Hostname: page-component-78c5997874-t5tsf Total loading time: 0 Render date: 2024-11-20T04:33:39.543Z Has data issue: false hasContentIssue false

Redefining the impact of nutrition on breast cancer incidence: is epigenetics involved?

Published online by Cambridge University Press:  02 July 2012

Dorothy Teegarden
Affiliation:
Department of Nutrition Sciences, Stone Hall, Purdue University, West Lafayette, IN, 47907-1264, USA Oncological Sciences Center and Purdue University Center for Cancer Research, Purdue University, West Lafayette, IN, 47907, USA
Isabelle Romieu
Affiliation:
Nutrition and Metabolism Section, International Agency for Research on Cancer (IARC), 150 cours Albert Thomas, 69372, Lyon cedex 08, France
Sophie A. Lelièvre*
Affiliation:
Oncological Sciences Center and Purdue University Center for Cancer Research, Purdue University, West Lafayette, IN, 47907, USA Department of Basic Medical Sciences, Lynn Hall, Purdue University, West Lafayette, IN, 47907-2026, USA
*
*Corresponding author: Sophie A. Lelièvre, fax +1 765 494 0781, email [email protected]
Rights & Permissions [Opens in a new window]

Abstract

Breast cancer incidence is rising worldwide with an increase in aggressive neoplasias in young women. Possible factors involved include lifestyle changes, notably diet that is known to make an impact on gene transcription. However, among dietary factors, there is sufficient support for only greater body weight and alcohol consumption whereas numerous studies revealing an impact of specific diets and nutrients on breast cancer risk show conflicting results. Also, little information is available from middle- and low-income countries. The diversity of gene expression profiles found in breast cancers indicates that transcription control is critical for the outcome of the disease. This suggests the need for studies on nutrients that affect epigenetic mechanisms of transcription, such as DNA methylation and post-translational modifications of histones. In the present review, a new examination of the relationship between diet and breast cancer based on transcription control is proposed in light of epidemiological, animal and clinical studies. The mechanisms underlying the impact of diets on breast cancer development and factors that impede reaching clear conclusions are discussed. Understanding the interaction between nutrition and epigenetics (gene expression control via chromatin structure) is critical in light of the influence of diet during early stages of mammary gland development on breast cancer risk, suggesting a persistent effect on gene expression as shown by the influence of certain nutrients on DNA methylation. Successful development of breast cancer prevention strategies will require appropriate models, identification of biological markers for rapid assessment of preventive interventions, and coordinated worldwide research to discern the effects of diet.

Type
Review Article
Copyright
Copyright © The Authors 2012

Triangular relationship: breast cancer incidence, gene transcription and nutrition

Burden of breast cancer

Globally an estimated 1·38 million new breast cancer cases were diagnosed in 2008, which represents 23 % of all cancers(Reference Ferlay, Shin and Bray1). Breast cancer is the most common cancer in women from high-income countries and its frequency has been rising in low- and middle-income (LMI) countries. The range of incidence worldwide is great, with high rates (above 80 per 100 000) in high-income regions of the world (with the exception of Japan) and low rates (less than 40 per 100 000) in most LMI regions. However, the mortality rate does not mirror that of incidence because of the more favourable survival from breast cancer in developed regions. Breast cancer ranks as the fifth cause of death from cancer overall (458 000 deaths in 2008). Yet, breast cancer is the leading cause of mortality by cancer among women from LMI countries, which is in part related to poor access to screening, diagnosis and treatment(Reference Franco-Marina, Lazcano-Ponce and Lopez-Carrillo2, Reference Velasquez-De Charry, Carrasquilla and Roca-Garavito3). The increase in incidence and mortality observed in LMI countries is thought to be due to a variety of factors such as population growth, ageing, lifestyle changes, and migration to urban communities(Reference Lozano-Ascencio, Gomez-Dantes and Lewis4, Reference Porter5). Noticeably, it is a major public health concern that the incidence of breast cancer is rising among premenopausal women, with neoplasias more likely to display aggressive phenotypes and poor responses to therapy(Reference Porter5, Reference Dunn, Agurs-Collins and Browne6).

The 20-year predictions for large increases in breast cancer incidence and mortality in LMI regions(Reference Ferlay, Shin and Bray1) substantiate the urgency of the WHO's call for actions to support primary cancer prevention research and to develop effective strategies such as those that might be related to the environment, and particularly nutrition which has been reported to change along with breast cancer incidence(Reference Prentice7). A number of risk factors have been identified that could help explain breast cancer incidence in different countries and are listed in the WHO–International Agency for Research on Cancer cancer report(Reference Zeisel8). Interestingly, a majority of risk factors are linked to nutrition (for example, obesity, alcohol consumption, birth weight, height, onset of puberty and menopause). As illustrated in the next sections, epidemiological, animal and clinical studies provide insights into the role of specific nutrients as well as dietary patterns in the development of breast cancer. However, a clear understanding of the impact of foods on the development of neoplasms requires scrutinising the mechanisms of action involved and timing during the lifespan of specific dietary intakes.

Genomic impact of nutrition

The growing research field referred to as nutrigenomics summarises it all: nutrition makes an impact on the genome to such a degree that it is paramount to understand this interaction in detail to prevent health disorders and help the treatment of diseases. Nutrigenomics may well unravel how genetic variations (for example, SNP) and epigenetic alterations (i.e. modifications at the gene level unrelated to changes in DNA sequence), which both control gene expression, influence the requirements for nutrients as well as the response to nutrients(Reference Zeisel8). Such an understanding will be particularly important for several types of cancers that appear to be influenced by nutrition for their development, progression and/or recurrence(Reference Boyle and Levin9). Breast cancer is cited among these nutrition-dependent cancers mainly because of the risk brought by an overweight status in postmenopausal women and alcohol consumption. However, there is much to learn regarding the influence of foods on the mammary gland before and during breast cancer development according to a plethora of reports. Many nutrients have been described to have a potential impact on the mammary gland and its tumorigenesis in population and animal studies, but thus far there is little consensus revealed by meta-analyses(Reference Michels, Mohllajee and Roset-Bahmanyar10). Issues such as measurement error in nutritional assessment, the length of study and the timing of exposure may contribute to the discrepancy among studies that focus on nutrition and breast cancer. Another source of variation that is usually not taken into account is genomic diversity. Indeed, different forms of breast cancer can be identified through specific gene expression profiles which correspond to distinct disease outcomes and sensitivity to treatment(Reference Weigelt, Baehner and Reis-Filho11). Importantly, an emerging view is that the type or form of breast cancer is determined at the time of its onset(Reference Lelievre12), suggesting that genetic and environmental factors that play a role in tumour initiation might also influence how the disease will progress.

Epigenetic regulation

Gene expression profiles are closely controlled through epigenetic changes that can be defined as variations in the chromatin environment of a gene. These changes include the post-translational modification of histones (notably methylation and acetylation of lysines) and alterations in the degree of methylation of certain gene promoters by addition of methyl groups on the cytosines of C-phosphate-G (CpG) islands (cytosine and guanine connected by a phosphodiester bond (CpG) dinucleotide clusters)(Reference Plachot and Lelievre13). Such islands are currently defined as regions of DNA of more than 500 bp with a C+G content equal to or greater than 55 % and observed CpG/expected CpG of 0·65(Reference Takai and Jones14). DNA methylation influences the type of histone modifications that will be introduced at the gene promoter. Also, regardless of whether a promoter can be methylated it will be wrapped with histones bearing specific modifications. The type of histone modification will create epigenetic marks, and the specificity of these marks will lead to the recruitment of factors that either create a dense chromatin (for example, via the addition of heterochromatin protein, HP1) that prevents access to the DNA by the transcription machinery, hence leading to gene silencing, or favour the access to DNA by the transcription machinery notably via the displacement of histones by chromatin remodelling factors, hence leading to increased gene expression(Reference Abad, Yagci, Lelièvre and Nalwa15) (Fig. 1).

Fig. 1 Epigenetic mechanisms of gene transcription. An average of 147 bp of double-stranded DNA (black thick line) are wrapped around histone octamers to form nucleosomes. Two sets of four distinct histones (3, 4, 2B and 2A) form the octamer. The loosening of DNA is obtained by triggering of histone modifications (for example, acetylation on lysine 12 of histone 4 and trimethylation on lysine 4 of histone 3) that leads to a decrease in the tightness of interactions among histones and between histones and DNA and, thus, an open chromatin stage amenable for transcription. Other histone modifications (for example, trimethylation of histone 3 on lysine 27 or on lysine 9) are conducive to gene silencing by compacting nucleosomes tightly. In certain gene promoters a stretch of DNA of several hundred bp enriched in C-phosphate-G (CpG) islands could become methylated. This chemical modification has been considered as one of the sustainable changes leading to epigenetic inheritance through cell division and is found in a number of tumour-suppressor genes when cancer develops. Note: histone octamers are shown as blocks of eight light grey barrels, each barrel representing an individual histone. This is a simplified representation of chromatin organisation. The complex orientation of histones within the octamer and the histone 1 linker are not shown; the multiple protein complexes that are necessary to chemically modify histones and DNA (for example, with methylases, histone deacetylases) as well as those involved in histone displacement (for example, chromatin remodelling complexes) are not drawn.

Depending on the location and the type of epigenetic modifications, the impact of these alterations on the expression of a particular gene will vary, ranging from silencing to full capacity expression. The complexity of epigenetic control is illustrated by the many possibilities to modify histones. For example, epigenetic marks can be found at defined lysines (for example, methylation on K4, K9, K27, K36, K79 on histone 3 and K20 on histone 4) of histones that participate either in gene expression or in gene repression and there exist different degrees of modifications for a given mark (for example, mono-, di- or trimethylation of lysines)(Reference Hublitz, Albert and Peters16). Histone modifications are controlled by enzymes, such as methyltransferases, and protein complexes, such as polycomb complexes, for their chemical modifications. There are also proteins that sense histone modifications and further epigenetic changes at a gene promoter, like those involved in abnormal DNA hypermethylation characteristic of certain genes silenced in cancer(Reference Mohammad, Cai and McGarvey17). The possibility of combining bivalent marks (i.e. the presence on the same gene promoter of histone modifications that favour transcription and histone modifications that repress transcription) is of extreme importance in stem cell populations(Reference Mathews, Crea and Farrar18) since these cells are ‘differentiation ready’ with genes that can be rapidly expressed or repressed. Stem cells are present throughout the development of the mammary gland and suspected to be involved in breast cancer initiation.

About 70 % of the human genome contains CpG islands (a stretch of 400 to 500 CpG dinucleotides) and most of the remaining genes contain cytosines more randomly distributed that can also be methylated. While CpG island-poor genes can be silenced by DNA methylation, CpG island-rich genes can be silenced via histone modifications, without necessarily requiring these islands to be methylated, especially in normal tissues(Reference Mathews, Crea and Farrar18). Yet, in cancer, CpG island-rich genes will often display DNA hypermethylation upon tumour development(Reference Hatziapostolou and Iliopoulos19). Since DNA methylation is considered to confer sustainable modifications in the epigenome(Reference Law and Jacobsen20), it will be critical to assess how foods might differentially have an impact on this epigenetic mechanism. Finally, a disconcerting observation is that the presence of a particular type of histone modification at a gene promoter is not sufficient to indicate whether a gene is silenced or not, with the exception of methylated H3K27, which is currently associated with repression of transcription(Reference Justin, De Marco and Aasland21). More generally, it is the combination of histones present that will determine the gene expression level. This outlines the possibility of fine-tuning for the control of gene transcription, but also renders epigenetic analysis difficult to interpret with current technologies.

The plasticity of epigenetic marks permits the establishment of the memory of past events in cells. Indeed, depending on the types of histone modifications, with or without association with the methylation of a promoter region, the silencing of a gene can be either stable or transient. The epigenetic environment of a particular gene may possibly be sustained over generations of cell divisions as well as generations of an individual, hence leading to long-term epigenetic memory. Therefore, when studying the effect of nutrition on the genome, there are two aspects to take into account. First, nutrients can make an impact on gene expression directly and their effect will be dependent on genetic variability (for example, SNP) as well as the cell type and status (for example, proliferation, degree of differentiation). Second, the transcriptional response to a particular nutrient can be different from one individual to another or even from one period to another in the life of an individual, depending on the cell's memory (i.e. the epigenome). The latter can be explained by the arrangement of different epigenetic modifications that contribute to the degree of chromatin compaction at gene loci, hence modulating the organisation of the cell nucleus at any given time. Such dynamic organisation of the cell nucleus acts as a soil that might respond or not to a given microenvironmental seed (for example, a nutrient) depending on the status of epigenetic modifications(Reference Lelievre12).

To alleviate the burden of breast cancer that is affecting countries worldwide and is an urgent public health problem in many LMI countries, we must re-evaluate our approach to this disease to promote primary prevention. In light of the existing relationship triad of breast cancer–epigenome–nutrition, the first part of the present review discusses how epigenetic studies have brought new insights into the origins of breast cancer. In the second part, we analyse the current status of the knowledge of the relationship between different groups of foods and breast cancer based on epidemiological, mechanistic and intervention studies. Whenever pertinent information is available, the impact of nutrition on breast cancer development via an effect on the epigenome is emphasised. Throughout the present review, necessary steps to develop strategies to prevent breast cancer are highlighted.

Epigenetics and breast cancer

It has long been known that breast cancer development is associated with modifications in the gene transcription profile. Since the discovery of tumour suppressors and oncogenes, and as a consequence of the development of genome-wide gene transcription analyses, a plethora of genes often involved in the regulation of cellular homeostasis (from proliferation to DNA repair and survival) has been implicated in the initiation and progression of cancer. In addition, the discovery of a variety of possible post-translational modifications of histones, the building blocks of chromatin, has shed new light on the mechanisms of gene transcription control and their importance in cancer. Efforts to prevent and treat neoplasias include epigenetic modifications to remodel the gene expression profile in cancer cells, with the goal notably to re-express tumour suppressors. Some success in the manipulation of the epigenome for treatment purposes is illustrated by US Food and Drug Administration approval to use agents that prevent DNA methylation in myeloma therapy; it has been followed by approval of the use of inhibitors of histone deacetylase for certain forms of lymphomas(Reference Sharma, Kelly and Jones22, Reference Mani and Herceg23). Targeting epigenetic mechanisms for therapy was initiated following results from a large body of studies indicating that preventing chromatin compaction by hypomethylating DNA and/or by inducing histone acetylation reduced cancer progression(Reference Sharma, Kelly and Jones22). Beyond the global attack on the epigenome by such systemic therapies, epigenetic alterations offer the prospect of targeting the expression of specific genes since each gene that changes expression may show modifications in histones and possibly DNA methylation in its promoter region. As discussed in the following sections, cancer development appears to be accompanied by permanent epigenetic modifications, suggesting an involvement of mechanisms such as DNA methylation. The mammary gland is subjected to different phases of development from life in utero to menopause; therefore, an important question to answer for breast cancer is during what periods of the lifespan and by what factors epigenetic modifications are introduced which then alter the risk of developing cancers.

The concept of permanent or long-term epigenetic modifications is critical to understand as it has enormous consequences for determining the effect of modifiable factors, such as diet, on the breast tissue and the development of cancer prevention strategies. ‘Permanent epigenetic modifications’ means, for instance, that the repression of transcription of specific genes will be sustained even if the factors originally responsible for the repressive state are no longer present. However, it might be possible to change these epigenetic modifications either naturally with the appropriate signals or therapeutically, thus unlocking the repression status. As we will discuss, the fact that nutrients might be capable of inducing permanent epigenetic modifications could explain why diets and foods can have an effect on breast cancer risk that is shown many years after their consumption, and even in the offspring.

Epigenetic modifications and breast cancer initiation

In order to understand how nutrients could control breast cancer risk by influencing the epigenome, it is important to review current knowledge on the involvement of epigenetic changes in breast cancer development. There have been relatively few studies linking breast cancer risk factors and epigenetic alterations in genes involved in breast cancer. The paucity of information is linked to the fact that most studies have reported analyses done in tumour tissues and, thus, were focused on already developed cancers. There are, however, some interesting research avenues to clarify the role of epigenetic modifications in breast cancer development.

