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Carcinogenesis Advance Access originally published online on August 18, 2008
Carcinogenesis 2008 29(11):2203-2209; doi:10.1093/carcin/bgn196
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© The Author 2008. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Plant foods and oestrogen receptor {alpha}- and β-defined breast cancer: observations from the Malmö Diet and Cancer cohort

Emily Sonestedt*, Signe Borgquist1, Ulrika Ericson, Bo Gullberg, Göran Landberg1, Håkan Olsson2 and Elisabet Wirfält

Department of Clinical Sciences in Malmö
1 Center of Molecular Pathology, Department of Laboratory Medicine, Lund University, SE-205 02 Malmö, Sweden
2 Department of Clinical Sciences in Lund, Lund University, Lund, SE-22185 Sweden

* To whom correspondence should be addressed. Department of Clinical Sciences in Malmö, Research group in Nutrition Epidemiology, Lund University, Malmö University Hospital, Clinical Research Centre Entrance 72, Building 60, Floor 13, SE-205 02 Malmö, Sweden. Tel: +46 40 39 13 24; Fax: +46 40 39 13 22; Email: emily.sonestedt{at}med.lu.se


   Abstract
Top
 Abstract
Introduction
 Materials and methods
 Results
 Discussion
 Funding
 References
 
The associations between plant foods and breast cancer incidence are inconsistent. The objective of this study was to examine prospectively the association between dietary fibre, plant foods and breast cancer, especially the association between plant food intake and oestrogen receptor (ER) {alpha}- and β-defined breast cancer. Among women without prevalent cancer from the population-based prospective Malmö Diet and Cancer cohort (n = 15 773, 46–75 years at baseline), 544 women were diagnosed with incident invasive breast cancer during a mean follow-up of 10.3 years. Information on dietary habits was collected by a modified diet history method. ER status of the tumours was determined by immunohistochemistry using tissue microarray. Cox proportional hazards regression estimated hazard ratios (HRs) and 95% confidence intervals (CIs) of breast cancer associated with fibre and 11 plant food groups. High-fibre bread was significantly associated with a decreased breast cancer incidence (HR, 0.75; 95% CI, 0.57–0.98, for highest compared with lowest quintile). The other plant food groups were not significantly associated with breast cancer incidence. There was a tendency for a negative association for high-fibre bread among ER{alpha} (+) breast cancer (P for trend = 0.06) and ERβ (+) breast cancer (P for trend = 0.06). Fried potatoes were statistically significantly associated with increased risk of ERβ (–) breast cancer (P = 0.01). This study suggests that different plant foods may be differently associated with breast cancer, with fibre-rich bread showing an inverse association. We did not observe strong evidence for differences in incidence according to the ER{alpha} and ERβ status of breast cancer.

Abbreviations: CI, confidence interval; ER, oestrogen receptor; HR, hazard ratio; MDC, Malmö Diet and Cancer; MHT, menopausal hormone therapy


   Introduction
Top
 Abstract
 Introduction
Materials and methods
 Results
 Discussion
 Funding
 References
 
Although fibres have been suggested to reduce the risk of breast cancer through several mechanisms, most prospective epidemiological studies have found weak or no associations between fibre intake and breast cancer (1–5). However, the Malmö Diet and Cancer (MDC) cohort have previously observed a breast cancer protective association with high-fibre, low-fat diets in post-menopausal women (6). Unlike other countries, where fruits and vegetables contribute to most of the fibre intake, grains are the major sources of fibre in the Nordic countries (4,6,7). Therefore, the specific plant food sources of fibre may be of particular interest when examining the association between food components and breast cancer.

Plausible mechanisms of the protective effect of fibre-rich foods are through the influence on the bioavailability and the action of oestrogens. Fibre might for example influence the enterohepatic recirculation of oestrogens, giving reduced levels of circulating oestrogens (8,9). In addition, fibre-rich foods are important sources of phytoestrogens, oestrogen-like plant compounds that may interact with and modulate the activity of oestrogen receptors (ERs) (10–12), which have been hypothesized to protect against breast cancer (13).

Epidemiological studies have examined the hypothesis that ER positive (+) and ER negative (–) tumours may represent biologically different cancers (14), and that they are associated with different risk factors (15). Conditions that influence oestrogen levels are believed to have a stronger influence on the development of ER (+) breast cancer (16), and consequently, factors related to reproduction tend to be associated with increased risk of ER (+) but not ER (–) tumours (15). However, more prospective observational studies are needed to clarify the aetiology of breast cancer defined by hormone receptor status (17).

