Diet and alcohol consumption in relation to p53 mutations in breast tumors

Jo L. Freudenheim1,6, Matthew Bonner1, Shiva Krishnan2, Christine B. Ambrosone3, Saxon Graham1, Susan E. McCann1, Kirsten B. Moysich3, Elise Bowman4, Takuma Nemoto5 and Peter G. Shields2,7

1 Department of Social and Preventive Medicine, University at Buffalo, Buffalo, NY 14214, USA, 2 Lombardi Cancer Center, Georgetown University, Washington, DC 20007, USA, 3 Roswell Park Cancer Institute, Buffalo, NY 14263, USA, 4 Laboratory for Human Carcinogenesis, National Cancer Institute, Bethesda, Maryland, USA and 5 Department of Surgery, University at Buffalo, Buffalo, NY 14214, USA

6 To whom correspondence should be addressed Email: Jfreuden{at}buffalo.edu
7To whom correspondence may also be addressed Email: pgs2{at}georgetown.edu


    Abstract
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
There is evidence linking alcohol consumption to p53 mutations in tumors, considerable evidence linking alcohol consumption with risk of breast cancer and some evidence that alcohol and folate consumption interact to affect risk. Further, while there is some indication that oxidation may play a role in breast cancer etiology, there has been little examination of an association of oxidative stress with p53 mutations. We examined several dietary components related to one-carbon metabolism and antioxidants to determine if these factors were related to the prevalence of p53 mutations in breast tumors. We conducted a case-control study of primary, histologically confirmed breast cancer in western New York. Controls <65 were selected from drivers license lists; those >=65 were selected from Health Care Finance Administration lists. p53 mutations in archived tumor blocks were identified in exons 2–11 and flanking intron sequences. Usual dietary intake was assessed by interview regarding intake in the previous 2 years; alcohol consumption was queried for 2, 10 and 20 years in the past. Our data were consistent with increased likelihood of tumors with p53 mutations for premenopausal breast cancer with increased alcohol intake 10 or 20 years previous; for intake of 16 or more drinks per month in the period 20 years before the interview compared with non-drinkers, the OR was 5.25, 95% CI 1.48–18.58. For postmenopausal women, there was increased likelihood of tumors with p53 mutations among women with higher folate. Antioxidant nutrients were not differentially related to p53 mutations. These results indicate that there may be heterogeneity in breast tumors, as indicated by differences in associations for those with or without p53 mutations, and that causal pathways for these nutrients may vary for pre- and postmenopausal women. For premenopausal women, alcohol consumption in the past was associated with p53 mutations.

Abbreviations: BMI, body mass index


    Introduction
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
There is accumulating evidence that alcohol consumption contributes to breast cancer risk (1,2). One possible mechanism for an effect of alcohol on breast cancer risk could be an interaction with folate status resulting in an effect on one-carbon metabolism. Alcohol is known to negatively impact folate at the level of absorption, utilization and excretion (3). In fact, recent evidence appears to indicate that risk associated with alcohol consumption may be limited to women with low folate intake (49). Folate, along with several other nutrients is important for the maintenance of one-carbon pools; the one-carbon pathway is important for maintenance of DNA methylation and nucleotide synthesis. There is evidence from both human and animal studies of increased DNA damage with diets low in nutrients important in the maintenance of one-carbon pools (1012) and with increased alcohol consumption (13).

In addition to folate and alcohol, there is evidence that nutrients and food components with antioxidant properties may be protective in relation to breast cancer risk (14). There is some, although not consistent, evidence of decreased risk of breast cancer related to carotenoids, vitamin C and retinol (1417). Oxidative stress, the excess of oxidants over antioxidants, has been shown in animal models to be related to tumor formation and DNA damage. There is also some likelihood that there could be an interaction of methyl depletion and oxidative damage leading to increased DNA damage (10,11). Homocysteine, which accumulates when sources of one-carbon units are low, may function as a pro-oxidant (11). Further, the damage to DNA related to oxidation may interact with damage from DNA uracil misincorporation related to one-carbon deficiency, to increase DNA damage (10).

The p53 gene product appears to play a central role in carcinogenesis; it is a tumor suppressor and is integral in cell-cycle control, DNA repair, cellular differentiation and apoptosis. The p53 gene is the single most commonly mutated gene in human cancer; mutations of p53 occur in >50% of all tumors (18,19). There is evidence relating particular p53 gene mutations to particular exposures, including aflatoxin exposure in liver cancer (2022), cigarette smoke in lung cancer (22) and sun exposure in skin tumors (22,23). These associations between particular exposures and mutations in this key protein are of interest in that they potentially provide insight into the mechanism of carcinogenesis.

An increased likelihood of p53 mutations and p53 expression in tumors among those consuming more alcohol has been found in some (13, 2429), but not all studies (3032). To our knowledge, there are no studies that have examined folate or dietary antioxidants in relation to p53 mutation frequency.