Logically, an active area of epigenetics research is to focus on tumour suppressors since these genes would have to be silenced to promote cancer development. BRCA1 is a gene involved in the onset of breast cancer and, if mutated, it increases the lifetime risk of breast cancer development by 45–85 %(Reference Struewing, Hartge and Wacholder24, Reference Ford, Easton and Stratton25). Interestingly, the breast tissue of women with BRCA1 mutations shows a different median DNA methylation index in a selected array of genes compared with non-BRCA1 mutation carriers, suggesting that a high breast cancer risk is associated with a different epigenetic pattern compared with women with an average risk(Reference Suijkerbuijk, Fackler and Sukumar26). Not surprisingly, BRCA1 has been found to be frequently hypermethylated in sporadic breast cancers(Reference Suijkerbuijk, Fackler and Sukumar26), indicating that even in the absence of mutation, epigenetic modifications linked to long-term silencing lead to shut-down of the expression of this important gene for breast cancer development. Another interesting area of investigation is the dysregulation of signalling pathways such as the complex wingless and integration site growth factor (Wnt) pathway that controls differentiation, proliferation and polarity. Negative regulators of the Wnt pathway, Wnt inhibitory factor-1 (WIF1)(Reference Ai, Tao and Zhong27) and Wnt inhibitor Dickkopf-3 (DKK3)(Reference Veeck, Bektas and Hartmann28), display a hypermethylated promoter (conducive to gene silencing) in cancer. WIF1 methylation seems to be under the control of the DNA methyltransferases DNMT1 and DNMT3β that are associated with de novo methylation, especially in ageing cells(Reference Ai, Tao and Zhong27). Other regulators of Wnt such as secreted frizzled-related protein 1 (SFRP1) and adenomatous polyposis coli (APC) have also been found to be methylated in breast cancer(Reference Klarmann, Decker and Farrar29). Thus, not only one element of a pathway, but also several up- and downstream components may be methylated on their gene promoter, ensuring the complete and sustained inactivation of that pathway.

In the breast, the status of the stroma (i.e. extracellular matrix (ECM), soluble factors and non-parenchymal cells present within the ECM) has been convincingly associated with the initiation and progression of cancers(Reference Polyak and Kalluri30). One of the current hypotheses is that fibroblasts, a major cellular compartment of the stroma involved in the making and modification of the ECM, are responsible for the modified stromal signalling that ultimately alters the epigenome of epithelial (parenchymal) cells(Reference Lin, Zuo and Chao31). Possible epigenetic modifications associated with early steps of breast tumorigenesis linked to the stroma include the hypermethylation of the TMS1 (target of methylation-induced silencing) gene promoter. TMS1 is involved in the control of ECM adhesion-dependent survival(Reference Conway, McConnell and Bowring32, Reference Parsons, Patel and Brat33). Unfortunately, examples of stroma-dependent changes in the epigenome of breast epithelial cells remain scarce. This field of research needs to be further developed in light of the influence that nutrients may have on the stroma by altering its exposure to hormones, promoting adiposity and triggering or reducing inflammatory pathways conducive to breast cancer development(Reference Bray34).

Micro RNA (miRNA), the newly discovered class of RNA that control mRNA translation into proteins, have now been associated with breast cancer development. Not surprisingly, the promoters of genes coding for miRNA mir-9-1, mir-124a3, mir-148, mir-152, and mir-663 were found to be hypermethylated, in parallel to the hypermethylation of promoters of tumour suppressor genes, in primary breast cancers(Reference Lehmann, Hasemeier and Christgen35). Thus, although miRNA are not part of epigenetic mechanisms of gene transcription (because they act downstream of chromatin), there is a strong epigenetic control of their expression upon cancer development that reinforces the direct epigenetic control observed for genes critical to prevent breast cancer development. The recent evidence that foods have an impact on miRNA expression(Reference Chen and Xu36) expands the possibilities for nutrition to influence breast cancer risk via epigenetic effects.

If the transcription of key genes needs to change in order for a tumour to develop, it is important to identify the types of local epigenetic modifications involved. It is also important to know whether an epigenetic alteration is temporary or permanent for a given gene based on epigenetic marks, so that proper intervention strategies are designed. Ultimately, it should be possible to harness pathways critical for breast cancer prevention by linking the knowledge related to specific epigenetic alterations associated with breast tumour initiation and the identification of foods that have an impact on the breast tissue before the onset of tumour development.

Effect of diet on epigenetic imprinting

The possibility for epigenetic modifications to be passed through cell division and maintain the same expression level for specific genes can be referred to as imprinting. When epigenetic modifications occur in a parent and affect germ cells, they can be passed on to the next generation and propagated through cell division in the embryo. This particular phenomenon is known as ‘genomic imprinting’ and might be an explanation for why certain families display a high risk of developing cancer although no breast cancer susceptibility gene mutation has been identified. Also, if epigenetic modifications occur early in an individual's life and in a particular organ, it can affect a portion of the organ in which cells continue to divide, creating a specific field with high risk of developing breast cancer (for example, an entire ductal system or lobe within the breast). In addition, there is no reason why external factors could not also modify the epigenome of non-dividing cells in a particular organ, hence altering future responses of these cells to external signalling factors. The difference compared with the previous two scenarios is that epigenetic modifications in non-dividing cells should not be transmissible to other cells; hence, there would be long-lasting epigenetic memory in these cells but no transmission of epigenetic marks to the next generation of these cells. Therefore, regardless of the stage of the mammary gland, necessary environmental factors such as foods are likely to exert profound epigenetic effects, with propagation of sustained epigenetic modifications likely when they occur during the three major development phases (fetal development, puberty, pregnancy) (Fig. 2). In the paragraphs below we give examples of how dietary intakes could differentially make an impact on cancer development depending on when during the lifespan a particular diet is followed.

Fig. 2 Possible impact of epigenetic modifications upon dietary influence during the lifespan of the mammary gland. There is still much to be understood regarding human breast development and a lot of information is extrapolated from studies in rodents. The human mammary gland evolves constantly with the formation, on average, of twelve individual ductal systems or lobes with limited branching of ducts with blunt-ended ductal termini during fetal development. Considerable secondary branching and elongation of the ductal systems and formation of terminal ductal lobular units (TDLU) occur upon hormonal stimulation during puberty, and lobes further branch out to develop into lactating tissue followed by involution of part of the glandular tissue during pregnancy/lactation cycles. All the phases of development will encompass TDLU (these structures are present in the majority starting at puberty and until menopause), thus affecting areas of the breast where cancers develop. Therefore, epigenetic alterations occurring at different periods during the lifespan of an individual might affect the mammary gland to various extents based on the possibility to propagate permanent/long-term epigenetic marks through cell division (see grey arrows). The period between birth and puberty is not accompanied by extensive breast development; instead, it is proposed to comprise an involution phase shortly after birth and slow growth that accompanies the body's growth afterwards; this period is represented by the dashed line on the drawing (periods of times between life events are not represented to scale). Menopause is characterised by a reduction in the number of TDLU and ducts(Reference Deeb, Luo and Karpf280).

Fetal programming, a period during which the methylation of genes will be modified by the parental profiles or exposure in utero, is a high-risk stage for abnormal derepression of imprinted genes. Indeed, following fertilisation the parental genomes undergo demethylation before de novo methylation. This period has been described as placing an individual at ‘increased risk of developing diseases as a result of intra-uterine constraint’(Reference Burdge, Slater-Jefferies and Torrens37). If proper methylation did not occur during embryogenesis, certain genes might become expressed and lead to enhanced risk of cancer development, such as when the gene for the stimulation of proliferation of insulin-like growth factor (IGF)-2 becomes demethylated. Food components that make an impact on IGF-2 notably include soya isoflavones as described later in the present review.

A clear correlation between early impact of diet and cancer development has been obtained with animal models. Rats receiving higher levels of the micronutrient choline in utero compared with controls showed reduced tumour growth and longer survival. The effects on the genome included higher expression of genes associated with favourable prognosis for breast cancer and decreased expression of certain genes associated with unfavourable prognosis compared with the control group (i.e. with deficient choline supplementation during gestation)(Reference Kovacheva, Davison and Mellott38).

The risk of developing diseases can continue for generations, such as in families with high incidence of breast cancer without a known breast cancer susceptibility gene mutation. On the other hand, the effect of exposure to certain risk factors for breast cancer later in life might be transient and disappear upon removal of the risk factor and mainly depend on the continuous presence of the implicated factors(Reference Collins, Blake and Crosignani39). Examples of this include hormone replacement therapy, although the effects are still debated and may also be protective(Reference Howell and Evans40), and hormonal contraception. Although several explanations exist for the duration of the ‘risk factor effect’ after the agent inducing the risk is gone, one possibility that we introduced earlier may be the existence of ‘permanent’ (or long-term) and temporary modifications in the epigenome. Indeed, it is currently accepted that epigenetic alterations that involve DNA methylation can be sustained(Reference Holmquist and Ashley41). Therefore dietary risk and protective factors that specifically make an impact on DNA methylation might be more readily associated with long-term effects.

The increasingly recognised impact of foods on the epigenome warrants exploration of whether diets or specific dietary components can contribute to epigenetic modifications associated with breast cancer development. Components of foods, including dietary fats and amino acids, have been reported to have an effect on mammary gland development(Reference Warri, Saarinen and Makela42Reference Maclennan and Ma44). Even though the impact of nutrition on epigenetics in the breast tissue remains largely unexplored(Reference Choi and Friso45), preliminary work reveals that nutrients associated with variations in breast cancer risk can indeed have an effect on the epigenome.

Diet and breast cancer

The large body of literature on nutrition and breast cancer has been recently reviewed and summarised by an international panel gathered by the World Cancer Research Fund (WCRF)(46). In reviewing the literature, it is important to consider a number of issues related to study design, model systems and interpretation of studies. These issues, along with scarce information on the interaction of the epigenome with the response to nutrients, lead to difficulty in understanding the impact of nutrients on breast cancer risk. First, the results of epidemiological studies need to be interpreted with caution, as they do not determine cause and effect. The size of the study, the lack of diversity in dietary habits analysed in each study, the measurement error in outcome variables, and individual variation in human genetics and lifestyle factors may limit the ability to measure the probably very small size effects due to diet. Human models used in epidemiological studies have the caveat that most cancers develop over a relatively long period of time and, thus, interventions related to primary prevention, i.e. to inhibit the development of abnormal tissue growth, cannot be determined in epidemiological studies or clinical trials as the length is not sufficient or the relevant window of exposure is not captured in the intervention trial to assess true prevention. Another important issue is the level of nutrients compared in studies pertaining to breast cancer risk. If this level is in the severely deficient range it might have multiple effects on the organism and breast cancer development might be a secondary consequence of the deficiency.

Advantages and limitations of study designs

Clinical trials investigating the impact of diet on breast cancer prevention are limited. There are a number of issues contributing to such paucity. As explained previously, studying cancer prevention requires lengthy trial periods as breast cancer generally takes years to develop and is influenced by critical periods in breast epithelial tissue growth, i.e. fetal development, adolescence and pregnancy. It has been suggested that the diet during adolescence is an important predisposing factor for breast cancer risk later in life(Reference Newmark47, Reference Colditz and Frazier48). Thus, nutritional exposures during pregnancy(Reference de Assis, Wang and Goel49) as well as during fetal development and adolescence alter breast cancer risk(Reference de Assis, Cruz and Warri50). The comparison of risks across a broad range of dietary patterns as well as specific periods of life has not been thoroughly studied. In addition, a large number of participants is required to achieve a reasonable amount of cases for statistical analysis in randomised trials of undiagnosed subjects. Also, previous studies demonstrate that the selection of ‘at-risk’ populations does not represent cancer prevention because this population may be more likely to have already developed cancer(Reference Tuma51). The effects of diets may also vary based on race, menopausal status, tumour characterisation (oestrogen receptor (ER)-positive (ER+) or ER-negative (ER–)) and weight or BMI, and these factors are not always considered in the analysis or the interpretation of the results. Finally, it is difficult to maintain compliance to dietary regimens for long periods of time. Therefore it will be critical to identify biomarkers for very early signs of breast cancer development that can be utilised to rapidly determine the impact of environmental factors on breast cancer risk and the success of actions proposed to reduce breast cancer incidence.

Animal models offer advantages because of genetic similarities and better control of environmental influences, including diet. However, animal models used to study cancer prevention often lack relevance to human breast cancer development. Rodent models provide opportunities for genetic manipulation that bring important information about the molecular mechanisms that underlie cancer progression and environmental interventions. Unfortunately, results are not consistently reproducible in human trials. Cell-based studies also contribute significantly to our understanding of the molecular mechanisms of dietary components to alter specific cellular processes essential to breast tumour development. However, the breast epithelial cell models most commonly used are cancer cells and, thus, they do not mimic stages of human breast cancer initiation. Even if some cell lines represent early stages in the development of breast cancer, rarely are they utilised in a physiologically relevant manner since most studies use traditional cell monolayer cultures that lack tissue morphogenesis and, thus, do not reproduce the three-dimensional tissue architecture known to direct the expression of genes involved in normal differentiation(Reference Adissu, Asem and Lelievre52).

However, the use of animal and cell models is critical to the overall determination of the impact of diet on breast cancer progression because these models contribute to determining mechanisms. Animal studies provide information that could not be obtained with human populations, particularly because it is difficult to assess diet in epidemiological studies and to achieve and maintain prescribed diets in intervention studies, and because the impact of diet may be specific to early exposure (prenatal to adolescence) which requires extended intervention periods. In rodent models cancer is generally experimentally induced (usually by means of a chemical carcinogen or irradiation), leading to the generation of tumours in all the animals in a relatively short period of time, thereby reducing the number of animals and time, i.e. cost required. However, there are no adequate models of cancer prevention that are easily translatable to humans and results must be considered with caution. Similarly, in vitro cell model systems often used to decipher the mechanisms of action of nutrients lack the physiological relevance to breast cancer development. Nevertheless, both animal and cell models, in spite of their limitations, can bring important insights into the role played by foods in breast cancer development.

Therefore, it is important to consider the cumulative results from each of these imperfect model systems to garner sufficient information in reviewing and establishing firm conclusions on how foods might make an impact on the breast. To simplify the review of the literature presented in the next paragraphs, whenever applicable, the results from the different models are subdivided into specific diet/foods categories. Within these categories the role of diet in modifying breast cancer risk and the proposed underlying mechanisms and potential roles of the interaction of diet and the epigenome are discussed.

Obesity

Epidemiological studies

There is substantial support for obesity increasing the risk of a variety of cancers, including breast cancer. The WCRF review panel concluded that weight is one of the few factors that convincingly leads to an increase in breast cancer risk in postmenopausal women(46). Measures of weight are generally BMI (kg/m2), waist and hip circumferences, or waist:hip ratio. These assessments are not only indirect measures of increased adiposity, but they also provide information about body fat distribution. An analysis of cohort studies suggests that in postmenopausal women, the smallest waist circumference lowers breast cancer risk compared with the largest waist circumference and that there is a 24 % lower risk in women with the smallest waist:hip ratio(Reference Harvie, Hooper and Howell53). However, further evidence suggests that the impact of obesity may be modified by race, as the relationship between BMI and breast cancer risk was noted in white but not African-American postmenopausal women(Reference Berstad, Coates and Bernstein54).

In contrast to the increased risk of breast cancer with obesity in postmenopausal women are reports that increased weight may protect premenopausal women from breast cancer. For example, the higher the BMI at 18 years of age, the lower the risk in premenopausal women in the overweight to obese category (BMI ≥  25 kg/m2) compared with a low BMI ( <  20 kg/m2) (OR 0·76; 95 % CI 0·63, 0·90)(Reference Berstad, Coates and Bernstein54). Moreover, a BMI of ≥  35 kg/m2 (morbidly obese) compared with normal to low weight BMI of < 25 kg/m2 is accompanied by a reduced breast cancer risk (OR 0·81; 95 % CI 0·61, 1·06) in premenopausal women. Neither of these associations with breast cancer risk is modified by race(Reference Burdge, Slater-Jefferies and Torrens37). Thus, obesity makes an impact on the risk of breast cancer positively and negatively, depending on the menopausal status (or age).