Two types of ERs have been identified: ER{alpha} and ERβ. Whereas ER{alpha} expression in breast tumours is used to guide treatment and provide prognostic information, ERβ was recently identified (18). ERβ is still not used in clinical settings, although a treatment-predictive value of ERβ has been reported (19–22). Although, the biological function of ERβ is yet not fully understood, it is suggested that ER{alpha} and ERβ differ in the interaction with other proteins (23,24), and that ERβ may have a negative modulatory effect on ER{alpha} (23). It also appears that some types of phyto-oestrogens show preferences for ER{alpha} (12) and others for ERβ (10,11). These observations demonstrate the importance of taking ER{alpha} as well as ERβ expression of the tumours into account. We are not aware of any study that has investigated the role of ERβ status on the association between plant foods and breast cancer. The aim of this paper was to examine prospectively the association between dietary fibre, plant foods and breast cancer, especially the association between intake of plant foods and ER{alpha}- and ERβ-defined breast cancer, respectively.


   Materials and methods
Top
 Abstract
 Introduction
 Materials and methods
Results
 Discussion
 Funding
 References
 
Study population
MDC is a population-based prospective cohort with baseline examinations from March 1991 to October 1996. Men born 1923–1945 and women born 1923–1950 and living in Malmö were invited to participate (source population 74 138). Limited skills in the Swedish language and mental incapacity were the only exclusion criteria. With a participation rate of ~40%, the cohort consists of 28 098 individuals (17 035 women and 11 063 men). Participants came to the study centre on two occasions. During the first visit, participants obtained detailed information about the dietary data collection procedure, received an extensive questionnaire to complete at home covering lifestyle, socioeconomic and reproductive factors and medical history and had anthropometric measurements taken. At the second visit, trained interviewers conducted the dietary interview. Ethical permission for the study was obtained (LU 51-90). A more detailed description of the cohort is given elsewhere (25,26).

Cases were identified via Swedish Cancer Registry and Southern Swedish Regional Cancer Registry until the end of follow-up 31 December 2004. The National Tax Board provided information on vital status. After exclusion of women with prevalent cancer (except those with cervix cancer in situ), 15 773 women remained. Until the end of follow-up, and during an average of 10.3 years, and 161 920 person-years of follow-up, 544 cases of incident invasive breast cancer were identified. Women with in situ breast cancer were not categorized as cases and were therefore under risk of breast cancer and not censored at diagnosis. Mean age at diagnosis was 63 years (range 46–81). The participants contributed person-time from date of enrolment until the time of invasive breast cancer diagnosis, death, migrating from Sweden or end of follow-up, whichever occurred first.

ER status assessment
For the construction of tissue microarrays, two 0.6 mm tissue cores were collected from each tumour block and arranged in a recipient block using a manual tissue arrayer (Beecher, Sun Prairie, WI). Slides were then processed in an automatic immunohistochemistry staining machine. The antibodies used were ER{alpha} (pre-diluted anti-ER 6F11, Ventana Tucson, Arizona) and ERβ (1:25 EMR02, Novocastra, Newcastle upon Tyne UK) (27). Tumours were grouped into categories according to the expression of ER{alpha} and ERβ (0–1, 2–10, 11–50 and 51–100% positive nuclei). Receptor status of all breast tumours was evaluated in a standardized way by one person, thereby eliminating inter-observer variation. All arrays were evaluated independently twice, and in case of discrepancy, a third examination was performed followed by a final decision, thereby reducing the potential intra-observer bias. The tumours were classified as positive (+) and negative (–) using the clinically established cut-off value of 10% positive nuclei. ER{alpha} and ERβ was estimated for 450 and 370 cases, respectively. For the remaining cases, adequate tumour samples were not available, either due to surgery performed at other hospitals or insufficient amount of tumour material left for histopathological evaluation. These cases were categorized as unknown.

Diet assessment methodology
The dietary assessment methodology of high relative validity has been described in detail elsewhere (28,29). It combined (i) a 7 day menu book that collected information on lunch and dinner meals and cold beverages, medications and dietary supplements; (ii) a 168-items dietary questionnaire covering regularly consumed foods during the past year, which included frequencies and portion sizes assessed using photographic aids and (iii) a 1 h interview, where participants were asked questions about portion sizes, food choices and food preparation practises, and the interviewer checked the menu book and dietary questionnaire for overlapping information. A total of 17 interviewers conducted the dietary interviews. The average daily intake of foods (grams per day) was calculated from the information of the menu book (and interview) and of the questionnaire. Food intake was converted to nutrient intake data using the MDC Food and Nutrient Database, specifically developed for the MDC study and originating from PC KOST2-93 of the Swedish National Food Administration. In September 1994, the routines for coding dietary data at data entry were slightly altered in order to shorten the interview time (30).

The relative validity of the dietary method has been examined among 105 women and 101 men, 50–69 years old, with 18 days of weighed food records (3 days every second month) collected during 1 year, as the reference method. Energy-adjusted Pearson correlations in women were 0.69 for fibre, 0.77 for fruits, 0.53 for vegetables, 0.51 for potato, 0.73 for cereals, 0.58 for bread and 0.24 for rice and pasta (29,31).

