1 Department of Epidemiology, School of Public Health, University of North Carolina, Chapel Hill, NC 27599, 2 Department of Otolaryngology/Head and Neck Surgery, School of Medicine, University of North Carolina, Chapel Hill, NC 27599 and 3 Laboratory of Computational Biology and Risk Assessment, National Institute of Environmental Health Services, Research Triangle Park, NC 27709, USA
4 To whom correspondence should be addressed Email: gaudet{at}email.unc.edu
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Abstract |
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Abbreviations: CI, confidence interval; GST, glutathione S-transferase; OR, odds ratio; SCCHN, squamous cell carcinoma of the head and neck
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Introduction |
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Use of tobacco and alcohol products has been estimated to account for 75% of SCCHN cases (4). Metabolic products of tobacco smoke and alcohol can induce direct DNA mutations and increase the production of reactive oxygen species, which can also lead to DNA damage and lipid peroxidation. Unrepaired damage to dividing cells increases the probability of mutations in critical oncogenes or tumor suppessor genes (5).
Glutathione S-transferase M1 (GSTM1) and glutathione S-transferase T1 (GSTT1) encode for enzymes involved in phase II detoxification of xenobiotics, such as tobacco smoke chemicals and plant alkaloids. These enzymes catalyze the conjugation reactions between glutathione and Phase I-reactive electrophilic intermediates to facilitate their elimination. The deletion (null) genotypes of GSTM1 and GSTT1 result in an absence of enzyme activity and are associated with increased levels of activated carcinogens (6). Some studies suggest that the GSTM1 and GSTT1-deletion polymorphisms are associated with an increased risk of SCCHN (7).
Conversely, the null genotypes and consequent reduction of enzyme activity allow greater exposure to chemopreventive compounds in fruits and vegetables. Recent studies have reported a reduction in lung cancer risk associated with detectable urinary levels of isothiocyanates among persons with the GSTM1 null genotype, but no change in risk among persons with the GSTM1 non-null genotype (8,9). These results may be relevant because, given that lung cancer and SCCHN share strong associations with tobacco, their etiologies may have other features in common as well.
No reports to date have explored the interactions of diet and GSTM1 and GSTT1 polymorphisms and the risk of SCCHN. Thus, we examined the relationship between consumption of fruits and vegetables, GST polymorphisms, and the incidence of SCCHN using data from a case-control study. We hypothesized that consumption of fruits and vegetables would be associated with reduced risk of SCCHN and that this effect would be accentuated among persons with GST null genotypes.
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Materials and methods |
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In the hospital clinic prior to surgery, trained interviewers questioned study participants about lifetime tobacco and alcohol use, occupation, medical history, family history of cancer, demographics and diet. Blood and buccal cell samples were also obtained for genotyping. DNA was extracted from the buffy coat of blood samples using the ABI Nucleic Acid Purification System (Applied Biosystems, Foster City, CA). DNA, extracted using the Qiagen method (Qiagen, Chatsworth, CA), from buccal cell samples was used when blood samples were unavailable (six cases, seven controls). GSTM1 and GSTT1 genotypes were determined using the multiplex PCR methods of Chen et al. (12). The details of the laboratory methods have been published previously (10,11).
A modified 44-item Block Food Frequency Questionnaire (13), concentrating on consumption of fruits, vegetables, breakfast foods, juices and the use of vitamin supplements, was used to assess habitual diet. Interviewers asked cases to estimate their usual intake 1 year prior to diagnosis, whereas controls were asked to estimate their usual intake for the previous year. For each individual food, participants reported their frequency of intake. Thirty-three questions related to the intake of fruits and vegetables.
Responses regarding intake frequencies of dietary variables were coded as per month, week or day and then converted to servings per week. Individual fruits and vegetables were categorized into seven food groups: all fruits and vegetables, all fruits, fruit juices, citrus fruits, all vegetables, cooked vegetables, raw vegetables, cruciferous vegetables and legumes (see Appendix 1 for composition of food groups). These composite food groups were selected based on the associations between diet and SCCHN in the current literature (14). The consumption frequencies of each group's component foods were summed to create a cumulative weekly intake (servings/week). For the overall estimation of diet, the cumulative frequencies for each food group were divided into three categories with cut-points, representing meaningful values of servings per day whenever possible, that best represented the shape of the quadratic spline created with a knot at the median of the control population (15).