The association between obesity and breast cancer risk may be, at least in part, dependent on tumour type. For example, waist and hip circumferences and waist:hip ratio were significantly associated with a 1·95– to 2·75-fold increased risk only for ER– breast cancer development in the Nurses' Health Study II (n 45 799)(Reference Harris, Willett and Terry55). Also, high ( ≥ 35 kg/m2) BMI was associated with increased risk of ER– and progesterone receptor (PR)-positive (PR+) tumours among postmenopausal African-American women compared with normal to low BMI ( <  25 kg/m2), with an OR of 1·83 (95 % CI 1·08, 3·09)(Reference Berstad, Coates and Bernstein54).

Intervention studies to determine the impact of increasing weight on breast cancer are not feasible, but the impact of reducing or gaining weight has been explored. Increasing weight loss in women who reached their highest adult weight at younger ages ( <  45 years), but not older ages, was associated with a reduced risk of postmenopausal breast cancer (OR 0·9; 95 % CI 0·84, 0·95 per 5 kg)(Reference Trentham-Dietz, Newcomb and Egan56). Further, reducing adiposity appeared to reduce the risk for breast cancer(Reference Harvie, Howell and Vierkant57, Reference Eliassen, Colditz and Rosner58). When weight gain was calculated from the lowest adult weight, greater weight gain modestly increased risk by 8 % for each 5 kg of gain (OR 1·08; 95 % CI 1·06, 1·11). Thus, epidemiological studies support that modification of weight can alter breast cancer risk.

Epidemiological studies also provided evidence that adiposity during pregnancy influences adiposity in the offspring, which might have consequences for breast cancer risk in the next generation(Reference Gluckman and Hanson59). For example, the strongest predictor of being in the upper tertile of weight and percentage body fat in children (8·8 (sd 1·8) years) followed prospectively from birth was a maternal BMI of >30 kg/m2 (OR 3·75 (95 % CI 1·39, 10·10) and OR 5·45 (95 % CI 1·62, 18·41), respectively)(Reference Catalano, Farrell and Thomas60). In a cross-sectional study, the BMI of children (5–7 years, n 3306) correlated with parental BMI, with the strongest association with maternal BMI (OR 2·9 for boys, 3·2 for girls)(Reference Danielzik, Langnase and Mast61). These results suggest that either maternal BMI during pregnancy may have a long-term impact on children's weight gain, or that environmental influences when parents have a high BMI may affect the BMI of their offspring. In addition, a recent pooled analysis including approximately 22 000 breast cancer cases shows that birth weight was positively associated with breast cancer risk in studies based on birth records (pooled relative risk (RR) per 1 sd (0·5 kg) increment in birth weight: 1·06; 95 % CI 1·02, 1·09) and parental recall when the participants were children (1·02; 95 % CI 0·99, 1·05). However, studies based on adult self-reports or maternal recall during the women's adulthood (0·98; 95 % CI 0·95, 1·01) did not report significant effects (P for heterogeneity between data sources 0·003)(Reference Silva, De Stavola and McCormack62). Birth length and head circumference from birth records were also positively associated with breast cancer risk (pooled RR per 1 sd increment: 1·06 (95 % CI 1·03, 1·10) and 1·09 (95 % CI 1·03, 1·15), respectively). These data emphasise the importance of recording birth weight and other birth anthropometric measures in a standardised manner to avoid misclassification related to recall.

The influence of maternal intake on adiposity in the offspring has also been investigated by studying the weight and BMI of monozygotic and dizygotic twins. Some of these studies suggested that height (which is a risk factor for breast cancer) and weight, but not BMI are influenced by the intra-uterine environment(Reference Allison, Paultre and Heymsfield63), although birth weight predicted higher BMI in other twin studies(Reference Loos, Beunen and Fagard64, Reference Loos, Beunen and Fagard65). Therefore, the epidemiological evidence to support a relationship between maternal BMI during pregnancy and the risk for obesity in the offspring, which confers a risk for breast cancer later in life, is suggestive but not definitive.

In summary, observational population studies suggest that breast cancer risk is increased in postmenopausal women with high BMI, waist circumference and waist:hip ratio. However, higher BMI may confer protection against breast cancer in premenopausal women. The distribution of the adiposity (central v. overall) may also influence the risk in addition to menopausal status and race. Finally, evidence supports that there may be a relationship between maternal BMI and offspring, but further evidence is required to clarify these relationships. Most interestingly, the fact that weight gain might be associated with a specific type of breast tumour suggests a link with determinants of breast cancer types, such as gene expression profile, which emphasises the need to study the relationship between obesity and epigenetics.

Animal models

It is particularly important to use animal models for nutrients or other lifestyle factors, such as obesity, that will not be tested for their impact in human trials because they lead to increased risk for diseases. It is now recognised that adipose tissue is not only a storage entity for excess energy in the form of TAG, but also functions as a source of hormones that could affect breast tissue homeostasis. Examples are found in the serum levels of the adipose tissue hormones leptin and adiponectin, which are positively and negatively, respectively, correlated with adiposity. These hormones are being explored as potential mediators or protectors of the development of breast cancer. In addition, obesity induces a state of chronic inflammation and greater adiposity is associated with insulin resistance and diabetes, which may play roles in the well-characterised relationship between obesity and increased risk of several cancers, including breast cancer. Importantly, dietary energy restriction protects against the development of mammary tumours in mice, regardless of the energy nutrient limited in the study(Reference Dirx, Zeegers and Dagnelie66). Determining if there is a relationship between obesity and breast cancer risk is complicated, as obesity is associated with high-fat diets, and models of obesity have often employed high-fat diets to increase energy density and induce greater adiposity, complicating the interpretation of experimental results. Therefore, studies related to obesity are confounded by the interaction of obesity with high-fat diets and health consequences, such as diabetes, which makes it difficult to decipher the role, and related specific mechanisms, of obesity in the development of breast cancer.

Mechanisms

The mechanisms, explored thus far, by which obesity may increase breast cancer risk are diverse(Reference Lorincz and Sukumar67, Reference Calle and Kaaks68). Adiponectin, which is inversely related to fat mass, inhibits cell proliferation and suppresses angiogenesis(Reference Barb, Williams and Neuwirth69Reference Mantzoros, Petridou and Dessypris71) and inflammation(Reference Ouchi, Parker and Lugus72, Reference Ouchi and Walsh73). Adiponectin levels are lower in the presence of breast cancer compared with controls in both pre- and postmenopausal women. Furthermore, tumours of women in the lowest tertile of serum adiponectin are larger and of higher grade compared with tumours of women in the other tertiles(Reference Miyoshi, Funahashi and Kihara74). In contrast, leptin, the serum levels of which are positively related to fat mass, may promote breast cancer progression(Reference Schaffler, Scholmerich and Buechler70). The ratio of serum levels of leptin to adiponectin may also be important(Reference Cleary, Ray and Rogozina75Reference Grossmann, Nkhata and Mizuno77). Other adipokines such as vascular endothelial growth factor, hepatocyte growth factor and heparin-binding epidermal growth factor-like growth factor also promote angiogenesis(Reference Vona-Davis and Rose78) and, hence, could participate in breast cancer development.

Other well-studied mechanisms that might be associated with breast cancer development include factors involved in insulin resistance and diabetes, which are consequences of increased adiposity. Insulin promotes cell proliferation and increased uptake of energy substrates for cell proliferation. Consequently, high serum insulin levels that occur in insulin resistance and type 2 diabetes are suggested to play a role in the development of breast cancer. Indeed, a two-fold increase in breast cancer risk was noted in the highest tertile of serum baseline insulin levels compared with the lowest tertile in postmenopausal women(Reference Kabat, Kim and Caan79). Furthermore, studies in animals showed that the insulin receptor and IGF receptor played a role in mammary carcinogenesis in a non-obese model of type 2 diabetes(Reference Novosyadlyy, Lann and Vijayakumar80). Insulin sensitivity may also be controlled by the adipokines(Reference Rabe, Lehrke and Parhofer81), further confounding the relationships between insulin and obesity. Inflammatory mediators, such as TNFα associated with high adiposity(Reference Subbaramaiah, Howe and Bhardwaj82), may also play a role in promoting tumour development(Reference Lorincz and Sukumar67). Therefore, both animal models and strong mechanistic-based studies support that adipokines, insulin and inflammatory mediators may underlie the relationship between obesity and breast cancer(Reference Lorincz and Sukumar67) although the specific mediator(s) are not yet clearly defined.

It is particularly important to note that some of these mediators might also be involved in the impact that maternal obesity may have on the offspring to increase their propensity of not only being overweight but also of developing mammary tumours. The well-known consequences of obesity proposed to increase the risk of breast cancer in adults may also alter the risk of the offspring for obesity(Reference Heerwagen, Miller and Barbour83). For example, offspring of female mice fed an obesogenic diet (40 % energy safflower-seed oil) during pregnancy had an increased mammary tumour incidence following chemical induction(Reference Lo, Hsieh and Chen84). Maternal overnutrition led to increased adipogenic, lipogenic and adipokine gene expression in fetal adipose tissue(Reference Heerwagen, Miller and Barbour83) and maternal high-fat diet during pregnancy and lactation altered hepatic expression of IGF-2 and key microRNA in the adult offspring(Reference Zhang, Zhang and Didelot85). Conversely, undernutrition during pregnancy was associated with increased risk for obesity and hyperphagia in the offspring(Reference Vickers, Breier and Cutfield86), which may confer increased risk for breast cancer. Several studies have shown that if the fetus were exposed to maternal diabetes, a frequent consequence of obesity, there would be increased obesity in the offspring(Reference Velie, Schairer and Flood87).

Epigenetics

There is a critical need for research in epigenetics related to obesity and breast cancer development. A compelling study demonstrated an effect of dietary methyl supplementation, which is used in methylation pathways, during the fetal period in preventing the development of obesity through generations of agouti mice(Reference Waterland, Travisano and Tahiliani88). Unfortunately, mammary tumour development was not assessed in this study. Another study using male Wistar rats showed that a high-fat diet was capable of methylating CpG sites at the leptin promoter and was associated with a reduction of the level of circulating leptin in rats that became obese(Reference Milagro, Campion and Garcia-Diaz89).

It has been emphasised by others that it will be particularly important to focus on life in utero in light of the relationship of fetal growth with obesity and breast cancer(Reference Thornburg, Shannon and Thuillier90). Notably, the review of studies on birth weight and breast cancer risk by Michels & Xue(Reference Michels and Xue91) pointed to the loss of imprinting of IGF-2 and high expression level of this stimulator of breast epithelial cell proliferation in women with high birth weight. However, the mechanism by which IGF-2 expression is epigenetically altered remains to be deciphered.

In conclusion, there is substantial evidence in animal and human models to support an impact of obesity on breast cancer. Clearly, dietary patterns such as macronutrient intake including alcohol, high-fat diet and carbohydrates, insulin sensitivity as well as micronutrients influence the development and maintenance of an obese status. Thus, the bearing of obesity on breast cancer risk may be due to the obese state and/or the dietary effect on obesity. There are multiple potential mechanisms that may mediate breast cancer risk associated with obesity and determining which mechanism is predominant will be a challenge. An important aspect to investigate is the potential epigenetic component of the risk brought by obesity, suggested by the impact of maternal exposures on the risk for the offspring to develop breast cancer.

Relationship of dietary patterns: healthy or Western?

A body of literature has focused on determining the relationship between dietary patterns and breast cancer development. Dietary patterns are comprised of a variety of dietary components that are prevalent in specific diets. Dietary components may function individually or in combination within the food matrix, hence increasing their impact. Generally, the dietary patterns investigated are a prudent or healthy dietary pattern (high in vegetables and/or fruits, poultry, fish, low-fat dairy products and/or whole grains) as compared with the Western diet or so-called unhealthy diet (red or processed meats, refined grains, sweets and/or high-fat dairy products). The results of epidemiological studies are inconsistent, with a variety of reports supporting that dietary patterns with fruit and vegetable intake(Reference Velie, Schairer and Flood87, Reference Malin, Qi and Shu92, Reference Bessaoud, Daures and Gerber93) or high-fibre–low-fat intake(Reference Mattisson, Wirfalt and Johansson94) are inversely associated with breast cancer risk when comparing lowest to highest intake while other reports find no association(Reference Agurs-Collins, Rosenberg and Makambi95Reference Adebamowo, Hu and Cho98).

Epidemiological studies

In a review of the literature by the WCRF, the evidence was not convincing that a healthy diet conferred protection from breast cancer(46). Consistent with this review, results of the large European Prospective Investigation into Cancer and Nutrition (EPIC) study (n > 360 000 women) demonstrated no relationship between breast cancer incidence and fruits and vegetable intake(Reference Gonzalez and Riboli99, Reference van Gils, Peeters and Bueno-de-Mesquita100). Contrasting results for a prudent/healthy diet were shown in a subsequent meta-analysis completed with strict inclusion criteria. From the sixteen studies used, it was concluded that a prudent/healthy dietary pattern conferred a reduced risk of breast cancer in the highest intake compared with the lowest intake categories, with an OR of 0·89 (95 % CI 0·82, 0·99; P = 0·02), whereas a similar comparison of high and low categories in the Western/unhealthy dietary intake groups showed no difference(Reference Brennan, Cantwell and Cardwell101). Still, a pooled analysis from eight prospective studies found no significant association either between vegetable intake and breast cancer or between fruit and breast cancer(Reference Smith-Warner, Spiegelman and Yaun102). In some cases, specific components of fruit and vegetable intake, such as dark yellow-orange vegetables (comparing lowest and highest quintile of intake; OR 0·79; 95 % CI 0·60, 0·98), dark green vegetables (comparing lowest and highest quintile of intake; OR 0·65; 95 % CI 0·51, 0·83)(Reference Malin, Qi and Shu92) and raw vegetables (comparing ≥  67·4 g/d with <  67·4 g/d; OR 0·63; 95 % CI 0·43, 0·93)(Reference Bessaoud, Daures and Gerber93) were associated with reduced risk of breast cancer.

Reasons for the discrepancy between study results may be found in other lifestyle factors that will influence breast cancer risk or interact with the dietary pattern. For example, in one study, lower risk was associated with a healthy dietary pattern with BMI less than 25 kg/m2Reference Sieri, Krogh and Pala103), but there was no association when BMI was ≥  25 kg/m2. Moreover, diet–breast cancer risk associations may be influenced by energy intake(Reference Cottet, Touvier and Fournier104), and age and menopausal status(Reference Gonzalez and Riboli99, Reference van Gils, Peeters and Bueno-de-Mesquita100). Interestingly, other examples suggest that an association between breast cancer risk and healthy/prudent diet may depend on the tumour type, such as ER and PR positive or negative tumours(Reference Lissowska, Gaudet and Brinton105). For example, a fruit and vegetable intake is associated with an increased risk of developing ER+tumours, but a decreased risk of developing ER–tumours(Reference Olsen, Tjonneland and Thomsen106, Reference Fung, Hu and McCullough107). Furthermore, the effect of a healthy diet to decrease breast cancer risk is strengthened with ER+/PR– tumours(Reference Cottet, Touvier and Fournier104). Results of studies with a Western diet are also inconsistent, with reported positive association(Reference Edefonti, Decarli and La Vecchia108, Reference de Stefani, Deneo-Pellegrini and Boffetta109), negative association(Reference Cui, Dai and Tseng110, Reference Murtaugh, Sweeney and Giuliano111) or no association with breast cancer risk(Reference Agurs-Collins, Rosenberg and Makambi95, Reference Terry, Suzuki and Hu97, Reference Adebamowo, Hu and Cho98, Reference Sieri, Krogh and Pala103). Similar to ‘healthy diets’, the unhealthy dietary pattern associations with breast cancer risk may be dependent on other factors, such as menopausal status(Reference Cui, Dai and Tseng110), BMI(Reference Hirose, Matsuo and Iwata112) and tumour types(Reference Velie, Schairer and Flood87, Reference Larsson, Bergkvist and Wolk113).

The divergence in results described here is potentially due to differences in the definition of the dietary patterns, the absence of careful control over confounding factors and the small number of cases after stratification by specific breast cancer characteristics. Moreover, as discussed in the present review, it may also be related to the epigenetic characteristics of the populations studied.