Food variables
The dietary variables examined in this study were fibre (gram) and energy (kilocalorie). The plant foods (gram) were categorized into 10 food groups: vegetables, fruits and berries, fruit juices, boiled potato, fried and deep-fried potato, cereals (grains, cereals and flours), low-fibre bread (<6% of fibre for soft bread, <10% for crisp bread and <10% for biscuits and rusks), high-fibre bread (≥6% of fibre for soft bread, ≥10% for crisp bread and ≥10% for biscuits and rusks), rice and pasta and nuts. Fruits, berries and vegetables were also combined into one variable.

Other variables
Information on age and gender was obtained through the person identification number (in Sweden, each person is assigned a 10-digit number at birth: six digits indicate the date of birth and one identifies gender). Weight (kilogram) was measured using balance beam scale with subjects wearing light clothing and no shoes, and height (centimetre) was measured with a fixed stadiometer calibrated in centimetres. Other lifestyle and socioeconomic variables were obtained through the extensive questionnaire. Educational status was categorized based on type of education attained: elementary, primary and secondary, upper secondary, further education without a degree and university degree. Smoking habits were categorized into current smokers (including irregular smoking), ex-smokers and non-smokers. Alcohol consumption was divided into four categories. Individuals with no consumption of alcohol in the menu book, and who indicated no consumption of alcohol during the previous year in the lifestyle and socioeconomic questionnaire, were categorized as zero consumers. The other subjects were categorized into three groups according to their alcohol consumption: <15 (low), 15–30 (medium) and >30 g alcohol per day (high). Leisure time physical activity was obtained from questions of different physical activities across the seasons where minutes per week of each activity were multiplied with an intensity factor, creating a leisure time physical activity score. The score was separated into quartiles. Household activities were divided into four categories: 0–9, 10–19, 20–29 and ≥30 h/week. Parity was aggregated into five answer categories: no children, one child, two children, three children and four or more children. Age at menopause was divided into five categories: <45, 45–49, 50–55, >55 years and those that reported no cessation of menses. Current users of menopausal hormone therapy (MHT) (yes/no) were identified through the menu book and the questionnaire. Dietary change in the past (yes/no) was derived from the questionnaire item ‘Have you substantially changed your eating habits because of illness or some other reasons?’ A variable was created for the seasons of data collection: winter (December–February), spring (March–May), summer (June–August) and fall (September–November).

Statistical analyses
SPSS (version 14.0; SPSS; Chicago, IL) was used for all statistical analyses. The differences in distribution of participant characteristics between cases and controls were tested using {chi}2 test. Student’s t-test examined differences in mean intakes of loge-transformed food variables between cases and non-cases. Crude mean and standard deviations of food intakes and participant characteristics were described for cases according to their ER{alpha} and ERβ status of the tumour, and we used general linear model with Tukey’s test to compare differences in means according to ER status. A small number (0.01) was added to dietary variables to handle zero intakes before transformation to normalize the distribution. The food variables were energy adjusted by regressing the food variable on total energy intake, and the individuals were divided into quintiles depending on their residual ranking (residual method). Because of low consumption (i.e. the 25th percentile included zero consumers) of several food groups (fruit juice, fried and deep-fried potato, rice and pasta and nuts), individuals that reported no consumption were categorized as zero consumers and the other individuals were divided into tertiles according to the energy-adjusted intakes (residual method) of the food group.

Hazard ratios (HRs) and 95% confidence intervals (CIs) of the food groups associated with breast cancer were estimated using Cox proportional hazard regression. Person-years of follow-up were included as the time-dependent variable. The basic model was adjusted for age and was stratified on method version (to avoid any undue influence of the different coding strategies of dietary data). The multivariate model was extended to adjust for total energy, season of data collection and diet interviewer, as well as established breast cancer risk factors and potential confounding variables: weight, height, educational status, smoking habits, leisure time physical activity, hours of household activities, alcohol consumption, age at menopause, parity and current use of MHT. Missing values among these variables were recoded as separate categories to avoid exclusion of individuals from analysis. We also repeated analysis excluding individuals <55 years at baseline (to further ensure that the analyses only included post-menopausal women) and individuals with reported dietary change in the past (in order to exclude individuals more probably to have instable food habits) (32). Test of trend was calculated as a linear trend over quintiles values.

HRs of ER-defined breast cancer [i.e. ER{alpha} (+), ER{alpha} (–), ERβ (+) and ERβ (–) as well as ER{alpha} (+)/ERβ (–) and ER{alpha} (+)/ERβ (+)] associated with each food group were estimated with the basic and the multivariate model. The number of cases with ER{alpha}–/ERβ– (n = 31) and ER{alpha}–/ERβ+ (n = 21) was very small and therefore not considered in the analysis. Individuals with the opposite and unknown types of breast cancer contributed to time of follow-up until the date of diagnosis.


