc status by using esophageal tissue concentration, we found that higher zinc concentration in esophageal tissue was associated with a lower risk of esophageal squamous cell carcinoma. This same patterni.e., an association between baseline nutritional status and cancer rate in an observational study but no association in a randomized trial with the same subjectswas also seen for selenium and -tocopherol in this Chinese population (21,22). There are several potential explanations for the discrepancy in findings between the observational study of baseline nutrient status and the randomized trial of nutrient supplementation in the same subjects. For zinc, these possibilities include that the trial supplementation period was too short and/or the dose was too low, that the effects of lifelong zinc deficiency on carcinogenesis are not remediable by zinc supplementation later in life, that the form and method of zinc supplementation was ineffective, or that the presence of other elements such as iron (23) in the multivitamin supplement inhibited zinc absorption.
Our study is unique in that it examined elements rarely included in other studies, regardless of design. Copper has been examined in ecologic studies of dietary intake (24), but to our knowledge, prospective studies have not been reported. High nail concentrations of iron have been associated with increased risk of esophageal cancer in a U.S. case-control study (25). Metallic nickel and certain nickel compounds are reasonably anticipated to be human carcinogens (26) but have not been associated with esophageal cancer in human studies. The role of sulfur in esophageal cancer risk is difficult to assess because of its ubiquitous role in biology. Our results for copper, iron, nickel, and sulfur are somewhat equivocal, and the importance of these elements in the risk of developing esophageal squamous cell carcinoma will require further study.
Our study has several strengths. We used prospectively collected biologic samples from subjects nested in a cohort with essentially complete follow-up and disease status ascertainment. We measured zinc status by using target tissue concentrations, which is arguably the best method for assessing associations being zinc and the risk of disease.
Our study also has limitations. First, x-ray fluorescence cannot provide information on the form of the element (e.g., valence state) and this may be important for some toxic metals, such as arsenic. Second, x-ray fluorescence provides only total element concentrations without regard to whether the element is bound or complexed, possibly limiting the utility of the technique for certain element hypotheses (e.g., iron). Finally, the study was relatively small. Because it is the first report of a prospective association between zinc tissue concentration and risk of esophageal cancer, it will require confirmation in an independent study.
Many prospective cohort studies and medical institutions have tissue banks that can provide samples for studies of cancer or other diseases that are similar in design to our study. Prospectively collected tissue samples are precious resources that can be used sparingly to address important hypotheses. But these hypotheses can be investigated using only analytical techniques with sufficient sensitivity and reproducibility for the small biological samples available. One advantage of our analytical method is the high sensitivity and multiple-element capabilities of x-ray fluorescence, which required only a single tissue section. Our study, which used x-ray fluorescence, provides a model for other studies of potential associations between nutritional or toxic elements and the risk of subsequent disease.
![]() |
NOTES |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
![]() |
REFERENCES |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
(1) Fong LY, Sivak A, Newberne PM. Zinc deficiency and methylbenzylnitrosamine-induced esophageal cancer in rats. J Natl Cancer Inst 1978;61:14550.[ISI][Medline]
(2) Fong LY, Magee PN. Dietary zinc deficiency enhances esophageal cell proliferation and N-nitrosomethylbenzylamine (NMBA)-induced esophageal tumor incidence in C57BL/6 mouse. Cancer Lett 1999;143:639.[CrossRef][ISI][Medline]
(3) Fong LY, Lau KM, Huebner K, Magee PN. Induction of esophageal tumors in zinc-deficient rats by single low doses of N-nitrosomethylbenzylamine (NMBA): analysis of cell proliferation, and mutations in H-ras and p53 genes. Carcinogenesis 1997;18:147784.[Abstract]
(4) Barch DH, Fox CC, Rosche WA, Rundhaugen LM, Wrighton SA. Inhibition of rat methylbenzylnitrosamine metabolism by dietary zinc and zinc in vitro. Gastroenterology 1992;103:8006.[ISI][Medline]
(5) Fong LY, Cheung T, Ho YS. Effect of nutritional zinc-deficiency on O6-alkylguanine-DNA-methyl-transferase activities in rat tissues. Cancer Lett 1988;42:21723.[CrossRef][ISI][Medline]
(6) Fong LY, Nguyen VT, Farber JL. Esophageal cancer prevention in zinc-deficient rats: rapid induction of apoptosis by replenishing zinc. J Natl Cancer Inst 2001;93:152533.