Animal models

Generally, animal studies indicate that diets rich in fruits and vegetables, including cruciferous vegetables, protect against mammary tumour development(Reference Steinmetz and Potter114). Because of the complexity of the nutrients and non-nutritional components in the diet, several underlying mechanisms have been suggested to prevent mammary tumours including antioxidant capability, protection against DNA damage, detoxification of carcinogens, and inhibition of specific cellular pathways that control proliferation, apoptosis and angiogenesis. Animal studies are strengthened by cell culture-based studies showing that specific components of these diets, such as isothiocyanates, which are capable of inhibiting histone deacetylase and thus could have an epigenetic effect(Reference Batra, Sahu and Kandala115), and indoles found in cruciferous vegetables, can limit cellular pathways characteristic of tumour progression. The discrepancy between animal studies showing a positive impact of diets rich in fruits and vegetables to inhibit mammary tumours, and the epidemiological studies showing mixed results, is potentially based on the limitations discussed above for population studies (i.e. the ability to measure dietary intake, the interaction with other lifestyle factors, the genetic and epigenetic make-up (or status), and the timing of exposure).

Intervention trials

The Women's Health Initiative is a randomised dietary intervention study in which postmenopausal women were counselled to reduce dietary fat intake and increase consumption of fruits and vegetables (n 48 835), with an average 8·1-year follow-up period(Reference Prentice, Caan and Chlebowski116). Overall, there was a small (9 %), non-significant reduced risk for invasive breast cancer in the intervention group compared with the control group(Reference Prentice, Caan and Chlebowski116). The intervention reduced the incidence of invasive breast cancer only in women with a high fat intake at baseline and the risk was significantly reduced only for PR– tumours and independent of ER status. In a randomised controlled multi-site (thirty-nine centres) intervention trial (n 2437) in women following early-stage breast cancer, lower fat intake (and thus energy intake) was accompanied with a 24 % reduction in recurrence risk, with an even greater impact on women with ER– cancer (42 % lower risk). Another randomised control trial to reduce fat intake and increase carbohydrate intake in which women were followed for 10 years had no effect of fat intake, but there was an increased risk of ER+ breast cancer with lower carbohydrate intake(Reference Martin, Li and Melnichouk117). However, the limitations of these trials in terms of a true link to dietary fats include maintenance of compliance to the intervention, inability to decipher confounding factors such as obesity and energy intake and the time or period of exposure. Indeed, regarding the latter, the intervention may be far later than when diet may be most effective in protecting the breast, such as during fetal development and adolescence. It is also important to note that this particular trial was focused on breast cancer recurrence, which might not be comparable with intervention studies on women who have never had breast cancer as the breast tissue will have undergone treatments and possible tumour field effects (i.e. modifications in normal tissues induced by paracrine and other microenvironmental effects from an adjacent cancer).

Epigenetic studies

There are few studies in this area and the ones that exist focus either on the impact of specific dietary patterns on epigenetic marks globally or on very specific organs excluding the breast. A study relating a vegetarian lifestyle and DNA methylation did not reveal any significant association(Reference Geisel, Schorr and Bodis118). In contrast, preliminary reports from animal studies indicated an effect of prenatal protein-restricted diet on the methylation of specific CpG dinucleotides in the PPARα gene promoter in the liver(Reference Lillycrop, Phillips and Torrens119). Studies such as this reveal the profound impact that maternal diet has on epigenetic make-up in the offspring and sets the course for susceptibility to certain diseases(Reference Mathers and McKay120).

Soya intake

Epidemiological studies

Overall, there is a significant record of research studies on the impact of soya intake on breast cancer. Generally, epidemiological studies suggest that higher soya isoflavone intakes are associated with lower breast cancer risk, though not all are supportive(Reference Wu, Yu and Tseng121Reference Wu, Ziegler and Nomura123). For example, in Asian populations where soya consumption is high, the incidence of breast cancer was found to be lower than in other cultures with low soya intake levels(Reference Henderson and Bernstein124). Daughters of Asian women who immigrated to countries with Western cultures have had a higher risk of developing breast cancer than either their mothers or their grandmothers(Reference Ziegler, Hoover and Pike125). A meta-analysis that included eighteen studies suggested that soya intake was inversely associated with breast cancer risk in women from the West, particularly in premenopausal women, but not in women from Asia(Reference Trock, Hilakivi-Clarke and Clarke126). However, the results of another meta-analysis supported that women from the West (with low soya intake ranging from 0·8 to 0·15 mg soya isoflavone per d) were not protected by greater soya intake; however, Asian women, including both Asian and Asian-American women, had a reduced breast cancer risk if they increased soya intake (comparing the lowest level of soya intake ≤  5 mg/d, OR 0·71, 95 % CI 0·60, 0·85 and intake ≥  20 mg isoflavone/d)(Reference Wu, Yu and Tseng121). Therefore, the results of the epidemiological studies investigating the relationship between soya intake and breast cancer risk remain controversial.

Interestingly, a number of studies have investigated the relationship between soya intake during childhood and adolescence and the risk of breast cancer development later in life. In a case–control study by Korde et al. (Reference Korde, Wu and Fears127) employing 966 controls and 597 cases selected among Asian-American women, childhood, adolescent and adult intakes were associated with a significantly reduced breast cancer risk among women who consumed the highest level of soya, with intakes during childhood showing the strongest and most consistent relationship with breast cancer risk (OR 0·40; 95 % CI 0·18, 0·83). These results are similar to other case–control studies which provide further evidence to support the importance of soya intake during adolescence as they showed that adolescent soya intake was inversely associated with breast cancer risk(Reference Thanos, Cotterchio and Boucher128) in both pre- and postmenopausal women(Reference Shu, Jin and Dai129). A recent meta-analysis including fourteen studies revealed that soya isoflavone intake was associated with a significant reduction of breast cancer risk in Asian populations (OR 0·76; 95 % CI 0·65, 0·86) but not in Western populations (OR 0·76; 95 % CI 0·87, 1·06)(Reference Dong and Qin130). Thus, the results of epidemiological studies relating soya intake to breast cancer risk are not clear, and the impact may depend on genetics/epigenetics, prior soya intake, timing of exposure and level of soya intake.

Animal and cell models

A variety of studies in animal models with chemically induced cancer showed that soya proteins reduced mammary tumour incidence(Reference Lamartiniere, Moore and Brown131Reference Lamartiniere, Wang and Smith-Johnson139). The active component proposed to mediate the effect on breast cancer is genistein, a metabolic product of soya, which is structurally very similar to oestradiol and activates α- and β-ER. Genistein is shown to prevent mammary tumours in animal models(Reference Lamartiniere, Moore and Brown131Reference Constantinou, Lantvit and Hawthorne136, Reference Lamartiniere, Wang and Smith-Johnson139), including xenograft models(Reference Hsieh, Santell and Haslam140), although results are contradictory(Reference Cohen, Zhao and Pittman141). Soya protein intake does not alter characteristics of mammary epithelial tissue that are associated with breast cancer risk, including proliferation, epithelial area and apoptosis, in premenopausal female monkeys(Reference Wood, Kaplan and Stute142). Similar to epidemiological studies, results with animal studies support that soya and genistein may reduce tumour progression in premenopausal mouse models(Reference Parsons, Patel and Brat33, Reference Bray34). However, soya and genistein promote tumorigenesis in postmenopausal rodent models(Reference Lehmann, Hasemeier and Christgen35, Reference Chen and Xu36). These observations suggest a link between oestrogen pathways and the effect of soya. An added level of potential variability for the effect of soya is shown by the fact that chemoprevention by genistein in carcinogen-induced mammary cancer in rats is dependent on the diet matrix(Reference Kim, Hall and Smith143).

A number of mechanisms have been proposed to explain the action of genistein on tumorigenicity. As mentioned above, one of the more studied mechanisms is through oestrogen-dependent pathways, as there is substantial evidence that genistein has oestrogenic activity. However, other mechanisms may play a role, as soya intake in adulthood does not influence oestrogenic effects in non-human primates(Reference Wood, Kaplan and Stute142). Other possible mechanisms of the impact of genistein on breast tumorigenesis include inhibition of epidermal growth factor receptor tyrosine kinase activity and of topoisomerase II activity, antioxidant properties, regulation of eicosanoid metabolism, and cell-specific effects such as cell cycle progression arrest, induction of apoptosis, and inhibition of angiogenesis(Reference Stedman, Nickel and Castillo144Reference Pavese, Farmer and Bergan146).

Clinical trials

There are a number of randomised clinical intervention trials for soya or isoflavones in which mammographic density was used as a marker for breast cancer risk. A meta-analysis of eight randomised controlled isoflavone intervention trials which extended from 6 months to 3 years suggested that there was no overall effect of dietary isoflavones on breast density, although isoflavone intervention led to a small increase in mammographic density in premenopausal women(Reference Hooper, Madhavan and Tice147). Because of the potential for oestrogenic activity, it is of particular concern that soya isoflavones may increase the risk of breast cancer in postmenopausal women, in particular for the development of ER+ tumours. A randomised clinical 2-year isoflavone supplementation trial in 358 postmenopausal women showed no modification of breast density(Reference Maskarinec, Verheus and Steinberg148). Other 1-year(Reference Verheus, van Gils and Kreijkamp-Kaspers149) and 3-year(Reference Powles, Howell and Evans150) randomised clinical trials in postmenopausal women also showed no effect. Similarly, a 2-year soya intervention trial in premenopausal women did not change mammographic density(Reference Maskarinec, Takata and Franke151). Overall, clinical trials do not support an impact of soya on breast density; however, there is still too little information from intervention trials to determine the impact of soya specifically on breast cancer development.

Epigenetic studies

In regards to epigenetics, there is much to learn from soya and related compounds. As for other nutrients, the modulation of gene expression, notably that controlled by oestrogen, occurring upon exposure to soya suggests that epigenetics-mediated effects might be involved in alterations in breast cancer risk. Furthermore, the effects of soya may differ given the time of exposure and have a long-lasting impact on the offspring. For example, exposure during pregnancy to oestrogen or genistein in rodents increases the risk of mammary cancer among the offspring(Reference Hilakivi-Clarke, Cho and Raygada152Reference Hilakivi-Clarke, Cho and Onojafe154). In contrast, results suggest that prepubertal genistein exposure may increase differentiation of the mammary ductal system(Reference Loos, Beunen and Fagard64), resulting in reduced breast cancer risk(Reference Adebamowo, Hu and Cho98).

One possible molecular mechanism of soya action is through the Wnt/β-catenin signalling pathway that regulates progenitor cells. Indeed, overactivity of this pathway leads to excessive mammary out-growth(Reference Klarmann, Decker and Farrar29). As Wnt/β-catenin is one of the pathways affected by genistein/soya, early-life exposure to soya may affect later breast cancer risk by influencing the differentiation and, thus, the epigenome of progenitor cells proposed to be involved in mammary tumour development(Reference Petersen and Polyak155). The hypothesis of a strong epigenetic impact of soya is supported by a study in which maternal exposure to genistein increased methylation of six cytosine-guanine sites upstream of the transcription start site of the Agouti gene in yellow Agouti mice(Reference Dolinoy, Weidman and Waterland156), enhancing the number of Agouti offspring that exhibited the pseudo agouti phenotype linked to lowered cancer risk. Genistein exposure also negated the DNA hypomethylating effect of an endocrine disruptor, bisphenol A(Reference Dolinoy, Huang and Jirtle157).

The few studies that have focused on the impact of foods on the epigenome in human subjects are quite revealing when investigating soya isoflavones. Work conducted with breast cancer-free premenopausal women using cells acquired by ductal lavage showed a correlation between soya isoflavone intake over one menstrual cycle and the induction of dose-specific modifications in the methylation of promoters of proliferation regulatory genes (RARβ2 (retinoic acid receptor β2) and CCND2 (cyclin D2)) associated with breast cancer development(Reference Qin, Zhu and Shi158). The fact that other genes analysed showed no significant epigenetic alteration suggests that the type of foods might have a selective epigenetic effect, and/or that in this particular and relatively homogeneous population of women, the other genes were not receptive to epigenetic modifications possibly due to the status of the mammary gland. In any case, real progress in understanding how foods might have an impact on breast cancer risk requires the identification of all specific genes that might be epigenetically modified. Additional candidate genes include cell cycle checkpoint gene p16, implicated in breast cancer development and the promoter of which might be differentially methylated depending on genistein. Noteworthy, RARβ and p16 are also influenced by dietary factors such as folic acid and resveratrol(Reference Qin, Zhu and Shi158, Reference Berner, Aumuller and Gnauck159). Moreover, soya isoflavone ingested by premenopausal women has been associated with increased methylation of genes coding for IGF-2 and cyclin G2 in mammary epithelial cells(Reference Qin, Zhu and Shi158). Thus, soya-related compounds could possibly prevent the expression of a number of genes associated with cell proliferation.

Macronutrients

Alcohol: epidemiological studies

The only dietary factor identified by the WCRF analysis for which there was convincing evidence for its association with increased breast cancer risk beside obesity in postmenopausal women is alcohol intake(46). An overwhelming number of epidemiological studies, including the Women's Health Initiative(Reference Kabat, Kim and Shikany160), have provided support for the positive relationship between alcohol, including wine, and breast cancer risk(46, Reference Engeset, Dyachenko and Ciampi161Reference Newcomb, Nichols and Beasley166). An intake of two or more alcoholic drinks per d for the past 5 years confers about an 82 % increase in risk compared with no alcohol consumption(Reference Berstad, Ma and Bernstein167). Another estimate is that each additional 10 g alcohol per d increases the risk of breast cancer approximately by 10 % based on two meta-analyses(Reference Ellison, Zhang and McLennan168, Reference Key, Hodgson and Omar169). According to the European Prospective Investigation into Cancer and Nutrition (EPIC) study, a 3 % increase in risk is associated with 10 g/d of recent alcohol intake(Reference Tjonneland, Christensen and Olsen170). However, like for the results related to dietary patterns and obesity, the relationship may be modified as a function of the tumour type since breast cancer risk is associated with alcohol in ER+ tumours(Reference Cottet, Touvier and Fournier104, Reference Lew, Freedman and Leitzmann171).

Alcohol: mechanisms

The mechanism underlying the relationship between alcohol consumption and breast cancer risk has not been clearly defined(Reference Poschl and Seitz172Reference Seitz and Stickel174). However, the action of alcohol consumption on breast cancer risk might be linked to the induction of endogenous oestrogen levels. For example, consumption of approximately one to two alcoholic drinks per d increases oestrogen levels in premenopausal and postmenopausal women(Reference Reichman, Judd and Longcope175, Reference Ginsburg, Walsh and Gao176). Moreover, a metabolite of alcohol, acetaldehyde, has genotoxic action that may contribute to the development of cancer(Reference Poschl and Seitz172, Reference Seitz and Stickel174). Alcohol is also a solvent, notably for tobacco carcinogens, and may allow greater permeability of carcinogens across cell membranes(Reference Poschl and Seitz172). Alcohol has also been proposed to modulate enzymes involved in carcinogen metabolism, increase the production of reactive oxygen species and inhibit DNA repair(Reference Seitz and Stickel174, Reference Brooks177). Thus, there are a variety of mechanistic pathways that may explain the relationship between alcohol and breast cancer and support epidemiological studies.

Alcohol: epigenetic studies

Epigenetic studies have revealed a trend towards decreased methylation in a cluster of cancer-related genes in primary tumours of 162 women (stage I–IV)(Reference Christensen, Kelsey and Zheng178), suggesting that alcohol consumption may lead to epigenetic modifications. Another study on DNA methylation profiles in breast tumours has reported that exposure to alcohol seems associated with a specific DNA methylation pattern(Reference Christensen, Kelsey and Zheng178). Therefore, the evidence supporting an impact of alcohol on breast cancer risk seems convincing, but understanding the relationship between alcohol intake and epigenetic modifications is necessary to unravel the basis for an effect on tumour development.

Fat intake: epidemiological studies

A correlation between high-fat diets and risk of cancer has been noted for more than two decades(Reference Mattisson, Wirfalt and Johansson94, Reference Hursting, Thornquist and Henderson179Reference Rose, Boyar and Wynder182). The WCRF did not find convincing evidence for a relationship between dietary fat intake and breast cancer risk; however, the support resource shows in the meta-analysis of case–control studies (n 22) a modest significant increased risk (OR 1·03) for total fat. Also, in a combined analysis of twelve case–control studies, there was a positive association between breast cancer risk and saturated fat intake(Reference Howe, Hirohata and Hislop183). In contrast, the results of a meta-analysis of eight prospective trials did not support a strong association between breast cancer incidence and total fat(Reference Smith-Warner, Spiegelman and Adami184). Not all studies associate increased intake of total fats with increased breast cancer risk, but these studies have shown relationships with other cancer sites(Reference Willett185, Reference Willett, Hunter and Stampfer186).