   Results
Top
 Abstract
 Introduction
 Materials and methods
 Results
Discussion
 Funding
 References
 
The majority of the cases had ER{alpha} (+) tumours (n = 392, 87% among cases with classified ER{alpha} tumours). Among cases where ERβ status could be identified, 182 (49%) had ERβ (+) tumours and 188 (51%) had ERβ (–) tumours. A total of 155 individuals could be classified as ER{alpha} (+)/ERβ (–) and 159 as ER{alpha} (+)/ERβ (+). There was no clear evidence of co-expression of the ER{alpha} and ERβ with a non-significant chi-square test (P = 0.18) (Table I). Age, weight, height and use of MHT were significantly different distributed between cases and non-cases (Table II). The mean intake of the plant foods did not significantly differ between cases and non-cases (Table II). Age and anthropometric measures did not differ between cases of different ER status (Table III). There were no differences in age and anthropometric measures in cases where receptor status could not be determined compared with other cases.


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  		Table I. Distribution of ER{alpha} and ERβ status of the tumours among incident breast cancer cases in the MDC cohort, until the end of follow-up 31 December 2004

 


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  		Table II. Baseline characteristics and food intakes among breast cancer cases and non-cases from the MDC study, until the end of follow-up 31 December 2004

 


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  		Table III. Participant characteristics and intake of food groups among breast cancer cases according to the ER status in the MDC cohort, until the end of follow-up 31 December 2004

 
The highest quintile of fibre was associated with a non-significant decreased risk of breast cancer with the multivariate model (HR, 0.82; 95% CI, 0.61–1.09, for highest versus lowest quintile) (Table IV). Among the food groups, highest quintile of high-fibre bread was significantly associated with a 25% decreased risk of breast cancer incidence compared with the lowest quintile. The risk estimates were essentially the same when restricting analyses to individuals >55 years at baseline (data not shown). However, the association with fibre was more pronounced when restricting the analysis to women without reported dietary change in the past (HR, 0.66; 95% CI, 0.46–0.95, for highest versus lowest quintile). Moreover, fruits, berries and vegetables were also associated with a decreased risk, when restricting analysis to individuals without dietary change in the past (HR, 0.65; 95% CI, 0.46–0.93, for highest versus lowest quintile, P for trend over quintiles = 0.03).


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  		Table IV. HR (95% CI) of invasive breast cancer by quintiles of intake of total fibre and of food sources of fibre in women of the MDC cohort, 1991–2004

 
Table V presents the risk trends associated with change from one category to the next (increasing intakes) with the basic model. Fried potato was associated with an increased risk of ERβ (–) breast cancer, with a 17% increased risk of ERβ (–) breast cancer for each increase in the intake categories (P = 0.01). The highest tertile of fried potatoes was associated with a significantly increased risk compared with zero consumers, HR, 1.61; 95% CI, 1.11–2.33 (data not shown). None of the other food groups were statistically significantly associated with any of the ER-defined breast cancers. The results were similar when adjusting for potential confounding factors (data not shown). However, there was a tendency in the multivariate analysis of an inverse association for high-fibre bread among ER{alpha} (+) breast cancer (HR, 0.93; 95% CI, 0.87–1.00; P = 0.06) and ERβ (+) breast cancer (HR, 0.90; 95% CI, 0.81–1.00; P = 0.06).


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  		Table V. The risk trends of ER characterized invasive breast cancer by quintilesa of total fibre and of food sources of fibre in women of the MDC cohort, 1991–2004b

 

   Discussion
Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
Funding
 References
 
This study suggests that intake of different plant foods may be differently associated with breast cancer, with fibre-rich bread showing an inverse association with breast cancer incidence. Similar to our previous report (6), the highest quintile of fibre was associated with a non-significant decreased risk of breast cancer. We did not observe any strong evidence for differences in breast cancer incidence according to the ER{alpha} and ERβ status of the tumours.

The major strength of the study is the prospective population-based study design of the MDC cohort with dietary exposures assessed before the cancer diagnosis. Moreover, the dietary assessment methodology of MDC has a high relative validity (29,31). Consumption of high-fibre bread might be associated with other health-conscious dietary and lifestyle habits (33), which in turn may confound the association between high-fibre bread and breast cancer. Even though we were able to control in the analyses for several potential confounding factors, e.g. physical activity, smoking and alcohol consumption, it is possible that residual confounding still exists.