(7) Van Greiken RE, Markowicz AA, editors. Handbook of x-ray spectrometry. 2nd ed. New York (NY): Marcel Dekker; 2002.
(8) Hunter DJ. Biochemical indicators of dietary intake. In: Willett WC, editor. Nutritional epidemiology. 2nd ed. New York (NY): Oxford University Press; 1998. p.174243.
(9) Lonnerdal B. Dietary factors influencing zinc absorption. J Nutr 2000;130(5S Suppl):1378S83S.
(10) Zheng SF, Liu XF, Li JL. Serum concentration of copper, iron, magnesium and zinc in esophageal cancer patients and normal controls in Linxian. Cancer Res Prev Treat 1980;7:47.
(11) Hu GG, Luo XM, Shang AL, Qin QS. Trace elements in esophageal canceranalysis of 44 cases. Zhongguo Yi Xue Ke Xue Yuan Xue Bao 1982;4:17880. [In Chinese.][Medline]
(12) Ke L. Mortality and incidence trends from esophagus cancer in selected geographic areas of China circa 197090. Int J Cancer 2002;102:2714.[CrossRef][ISI][Medline]
(13) Li B, Taylor PR, Li J-Y, Dawsey SM, Wang W, Tangrea JA, et al. Linxian nutrition intervention trials. Design, methods, participant characteristics, and compliance. Ann Epidemiol 1993;3:57785.[Medline]
(14) Dawsey SM, Lewin KJ, Liu FS, Wang GQ, Shen Q. Esophageal morphology from Linxian, China. Squamous histologic findings in 754 patients. Cancer 1994;73:202737.[ISI][Medline]
(15) Henke BL, Gullikson EM, Davis JC. X-ray interactions: photoabsorption, scattering, transmission, and reflection at E=530 000 eV, Z=192. Atomic Data and Nuclear Data Tables 54. Elsevier; 1993. p.181342.
(16) Mark SD. Nonparametric and semiparametric survival estimation in two-stage (nested) cohort studies. In: 2003 Proceedings of the American Statistical Association Statistics in Epidemiology Section [CD-Rom]. Alexandria (VA): American Statistical Association; 2003. p. 267591.
(17) Mark SD, Katki HR. Specifying and implementing nonparametric and semiparametric survival estimators in two-stage (sampled) cohort studies with missing case data. J Am Stat Assoc In press 2004.
(18) Ihaka R, Gentleman R. R: A Language for Data Analysis and Graphics. J Comput Graph Stat 1996;5:299314.
(19) Mark SD, Katki HR. R and S-PLUS code for -estimation of nonparametric and semiparametric estimators of survival and relative risk from two-stage cohort studies. Technical Report, DCEG, Biostatistics Bronch. National Cancer Institute; 2003.
(20) Andersen PK, Borgan O, Gill RD, Keiding N. Statistical models based on counting processes. New York (NY): Springer-Verlag; 1993.
(21) Mark SD, Qiao YL, Dawsey SM, Wu YP, Katki H, Gunter EW, et al. Prospective study of serum selenium levels and incident esophageal and gastric cancers. J Natl Cancer Inst 2000;92:175363.
(22) Taylor PR, Qiao Y-L, Abnet CC, Dawsey SM, Yang CS, Gunter EW, et al. Prospective study of serum vitamin E levels and esophageal and gastric cancers. J Natl Cancer Inst 2003;95:14146.
(23) Sandstrom B, Davidsson L, Cederblad A, Lonnerdal B. Oral iron, dietary ligands and zinc absorption. J Nutr 1985;115:4114.[ISI][Medline]
(24) Chen F, Cole P, Mi Z, Xing L. Dietary trace elements and esophageal cancer mortality in Shanxi, China. Epidemiology 1992;3:4026.[ISI][Medline]
(25) Rogers MA, Thomas DB, Davis S, Vaughan TL, Nevissi AE. A case-control study of element levels and cancer of the upper aerodigestive tract. Cancer Epidemiol Biomarkers Prev 1993;2:30512.[Abstract]
(26) 10th report on carcinogens. U.S. Department of Health and Human Services, Public Health Service, National Toxicology Program; 2002. Available at: http://ehp.niehs.nih.gov/roc/toc10.html.
Manuscript received July 9, 2004; revised December 2, 2004; accepted December 14, 2004.
This article has been cited by other articles in HighWire Press-hosted journals:
![]() |
||||
|
Oxford University Press Privacy Policy and Legal Statement |