Certainly, one of the issues that complicates any epidemiologically based study is that fat intake is comprised of a variety of fats, including animal or saturated fats, polyunsaturated fats such as n-3 or n-6 PUFA, MUFA and trans-fatty acids. Fatty acid types have differential effects on the progression of diseases and different mechanisms of action. Therefore, each of the family of fats, or individual fatty acids, may have a different impact on the development and progression of breast cancer. Unfortunately, the ability to measure the dietary levels of fatty acids accurately is very limited. It is not surprising then that studies produce opposite results. For example, the European Prospective Investigation into Cancer and Nutrition (EPIC)-Postdam study showed that a high intake of SFA, MUFA, n-3 PUFA and n-6 PUFA led to a two-fold increase in breast cancer risk when comparing highest to lowest tertiles of processed meat, animal fats and margarine (n 15 351 with an average follow-up of 6 years)(Reference Schulz, Hoffmann and Weikert187). No association could be noted between breast cancer risk and specific fatty acids or fat intake patterns(Reference Velie, Schairer and Flood87). Similar conclusions were made for a meta-analysis of prospective studies on animal fat(Reference Alexander, Morimoto and Mink188). Furthermore inverse associations were found between breast cancer risk and dietary patterns relying on animal product intake as well as dietary patterns rich in unsaturated fat(Reference Edefonti, Decarli and La Vecchia108). Data obtained using the lipidome approach (i.e. an integrated view of the complex lipid interaction or lipid profile based on adipose tissue samples) suggested that elevated MUFA intake and a low n-6:n-3 fatty acids ratio intake were associated with decreased breast cancer risk(Reference Bougnoux, Hajjaji and Couet189). In contrast, trans-fatty acids, for which the main source is industrial hydrogenation processing (for example, margarine), have been linked to an increase in breast cancer risk(Reference Chajes, Thiebaut and Rotival190). Results of the Nurses' Health Study, in a 20-year follow-up, showed no association between fats and breast cancer risk, even when specific types of fat, and ER or PR status were considered(Reference Kim, Willett and Colditz191). However, fat intake during adolescence may have to be further investigated, as the RR for breast cancer in premenopausal women in the Nurses' Health Study was 1·35 in the highest quintile of dietary fat intake (mean 142 g/d) compared with the lowest quintile (mean 105 g/d) (OR 1·35; 95 % CI 1·00, 1·81)(Reference Linos, Willett and Cho192). Overall, epidemiological studies reveal highly variable results, and until dietary intake of specific types of fats can be measured with greater accuracy or precise status measures are developed, these study designs are unlikely to decipher relationships between dietary fats and breast cancer.

Fat intake: animal studies

Consistent with epidemiological data in human subjects, a significant body of literature shows that diets high in fat increase the progression of mammary tumours in rodents(Reference Fay and Freedman193, Reference Freedman, Clifford and Messina194). Rodent studies consistently show that a high-fat diet promotes hyperproliferation in the mammary gland, and shortened latency and increased incidence of carcinogen-induced mammary tumours(Reference Welsch, House and Herr195, Reference Welsch196). As noted above, the interpretation of these studies is complicated by greater adiposity and excess energy intake associated with the intake of high-fat diets. When energy intake is controlled in animal studies, the effect of fat intake is weak or eliminated(Reference Kritchevsky, Weber and Klurfeld197, Reference Klurfeld, Weber and Kritchevsky198), suggesting that energy intake may be the most important factor for breast cancer risk.

Fat intake: mechanisms

Multiple mechanisms are proposed to underlie an impact of fats on breast cancer, but the specific pathways remain unclear(Reference Woutersen, Appel and Van Garderen-Hoetmer199). Enrichment of cell membranes with dietary fats may alter membrane fluidity and potentially the size and distribution of lipid rafts(Reference Chapkin, Wang and Fan200) and the level of oxidative stress. Specific types of fat, provided with the diet and normally stored in cell membranes, are metabolised very differently in cells, serving not only as an energy substrate that can alter membrane susceptibility to lipid oxidation, but also produce biologically active signals. For example, arachidonic acid and EPA are precursors for eicosanoids, which are potent intracellular signals. More specifically, n-3 fatty acids can inhibit inflammatory mediators that are proposed to promote cancer progression. Different types of lipids may differentially affect breast cancer risk, and the mechanisms involved are likely to also differ depending on the type of lipid(Reference Simopoulos201). The biological effects of n-6 PUFA and n-3 PUFA proposed to promote and suppress cancer progression, respectively, are diverse and include characteristics of cells such as proliferation and apoptosis, as well as an influence on angiogenic factors(Reference Larsson, Kumlin and Ingelman-Sundberg202) that play a critical role in cancer development and progression. Interestingly, a high dietary intake of n-6 PUFA during pregnancy increases mammary tumorigenesis in the offspring in rats(Reference Hilakivi-Clarke, Cho and Raygada152), suggesting a long-lasting effect of fats on cancer risk. Another link with mammary cancer susceptibility was found in a study focused on a high-fat diet in rats, a diet which has been linked with increased incidence of induced mammary tumours in the offspring(Reference de Assis, Khan and Hilakivi-Clarke203). Interestingly, the normal mammary tissue of offspring from mothers fed a high-fat diet during pregnancy was altered, with denser epithelial tree and higher number of proliferating cells compared with controls. The offspring of high-fat diet-fed mothers had higher birth weight and displayed shorter latency for mammary tumour development.

Thus, there is a mechanistic basis for the purported relationship between several specific fatty acids and breast cancer risk. However, deciphering the mechanisms will require well-defined models in order to later on translate these results into population studies and interventions.

Fat intake: epigenetic studies

There are virtually no studies on the interaction of fat intake and epigenetics as it relates to breast cancer. There have been some studies unrelated to the mammary gland, such as that showing a DNA hypomethylating effect of a high-fat diet globally and at the promoter of specific genes in the brain(Reference Vucetic, Kimmel and Totoki204). Another study suggests an impact on mammary tissue by showing that ER methylation was lost in the mammary tissue of a majority of rats at an increased risk of developing breast cancer due to manipulation of dietary fat intake in utero (Reference Yenbutr, Hilakivi-Clarke and Passaniti205). Unfortunately, in whole organisms it is difficult to separate the effect of a high-fat diet from obesity. Therefore, studies performed in appropriate cell model systems are necessary to tease out a possible link between specific fatty acids and epigenetic mechanisms. For instance, our recent results in cultures of non-neoplastic human mammary epithelial cells that mimic pre- and postglandular differentiation stages indicate that fatty acid treatment that protects the normal phenotype also globally has an impact on the level of a number of histone modifications (K McDole and S Lelièvre, unpublished results). It will be important to identify which modifications are sustained and the specific genomic regions involved.

Carbohydrates, glycaemic index and glycaemic load: epidemiological studies

Carbohydrates and carbohydrate quality could influence breast cancer risk potentially by affecting insulin resistance and plasma levels of insulin and glucose(Reference Michels, Mohllajee and Roset-Bahmanyar10). To date, twelve prospective cohort studies have shown inconsistent associations between total carbohydrate, glycaemic index, glycaemic load and breast cancer(Reference Mahoney, Bevers and Linos206). Nevertheless, data from Mexico, where carbohydrates account for close to 64 % of energy intake in the population, support an association between carbohydrate intake as well as glycaemic load and breast cancer among pre- and postmenopausal women(Reference Romieu, Lazcano-Ponce and Sanchez-Zamorano207). High intake of refined carbohydrates may have stronger associations with breast cancer risk in populations genetically susceptible to insulin resistance, such as in Mexico, particularly when combined with obesity and low levels of physical activity(Reference Gomez, Hernandez-Prado and Morales208). Further, a higher glycaemic index during adolescence is associated with an increased risk for breast cancer in adults in the Nurses' Health Study II(Reference Frazier, Li and Cho209). In addition, carbohydrate quality may differently affect breast tumour types including positive associations of carbohydrate intake, glycaemic index and glycaemic load with risk of ER+/PR– breast cancer, but not ER+/PR+ or ER–/PR– breast tumour(Reference Larsson, Bergkvist and Wolk210), or an increased risk of ER– breast cancer(Reference Lajous, Boutron-Ruault and Fabre211, Reference Nielsen, Olsen and Christensen212). Thus, evidence of an association between carbohydrate intake, glycaemic index and glycaemic load is conflicting and may be confounded by insulin resistance and the type of tumour.

Carbohydrates, glycaemic index and glycaemic load: mechanisms

The mechanisms underlying the relationship between carbohydrate intake, and particularly glycaemic index, and breast cancer risk is proposed to be through greater insulin action. Chronically raised insulin levels may increase carcinogenesis in breast tissue by directly stimulating insulin receptors. Insulin can also reduce plasma and tissue levels of IGF-binding proteins 1 and 2, which may in turn increase the availability of IGF-1(Reference Calle and Kaaks68), and experimental studies have revealed strong proliferative and anti-apoptotic effects of IGF-1 in breast tissue(Reference Yanochko and Eckhart213). A recent pooled analysis including seventeen prospective studies reported a positive association between IGF-1 and the risk of developing ER+ tumours (OR 1·38; 95 % CI 1·14, 1·68; comparing highest with lowest fifth)(Reference Key, Appleby and Reeves214). Therefore, potential mechanisms to explain the impact of carbohydrates on breast tumour development include higher insulin levels (similar to obesity) and increased availability of IGF-1, both of which activate cellular responses consistent with cancer progression.

Carbohydrates, glycaemic index and glycaemic load: epigenetics

Similar to fatty acids, the specific effect of carbohydrates on the epigenome has not been examined. Most studies currently available are linked to obesity. As mentioned above, specific three-dimensional cell models that mimic phenotypically normal breast glandular differentiation might be an interesting first approach to sort out epigenetic effects directly related to carbohydrates.

Micronutrients

Research pertaining to elements required in minute amounts in the diet has generated many reports, particularly in regards to an effect on epigenetic mechanisms. Among the most studied elements for breast cancer are folate, vitamin D and carotenoids.

Folate: epidemiological studies

Most prospective studies do not provide evidence of an association between folate intake and breast cancer risk(Reference Lewis, Harbord and Harris215Reference Larsson, Giovannucci and Wolk217). In contrast and consistent with the literature related to colorectal cancer(Reference Mason and Choi218), there is also evidence to support that folate supplementation may increase the risk for breast cancer(Reference Stolzenberg-Solomon, Chang and Leitzmann219). Interestingly, a benefit from folate intake is observable in individuals with low folate status (in non-vitamin users, highest (356 μg/d) v. lowest ( ≤ 159 μg/d), OR 0·61; 95 % CI 0·41, 0·93), suggesting a protective effect against breast cancer only in non-supplemented vitamin B users(Reference Chen, Gammon and Chan220). Protective effects have also been observed in populations with low folate status, in which vitamin supplementation is infrequent(Reference Lajous, Lazcano-Ponce and Hernandez-Avila221Reference Shrubsole, Gao and Cai225). In a case–control study conducted among Mexican populations, women with the highest folate intake (mean 454 μg/d) compared with women with the lowest intake (mean 224 μg/d) had a risk for breast cancer of 0·64 (95 % CI 0·45, 0·90)(Reference Chen, Gammon and Chan220). Furthermore, vitamin B12, a coenzyme in folate metabolism, might be associated with a lower risk of breast cancer and low vitamin B12 intake may reduce the potential protection conferred by folate against breast cancer development(Reference Stolzenberg-Solomon, Chang and Leitzmann219, Reference Lajous, Lazcano-Ponce and Hernandez-Avila221, Reference Lajous, Romieu and Sabia226, Reference Shrubsole, Jin and Dai227).

Folate studies are further complicated by the fact that, as for other dietary components, additional factors may have an impact on the relationship between folate intake and breast cancer risk. For example, an inverse association between breast cancer development and circulating folate levels among alcohol drinkers has been noted(Reference Zhang, Hunter and Hankinson216, Reference Zhang, Willett and Selhub228). Ethanol may induce a physiological deficiency that affects the one-carbon metabolism involved in the epigenetic control of gene transcription by reducing folate absorption from the gastrointestinal tract or by inhibiting enzymic activity(Reference Mason and Choi218). The impact of folate may also be related to the tumour type, since the incidence of ErbB2-positive breast cancers is increased in women in the highest tertile of plasma folate compared with the lowest(Reference Ericson, Borgquist and Ivarsson229).

Folate: animal models

The impact of folic acid on the initiation and progression of mammary tumorigenesis in animal models is complex and dependent on the dose and timing of dietary manipulation. Generally, studies in animal models support that folate deficiency is associated with a reduced risk of developing mammary tumours, although some studies show no effect when dietary intervention is initiated before chemical induction of tumorigenesis(Reference Ai, Tao and Zhong27, Reference Kim230Reference Choi and Mason232). On the other hand, folate deficiency developed after tumour initiation is shown to inhibit the progression of mammary neoplasias(Reference Kotsopoulos, Medline and Renlund233Reference Baggott, Vaughn and Juliana235), suggesting that high-folate diets may enhance the progression of tumours.

Folate: mechanisms

Knowing the mechanisms of folate impact on the mammary gland would help greatly in deciphering how to integrate this nutrient in prevention studies. As mentioned above, epidemiological studies suggest an interaction between alcohol intake and folate on risk of cancers, and there is a mechanistic basis for this observation, as alcohol has an impact on folate metabolism(Reference Mason and Choi236). Overall, the results suggest that folate deficiency may increase initiation, but decrease progression of breast cancer, which is consistent with the concept first proposed for colon cancer that folate prevents the development of cancers, but high folate intake may promote progression of already established tumours(Reference Mason and Choi218). This discrepancy might in part be explained by epigenetic effects.

Folate: epigenetics

Folate is a central player in one-carbon metabolism, including methylation of DNA. It is converted to 5,10-methylenetetrahydrofolate (MTHF), the metabolites of which are important for the synthesis of DNA components, guanine and adenine. Importantly, the product of MTHF reductase, 5-methyltetrahydrofolate, is a methyl donor for the conversion of homocysteine to methionine, which ultimately serves in the form of S-adenosylmethionine for a variety of reactions, including methylation of DNA. Polymorphism in MTHF reductase has been shown to interact with B vitamins to modulate breast cancer risk(Reference Chen, Gammon and Chan220). Indeed, there is evidence that folate deficiency may lead to global hypomethylation(Reference Chen, Gammon and Chan220). Thus, there is a strong mechanistic basis for a role of alterations in dietary intake levels of folate in the initiation and progression of breast cancer by acting on DNA integrity, synthesis, repair and methylation. So far, studies have suggested that folate may confer protection in early carcinogenesis and also promote cancer growth later during the neoplastic process, including that of mammary tumours(Reference Stolzenberg-Solomon, Chang and Leitzmann219, Reference Lin, Lee and Cook237). This is a plausible scenario because, as the disease progresses, the organisation of the cell nucleus, including the genome, may be modified(Reference Lelievre12). Therefore, one-carbon metabolism-mediated DNA methylation triggered by folate might affect genes that are protecting against breast cancer development as well as genes that are promoting tumour development and progression depending whether or not nuclear organisation renders these genes accessible for epigenetic modification.

One critical way for nutrients to affect the epigenome is to influence the availability of methyl groups. By doing so they could modify the methylation status of DNA and, thus, gene transcription(Reference Choi and Friso45). In the preceding paragraph, it was explained that folate contributes to the one-carbon metabolism pathway(Reference Williams and Schalinske238). Particularly, folate carries a methyl group used for the synthesis of the methyl donor metabolite S-adenosylmethionine(Reference Mehedint, Niculescu and Craciunescu239), and could also make an impact on the activity of methyltransferase via S-adenosylhomocysteine(Reference Choi and Friso45). As a result, bioactive foods can modify the epigenetic landscape, possibly leading to permanent gene silencing.

The epigenetic effect might also be critical for the influence of maternal diet on the offspring. Folate supplementation before and during pregnancy in rats increased the risk of tumour development induced chemically by 7,12-dimethylbenz(a)anthracene (DMBA) in the offspring compared with a control (adequate) diet, and induced a decrease in global DNA methylation(Reference Ly, Lee and Chen240). Folate supplementation during pregnancy and weaning reduced the number of mammary terminal end buds, a marker of breast cancer risk, suggesting a protection from breast cancer compared with a control diet(Reference Sie, Chen and Sohn241). The potential link between terminal end bud density and an effect on DNA methylation by folate remains to be clarified. In humans, it is also possible to influence methylation in the offspring via nutritional changes in the mother. For instance, studies have shown that folic acid supplementation of women during the periconceptional time increases IGF-2 gene methylation in children(Reference Steegers-Theunissen, Obermann-Borst and Kremer242).