Studies indicate that whole grains show protective associations with several forms of cancer (34). High-fibre bread is a major source of whole grains in the Western diet (35). However, dietary assessments in epidemiological studies may have difficulties in separating whole grains from refined products as many people find it difficult to accurately identify wholegrain foods (36). The dietary methodology that was used in the MDC study has certain advantages over other more common dietary assessment methods (e.g. food frequency questionnaires). Individuals had to specify the brand of the bread, in order to accurately assess the fibre content of the bread, and this was checked during the 1 h dietary interview. Biomarkers of wholegrain products are, however, under development, for example alkylresorcinols (rye and wheat) (37) and avenanthramides (oat) (38). Such biomarkers would in future studies be used to confirm the role of whole grains in cancer prevention. Enterolactone has also been suggested as a biomarker for a high-fibre diet (39), and several studies have observed a breast cancer protective effect of high circulating enterolactone concentrations (40,41).

Although the protective association between high-fibre bread and breast cancer in the present study was clearer, a tendency of an inverse association was also observed for fruits, berries and vegetables. Among individuals without self-reported dietary change in the past, fruits, berries and vegetables were significantly associated with a decreased risk. As we have reported previously, individuals with reported past food habit change were more probably to be obese. They also reported healthier food habits and lower energy intake compared with non-changers, a finding that raises issues regarding possible reporting biases (42). Individuals without reported dietary change may have more stable food habits and consequently to a higher degree report the diet responsible for tumour development (32).

We could not observe any obvious differences in dietary intakes between cases with different ER status of the tumour (Table II), and we did not observe any strong evidence for differences in breast cancer incidence according to the ER{alpha} and ERβ status of the tumours (Table IV). Although there were enough cases to investigate the role of dietary factors among all cases, some statistical power was lost when restricting the analyses to ER-defined breast cancer. However, in spite of reduced power, we observed an increased risk associated with fried potato among cases with ERβ (–) tumours. Fried potato and French fries are major contributors to the dietary exposure of acrylamide in this population (43). Acrylamide and its metabolites are well-known environmental toxins and potent carcinogens (44,45). Although, several epidemiological studies have not shown positive association between estimated intakes of acrylamide and cancer (46), a recent study indicated increased risk of estimated acrylamide intake with endometrial and ovarian cancer (47). It is hypothesized that oestrogen-related factors have the greatest impact in ER (+) cancers. Non-oestrogen-related environmental factors (like acrylamide), on the other hand, may have a stronger impact among breast tumours that are not sensitive to oestrogen (ER negative), which is supported by our observation that fried potatoes were positively associated with ERβ (–) tumours. It appears that high-fibre bread shows stronger association with tumours with high expression of ERs. This observation supports the hypothesis that whole grains contain substances that might influence the oestrogen-signalling pathways (12). However, these observations should be interpreted with caution as some significant findings are expected to occur by chance when a large number of tests are performed.

Few studies have investigated the association between fibre or plant foods and ER-defined breast cancer. Higher consumption of fruits and vegetables were associated with decreased risk of ER{alpha} (–) breast cancer in the Nurses Health Study (48). A Danish cohort study has found that fruit and vegetable intakes were differentially associated with ER{alpha} (+) and ER{alpha} (–) breast cancer, with a protective effect only observed among ER{alpha} (–) tumours (49). On the other hand, a large case–control study found that the inverse associations for fruits and vegetables were stronger with ER{alpha} (+) tumours than ER{alpha} (–) tumours (50). A large Swedish cohort study did not detect any heterogeneity in breast cancer risk associated with fibre intake across hormone receptors status (4). Although previous studies have suggested that ER{alpha} (+) tumours are related to high fat intakes (16,51,52), another study using MDC data found that intake of total energy, macronutrients nor fatty acids differed according to ER{alpha} status of the breast tumours (53).

A potential misclassification of ER status of the tumours may influence the results. The tissue microarray technique used in this study is a well-documented method for high-throughput tissue screening and is now the preferable method to evaluate large tumour materials (54,55). Potential inter- and intra-observer variation regarding classification of tumours were probably limited, as receptor status of all breast tumours was evaluated twice in a standardized way by one person. The number of cases with missing ER status (especially ERβ) is relatively high. This will decrease the statistical power to examine the association between diet and ER-defined breast cancer. However, as individuals with missing data of ER status were not different from other cases according to major risk factors (i.e. age, weight, height and use of MHT), this should not have introduced bias.

We are not aware of any study that has examined the association between dietary factors and ERβ-defined breast cancer. ERβ was recently discovered (18) and its biological function and prognostic role is still not fully understood (21,56). Expression of ERβ has, however, been observed in various cancer types, including breast tumours (57). There is considerable variation in the reported specificity of ERβ antibodies for immunohistochemical evaluation (58), which contributes to the controversial view of ERβ. The ERβ antibody used in this study has been validated by comparing the immunohistochemical method with western blot (22). Some studies tend to find co-expression of ERβ and ER{alpha} in breast cancers (59,60). However, our study does not support these findings. Experimental studies have observed down-regulation of ERβ along with breast cancer development (61,62), and ERβ has been suggested to have a regulatory role in ER{alpha} activity (23). It also appears that some phyto-oestrogens have higher affinity to ERβ compared with ER{alpha} (10). However, Penttinen et al. (12) recently demonstrated that enterolactone show preference for ER{alpha}. We could not in the present study detect any significant heterogeneity in the risk associated with plant foods groups between cases with ER{alpha} (+)/ERβ (–) or ER{alpha} (+)/ERβ (+) status.