For breast cancer, the p53 gene is mutated in between 15 and 50% of tumors (33). There have been several studies on p53 mutations and p53 over-expression in relation to breast cancer risk (25,31,34,35). There has been just one small study examining alcohol consumption in relation to p53 mutations in breast tumors: in that study there was no evidence of an association in a group of mostly postmenopausal patients (25). In studies of p53 expression in relation to alcohol consumption, there was no association (31,32). One study reported on the likelihood of tumors with p53 protein over-expression compared with those without over-expression in relation to fruit and vegetable consumption. They found a decreased likelihood of the protein over-expression among women with higher intake levels (32). While the animal literature and studies of other tumor types would indicate that alcohol, one-carbon metabolism and oxidation may be related to p53 mutations, this question has received relatively little attention. We report here on the results of a case-control study of breast cancer where we examined alcohol consumption, dietary factors involved in one-carbon metabolism and dietary antioxidants, in relation to p53 mutations in breast tumors.


    Materials and methods
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
A population-based case-control study of diet and other factors in relation to breast cancer risk, the Western New York Diet Study, was conducted in 1986–1991. Methods of the study have been described in detail elsewhere (3638). Briefly, women, between 40 and 85 years, with primary, incident, histologically confirmed breast cancer, who resided in one of two counties and were able to speak English were eligible; all participants were Caucasian. Controls were frequency matched to the cases on age and county of residence. Controls aged 40–64 years were randomly selected from women who were New York State licensed drivers. Those 65 years and over were selected from the rolls of the Health Care Finance Administration. All participants provided informed consent; the protocol was approved by the Institutional Review Boards of the University at Buffalo and of the participating hospitals.

Interview
Interviews were conducted by trained interviewers in participants' homes. An in-depth food frequency questionnaire focused on usual intake of 172 foods in the year 2 years before the interview (37). Questions included frequency and portion size as well as consumption of foods in and out of season, and cooking methods. For assessment of alcohol intake, participants reported on usual quantity and frequency of consumption of individual alcoholic beverages 2, 10 and 20 years ago.

Laboratory methods
Of the 736 women with breast cancer originally interviewed, we were able to obtain archived tumor blocks for 418 of them. For several hospitals we were not able to obtain blocks because of the time lag between the interview and the collection of tumor blocks. Of those we obtained, we got usable results for 368 (50% of those interviewed). Slides were cut from the blocks with replacement of blades between the each block and cleaning of the block holder with xylene between blocks to prevent contamination of tissue from one block to the next. Glass slides were treated to prevent contamination with DNAases and RNAases.

p53 mutational spectra were identified using the Affymetrix Gene Chip System (39) (Santa Clara, CA), which analyzes specific nucleic acid sequences and identifies nucleotide base changes in the p53 tumor suppressor gene. The gene chip p53 assay performs sequence analysis on exons 2–11 of the human p53 gene in addition to the flanking intron sequences for splice junction analysis. The technique involves a single PCR reaction that amplifies the 10 exons, which is followed by enzymatic fragmentation and fluorescent labeling of the fragmented PCR products. These products are then hybridized onto the oligonucleotide probe array. The array contains oligonucleotide probes with the wild-type p53 sequence in addition to the most commonly occurring p53 mutations (hot spots). The relative binding of the template DNA to each probe in the array is determined with a laser scanner and evaluated with software that uses algorithmic analysis to give a valid numerical score for p53 mutations. We compared 170 samples with direct sequencing to the gene chip and the results were identical. We have also examined re-extraction of DNA from different slides from the same tumor and from different parts of the same slide. All results were consistent.

Statistical analysis
Characteristics of participating cases with and without p53 mutations and controls were compared using the Student's t-test (40) for continuous variables and {chi}2 test for categorical variables. Similarly, comparisons were made of cases for whom we were able to obtain a tumor block with those for whom we were not able to obtain a block.

In order to determine the risk of either a p53+ or a p53– tumor in relation to cancer-free controls, comparisons were made for the p53+ and for the p53– cases to controls. Odds ratios (OR) and 95% confidence intervals (CI) were calculated using unordered polytomous regression (41). Further, we did a case–case comparison of p53+ to p53– cases (42,43) to determine the relative prevalence of the mutations by exposure categories. Tertiles for dietary variables were determined by equal division of the combined pre- and postmenopausal controls. For alcohol, one category was created of non-drinkers and the drinkers were divided into three approximately equal groups of controls. P-values for the analysis of trend were computed for analysis of continuous rather than categorical variables. Known breast cancer risk factors were assessed for confounding: age, education, age at menarche, body mass index (BMI) (kg/m), previous benign breast disease, age at first birth, family history of breast cancer, smoking status and caloric intake. Because of the small sample size, we were concerned that the model was parsimonious; we evaluated the impact of removal of each potential confounder. After forcing in terms for age and education, included in the model were only those variables that affected the estimate by 10% or more. In the final model were terms for age, education, BMI, age at first pregnancy, smoking status and calorie intake.

In addition to examination of the association of diet and alcohol and the likelihood of all p53 mutations, we examined particular mutations: those likely to be related to one-carbon metabolism (transition mutations and mutations in the CpG region) and those likely to be related to oxidation (A to C, A to G, C to T and G to A).