To obtain sufficient numbers for the GST-diet interaction analyses, the three categories were collapsed down to two by combining the lowest two categories to compare with the highest category. Analyses conducted to examine the sensitivity of the binary scale boundary selections generally yielded similar results. Exceptions are noted.
Unconditional logistic regression was used to estimate the odds ratios (OR) and 95% confidence intervals (CI) for the overall association of selected plant foods and GST genotypes with SCCHN. The matching factors, age and gender, as well as, race (white, non-white), body mass index (>20, 2025, 2630, 31+ kg/m2), use of vitamin/mineral supplements (yes, no), smoking (0, 119, 2039, 40+ pack-years) and alcohol intake (0, 1499, 5001899, 1900+ drink-years) were examined as potential confounders. Race was categorized as white and non-white. Ninety-three percent of non-white cases and controls were African-American. Cases and controls were not matched by race in the study design. Race was treated as a potential confounder (i.e. as an adjustment variable) in the logistic models. To explore race-specific associations, we stratified by race. As the number of non-white participants was very small, we compared the results for the white participants with those for the overall study population.
Confounders were selected on the basis of their hypothesized relationship with diet, genotypes and SCCHN using directed acyclic graphs (16), and changes in point estimates and confidence intervals. For the overall OR estimation for diet variables, the adjustment variables were age, gender, race, smoking and alcohol. To estimate ORs for GSTM1 and GSTT1, only age, gender and race were the only adjustment variables. Unadjusted models yielded similar results to these models and further adjustment for alcohol and tobacco did not appreciably change the estimates. For the diet and genotype models, inclusion of variables for use of vitamin and mineral supplements and for body mass index did not measurably alter the estimates.
To evaluate the interaction of fruit and vegetable intake with GSTM1 and GSTT1 genotypes, logistic regression analyses were performed to estimate the ORs and 95% confidence limits (17). Indicator variables were created for each combination of genotype and plant foods. Persons hypothesized to be at greatest risk, low consumers of plant foods with the non-null genotype, were selected to form the reference category. A common referent category will permit evaluation of departures from the additive and multiplicative benchmark (17). Age, gender, race, tobacco and alcohol use were included in these models.
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Results |
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The frequency of the GSTM1 null genotype was 42% (n = 63) among cases and 46% (n = 82) among controls. Eighteen percent (n = 27) of cases and 12% (n = 22) of controls had the GSTT1 null genotype. Among the controls, the GSTM1 and GSTT1 present genotypes were evenly distributed among whites and non-whites. Forty-six percent of whites and 42% of non-whites had the GSTM1 null genotype and 12% of whites and 17% of non-whites had the GSTT1 null genotype. In the age-, gender- and race-adjusted model, neither the null genotype of GSTM1 (OR = 0.88, 95% CI 0.501.5) nor of GSTT1 (OR = 1.2, 95% CI 0.552.5) was associated with incidence of SCCHN.
The interactions between GSTM1 genotypes and selected dietary factors were examined with persons who have the non-null genotype and who are in the lowest category of intake making up a common reference category (Table III). One OR contrasts the combination of the highest category of food intake and the GSTM1 null genotype with the common reference category. Another OR contrasts the combination of high food intake and the non-null genotype with the common referent. A third OR contrasts the combination of low food intake and the null genotype with the common referent.
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For all fruits and citrus fruits, GSTM1 did not seem to modify the inverse associations with SCCHN (Table III). A suggestion of antagonism was seen among high consumers of fruit juices with the GSTM1 null genotype when contrasted with the associations for either factor alone.
The results for GSTM1 and raw vegetables suggested synergism. There appeared to be little or no association between SCHNC and either raw vegetables alone or the null GSTM1 genotype alone, a reduction in incidence when the two were combined. The results for GSTM1 and cooked vegetables were more complex. Higher cooked vegetable intake was associated with increased incidence regardless of GSTM1 status. The GSTM1-deletion polymorphism, however, was associated with decreased incidence if cooked vegetable intake was low and with increased incidence if cooked vegetable intake was high.