The broad mechanisms by which foods seem to influence the epigenome (for example, via one-carbon metabolism and methyltransferase activity) could potentially affect many genes. Indeed, a minimum of 60 % of genes are proposed to be methylated. Also a majority of genes will be sensitive to acetylation and methylation of histones. Yet, as shown with the example of folate, only certain genes seem to be responsive to the modulation of common epigenetic pathways. A plausible hypothesis is that only genes in a receptive chromatin environment will respond to such broad epigenetic modulation. Therefore, probably the effect of dietary compounds will depend on the gene, the cell type (with its specific nuclear organisation)(Reference Lelievre243), the cell status (i.e. proliferation) and previous epigenetic conditions. For instance, deprivation of folate has been associated with gene hypermethylation specifically in the liver in a rat model(Reference Kim230, Reference Stempak, Sohn and Chiang244). Timing might also be important, as the effect of folate might be opposite depending on when it is given. For instance, it stimulates tumour development if a preneoplastic lesion is already in place(Reference Song, Medline and Mason245). Therefore, promoting or preventing methylation and acetylation reactions via foods could have various outcomes depending on when during life such an influence occurs. Of particular interest is the consequence of diet received before mammary gland development on epigenetic modifications and breast cancer risk.

Overall, there is evidence of a biphasic effect of folate deficiency and supplementation on breast cancer risk depending on the timing of dietary intervention and involving epigenetics, but the results remain controversial and the underlying mechanisms are not definitively determined.

Vitamin D

Vitamin D is one of the most studied micronutrients as a cancer-preventive agent, but the controversy regarding its potential use in prevention is not yet settled. A main reason is that, like for folate, the efficacy of vitamin D may depend on individual baseline level, dose and supplementation period.

Vitamin D: epidemiological studies

Results from many epidemiological studies support that vitamin D is associated with reduced breast cancer risk(Reference Garland, Gorham and Mohr246, Reference Cui and Rohan247). First were ecological studies showing a relationship between exposure to UV light and reduced risk of breast cancer(Reference Garland, Garland and Gorham248). The potential explanation for this relationship is that vitamin D is synthesised in the skin under the influence of UV light. Both UV light-produced vitamin D and dietary vitamin D are then converted in the liver to 25-hydroxyvitamin D (25OHD), the serum levels of which are used as a vitamin D status marker. In a pooled analysis, the results revealed that 25OHD serum levels of approximately 52 ng/ml were associated with a 50 % reduction in breast cancer risk compared with women with 25OHD levels <  13 ng/ml(Reference Garland, Gorham and Mohr246). One case–control study revealed that women with 25OHD plasma concentration <  50 nmol/l had five times greater risk of developing breast cancer than women with concentrations exceeding 150 nmol/l(Reference Lowe, Guy and Mansi249). Similarly, a meta-analysis reported a 45 % decrease in breast cancer risk among women in the highest quartile (60 nmol/l) of circulating 25OHD compared with women with the lowest level(Reference Chen, Hu and Xie250). Epidemiological studies have also shown an inverse association between vitamin D intake or serum 25OHD and breast cancer development, in both premenopausal women(Reference Lin, Manson and Lee251, Reference Shin, Holmes and Hankinson252) and postmenopausal women(Reference Robien, Cutler and Lazovich253).

Similar to other dietary components, menopausal status may play a role in the association between vitamin D and breast cancer risk. In an ecological study, the inverse relationship between geographical UV exposure and breast cancer was specific to premenopausal women(Reference Blot, Fraumeni and Stone254). Similarly, in the Nurses' Health Study (n about 90 000) with an approximate 14-year follow-up, vitamin D intake was inversely associated with breast cancer risk only in premenopausal women, which is consistent with results from the Cancer Prevention Study II Nutrition Cohort. In the latter, dietary vitamin D intake was not associated with breast cancer risk in postmenopausal women(Reference McCullough, Rodriguez and Diver255). Thus, although a strong body of work supports the relationship between vitamin D and breast cancer, the results of epidemiological studies remain controversial, and discrepancies noted in the relationship may be due to the influence of other factors. It is hoped that ongoing trials will take note of the many variables that could affect the outcome of the results to better pinpoint the relationship between vitamin D and breast cancer.

Vitamin D: animal studies and mechanisms

Vitamin D is best characterised for its role on the regulation of Ca status. High vitamin D status leads to the suppression of serum parathyroid hormone levels. Parathyroid hormone is a strong stimulator of renal 25-hydroxyvitamin D-1α hydroxylase which catalyses the conversion of 25OHD to 1,25-dihydroxyvitamin D (1,25(OH)2D)(Reference Zierold, Mings and Deluca256, Reference Armbrecht, Boltz and Hodam257), leading to an inverse relationship between vitamin D status (serum 25OHD levels) and serum 1,25(OH)2D. This inverse relationship is difficult to reconcile with observations that higher vitamin D status is associated with a decrease in breast cancer risk but 1,25(OH)2D directly inhibits cancer-relevant endpoints in cells. However, extra-renal 1α-hydroxylase enzymes have also been identified in a variety of tissues(Reference Li, Byrne and Chang258) and in mammary epithelial cells(Reference Kemmis, Salvador and Smith259), which may lead to greater local production of 1,25(OH)2D under conditions of high vitamin D status(Reference Zehnder, Bland and Williams260).

The activity of 1,25(OH)2D is regulated through vitamin D receptor (VDR)-mediated transcriptional regulation as well as rapid, non-genomic actions. The VDR, a member of the steroid hormone receptor family, mediates 1,25(OH)2D transcriptional actions by heterodimerising with retinoid X receptor and interacting with vitamin D response elements to up-regulate and down-regulate a wide variety of genes(Reference Norman261, Reference Haussler, Haussler and Bartik262). Other evidence supports that 1,25(OH)2D regulates kinase signalling cascades involving protein kinase C, extracellular signal-regulated protein kinases 1 and 2, phosphoinositide-3-kinase, and Src(Reference Bernardi, Johnson and Modzelewski263Reference Li and Farach-Carson266), which are generally shown to be rapid and independent of new RNA and protein synthesis(Reference Bernardi, Johnson and Modzelewski263, Reference Norman, Okamura and Bishop267).

Consistent with the epidemiological results, there is also substantial evidence in animal models to support a protective effect of vitamin D for breast cancer(Reference Matthews, LaPorta and Zinser268). For example, susceptibility to hyperplasia and tumours in the mammary gland is greatly increased in mice lacking the VDR(Reference Zinser and Welsh269, Reference Zinser, Suckow and Welsh270). Further, mammary gland proliferation and tumour development is reduced by high vitamin D intake in animals(Reference Kurihara, Fan and Thaler271, Reference Jacobson, James and Newmark272).

Overall, in vitro studies have shown that vitamin D can regulate critical characteristics of cells necessary for carcinogenesis, including inhibiting cell proliferation, promoting apoptosis and reducing angiogenesis(Reference Welsh273). Furthermore, alterations in genes related to vitamin D metabolism have been associated with breast cancer risk(Reference Matthews, LaPorta and Zinser268). Thus, there is substantial evidence in both animal and cell culture studies to support that vitamin D reduces breast cancer risk. However, as for fatty acids, the translation of the information to human populations will require consideration of many factors and well-designed clinical trials.

Vitamin D: intervention studies

The largest clinical trial in which the impact of dietary vitamin D on breast cancer development was investigated is the Women's Health Initiative. In this study, no impact of vitamin D supplementation on breast cancer risk was noted(Reference Chlebowski, Johnson and Kooperberg274). However, the levels of vitamin D supplement used in this trial (400 IU/d; 10 μg/d) are now considered potentially too low to elicit maximal effects on bone and, thus, also the proposed effect on breast cancer development. In addition, because the duration was only 7 years, this trial does not represent the testing of a meaningful intervention to prevent breast cancer. An example of the issue of timing of the intervention is shown in the study by Lappe et al. who completed a randomised placebo-controlled Ca and vitamin D intervention trial in postmenopausal women (> 55 years; n 1179), followed during 4 years(Reference Lappe, Travers-Gustafson and Davies275). The RR of developing breast cancer with Ca supplementation (about 1450 mg/d) alone was 0·54, and no difference was found for the group with both Ca and vitamin D (1100 IU/d (27·5 μg/d), RR 0·40). It was hypothesised that vitamin D might be less effective in preventing breast cancer development if the cancer is already present, although not yet detectable with current screening methods. Therefore, women who were diagnosed with breast cancer in the first year of the trial were excluded from the analysis. In that case the risk of developing breast cancer in the vitamin D plus Ca group was significantly reduced (RR 0·23) compared with the placebo and compared with Ca supplementation alone (RR 0·59). This study provides strong evidence that vitamin D, at least in the presence of Ca, significantly reduces breast cancer risk and reveals that the timing of the intervention (i.e. before breast cancer is present) may be critical.

Vitamin D: epigenetics

First, epigenetic modifications are suggested to alter the effects of 1,25(OH)2D. For example, the use of inhibitors to epigenetic modifications restores signals associated with anti-proliferative effects in vitamin D-resistant breast cancer cells(Reference Banwell, MacCartney and Guy276). Suppression of 1α-hydroxylase expression, which influences the production of the most active form of the vitamin, is modified in part by histone deacetylation and mediation of this repression by the VDR requires DNA methylation in the promoter of the gene(Reference Kim, Fujiki and Kitagawa277). Further, epigenetic alterations in the gene producing the 24-hydroxylase that mediates the first step in the degradation of 1,25(OH)2D was shown in full-term human placental tissue, but not methylation of the VDR and 1α-hydroxylase genes(Reference Novakovic, Sibson and Ng278). Reduction in 24-hydroxylase expression is mediated at least in part by methylation of the promoter in human prostate cancer(Reference Luo, Karpf and Deeb279, Reference Deeb, Luo and Karpf280). Therefore, epigenetic modifications may alter the metabolism as well as the action of vitamin D, but little information is available in breast tissue. On the other hand, although the active metabolite, 1,25(OH)2D, was shown to have an effect on gene expression in breast cancer cells(Reference Margolis and Christakos281), the role of vitamin D in modifying the epigenome in relation to breast cancer has not been explored. Nevertheless, nuclear receptors (to which the VDR belongs) and associated mediators are known to influence chromatin remodelling and epigenetic modifications. In conclusion, there is an interaction of vitamin D with the epigenome, but a consequence for breast cancer risk is not clear.

Carotenoids: epidemiological studies

A substantial literature exists investigating the relationship between carotenoids and cancer(46, Reference Giovannucci282, Reference Rohan283). In epidemiological studies, intake of carotenoids is assessed both by dietary analysis and serum levels of the carotenoids. Some studies have indicated a protective effect of carotenoids(Reference Toniolo, Van Kappel and Akhmedkhanov284, Reference Zhang, Hunter and Forman285), whereas other studies showed no association with breast cancer(Reference Hulten, Van Kappel and Winkvist286Reference Epplein, Shvetsov and Wilkens289). The putative effect of carotenoids may be modified by age or menopausal status since an inverse association with breast cancer risk was noted in premenopausal women rather than in postmenopausal women(Reference Mignone, Giovannucci and Newcomb290). Furthermore, the potential impact of carotenoids may be greater when associated with other lifestyle factors. This is exemplified by the link between carotenoids and the reduced risk of invasive breast cancer in premenopausal, but not postmenopausal, smokers(Reference Mignone, Giovannucci and Newcomb290).

It is important to note that carotenoids are a family of compounds including retinol, retinyl palmitate, α-carotene, β-carotene, β-cryptoxanthin, lutein and lycopene. Like fats, the type of carotenoid may have a different impact on the risk of breast cancer. A nested case–control study for women who donated blood before diagnosis revealed that women who developed breast cancer had significantly lower serum concentrations of β-carotene, lycopene and total carotene than the breast cancer-free controls(Reference Sato, Helzlsouer and Alberg291). Similarly, serum lycopene levels have been associated with a reduced breast cancer risk(Reference Hulten, Van Kappel and Winkvist286). Contradictory results exist among the types of carotenoids as revealed by the Women's Health Initiative since baseline serum levels of α-carotene and β-carotene were negatively associated, while lycopene levels were positively associated with invasive breast cancer in postmenopausal women(Reference Kabat, Kim and Adams-Campbell292). Therefore, the relative levels of the different types of carotenoids are important to take into account as well as a potential influence from other lifestyle factors.

Carotenoids: mechanisms

A number of mechanisms have been examined that may underlie the purported relationship between carotenoids and breast cancer development. Cell culture studies show that retinoids may reduce proliferation and induce differentiation of epithelial cells(Reference Rabi and Bishayee293, Reference Okuno, Kojima and Matsushima-Nishiwaki294). Carotenoids function as antioxidants and, thus, may also protect DNA from damage induced by reactive oxygen species. On the other hand, at high doses, β-carotene may act as a pro-oxidant, hence potentially promoting tumorigenesis(Reference Black295, Reference Valko, Izakovic and Mazur296). Therefore, although mechanisms exist to explain the relationship between carotenoids and breast cancer, there is still much to learn about the effect of these nutrients on the breast tissue.

Carotenoids: epigenetic studies

Lycopene has been reported to influence the epigenome by partially demethylating the tumour suppressor gene GSTP1 (glutathione S-transferase P1) in breast cancer cells. Interestingly, treatment of non-neoplastic breast epithelial cells MCF10A with lycopene led to demethylation of RARβ2 (retinoic acid receptor β2)(Reference King-Batoon, Leszczynska and Klein297), a gene silenced before the onset of tumour development(Reference Bistulfi, Pozzi and Ren298). Although lycopene is currently classified as displaying a possible preventive action against cancer because of its influence on the epigenome, additional mechanistic studies are needed to clearly establish this possibility and will require the use of appropriate cell models.

The complexity of epigenetics and diet interaction

Most of the studies related to the epigenome, diet and cancer have focused on DNA methylation. Yet, as explained in the introduction, a large area of epigenetics relies on the study of histone modifications. Unfortunately, much less is known regarding the potential effect of foods and nutrients on histones. One of the rare studies suggests that resveratrol contained in red wine and possibly associated with protection against cancer development(Reference Ndiaye, Kumar and Ahmad299) could lead to histone deacetylase (HDAC) inhibition via an effect on Sirt1(Reference Koo and Montminy300, Reference Binda, Nassif and Branton301), thus potentially promoting histone hyperacetylation and preventing transcriptional repression.

The influence of diet early in life on cancer development occurring years later has to be regarded as a ‘life-course perspective on cancer risk’ to quote Burdge et al. (Reference Burdge, Slater-Jefferies and Torrens37). Indeed, it has been proposed that breast cancer might develop over 10 to 30 years; therefore it seems logical that some of the initiating events would occur early in life, even as soon as embryonic development, either because of epigenetic imprinting from the parent gametes or because of nutrition received in utero (or before puberty). Further emphasis on studies related to the impact of diet early in life on breast cancer development is critical. But the truth remains that not all women subjected to risk factors early in life will develop breast cancer. It is likely that the complex epigenetic profile of each individual will provide a different soil in each individual and, thus, a different response to risk factors. Yet, it is likely that variations in soils are not infinite; rather, a subset of specific genes might have to be altered to favour breast cancer development. By finding or defining the protective signature of the epigenome in the breast (i.e. an epigenetic profile that prevents tumour development), we might be able to develop ways to return to this signature once it is altered and use this signature as a method to assess preventive strategies. Indeed, it is critical to develop biomarkers of breast cancer initiation to complete cost-effective and rapid assessment of the impact of potential preventive agents on the development of the disease. It seems that understanding the link between diet, the epigenome and specific types of breast cancers might be a way to achieve this goal.