    Results
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
We compared characteristics of breast cancer cases for whom we were able to obtain p53 results and those for whom we were not either because there was no tumor block available or no usable tissue on an obtained block. We found no difference in the two groups for age, education or for any of the dietary factors examined here (Table I). Characteristics of cases with and without p53 mutations and of controls are also shown in Table I. There were 130 cases with mutations (78 pre- and 52 postmenopausal), ~44 and 27% of the pre- and postmenopausal cases, respectively. Of the 130 mutations, 24% were G->T transversions, and 6% were found at CpG sites. As expected, the majority (89%) of mutations were in the evolutionarily conserved regions of exons 5–8. For the premenopausal cases, for those with p53 mutations, intake of vegetables was lower than intake for controls; for those without p53 mutations, intakes of {alpha}- and ß-carotene were lower than for controls. For postmenopausal cases, for those without a p53 mutation, vegetable intake was lower than for controls.


View this table:
[in this window]
[in a new window]
 
Table I. Characteristics of cases with unknown p53 status, with p53+ tumors or p53– tumors, and controls: Western New York Diet Study 1986–1991

 
In Table II, adjusted odds ratios and 95% confidence intervals are shown for intake of folate 2 years previous and for alcohol 2, 10 and 20 years previous. Included in this table are comparisons of: (i) those cases whose tumor had a p53 mutation (p53+) with controls, (ii) those cases whose tumor did not have a p53 mutation (p53–) with controls and (iii) p53+ to p53–. In general the number of cases was small and the confidence intervals were wide. We had 80% power to detect odds ratios of 2.4 for the comparison of p53+ to p53–; for the comparison of either p53+ or p53– tumors with controls, we had power to detect odds ratios of 2.0. For premenopausal breast cancer, there was evidence of heterogeneity with regard to p53 mutations and alcohol intake; there was increased likelihood of p53+ compared with p53– tumors, particularly for alcohol intake 10 (OR 3.62, 95% CI 0.98–13.39) or 20 years (OR 5.25, 95% CI 1.48–18.58) before the interview. For both time periods, ORs for this case–case comparison were increased for all categories of drinkers compared with non-drinkers; confidence intervals did not include the null for second through to fourth category for consumption 20 years ago. The likelihood of p53+ tumors increased and p53– tumors decreased with increasing alcohol consumption. For folate, there was a lower likelihood of both p53+ and p53– tumors for those with higher intakes of folate. For the case–case comparison, the point estimate was 0.78 and the confidence interval included the null (95% CI 0.30–2.01).


View this table:
[in this window]
[in a new window]
 
Table II. Folate and alcohol consumption: adjusted odds ratiosa and 95% confidence intervals for the likelihood of p53 mutations in breast tumors, case–control and case–case comparisons: Western New York Diet Study, 1986–1991

 
For postmenopausal women, there was increased likelihood of p53+ compared with p53– tumors for women with higher folate intake. It appeared that a protective effect of folate was limited to women with p53– tumors.

For alcohol and folate, we examined pre- and postmenopausal breast cancer together. For both alcohol and folate, estimates were close to the null and all the confidence intervals included unity (data not shown).

In Table III, adjusted odds ratios are shown for nutrients and food components with antioxidant properties. For the premenopausal women, there were statistically significant inverse trends for the comparison of p53+ tumors with controls for ß-carotene, lutein + zeaxanthin and vegetable intakes. The p53– tumors were inversely associated with {alpha}- and ß-carotene, and vegetable intakes. There was little evidence for difference in the likelihood of p53+ compared with p53– tumors with higher intakes of these dietary components for premenopausal women; all upper category confidence intervals included the null. For the postmenopausal women, the associations of p53+ tumors with these dietary factors were generally null. For the p53– tumors, there were inverse associations with {alpha}- and ß-carotene, lutein + zeaxanthin, lycopene, vitamin C, {alpha}-tocopherol and vegetables. In the case–case comparisons, there was no indication of a lower likelihood of p53 mutations in tumors of women reporting higher intake of these factors. There was a significantly increased trend for the likelihood of p53+ tumors with higher intakes lycopene.


View this table:
[in this window]
[in a new window]
 
Table III. Dietary components with antioxidant properties: adjusted odds ratiosa and 95% confidence intervals for the likelihood of p53 mutations in breast tumors, case–control and case–case comparisons: Western New York Diet Study, 1986–1991

 
We analyzed the data for the pre- and postmenopausal women together; the results were close to the null for all these nutrients (data not shown).

We next examined those mutations likely to be related to low levels of one-carbon groups. The numbers of tumors with these mutations was quite small: 38 premenopausal cases and 24 postmenopausal cases. For these analyses, we had 80% power to detect odds ratios on the order of 2.9. In general, there was little evidence of any association of the nutrients related to one-carbon metabolism and increased likelihood of these specific p53 mutations. For the premenopausal women, likelihood of these mutations associated with increased alcohol consumption 20 years ago, comparing intake of >16 drinks/month to non-drinkers, the OR was 6.04, 95% CI 0.9–40.0. While the point estimate was quite high, the wide confidence interval was an indication of the instability of these results. For the oxidation-related mutations, there were 41 premenopausal and 29 postmenopausal women with these p53 mutations; power was similar to that for the methylation-related mutations. There was no evidence of decreased likelihood of p53 mutations for tumors in either pre- or postmenopausal women by level of intake of antioxidants (data not shown).