The GSTT1 null genotype appeared to suppress some of the inverse associations between all fruits, fruit juices and citrus fruits, and SCCHN (Table IV). Persons with the non-null GSTT1 genotype who were high consumers of fruits had a lower incidence than persons with the null GSTT1 genotype who ate any amount of fruit. A similar trend of lower incidence among persons with the GSTT1 non-null genotype and high intake was also seen for fruit juices and citrus fruits.
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Discussion |
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A variety of US and international studies on head and neck cancer have pointed to a protective effect of fruit and vegetable intake (e.g. 14,18,19). In a previous study of North Carolina women, consumption of >15 servings per week of fruits and vegetables was associated with a 50% reduction in risk of oral and pharyngeal cancer (OR = 0.50) (20). Likewise, a reduction in risk was also found among high consumers of fresh fruits (OR = 0.4), green leafy vegetables (OR = 0.7) and other vegetables (OR = 0.7). However, the largest US study of head and neck cancer reported that vegetable intake was not associated with oral and pharyngeal cancer (21). Among both men and women consuming the highest intake of legumes and women consuming the highest intake of cruciferous vegetable consumption, risk was elevated (OR = 1.3, OR = 1.4, OR = 1.8, respectively). Consistent with the North Carolina study and our study, fruit consumption averaging 4.5 servings per day had a 50% reduction in risk compared to those consuming an average of 0.7 servings per day.
Fruits and vegetables contain antioxidants, other water- soluble vitamins, minerals and chemopreventive compounds, such as phenols and flavonoids. Raw vegetables and fruits are particularly good sources of these compounds as cooking accounts for a measurable loss of vitamins and minerals (22). The mechanistic actions, by which these nutrients and phytochemicals are involved in the prevention of SCCHN, may include involvement with alcohol and tobacco pathways. The excess burden of free radicals caused by cigarette smoke may be balanced, in part, by the intake of antioxidants in plant foods. High consumers of alcohol also have a greater requirement for fruits and vegetables to replace the water-soluble vitamins and minerals lost at greater rates (2).
The unexpected increased risk associated with the highest categories of total vegetable, cooked vegetable and legumes intake may be due to specific cooking practices of North Carolina, although our data did not include information regarding cooking practices. Vegetable preparation may involve the addition of fatback, bacon and other pork-derived fats. Other researchers have found a consistent increase in risk of SCCHN from consumption of saturated fats (21,2326).
Components of fruits and vegetables, including limonene, isothiocyanate and allium compounds, are inducers of glutathione transferases (3). Additionally, these phytochemicals are substrates for glutathione transferases (27). It has been suggested that those with the null genotype for GSTM1 and GSTT1 (i.e. those lacking enzyme activity) would receive a greater benefit from the chemopreventative constituents of fruits and vegetables because they would not be metabolized. In a recent study of isothiocyanates, glutathione S-transferases M1 and T1 polymorphisms and lung-cancer risk in a prospective cohort of Chinese men, London et al. found an inverse association with isothiocyanates among individuals with the GSTM1 or GSTT1 null genotype (OR, 0.36), but no association among those with the GSTM1 or GSTT1 non-null genotype (8).
Our results do not provide clear evidence to support the role of an interaction between plant foods and GST genotypes in the development of SCCHN. A potential biological interaction between phytochemicals and GST genotypes is complicated by the role of tobacco carcinogens, other detoxifying enzymes and the multitude of constituents in plant foods. Smoking may overwhelm the detoxifying pathway such that the further induction of the enzymes does little to remove the damaging effect of the carcinogens. Inducers of the glutathione S- transferases may also interact with Phase I enzymes, which may confound the effect estimates (28). Finally, fruits and vegetables contain other vitamins, minerals and chemopreventative compounds that may work outside the GST pathway in the prevention of cancer, such as induction of apoptosis and modification of cell cycle regulation (3). However, the results from two recent studies of lung cancer conducted in Chinese cohorts, male smokers (8) and non-smoking women (9), have provided some evidence of an interaction between isothiocyanates and the GST's enzymes.