Conclusion

It is evident from the studies reported in the present review that there is a divergence in the results from population studies compared with more controlled conditions. There are several reasons for this lack of consensus beside the possibility of confounding factors and the many differences in the experimental design and endpoints. We need to resolve the discrepancies to launch a global effort to fight the rise of breast cancer incidence which includes diverse populations. Indeed, few studies are available from LMI countries where variability in food intake is large and nutritional supplementation less prevalent. In addition, stratification of breast cancer by specific characteristic has to be further considered, particularly breast cancer grades, receptor status (ER, PR, HER2 (human epidermal growth factor receptor-2)) and other molecular classification, as specific diets and nutrients interact with these factors to promote or protect from a defined type of breast cancer (Fig. 3). Finally, it seems that dietary factors are particularly important in determining premenopausal breast cancer risk. Efforts ought to be placed on developing studies in countries where breast cancer incidence is high in younger women.

Fig. 3 Venn diagram of a relationship between diets/food components and factors that influence their impact on breast cancer risk. Major life characteristics share specific relationships with diets/food components when it comes to breast cancer. These characteristics include the stage of mammary gland development (which encompasses menopausal status/age) and the individual's background (race/ethnicity and lifestyle other than dietary habits). The combination of these different factors might explain why certain nutrients will have an impact on the development of a certain type of breast tumour. Such knowledge is critical for optimal primary prevention, as it suggests that (1) the study of the impact of diets/food components on breast cancer has to take into account diversity and (2) the link between the development of a certain type of breast tumour and nutrition has to be further scrutinised, notably via the identification of the early alterations in the breast specific to a given type of neoplasia. ER+, oestrogen-positive; ER–, oestrogen-negative; PR+, progesterone-positive; PR–, progesterone-negative.

Gene–diet interaction and long-term epigenetic mechanisms are paramount in determining breast cancer risk. Further investigations are needed in order to unravel the role of diet on long-term and temporary epigenetic modifications. On a side note, another aspect that should not be forgotten in future studies is the possibility for foods to convey environmental pollutants, some of which have hormonal activity, and which could also contribute to epigenetic changes. The endeavour of identifying the meaning of epigenetic alterations will require taking into account the complexity of histone changes. Indeed, one nutrient might have different effects depending on the chromatin environment of a specific gene. Therefore, global epigenetic modifications need to be correlated with modifications at specific gene loci and new technologies, notably microscopy-based imaging(Reference Miller, Chen and Takasuka302), might enable scientists to perform these studies with high-throughput efficacy. There is increasing evidence that large-scale chromatin organisation or higher-order chromatin organisation that involves gene neighbourhoods or groups directs tissue development and differentiation(Reference Abad, Lewis and Mian303, Reference Vasanthi and Mishra304). Therefore, as the epigenome is modified by environmental stimuli, many genes might change expression although only a few genes will be required to determine breast cancer development. These few genes need to be identified and their epigenetic environment scrutinised. Similarly, understanding the impact of diet on methylases and demethylases specific to certain histone modifications and on chromatin remodelling complexes involved in facilitating or preventing gene transcription would help unravel mechanisms involved in epigenetic alterations that lead to breast cancer. Animal and appropriate cell culture models should help sort through key genes for breast cancer initiation and their epigenetic susceptibility to diet. Animal models to study mammary cancer prevention are well defined but they do not always represent the behaviour of human cells. Implementing the use of powerful human cell models of phenotypically normal mammary differentiation and early stages of tumour development provided by three-dimensional cell culture(Reference Plachot, Chaboub and Adissu305), instead of using cancer cells or cells in flat monolayer culture that lack tissue morphogenesis, should bring significant information regarding the molecular mechanisms involved in the impact of food on the breast epithelium.

Acknowledgements

The present review was supported by The National Institutes of Health (R25CA128770 to D. T. and S. A. L., and R01CA112017 to S. A. L.) and the Komen Foundation for the Cure (BCTR-0707641 to S. A. L.). All three co-authors contributed to ideas and writing for this paper. The present review is part of the International Breast Cancer and Nutrition (IBCN) Project initiated at Purdue University.

The authors declare no conflict of interest.