    Discussion
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
This study was an examination of differences in the associations of diet and alcohol with breast cancer depending on whether the tumor did or did not have a p53 mutation. We found that alcohol consumption 20 years previous was associated with increased risk of p53 mutations in the premenopausal women; more recent consumption was less strongly associated with p53 mutations in breast tumors. With increased folate intake, we found decreased risk of both p53+ and p53– tumors; there was no evidence of heterogeneity by p53 status. For the postmenopausal women, folate intake was associated with a protective effect only for the p53– tumors and there was a significant difference in the likelihood of p53+ compared with p53– tumors. There was no evidence of a difference in the likelihood of p53+ or p53– tumors associated with consumption of antioxidants with one exception; there was a significant association with increased likelihood of the p53+ tumors with increased intake of lycopene. While this study is the first to have a sample size of this magnitude in the examination of mutational spectra with risk factors, we remained constrained by small numbers. Nonetheless, these findings imply that there may a difference in etiology leading to p53+ compared with p53– tumors, particularly with regard to past alcohol consumption for premenopausal women.

To our knowledge, there have been just two other studies that examined p53 mutational spectra in relation to risk of breast cancer (25,33). Just one of those examined alcohol consumption (25). In that study of primarily postmenopausal women, there was no association for p53+ compared with p53– for those reporting alcohol consumption; the point estimate indicated a reduced likelihood of p53+ tumors among drinkers. Similarly in our study, for the postmenopausal women, there was a trend toward reduced likelihood of the p53+ compared with p53– tumors among the heavier drinkers for alcohol consumption 10 and 20 years previous. There are three studies that examined p53 mutations measured by immunohistochemistry in relation to risk of disease (32,34,35). In the two studies assessing alcohol in relation to p53 expression, there was no association with drinking (34,35). In one, they reported on fruit and vegetable intake in relation to the frequency of p53 protein expression in a study of young women aged <45 years (35). Unlike most other studies, they found an increase in all tumors with increased intake of both fruits and vegetables. Comparing p53+ with p53, they found, as we did for the premenopausal women, that there was some evidence of decreased frequency of the p53+ tumors in the higher categories of intake of both fruits and point estimate <1 for the frequency of tumors positive for expression of p53 for both vegetables and fruits. While there are problems of both specificity and sensitivity in the use of immunohistochemistry to identify mutations, these studies provide evidence of possible heterogeneity in the relationship between these dietary risk factors and p53 positive and negative breast tumors.

For breast cancer, evidence is accumulating that would implicate folate and alcohol in relation to risk (49). In one study, the association of risk with high alcohol and low folate was limited to women with estrogen receptor negative tumors (9). We did not have data regarding estrogen receptor status in our study. Effects on one-carbon metabolism could be the mechanism for this apparent interaction. Reactions in this pathway are essential to the synthesis of nucleotides and methylation of DNA (44,45). There is accumulating evidence from experimental animal and cell models and from epidemiologic studies in humans that a diet depleted or low in the compounds related to one-carbon metabolism can contribute to carcinogenesis (1012). There is also evidence from other tumor sites that p53 mutations may be more frequent in those individuals with higher consumption of alcohol (13,2429). Dietary factors that have been identified as being of importance in the maintenance of one-carbon pools for methylation and other functions are folate, vitamin B6, B12 and the amino acid methionine. Alcohol consumption can negatively affect folate status, at the level of absorption, utilization and excretion (3). We found that specific mutations potentially related to methyl depletion were also associated with a trend toward increased alcohol consumption 20 years previous in the premenopausal women; the wide confidence interval, however, limits the conclusions that can be drawn. Nonetheless, our findings are consistent with a protective effect of a ‘methyl-replete’ diet for premenopausal women and are suggestive of another biological pathway for tumors with p53 mutations for postmenopausal women. Alternatively, for the postmenopausal women, a ‘methyl-depleted’ diet may contribute to mutation of another gene for cases with p53– tumors.

While most studies have examined recent alcohol consumption, some have examined breast cancer risk in relation to lifetime consumption. Most evidence would indicate that more recent consumption is more strongly associated with risk (46,47). There is also evidence that alcohol may be associated with increased breast density, which has been shown to be strongly associated with subsequent breast cancer (48). Our results indicate that there may also be earlier events that affect breast cancer risk. There are not many data regarding the timing of p53 mutations with regard to carcinogenesis in general. Evidence of p53 mutations in pre-neoplastic lesions in the lung provides some indication that the mutation may be an early event in carcinogenesis (49). There is also evidence of p53 mutations in breast ductal carcinoma in situ and in breast atypical hyperplasia (5053).

In addition to one-carbon metabolism in relation to risk, oxidative damage may also be an important potential component to breast cancer etiology. Nutrients of potential importance in this pathway would include dietary antioxidants: vitamins C, E and A and some of the carotenoids. Total vegetable and fruit intake may also be indicators of antioxidant exposure and alcohol may be important because of its oxidant properties, at least in heavy drinkers. Epidemiologic research regarding the association of these nutrients and of fruit and vegetable intake and risk of breast cancer is not consistent (14,54). Oxidative stress, the excess of oxidants over antioxidants, has been shown in animal models to be related to tumor formation and DNA damage. Further, spontaneous oxidative damage to DNA is not uncommon (10). Our findings were consistent with no impact of intake of these nutrients on p53 mutations. Again for postmenopausal women, the associations were the opposite; there appeared to be increased likelihood of p53– tumors with higher lycopene intakes.