Potential misclassification in studies involving dietary assessment by questionnaire is of concern. Disease status may have differentially affected responses to the dietary questionnaire, whereby cases have different motivations for completing the questionnaire. From analysis of the outliers of fruit and vegetable consumption, it appears that the tails of the distribution of cases and controls were similar. Additionally, exclusion of the upper 10% of fruit and vegetable consumers did not appreciably alter the results of the overall associations of diet and incidence of SCCHN. Both previous results suggest differential reporting of diet by cases and controls were not strongly influential in our analysis. The range of fruit and vegetable intake in our study was wider compared with a previous study in North Carolina (20). Health messages and campaigns over the years may have effectively increased the consumption of fruits and vegetables (29).
Our sample size affected the stability of our odds ratios estimates and limited our ability to quantify effect estimates and effect-measure modification. The selection of hospital-based controls may raise a concern about selection bias, but the frequencies of the null genotypes for GSTM1 and GSTT1 in the control population were similar to general-population prevalence estimates in the literature (7). Additionally, the doseresponse relationship for tobacco use found in our study was similar to the one reported previously in a large case-control study with general population controls (4).
Hospital-based controls may also introduce BMI-mediated control-selection bias. An inverse association for BMI and incidence of SCCHN was seen in our study and other recent studies (14,30). While the observed association may be related to other risk factors, it may also be due to the selection of hospital controls with diagnoses related to higher BMI. However, the prevalence of obesity in our controls was similar to that of the US population (18 versus 19.8%, respectively). In addition, controlling for BMI did not change our odds ratios for fruit and vegetable intake nor for the interactions of diet and GSTs.
We investigated the possibility of confounding related to race, specifically blackwhite differences. The prevalence of the null genotypes of GSTM1 and GSTT1 did not meaningfully differ between self-described blacks and whites. Moreover, direct adjustment for race in logistic regression did not materially affect the odds ratio estimates. Further, when we restricted our analyses to whites only (our largest sub-group), noteworthy differences were not found in comparison with analyses based on the entire study sample, with the exception of the interaction results of GSTM1 and cruciferous vegetables.
Our results failed to support clearly the hypothesized role of an interaction between plant food and GSTM1 or GSTT1 on the risk of SCCHN. Positive findings from lung cancer studies (8,9) lend support to the hypothesized interaction between plant foods and GSTs in a SCCHN model and suggest the need for further research. Cooking methods of vegetables, in particular the addition of animal fats may also be involved in an interaction with GSTM1. To explore this hypothesis further, dietary questionnaires need additional questions to assess food preparation methods. Future research may benefit from larger, population-based studies that will allow for the stratification by smoking and drinking status.
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Appendix 1 |
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All vegetables: string beans, green beans; peas; chilli with beans; other beans such as baked beans, pintos, kidneys, limas, and lentils; corn; winter squash/baked squash; red chilli sauce, taco sauce, salsa picante; broccoli; cauliflower or Brussels sprouts; spinach (raw); spinach (cooked); mustard greens, turnip greens, collards; coleslaw, cabbage, sauerkraut; carrots or mixed vegetables containing carrots; green salad; sweet potatoes, yams; other potatoes, including boiled, baked, mashed, and potato salad; other vegetables, including cooked onions, summer squash.
All fruits and vegetables: all previous food items in All fruits and All vegetables.
Citrus fruits: oranges; grapefruit; orange and grapefruit juices.
Juices: orange or grapefruit juice; fruit drinks with added vitamin C.
Cooked vegetables: string beans, green beans; peas; corn; winter squash/ baked squash; broccoli; cauliflower or Brussels sprouts; spinach (cooked); mustard greens, turnip greens, collards; carrots or mixed vegetables containing carrots; sweet potatoes, yams; other potatoes, including boiled, baked, mashed, and potato salad; other vegetables, including cooked onions, summer squash.
Raw vegetables: red chilli, taco sauce, salsa picante; spinach (raw); coleslaw, cabbage, sauerkraut; green salad.
Cruciferous vegetables: broccoli; cauliflower or Brussels sprouts; mustard greens, turnip greens, collards; coleslaw, cabbage, sauerkraut.
Legumes: chilli with beans; other beans such as baked beans, pintos, kidneys, limas and lentils.
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Acknowledgments |
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References |
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