In conclusion, high intake of fibre-rich bread was inversely associated with breast cancer. We did not, however, observe strong evidence for differences in incidence according to the ER{alpha} and β status of breast cancer. The findings from our study will need to be confirmed by other studies, especially the positive association with fried potato in ERβ-negative tumours. Some of the cancer-protective effects associated with high-fibre diet may come from components other than fibre itself. For example, wholegrain bread contains many phytochemicals, including phyto-oestrogens, antioxidants and phenols (63), which need to be evaluated further.


   Funding
Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 Funding
References
 
Swedish Research Council (K2006-27X-20060-01-3); Swedish Research Council Formas (222-2005-1833); Swedish Council for working life and social research (2005-0251); Albert Påhlssons Foundation; Swedish Cancer Society (4886-B03-01XAB).


   References
Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 Funding
 References
 

  1. Holmes MD, et al. Dietary carbohydrates, fiber, and breast cancer risk. Am. J. Epidemiol. (2004) 159:732–739.[Abstract/Free Full Text]
  2. Terry P, et al. No association among total dietary fiber, fiber fractions, and risk of breast cancer. Cancer Epidemiol. Biomarkers Prev. (2002) 11:1507–1508.[Free Full Text]
  3. Cade JE, et al. Dietary fibre and risk of breast cancer in the UK Women’s Cohort Study. Int. J. Epidemiol. (2007) 36:431–438.[Abstract/Free Full Text]
  4. Suzuki R, et al. Dietary fiber intake and risk of postmenopausal breast cancer defined by estrogen and progesterone receptor status—a prospective cohort study among Swedish women. Int. J. Cancer (2008) 122:403–412.[CrossRef][Web of Science][Medline]
  5. Giles GG, et al. Dietary carbohydrate, fibre, glycaemic index, glycaemic load and the risk of postmenopausal breast cancer. Int. J. Cancer (2006) 118:1843–1847.[CrossRef][Web of Science][Medline]
  6. Mattisson I, et al. Intakes of plant foods, fibre and fat and risk of breast cancer—a prospective study in the Malmo Diet and Cancer cohort. Br. J. Cancer (2004) 90:122–127.[CrossRef][Web of Science][Medline]
  7. Bingham SA, et al. Dietary fibre in food and protection against colorectal cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC): an observational study. Lancet (2003) 361:1496–1501.[CrossRef][Web of Science][Medline]
  8. Monroe KR, et al. Dietary fiber intake and endogenous serum hormone levels in naturally postmenopausal Mexican American women: the multiethnic cohort study. Nutr. Cancer (2007) 58:127–135.[Web of Science][Medline]
  9. Adlercreutz H, et al. Effect of dietary components, including lignans and phytooestrogens, on enterohepatic circulation and liver metabolism of estrogens and on sex hormone binding globulin (SHBG). J. Steroid Biochem. (1987) 27:1135–1144.[CrossRef][Web of Science][Medline]
  10. Kuiper GG, et al. Interaction of estrogenic chemicals and phytooestrogens with estrogen receptor beta. Endocrinology (1998) 139:4252–4263.[Abstract/Free Full Text]
  11. Mueller SO, et al. Phytooestrogens and their human metabolites show distinct agonistic and antagonistic properties on estrogen receptor alpha (ERalpha) and ERbeta in human cells. Toxicol. Sci. (2004) 80:14–25.[Abstract/Free Full Text]
  12. Penttinen P, et al. Diet-derived polyphenol metabolite enterolactone is a tissue-specific estrogen receptor activator. Endocrinology (2007) 148:4875–4886.[Abstract/Free Full Text]
  13. Adlercreutz H. Phytooestrogens and breast cancer. J. Steroid Biochem. Mol. Biol. (2002) 83:113–118.[CrossRef][Web of Science][Medline]
  14. Dontu G, et al. Breast cancer, stem/progenitor cells and the estrogen receptor. Trends Endocrinol. Metab. (2004) 15:193–197.[CrossRef][Web of Science][Medline]
  15. Althuis MD, et al. Etiology of hormone receptor-defined breast cancer: a systematic review of the literature. Cancer Epidemiol. Biomarkers Prev. (2004) 13:1558–1568.[Abstract/Free Full Text]
  16. Kushi LH, et al. Dietary fat and risk of breast cancer according to hormone receptor status. Cancer Epidemiol. Biomarkers Prev. (1995) 4:11–19.[Abstract]
  17. Michels KB, et al. Diet and breast cancer: a review of the prospective observational studies. Cancer (2007) 109:2712–2749.[CrossRef][Medline]