For all the analyses we examined risk stratified by menopausal status. There is evidence that for breast cancer there may be differences in etiology based on menopausal status for a number of risk factors such as BMI (55) and fat (56). For alcohol, associations have differed by menopausal status in some studies but not others (48). Because of these potential differences in causal pathway, we examined all the findings within these strata. When the two groups were combined, all estimates were close to the null.

This study has several methodological limitations that need to be considered in the interpretation of the findings. As noted, the chief of these is the issue of statistical power. The numbers were generally small with attendant instability in estimates. This lack of power may explain the difference in findings for pre- and postmenopausal women. For the pre- but not the postmenopausal women, our point estimates were generally in the direction that we had originally hypothesized. It may also be that there are etiologic differences for the pre- and postmenopausal women that these findings reflect.

A second limitation of this study is selection bias. Non-participation in the study coupled with a failure to obtain all of the tumors for those women with breast cancer who did participate could have biased our results. We have compared the characteristics of participants and non-participants and have not found them to differ (36). We compared those women for whom we did obtain an archived tumor block with those for whom we did not and saw no difference in their characteristics either. It is not likely that there would be a difference in selection of those women with breast cancer who either had or did not have a p53 mutation or those with particular mutations, so selection bias is less likely for the case–case comparisons.

Another concern in the interpretation of these findings is the question as to the proper time frame when one might expect p53 mutations to occur. The dietary data that we had was limited to queries regarding intake of foods in the year 2 years before diagnosis. If intakes in the more distant past are more relevant, there could be resultant error in estimates of association to the extent that usual intakes varied during that time period. In fact, there was an indication that more recent alcohol consumption was not related to risk while intake 20 years ago was.

In addition to the two pathways that we were examining, there are a multitude of other pathways potentially important in carcinogenesis of the breast such as hormonal effects or differences in DNA repair. Our inability to account for all these other pathways might also diminish our ability to find differences. Further, there could be effects of the exposures that we were examining on genes other than the p53 gene, including other genes in the p53 pathway. For example, there is evidence that hypermethylation of the p53 gene may also contribute to breast carcinogenesis (57). This pathway, which may also involve alterations in one-carbon metabolism, would not be detected in these analyses. Finally, it is important to note that the frequency of particular mutations is an indication not only of exposure to mutagens but also of clonal selection. The low frequency of finding of mutations in regions outside of the DNA binding region is probably a result of these selective pressures.

While, certainly this study needs to be replicated in other, larger samples, these findings do provide some evidence of heterogeneity in breast tumors. With studies such as this one and such as the ones that have been done for other tumor sites, particularly colon cancer (5860), it may be possible to identify tumors with different molecular characteristics and potentially of different etiologic pathways and to better define the risk associated with particular exposures. Such research has important implications for our understanding of etiology and of prevention and possibly for treatment. For premenopausal breast cancer, our study provides an indication that alcohol consumption 10–20 years previous may increase the risk of p53+ compared with p53– tumors. The examination of tumor heterogeneity is of interest in terms of clarifying the processes related to tumorigenesis.


    Acknowledgments
 
This research was supported in part by grants CA11535, and CA/ES 62995 and USAMRMC#DAMD17-94-J-4108 and DAMD 17-95-1-5022.


    References
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 

  1. Longnecker,M.P. (1994) Alcoholic beverage consumption in relation to risk of breast cancer: meta-analysis and review. Cancer Causes Control, 5, 73–82.[ISI][Medline]
  2. Smith-Warner,S.A., Spiegelman,D., Yaun,S.S. et al. (1998) Alcohol and breast cancer in women: a pooled analysis of cohort studies. J. Am. Med. Assoc., 279, 535–540.[Abstract/Free Full Text]
  3. Herbert,V. and Kshitish,C.D. (1994) Folic acid and vitamin B12. In Shils,M.E., Olson,J.A. and Shike,M. (eds) Modern Nutrition in Health and Disease, 8th Edn. Lea & Febiger, Pennsylvania, pp. 402–425.
  4. Zhang,S., Hunter,D.J., Hankinson,S., Giovannucci,E., Rosner,B.A., Colditz,G.A., Speizer,F.E. and Willett,W.C. (1999) A prospective study of folate intake and the risk of breast cancer. J. Am. Med. Assoc., 281, 1632–1637.[Abstract/Free Full Text]
  5. Rohan,T.E., Jain,M.G., Howe,G.R. and Miller,A.B. (2000) Dietary folate consumption and breast cancer risk. J. Natl Cancer Inst., 92, 266–269.[Free Full Text]
  6. Sellers,T.A., Kushi,L.H., Cerhan,J.R., Vierkant,R.A., Gapstur,S.M., Vachon,C.M., Olson,J.E., Therneau,T.M. and Folsom,A.R. (2001) Dietary folate intake, alcohol, and risk of breast cancer in a prospective study of postmenopausal women. Epidemiology, 12, 420–428.[CrossRef][ISI][Medline]
  7. Negri,E., LaVecchia,C. and Franceschi,S. (2000) Re: Dietary folate consumption and breast cancer risk. J. Natl Cancer Inst., 92, 1270–1271.[Free Full Text]
  8. Zhang,S.M., Willett,W.C., Selhub,J., Hunter,D.J., Giovannucci,E.L., Holmes,M.D., Colditz,G.A. and Hankinson,S.E. (2003) Plasma folate, vitamin B6, vitamin B12, homocysteine, and risk of breast cancer. J. Natl Cancer Inst., 95, 373–380.[Abstract/Free Full Text]
  9. Sellers,T.A., Vierkant,R.A., Cerhan,J.R., Gapstur,S.M., Vachon,C.M., Olson,J.E., Pankratz,V.S., Kushi,L.H. and Folsom,A.R. (2003) Interaction of dietary folate intake, alcohol, and risk of hormone receptor-defined breast cancer in a prospective study of postmenopausal women. Cancer Epidemiol. Biomarkers Prev., 11, 1104–1107.[ISI]
  10. Blount,B.C., Mack,M.M., Wehr,C.M. et al. (1997) Folate deficiency causes uracil misincorporation into human DNA and chromosome breakage: implications for cancer and neuronal damage. Proc. Natl Acad. Sci. USA, 94, 3290–3295.[Abstract/Free Full Text]
  11. Jacob,R.A., Gretz,D.M., Taylor,P.C. et al. (1998) Moderate folate depletion increases plasma homocysteine and decreases lymphocyte DNA methylation in postmenopausal women. J. Nutr., 128, 1204–1212.[Abstract/Free Full Text]
  12. Kim,Y.I., Pogribny,I.P., Basnakian,A.G. et al. (1997) Folate deficiency in rats induces DNA strand breaks and hypomethylation within the p53 tumor suppressor gene. Am. J. Clin. Nutr., 65, 46–52.[Abstract]
  13. Ahrendt,S.A., Chow,J.T., Yang,S.C., Wu,L., Zhang,M.J., Jen,J. and Sidransky,D. (2000) Alcohol consumption and cigarette smoking increase the frequency of p53 mutations in non-small cell lung cancer. Cancer Res., 60, 3155–3159.[Abstract/Free Full Text]
  14. World Cancer Research Fund in Association with American Institute for Cancer Research. (1997) Food, Nutrition and the Prevention of Cancer: A Global Perspective. Washington, DC.
  15. Howe,G.R., Hirohata,T. and Hislop,G. et al. (1990) Dietary factors and risk of breast cancer: combined analysis of 12 case-control studies. J. Natl Cancer Inst., 82, 561–569.[Abstract]
  16. Freudenheim,J.L., Marshall,J.R., Vena,J.E., Laughlin,R., Brasure,J.R., Swanson,M.K., Nemoto,T. and Graham,S. (1996) Premenopausal breast cancer risk and intake of vegetables, fruits and related nutrients. J. Natl Cancer Inst., 88, 340–348.[Abstract/Free Full Text]
  17. Hunter,D.J., Manson,J.E., Colditz,G.A., Stampfer,M.J., Rosner,B., Hennekens,C.H., Speizer,F.E. and Willett,W.C. (1993) A prospective study of the intake of vitamins C, E, and A and the risk of breast cancer. N. Engl. J. Med., 329, 234–240.[Abstract/Free Full Text]
  18. Harris,C.C. (1996) Structure and function of the p53 tumor suppressor gene: clues for rational cancer therapeutic strategies. J. Natl Cancer Inst., 88, 1442–1455.[Abstract/Free Full Text]
  19. Hollstein,M., Sidransky,D., Vogelstein,B. and Harris,C.C. (1991) P53 mutations in human cancers. Science, 253, 49–53.[ISI][Medline]
  20. Hsu,I.C., Metcalf,R.A., Sun,T., Welsh,J.A., Wang,N.J. and Harris,C.C. (1991) Mutational hotspot in the p53 gene in human hepatocellular carcinomas. Nature, 350, 427–428.[CrossRef][ISI][Medline]