  18. Kuiper GG, et al. Cloning of a novel receptor expressed in rat prostate and ovary. Proc. Natl. Acad. Sci. USA (1996) 93:5925–5930.[Abstract/Free Full Text]
  19. Esslimani-Sahla M, et al. Estrogen receptor beta (ER beta) level but not its ER beta cx variant helps to predict tamoxifen resistance in breast cancer. Clin. Cancer Res. (2004) 10:5769–5776.[Abstract/Free Full Text]
  20. Hopp TA, et al. Low levels of estrogen receptor beta protein predict resistance to tamoxifen therapy in breast cancer. Clin. Cancer Res. (2004) 10:7490–7499.[Abstract/Free Full Text]
  21. Murphy LC, et al. Is oestrogen receptor-beta a predictor of endocrine therapy responsiveness in human breast cancer? Endocr. Relat. Cancer (2006) 13:327–334.[Abstract/Free Full Text]
  22. Borgquist S, et al. Oestrogen receptors alpha and beta show different associations to clinicopathological parameters and their co-expression might predict a better response to endocrine treatment in breast cancer. J. Clin. Pathol. (2008) 61:197–203.[Abstract/Free Full Text]
  23. Saji S, et al. Clinical significance of estrogen receptor beta in breast cancer. Cancer Chemother. Pharmacol. (2005) 56(suppl. 1):21–26.[CrossRef][Medline]
  24. Duffy MJ. Estrogen receptors: role in breast cancer. Crit. Rev. Clin. Lab. Sci. (2006) 43:325–347.[CrossRef][Web of Science][Medline]
  25. Manjer J, et al. The Malmo diet and cancer study: representativity, cancer incidence and mortality in participants and non-participants. Eur. J. Cancer Prev. (2001) 10:489–499.[CrossRef][Web of Science][Medline]
  26. Berglund G, et al. The Malmo Diet and Cancer Study. Design and feasibility. J. Intern. Med. (1993) 233:45–51.[Web of Science][Medline]
  27. Fuqua SA, et al. Expression of wild-type estrogen receptor beta and variant isoforms in human breast cancer. Cancer Res. (1999) 59:5425–5428.[Abstract/Free Full Text]
  28. Callmer E, et al. Dietary assessment methods evaluated in the Malmo food study. J. Intern. Med. (1993) 233:53–57.[Web of Science][Medline]
  29. Riboli E, et al. The Malmo Food Study: validity of two dietary assessment methods for measuring nutrient intake. Int. J. Epidemiol. (1997) 26(suppl. 1):S161–S173.[Abstract/Free Full Text]
  30. Wirfalt E, et al. A methodological report from the Malmo diet and cancer study: development and evaluation of altered routines in dietary data processing. Nutr. J. (2002) 1:3.[CrossRef][Medline]
  31. Elmstahl S, et al. The Malmo Food Study: the relative validity of a modified diet history method and an extensive food frequency questionnaire for measuring food intake. Eur. J. Clin. Nutr. (1996) 50:143–151.[Web of Science][Medline]
  32. Sonestedt E, et al. Both food habit change in the past and obesity status may influence the association between dietary factors and postmenopausal breast cancer. Public Health Nutr. (2007) 10:769–779.[Web of Science][Medline]
  33. World Cancer Research Fund and American Institute for Cancer Research. Food, Nutrition, Physical Activity, and the Prevention of Cancer: A Global Perspective (2007) Washington, DC: AICR.
  34. Jacobs DR Jr, et al. Whole-grain intake and cancer: an expanded review and meta-analysis. Nutr. Cancer (1998) 30:85–96.[Web of Science][Medline]
  35. Lang R, et al. Who consumes whole grains, and how much? Proc. Nutr. Soc. (2003) 62:123–127.[Web of Science][Medline]
  36. Jacobs DR Jr, et al. Reduced mortality among whole grain bread eaters in men and women in the Norwegian County Study. Eur. J. Clin. Nutr. (2001) 55:137–143.[CrossRef][Web of Science][Medline]
  37. Ross AB, et al. Dietary alkylresorcinols: absorption, bioactivities, and possible use as biomarkers of whole-grain wheat- and rye-rich foods. Nutr. Rev. (2004) 62:81–95.[CrossRef][Web of Science][Medline]
  38. Chen CY, et al. Avenanthramides are bioavailable and have antioxidant activity in humans after acute consumption of an enriched mixture from oats. J. Nutr. (2007) 137:1375–1382.[Abstract/Free Full Text]
  39. Lampe JW. Isoflavonoid and lignan phytooestrogens as dietary biomarkers. J. Nutr. (2003) 133(suppl. 3):956S–964S.[Abstract/Free Full Text]
  40. Pietinen P, et al. Serum enterolactone and risk of breast cancer: a case-control study in eastern Finland. Cancer Epidemiol. Biomarkers Prev. (2001) 10:339–344.[Abstract/Free Full Text]