  21. Bressac,B., Kew,M., Wands,J. and Ozturk,M. (1991) Selective G to T mutations of p53 gene in hepatocellular carcinoma from southern Africa. Nature, 350, 429–431.[CrossRef][ISI][Medline]
  22. Hussain,S.P., Hollstein,M.H. and Harris,C.C. (2000) p53 suppressor gene. At the crossroads of molecular carcinogenesis and human risk assessment. Annal. N.Y. Acad. Sci., 919, 79–85.[Abstract/Free Full Text]
  23. Brash,D.E., Rudolph,J.A., Simon,J.A., Lin,A., McKenna,G.J., Baden,H.P. and Halperin,A.J. (1991) A role for sunlight in skin cancer: UV-induced p53 mutations in squamous cell carcinoma. Proc. Natl Acad. Sci. USA, 88, 10124–10128.[Abstract]
  24. Saeki,H., Ohno,S., Araki,K., Egashira,A., Kawaguchi,H., Ikeda,Y., Morita,M., Kitamura,K. and Sugimachi,K. (2000) Alcohol consumption and cigarette smoking in relation to high frequency of p53 protein accumulation in oesophageal squamous cell carcinoma in the Japanese. Br. J. Cancer, 82, 1892–1894.[CrossRef][ISI][Medline]
  25. Simão,T.A., Ribeiro,F.S., Amorim,L.M.F., Albano,R.M., Andrada-Serpa,M.J., Cardoso,L.E.B., Medonça,G.A.S. and de Moura-Gallo,C.V. (2002) TP53 mutations in breast cancer tumors of patients from Rio de Janeiro, Brazil: association with risk factors and tumor characteristics. Int. J. Cancer, 101, 69–73.[CrossRef][ISI][Medline]
  26. Pütz,A., Hermann,A.A., Fontes,P.R.O., Alexandre,C.O.P., Silveira,D.A., Klug,S.J. and Rabes,H.M. (2002) TP53 mutation pattern of esophageal squamous cell carcinomas in a high risk area (Southern Brazil): role of life style factors. Int. J. Cancer, 98, 99–105.[CrossRef][ISI][Medline]
  27. Kerdpon,D., Sriplung,H. and Kietthubthew,S. (2001) Expression of p53 in oral squamous cell carcinoma and its association with risk habits in southern Thailand. Oral Oncol., 37, 553–557.[CrossRef][ISI][Medline]
  28. Kato,H., Yoshikawa,M., Miyazaki,Y. et al. (2001) Expression of p53 protein related to smoking and alcoholic beverage drinking habits in patients with esophageal cancers. Cancer Lett., 167, 65–72.[CrossRef][ISI][Medline]
  29. Miyazaki,M., Ohno,S., Futatsugi,M., Saeki,H., Ohga,T. and Watanabe,M. (2002) The relation of alcohol consumption and cigarette smoking to the multiple occurrence of esophageal dysplasia and squamous cell carcinoma. Surgery, 131 (1 suppl.), S7–S13.[CrossRef][ISI][Medline]
  30. Cruz,I., Snijders,P.J., Van Houten,V., Vosjan,M., Van der Waal,I. and Meijer,C.J. (2002) Specific p53 immunostaining patterns are associated with smoking habits in patients with oral squamous cell carcinomas. J. Clin. Pathol., 55, 834–840[Abstract/Free Full Text]
  31. van der Kooy,K., Rookus,M.A., Peterse,H.L. and van Leeuwen,F.E. (1996) P53 overexpression in relation to risk factors for breast cancer. Am. J. Epidemiol., 144, 924–933.[Abstract]
  32. Gammon,M.D., Hibshoosh,H., Terry,M.B., Bose,S., Schoenberg,J.B., Brinton,L.A., Bernstein,J.L. and Thompson,W.D. (1999) Cigarette smoking and other risk factors in relation to p53 expression in young women. Cancer Epidemiol. Biomark. Prev., 8, 255–263.[Abstract/Free Full Text]
  33. Olivier,M. and Hainaut,P. (2001) TP53 mutation patterns in breast cancers: searching for clues of environmental carcinogenesis. Semin. Cancer Biol., 11, 353–360.[CrossRef][ISI][Medline]
  34. Furberg,H., Millikan,R.C., Geradts,J., Gammon,M.D., Dressler,L.G., Ambrosone,C.B. and Newman,B. (2002) Environmental factors in relation to breast cancer characterized by p53 protein expression. Cancer Epidemiol. Biomark. Prev., 11, 829–835.[Abstract/Free Full Text]
  35. Conway,K., Edmiston,S.N., Cui,L. et al. (2002) Prevalence and spectrum of p53 mutations associated with smoking in breast cancer. Cancer Res., 62, 1987–1995.[Abstract/Free Full Text]
  36. Freudenheim,J.L., Marshall,J.R., Vena,J.E., Laughlin,R., Brasure,J.R., Swanson,M.K., Nemoto,T. and Graham,S. (1996) Premenopausal breast cancer risk and intake of vegetables, fruits and related nutrients. J. Natl Cancer Inst., 88, 340–348.[Abstract/Free Full Text]
  37. Graham,S., Hellmann,R., Marshall,J., Freudenheim,J., Vena,J., Swanson,M., Zielezny,M., Nemoto,T., Stubbe,N. and Raimondo,T. (1991) Nutritional epidemiology of postmenopausal breast cancer in western New York. Am. J. Epidemiol., 15, 552–566.
  38. Freudenheim,J.L., Ambrosone,C.B., Moysich,K.B. et al. (1999) Alcohol dehydrogenase 3 genotype modification of the association of alcohol consumption with breast cancer. Cancer Causes Control, 10, 369–377.[CrossRef][ISI][Medline]
  39. Ahrendt,S.A., Halachmi,S., Chow,J.T., Wu,L., Halachmi,N., Yang,S.C., Wehage,S., Jen,J. and Sidransky,D. (1999) Rapid p53 sequence analysis in primary lung cancer using an oligonucleotide probe array. Proc. Natl Acad. Sci. USA, 96, 7382–7387.[Abstract/Free Full Text]
  40. Snedecor,G.W. and Cochran,G.C. (1980) Statistical Methods. The Iowa State University Press, Ames, Iowa.
  41. Hosmer,D.W. and Lemeshow,S. (2000) Applied Logistic Regression. John Wiley and Sons, New York.
  42. Begg,C.B. and Zhang,Z.F. (1994) Statistical analysis of molecular epidemiology studies employing case-series. Cancer Epidemiol. Biomark. Prev., 3, 173–175.[Abstract]
  43. Piergorsch,W.W., Weinberg,C.R. and Taylor,J.A. (1994) Non-hierarchical logistic models and case-only designs for assessing susceptibility in population-based case-control studies. Stat. Med., 13, 153–162.[ISI][Medline]
  44. Eto,T. and Krumdieck,C.L. (1986) Role of vitamin B12 and folate deficiencies in carcinogenesis. Adv. Exptl Med. Biol., 206, 313–330.[Medline]
  45. Compere,S.J. and Palmiter,R.D. (1981) DNA methylation controls the inducibility of the mouse metallothionein-I gene in lymphoid cells. Cell, 25, 233–240[ISI][Medline]
  46. Swanson,C.A., Coates,R.J., Malone,K.E., Gammon,M.D., Schoenberg,J.B., Brogan,D.J., McAdams,M., Potischman,N., Hoover,R.N. and Brinton,L.A. (1997) Alcohol consumption and breast cancer risk among women under age 45 years. Epidemiology, 8, 231–237.[ISI][Medline]
  47. Willett,W.C. and Stampfer,M.J. (1997) Sobering data on alcohol and breast cancer. Epidemiology, 8, 225–227.[ISI][Medline]
  48. Singletary,K.W. and Gapstur,S.M. (2001) Alcohol and breast cancer: review of epidemiologic and experimental evidence and potential mechanisms. J. Am. Med. Assoc., 286, 2143–2151.[Abstract/Free Full Text]
  49. Hainaut,P. and Pfeifer,G.P. (2001) Patterns of p53 G->T transversions in lung cancer reflect the primary mutagenic signature of DNA-damage by tobacco smoke. Carcinogenesis, 22, 367–734.[Abstract/Free Full Text]
  50. Poller,D.N., Roberts,E.C., Bell,J.A., Elston,C.W., Blamey,R.W. and Ellis,I.O. (1993) p53 protein expression in mammary ductal carcinoma in situ: relationship to immunohistochemical expression of estrogen receptor and c-erb-2 protein. Hum. Pathol., 24, 463–468.[CrossRef][ISI][Medline]
  51. Aubele,M., Werner,M. and Hofler,H. (2002) Genetic alterations in presumptive precursor lesions of breast carcinomas. Anal. Cell. Pathol., 24, 69–76.[ISI][Medline]
  52. Kang,J.H., Kim,S.J., Noh,D.Y., Choe,K.J., Lee,E.S. and Kang,H.S. (2001) The timing and characterization of p53 mutations in progression from atypical ductal hyperplasia to invasive lesions in the breast cancer. J. Mol. Med., 79, 648–655.[CrossRef][ISI][Medline]
  53. Done,S.J., Eskandarian,S., Bull,S., Redston,M. and Andrulis,I.L. (2001) p53 missense mutations in microdissected high-grade ductal carcinoma in situ of the breast. J. Natl Cancer Inst., 93, 700–704.[Abstract/Free Full Text]
  54. Smith-Warner,S.A., Spiegelman,D., Yaun,S.-S. et al. (2001) Fruits and vegetables and breast cancer: a pooled analysis of cohort studies. J. Am. Med. Assoc., 285, 769–776.[Abstract/Free Full Text]
  55. Friedenreich,C.M. (2001) Review of anthropometric factors and breast cancer risk. Eur. J. Cancer Prev., 10, 15–32.[CrossRef][ISI][Medline]
  56. Cho,E., Spiegelman,D., Hunter,D.J., Chen,W.Y., Stampfer,M.J., Colditz,G.A. and Willett,W.C. (2003) Premenopausal fat intake and risk of breast cancer. J. Natl Cancer Inst., 95, 1079–1085.[Abstract/Free Full Text]
  57. Kang,J.H., Kim,S.J., Noh,D.-Y., Park,I.A., Choe,K.J., Yoo,O.J. and Kang,H.-S. (2001) Methylation in the p53 promoter is a supplementary route to breast carcinogenesis: correlation between CpG methylation in the promoter and the mutation of the p53 gene in the progression from ductal carcinoma in situ to invasive ductal carcinoma. Lab. Invest., 81, 573–579.[ISI][Medline]
  58. Slattery,M.L., Curin,K., Anderson,K., Ma,K.-N., Ballard,L., Edwards,S., Schaffer,D., Potter,J., Leppert,M. and Samowitz,W.S. (2000) Associations between cigarette smoking, lifestyle factors and microsatellite instability in colon tumors. J. Natl Cancer Inst., 92, 1831–1836.[Abstract/Free Full Text]
  59. Slattery,M.L., Anderson,K., Curtin,K., Ma,K.N., Schaffer,D., Edwards,S. and Samowitz,W. (2001) Lifestyle factors and Ki-ras mutations in colon cancer tumors. Mutat. Res. Fund. Mol. Mech. Mutagen., 483, 73–81.[ISI]
  60. Slattery,M.L., Anderson,K., Curtin,K., Ma,K.N., Schaffer,D. and Samowitz,W. (2001) Dietary intake and microsatellite instability in colon tumors. Int. J. Cancer, 93, 601–607.[CrossRef][ISI][Medline]
Received July 24, 2003; revised December 8, 2003; accepted January 10, 2004.