  41. Hulten K, et al. An incident case-referent study on plasma enterolactone and breast cancer risk. Eur. J. Nutr. (2002) 41:168–176.[CrossRef][Web of Science][Medline]
  42. Sonestedt E, et al. Past food habit change is related to obesity, lifestyle and socio-economic factors in the Malmo Diet and Cancer Cohort. Public Health Nutr. (2005) 8:876–885.[CrossRef][Web of Science][Medline]
  43. Wirfalt E, et al. Associations between estimated acrylamide intakes, and hemoglobin AA adducts in a sample from the Malmo diet and cancer cohort. Eur. J. Clin. Nutr (2007) 62:314–323.[Web of Science][Medline]
  44. Besaratinia A, et al. A review of mechanisms of acrylamide carcinogenicity. Carcinogenesis (2007) 28:519–528.[Abstract/Free Full Text]
  45. Parzefall W. Minireview on the toxicity of dietary acrylamide. Food Chem. Toxicol (2007) 46:1360–1364.[Web of Science][Medline]
  46. Mucci LA, et al. Acrylamide intake and breast cancer risk in Swedish women. JAMA (2005) 293:1326–1327.[Free Full Text]
  47. Hogervorst JG, et al. A prospective study of dietary acrylamide intake and the risk of endometrial, ovarian, and breast cancer. Cancer Epidemiol. Biomarkers Prev. (2007) 16:2304–2313.[Abstract/Free Full Text]
  48. Fung TT, et al. Dietary patterns and the risk of postmenopausal breast cancer. Int. J. Cancer (2005) 116:116–121.[CrossRef][Web of Science][Medline]
  49. Olsen A, et al. Fruits and vegetables intake differentially affects estrogen receptor negative and positive breast cancer incidence rates. J. Nutr. (2003) 133:2342–2347.[Abstract/Free Full Text]
  50. Gaudet MM, et al. Fruits, vegetables, and micronutrients in relation to breast cancer modified by menopause and hormone receptor status. Cancer Epidemiol. Biomarkers Prev. (2004) 13:1485–1494.[Abstract/Free Full Text]
  51. Jain M, et al. Tumor characteristics and survival of breast cancer patients in relation to premorbid diet and body size. Breast Cancer Res. Treat. (1997) 42:43–55.[CrossRef][Web of Science][Medline]
  52. Harlan LC, et al. Estrogen receptor status and dietary intakes in breast cancer patients. Epidemiology (1993) 4:25–31.[Web of Science][Medline]
  53. Borgquist S, et al. Diet and body constitution in relation to subgroups of breast cancer defined by tumour grade, proliferation and key cell cycle regulators. Breast Cancer Res. (2007) 9:R11.[CrossRef][Medline]
  54. Camp RL, et al. Validation of tissue microarray technology in breast carcinoma. Lab. Invest. (2000) 80:1943–1949.[Web of Science][Medline]
  55. Hoos A, et al. Tissue microarray profiling of cancer specimens and cell lines: opportunities and limitations. Lab. Invest. (2001) 81:1331–1338.[Web of Science][Medline]
  56. Palmieri C, et al. Estrogen receptor beta in breast cancer. Endocr. Relat. Cancer (2002) 9:1–13.[Abstract]
  57. Omoto Y, et al. Evaluation of oestrogen receptor beta wild-type and variant protein expression, and relationship with clinicopathological factors in breast cancers. Eur. J. Cancer (2002) 38:380–386.[CrossRef][Web of Science][Medline]
  58. Skliris GP, et al. Evaluation of seven oestrogen receptor beta antibodies for immunohistochemistry, western blotting, and flow cytometry in human breast tissue. J. Pathol. (2002) 197:155–162.[CrossRef][Web of Science][Medline]
  59. Hayashi SI, et al. The expression and function of estrogen receptor alpha and beta in human breast cancer and its clinical application. Endocr. Relat. Cancer (2003) 10:193–202.[Abstract]
  60. Speirs V, et al. Oestrogen receptor beta: what it means for patients with breast cancer. Lancet Oncol. (2004) 5:174–181.[CrossRef][Web of Science][Medline]
  61. Roger P, et al. Decreased expression of estrogen receptor beta protein in proliferative preinvasive mammary tumors. Cancer Res. (2001) 61:2537–2541.[Abstract/Free Full Text]
  62. Leygue E, et al. Altered estrogen receptor alpha and beta messenger RNA expression during human breast tumorigenesis. Cancer Res. (1998) 58:3197–3201.[Abstract/Free Full Text]
  63. Slavin J. Why whole grains are protective: biological mechanisms. Proc. Nutr. Soc. (2003) 62:129–134.[CrossRef][Web of Science][Medline]
Received March 17, 2008; revised August 12, 2008; accepted August 13, 2008.


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