References

1Ferlay, J, Shin, H-R, Bray, F, et al. . (2010) Estimates of worldwide burden of cancer in 2008: GLOBOCAN 2008. Int J Cancer 127, 28932917.CrossRefGoogle ScholarPubMed
2Franco-Marina, F, Lazcano-Ponce, E & Lopez-Carrillo, L (2009) Breast cancer mortality in Mexico: an age–period–cohort analysis. Salud Publica Mex 51, Suppl. 2, s157s164.CrossRefGoogle ScholarPubMed
3Velasquez-De Charry, LC, Carrasquilla, G & Roca-Garavito, S (2009) Equity in access to treatment for breast cancer in Colombia (article in Spanish). Salud Publica Mex 51, Suppl. 2, s246s253.Google Scholar
4Lozano-Ascencio, R, Gomez-Dantes, H, Lewis, S, et al. . (2009) Breast cancer trends in Latin America and the Caribbean (article in Spanish). Salud Publica Mex 51, Suppl. 2, s147s156.CrossRefGoogle Scholar
5Porter, P (2008) “Westernizing” women's risks? Breast cancer in lower-income countries. N Engl J Med 358, 213216.CrossRefGoogle ScholarPubMed
6Dunn, BK, Agurs-Collins, T, Browne, D, et al. . (2010) Health disparities in breast cancer: biology meets socioeconomic status. Breast Cancer Res Treat 121, 281292.CrossRefGoogle ScholarPubMed
7Prentice, RL (2008) Women's health initiative studies of postmenopausal breast cancer. Adv Exp Med Biol 617, 151160.CrossRefGoogle ScholarPubMed
8Zeisel, SH (2007) Nutrigenomics and metabolomics will change clinical nutrition and public health practice: insights from studies on dietary requirements for choline. Am J Clin Nutr 86, 542548.CrossRefGoogle Scholar
9International Agency for Research on Cancer and World Health Organization (2008) In World Cancer Report 2008, [Boyle, P and Levin, B, editors]. Lyon: IARC.Google Scholar
10Michels, KB, Mohllajee, AP, Roset-Bahmanyar, E, et al. . (2007) Diet and breast cancer: a review of the prospective observational studies. Cancer 109, 27122749.CrossRefGoogle ScholarPubMed
11Weigelt, B, Baehner, FL & Reis-Filho, JS (2010) The contribution of gene expression profiling to breast cancer classification, prognostication and prediction: a retrospective of the last decade. J Pathol 220, 263280.CrossRefGoogle ScholarPubMed
12Lelievre, SA (2010) Tissue polarity-dependent control of mammary epithelial homeostasis and cancer development: an epigenetic perspective. J Mammary Gland Biol Neoplasia 15, 4963.CrossRefGoogle ScholarPubMed
13Plachot, C & Lelievre, SA (2004) DNA methylation control of tissue polarity and cellular differentiation in the mammary epithelium. Exp Cell Res 298, 122132.CrossRefGoogle ScholarPubMed
14Takai, D & Jones, PA (2002) Comprehensive analysis of CpG islands in human chromosomes 21 and 22. Proc Natl Acad Sci U S A 99, 37403745.CrossRefGoogle Scholar
15Abad, PC, Yagci, B & Lelièvre, SA (2011) Nanocellular processes. In Encyclopedia of Nanoscience and Nanotechnology, vols 11–20 [Nalwa, HS, editor]. Valencia, CA: American Scientific Publishers.Google Scholar
16Hublitz, P, Albert, M & Peters, AH (2009) Mechanisms of transcriptional repression by histone lysine methylation. Int J Dev Biol 53, 335354.CrossRefGoogle ScholarPubMed
17Mohammad, HP, Cai, Y, McGarvey, KM, et al. . (2009) Polycomb CBX7 promotes initiation of heritable repression of genes frequently silenced with cancer-specific DNA hypermethylation. Cancer Res 69, 63226330.CrossRefGoogle ScholarPubMed
18Mathews, LA, Crea, F & Farrar, WL (2009) Epigenetic gene regulation in stem cells and correlation to cancer. Differentiation 78, 117.CrossRefGoogle ScholarPubMed
19Hatziapostolou, M & Iliopoulos, D (2011) Epigenetic aberrations during oncogenesis. Cell Mol Life Sci 68, 16811702.CrossRefGoogle ScholarPubMed
20Law, JA & Jacobsen, SE (2010) Establishing, maintaining and modifying DNA methylation patterns in plants and animals. Nat Rev Genet 11, 204220.CrossRefGoogle ScholarPubMed
21Justin, N, De Marco, V, Aasland, R, et al. . (2010) Reading, writing and editing methylated lysines on histone tails: new insights from recent structural studies. Curr Opin Struct Biol 20, 730738.CrossRefGoogle ScholarPubMed
22Sharma, S, Kelly, TK & Jones, PA (2010) Epigenetics in cancer. Carcinogenesis 31, 2736.CrossRefGoogle ScholarPubMed
23Mani, S & Herceg, Z (2010) DNA demethylating agents and epigenetic therapy of cancer. Adv Genet 70, 327340.CrossRefGoogle ScholarPubMed
24Struewing, JP, Hartge, P, Wacholder, S, et al. . (1997) The risk of cancer associated with specific mutations of BRCA1 and BRCA2 among Ashkenazi Jews. N Engl J Med 336, 14011408.CrossRefGoogle ScholarPubMed
25Ford, D, Easton, DF, Stratton, M, et al. . (1998) Genetic heterogeneity and penetrance analysis of the BRCA1 and BRCA2 genes in breast cancer families. The Breast Cancer Linkage Consortium. Am J Hum Genet 62, 676689.CrossRefGoogle ScholarPubMed
26Suijkerbuijk, KP, Fackler, MJ, Sukumar, S, et al. . (2008) Methylation is less abundant in BRCA1-associated compared with sporadic breast cancer. Ann Oncol 19, 18701874.CrossRefGoogle ScholarPubMed
27Ai, L, Tao, Q, Zhong, S, et al. . (2006) Inactivation of Wnt inhibitory factor-1 (WIF1) expression by epigenetic silencing is a common event in breast cancer. Carcinogenesis 27, 13411348.CrossRefGoogle ScholarPubMed
28Veeck, J, Bektas, N, Hartmann, A, et al. . (2008) Wnt signalling in human breast cancer: expression of the putative Wnt inhibitor Dickkopf-3 (DKK3) is frequently suppressed by promoter hypermethylation in mammary tumours. Breast Cancer Res 10, R82.CrossRefGoogle ScholarPubMed
29Klarmann, GJ, Decker, A & Farrar, WL (2008) Epigenetic gene silencing in the Wnt pathway in breast cancer. Epigenetics 3, 5963.CrossRefGoogle ScholarPubMed
30Polyak, K & Kalluri, R (2010) The role of the microenvironment in mammary gland development and cancer. Cold Spring Harb Perspect Biol 2, a003244.CrossRefGoogle ScholarPubMed
31Lin, HJ, Zuo, T, Chao, JR, et al. . (2009) Seed in soil, with an epigenetic view. Biochim Biophys Acta 1790, 920924.CrossRefGoogle ScholarPubMed
32Conway, KE, McConnell, BB, Bowring, CE, et al. . (2000) TMS1, a novel proapoptotic caspase recruitment domain protein, is a target of methylation-induced gene silencing in human breast cancers. Cancer Res 60, 62366242.Google ScholarPubMed
33Parsons, MJ, Patel, P, Brat, DJ, et al. . (2009) Silencing of TMS1/ASC promotes resistance to anoikis in breast epithelial cells. Cancer Res 69, 17061711.CrossRefGoogle ScholarPubMed
34Bray, GA (2002) The underlying basis for obesity: relationship to cancer. J Nutr 132, 3451S3455S.CrossRefGoogle ScholarPubMed
35Lehmann, U, Hasemeier, B, Christgen, M, et al. . (2008) Epigenetic inactivation of microRNA gene hsa-mir-9-1 in human breast cancer. J Pathol 214, 1724.CrossRefGoogle ScholarPubMed
36Chen, J & Xu, X (2010) Diet, epigenetic, and cancer prevention. Adv Genet 71, 237255.CrossRefGoogle ScholarPubMed
37Burdge, GC, Slater-Jefferies, J, Torrens, C, et al. . (2007) Dietary protein restriction of pregnant rats in the F0 generation induces altered methylation of hepatic gene promoters in the adult male offspring in the F1 and F2 generations. Br J Nutr 97, 435439.CrossRefGoogle ScholarPubMed
38Kovacheva, VP, Davison, JM, Mellott, TJ, et al. . (2009) Raising gestational choline intake alters gene expression in DMBA-evoked mammary tumors and prolongs survival. FASEB J 23, 10541063.CrossRefGoogle ScholarPubMed
39Collins, JA, Blake, JM & Crosignani, PG (2005) Breast cancer risk with postmenopausal hormonal treatment. Hum Reprod Update 11, 545560.CrossRefGoogle ScholarPubMed
40Howell, A & Evans, GD (2011) Hormone replacement therapy and breast cancer. Recent Results Cancer Res 188, 115124.CrossRefGoogle ScholarPubMed
41Holmquist, GP & Ashley, T (2006) Chromosome organization and chromatin modification: influence on genome function and evolution. Cytogenet Genome Res 114, 96125.CrossRefGoogle ScholarPubMed
42Warri, A, Saarinen, NM, Makela, S, et al. . (2008) The role of early life genistein exposures in modifying breast cancer risk. Br J Cancer 98, 14851493.CrossRefGoogle ScholarPubMed
43Kim, SW & Wu, G (2009) Regulatory role for amino acids in mammary gland growth and milk synthesis. Amino Acids 37, 8995.CrossRefGoogle ScholarPubMed
44Maclennan, M & Ma, DW (2010) Role of dietary fatty acids in mammary gland development and breast cancer. Breast Cancer Res 12, 211.CrossRefGoogle ScholarPubMed
45Choi, SW & Friso, S (2011) Epigenetics: a new bridge between nutrition and health. Adv Nutr 1, 816.CrossRefGoogle Scholar
46World Cancer Research Fund and American Institute for Cancer Research (2007) Food, Nutrition, Physical Activity, and the Prevention of Cancer: A Global Perspective, pp. 289298. Washington, DC: American Institute for Cancer Research.Google Scholar
47Newmark, HL (1994) Vitamin D adequacy: a possible relationship to breast cancer. Adv Exp Med Biol 364, 109114.CrossRefGoogle ScholarPubMed
48Colditz, GA & Frazier, AL (1995) Models of breast cancer show that risk is set by events of early life: prevention efforts must shift focus. Cancer Epidemiol Biomarkers Prev 4, 567571.Google ScholarPubMed
49de Assis, S, Wang, M, Goel, S, et al. . (2006) Excessive weight gain during pregnancy increases carcinogen-induced mammary tumorigenesis in Sprague–Dawley and lean and obese Zucker rats. J Nutr 136, 9981004.CrossRefGoogle ScholarPubMed
50de Assis, S, Cruz, I, Warri, A, et al. . (2010) Exposure of rat dams to a high-fat or estradiol-supplemented diet during pregnancy alters mammary gland morphology and increases mammary cancer risk in their daughters and granddaughters. American Association of Cancer Research 101st Annual Meeting, 2931, abstract no. 2931.Google Scholar
51Tuma, RS (2002) Retinoids and lung cancer: targeting the right population. J Natl Cancer Inst 94, 969970.CrossRefGoogle ScholarPubMed
52Adissu, HA, Asem, EK & Lelievre, SA (2007) Three-dimensional cell culture to model epithelia in the female reproductive system. Reprod Sci 14, 1119.CrossRefGoogle ScholarPubMed
53Harvie, M, Hooper, L & Howell, AH (2003) Central obesity and breast cancer risk: a systematic review. Obes Rev 4, 157173.CrossRefGoogle ScholarPubMed
54Berstad, P, Coates, RJ, Bernstein, L, et al. . (2010) A case–control study of body mass index and breast cancer risk in white and African-American women. Cancer Epidemiol Biomarkers Prev 19, 15321544.CrossRefGoogle ScholarPubMed
55Harris, HR, Willett, WC, Terry, KL, et al. . (2010) Body fat distribution and risk of premenopausal breast cancer in the Nurses' Health Study II. J Natl Cancer Inst 103, 273278.CrossRefGoogle ScholarPubMed
56Trentham-Dietz, A, Newcomb, PA, Egan, KM, et al. . (2000) Weight change and risk of postmenopausal breast cancer (United States). Cancer Causes Control 11, 533542.CrossRefGoogle ScholarPubMed
57Harvie, M, Howell, A, Vierkant, RA, et al. . (2005) Association of gain and loss of weight before and after menopause with risk of postmenopausal breast cancer in the Iowa Women's Health Study. Cancer Epidemiol Biomarkers Prev 14, 656661.CrossRefGoogle ScholarPubMed
58Eliassen, AH, Colditz, GA, Rosner, B, et al. . (2006) Adult weight change and risk of postmenopausal breast cancer. JAMA 296, 193201.CrossRefGoogle ScholarPubMed
59Gluckman, PD & Hanson, MA (2008) Developmental and epigenetic pathways to obesity: an evolutionary–developmental perspective. Int J Obes (Lond) 32, Suppl. 7, S62S71.CrossRefGoogle ScholarPubMed
60Catalano, PM, Farrell, K, Thomas, A, et al. . (2009) Perinatal risk factors for childhood obesity and metabolic dysregulation. Am J Clin Nutr 90, 13031313.CrossRefGoogle ScholarPubMed
61Danielzik, S, Langnase, K, Mast, M, et al. . (2002) Impact of parental BMI on the manifestation of overweight 5–7 year old children. Eur J Nutr 41, 132138.CrossRefGoogle ScholarPubMed
62Silva, IS, De Stavola, B & McCormack, V (2008) Birth size and breast cancer risk: re-analysis of individual participant data from 32 studies. PLoS Med 5, e193.CrossRefGoogle ScholarPubMed
63Allison, DB, Paultre, F, Heymsfield, SB, et al. . (1995) Is the intra-uterine period really a critical period for the development of adiposity? Int J Obes Relat Metab Disord 19, 397402.Google ScholarPubMed
64Loos, RJ, Beunen, G, Fagard, R, et al. . (2001) Birth weight and body composition in young adult men – a prospective twin study. Int J Obes Relat Metab Disord 25, 15371545.CrossRefGoogle Scholar
65Loos, RJ, Beunen, G, Fagard, R, et al. . (2002) Birth weight and body composition in young women: a prospective twin study. Am J Clin Nutr 75, 676682.CrossRefGoogle ScholarPubMed
66Dirx, MJ, Zeegers, MP, Dagnelie, PC, et al. . (2003) Energy restriction and the risk of spontaneous mammary tumors in mice: a meta-analysis. Int J Cancer 106, 766770.CrossRefGoogle ScholarPubMed
67Lorincz, AM & Sukumar, S (2006) Molecular links between obesity and breast cancer. Endocr Relat Cancer 13, 279292.CrossRefGoogle ScholarPubMed
68Calle, EE & Kaaks, R (2004) Overweight, obesity and cancer: epidemiological evidence and proposed mechanisms. Nat Rev Cancer 4, 579591.CrossRefGoogle ScholarPubMed
69Barb, D, Williams, CJ, Neuwirth, AK, et al. . (2007) Adiponectin in relation to malignancies: a review of existing basic research and clinical evidence. Am J Clin Nutr 86, s858s866.CrossRefGoogle ScholarPubMed
70Schaffler, A, Scholmerich, J & Buechler, C (2007) Mechanisms of disease: adipokines and breast cancer – endocrine and paracrine mechanisms that connect adiposity and breast cancer. Nat Clin Pract Endocrinol Metab 3, 345354.CrossRefGoogle ScholarPubMed
71Mantzoros, C, Petridou, E, Dessypris, N, et al. . (2004) Adiponectin and breast cancer risk. J Clin Endocrinol Metab 89, 11021107.CrossRefGoogle ScholarPubMed
72Ouchi, N, Parker, JL, Lugus, JJ, et al. . (2011) Adipokines in inflammation and metabolic disease. Nat Rev Immunol 11, 8597.CrossRefGoogle ScholarPubMed
73Ouchi, N & Walsh, K (2007) Adiponectin as an anti-inflammatory factor. Clin Chim Acta 380, 2430.CrossRefGoogle ScholarPubMed
74Miyoshi, Y, Funahashi, T, Kihara, S, et al. . (2003) Association of serum adiponectin levels with breast cancer risk. Clin Cancer Res 9, 56995704.Google ScholarPubMed
75Cleary, MP, Ray, A, Rogozina, OP, et al. . (2009) Targeting the adiponectin:leptin ratio for postmenopausal breast cancer prevention. Front Biosci (Schol Ed) 1, 329357.CrossRefGoogle ScholarPubMed
76Grossmann, ME, Ray, A, Dogan, S, et al. . (2008) Balance of adiponectin and leptin modulates breast cancer cell growth. Cell Res 18, 11541156.CrossRefGoogle ScholarPubMed
77Grossmann, ME, Nkhata, KJ, Mizuno, NK, et al. . (2008) Effects of adiponectin on breast cancer cell growth and signaling. Br J Cancer 98, 370379.CrossRefGoogle ScholarPubMed
78Vona-Davis, L & Rose, DP (2007) Adipokines as endocrine, paracrine, and autocrine factors in breast cancer risk and progression. Endocr Relat Cancer 14, 189206.CrossRefGoogle ScholarPubMed
79Kabat, GC, Kim, M, Caan, BJ, et al. . (2009) Repeated measures of serum glucose and insulin in relation to postmenopausal breast cancer. Int J Cancer 125, 27042710.CrossRefGoogle ScholarPubMed
80Novosyadlyy, R, Lann, DE, Vijayakumar, A, et al. . (2010) Insulin-mediated acceleration of breast cancer development and progression in a nonobese model of type 2 diabetes. Cancer Res 70, 741751.CrossRefGoogle Scholar
81Rabe, K, Lehrke, M, Parhofer, KG, et al. . (2008) Adipokines and insulin resistance. Mol Med 14, 741751.CrossRefGoogle ScholarPubMed
82Subbaramaiah, K, Howe, LR, Bhardwaj, P, et al. . (2011) Obesity is associated with inflammation and elevated aromatase expression in the mouse mammary gland. Cancer Prev Res (Phila) 4, 329346.CrossRefGoogle ScholarPubMed
83Heerwagen, MJ, Miller, MR, Barbour, LA, et al. . (2010) Maternal obesity and fetal metabolic programming: a fertile epigenetic soil. Am J Physiol Regul Integr Comp Physiol 299, R711R722.CrossRefGoogle ScholarPubMed
84Lo, CY, Hsieh, PH, Chen, HF, et al. . (2009) A maternal high-fat diet during pregnancy in rats results in a greater risk of carcinogen-induced mammary tumors in the female offspring than exposure to a high-fat diet in postnatal life. Int J Cancer 125, 767773.CrossRefGoogle Scholar
85Zhang, J, Zhang, F, Didelot, X, et al. . (2009) Maternal high fat diet during pregnancy and lactation alters hepatic expression of insulin like growth factor-2 and key microRNAs in the adult offspring. BMC Genomics 10, 478.CrossRefGoogle ScholarPubMed
86Vickers, MH, Breier, BH, Cutfield, WS, et al. . (2000) Fetal origins of hyperphagia, obesity, and hypertension and postnatal amplification by hypercaloric nutrition. Am J Physiol Endocrinol Metab 279, E83E87.CrossRefGoogle ScholarPubMed
87Velie, EM, Schairer, C, Flood, A, et al. . (2005) Empirically derived dietary patterns and risk of postmenopausal breast cancer in a large prospective cohort study. Am J Clin Nutr 82, 13081319.CrossRefGoogle Scholar
88Waterland, RA, Travisano, M, Tahiliani, KG, et al. . (2008) Methyl donor supplementation prevents transgenerational amplification of obesity. Int J Obes (Lond) 32, 13731379.CrossRefGoogle ScholarPubMed
89Milagro, FI, Campion, J, Garcia-Diaz, DF, et al. . (2009) High fat diet-induced obesity modifies the methylation pattern of leptin promoter in rats. J Physiol Biochem 65, 19.CrossRefGoogle ScholarPubMed
90Thornburg, KL, Shannon, J, Thuillier, P, et al. . (2010) In utero life and epigenetic predisposition for disease. Adv Genet 71, 5778.CrossRefGoogle ScholarPubMed
91Michels, KB & Xue, F (2006) Role of birthweight in the etiology of breast cancer. Int J Cancer 119, 20072025.CrossRefGoogle ScholarPubMed
92Malin, AS, Qi, D, Shu, XO, et al. . (2003) Intake of fruits, vegetables and selected micronutrients in relation to the risk of breast cancer. Int J Cancer 105, 413418.CrossRefGoogle Scholar
93Bessaoud, F, Daures, JP & Gerber, M (2008) Dietary factors and breast cancer risk: a case control study among a population in Southern France. Nutr Cancer 60, 177187.CrossRefGoogle Scholar
94Mattisson, I, Wirfalt, E, Johansson, U, et al. . (2004) 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 90, 122127.CrossRefGoogle Scholar
95Agurs-Collins, T, Rosenberg, L, Makambi, K, et al. . (2009) Dietary patterns and breast cancer risk in women participating in the Black Women's Health Study. Am J Clin Nutr 90, 621628.CrossRefGoogle ScholarPubMed
96Sieri, S, Krogh, V, Bolelli, G, et al. . (2009) Sex hormone levels, breast cancer risk, and cancer receptor status in postmenopausal women: the ORDET cohort. Cancer Epidemiol Biomarkers Prev 18, 169176.CrossRefGoogle ScholarPubMed
97Terry, P, Suzuki, R, Hu, FB, et al. . (2001) A prospective study of major dietary patterns and the risk of breast cancer. Cancer Epidemiol Biomarkers Prev 10, 12811285.Google ScholarPubMed
98Adebamowo, CA, Hu, FB, Cho, E, et al. . (2005) Dietary patterns and the risk of breast cancer. Ann Epidemiol 15, 789795.CrossRefGoogle ScholarPubMed
99Gonzalez, CA & Riboli, E (2010) Diet and cancer prevention: contributions from the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Eur J Cancer 46, 25552562.CrossRefGoogle ScholarPubMed
100van Gils, CH, Peeters, PH, Bueno-de-Mesquita, HB, et al. . (2005) Consumption of vegetables and fruits and risk of breast cancer. JAMA 293, 183193.CrossRefGoogle ScholarPubMed
101Brennan, SF, Cantwell, MM, Cardwell, CR, et al. . (2010) Dietary patterns and breast cancer risk: a systematic review and meta-analysis. Am J Clin Nutr 91, 12941302.CrossRefGoogle Scholar
102Smith-Warner, SA, Spiegelman, D, Yaun, SS, et al. . (2001) Intake of fruits and vegetables and risk of breast cancer: a pooled analysis of cohort studies. JAMA 285, 769776.CrossRefGoogle ScholarPubMed
103Sieri, S, Krogh, V, Pala, V, et al. . (2004) Dietary patterns and risk of breast cancer in the ORDET cohort. Cancer Epidemiol Biomarkers Prev 13, 567572.CrossRefGoogle ScholarPubMed
104Cottet, V, Touvier, M, Fournier, A, et al. . (2009) Postmenopausal breast cancer risk and dietary patterns in the E3N-EPIC prospective cohort study. Am J Epidemiol 170, 12571267.CrossRefGoogle ScholarPubMed
105Lissowska, J, Gaudet, MM, Brinton, LA, et al. . (2008) Intake of fruits, and vegetables in relation to breast cancer risk by hormone receptor status. Breast Cancer Res Treat 107, 113117.CrossRefGoogle ScholarPubMed
106Olsen, A, Tjonneland, A, Thomsen, BL, et al. . (2003) Fruits and vegetables intake differentially affects estrogen receptor negative and positive breast cancer incidence rates. J Nutr 133, 23422347.CrossRefGoogle ScholarPubMed
107Fung, TT, Hu, FB, McCullough, ML, et al. . (2006) Diet quality is associated with the risk of estrogen receptor-negative breast cancer in postmenopausal women. J Nutr 136, 466472.CrossRefGoogle ScholarPubMed
108Edefonti, V, Decarli, A, La Vecchia, C, et al. . (2008) Nutrient dietary patterns and the risk of breast and ovarian cancers. Int J Cancer 122, 609613.CrossRefGoogle ScholarPubMed
109de Stefani, E, Deneo-Pellegrini, H, Boffetta, P, et al. . (2009) Dietary patterns and risk of cancer: a factor analysis in Uruguay. Int J Cancer 124, 13911397.CrossRefGoogle Scholar
110Cui, X, Dai, Q, Tseng, M, et al. . (2007) Dietary patterns and breast cancer risk in the Shanghai Breast Cancer Study. Cancer Epidemiol Biomarkers Prev 16, 14431448.CrossRefGoogle ScholarPubMed
111Murtaugh, MA, Sweeney, C, Giuliano, AR, et al. . (2008) Diet patterns and breast cancer risk in Hispanic and non-Hispanic white women: the Four-Corners Breast Cancer Study. Am J Clin Nutr 87, 978984.CrossRefGoogle ScholarPubMed
112Hirose, K, Matsuo, K, Iwata, H, et al. . (2007) Dietary patterns and the risk of breast cancer in Japanese women. Cancer Sci 98, 14311438.CrossRefGoogle ScholarPubMed
113Larsson, SC, Bergkvist, L & Wolk, A (2009) Long-term meat intake and risk of breast cancer by oestrogen and progesterone receptor status in a cohort of Swedish women. Eur J Cancer 45, 30423046.CrossRefGoogle Scholar
114Steinmetz, KA & Potter, JD (1996) Vegetables, fruit, and cancer prevention: a review. J Am Diet Assoc 96, 10271039.CrossRefGoogle ScholarPubMed
115Batra, S, Sahu, RP, Kandala, PK, et al. . (2010) Benzyl isothiocyanate-mediated inhibition of histone deacetylase leads to NF-κB turnoff in human pancreatic carcinoma cells. Mol Cancer Ther 9, 15961608.CrossRefGoogle ScholarPubMed
116Prentice, RL, Caan, B, Chlebowski, RT, et al. . (2006) Low-fat dietary pattern and risk of invasive breast cancer: the Women's Health Initiative Randomized Controlled Dietary Modification Trial. JAMA 295, 629642.CrossRefGoogle ScholarPubMed
117Martin, LJ, Li, Q, Melnichouk, O, et al. . (2011) A randomized trial of dietary intervention for breast cancer prevention. Cancer Res 71, 123133.CrossRefGoogle ScholarPubMed
118Geisel, J, Schorr, H, Bodis, M, et al. . (2005) The vegetarian lifestyle and DNA methylation. Clin Chem Lab Med 43, 11641169.CrossRefGoogle ScholarPubMed
119Lillycrop, KA, Phillips, ES, Torrens, C, et al. . (2008) Feeding pregnant rats a protein-restricted diet persistently alters the methylation of specific cytosines in the hepatic PPARα promoter of the offspring. Br J Nutr 100, 278282.CrossRefGoogle ScholarPubMed
120Mathers, JC & McKay, JA (2009) Epigenetics – potential contribution to fetal programming. Adv Exp Med Biol 646, 119123.CrossRefGoogle ScholarPubMed
121Wu, AH, Yu, MC, Tseng, CC, et al. . (2008) Epidemiology of soy exposures and breast cancer risk. Br J Cancer 98, 914.CrossRefGoogle ScholarPubMed
122Messina, M, McCaskill-Stevens, W & Lampe, JW (2006) Addressing the soy and breast cancer relationship: review, commentary, and workshop proceedings. J Natl Cancer Inst 98, 12751284.CrossRefGoogle ScholarPubMed
123Wu, AH, Ziegler, RG, Nomura, AM, et al. . (1998) Soy intake and risk of breast cancer in Asians and Asian Americans. Am J Clin Nutr 68, 1437S1443S.CrossRefGoogle ScholarPubMed
124Henderson, BE & Bernstein, L (1991) The international variation in breast cancer rates: an epidemiological assessment. Breast Cancer Res Treat 18, Suppl. 1, S11S17.CrossRefGoogle ScholarPubMed
125Ziegler, RG, Hoover, RN, Pike, MC, et al. . (1993) Migration patterns and breast cancer risk in Asian-American women. J Natl Cancer Inst 85, 18191827.CrossRefGoogle ScholarPubMed
126Trock, BJ, Hilakivi-Clarke, L & Clarke, R (2006) Meta-analysis of soy intake and breast cancer risk. J Natl Cancer Inst 98, 459471.CrossRefGoogle ScholarPubMed
127Korde, LA, Wu, AH, Fears, T, et al. . (2009) Childhood soy intake and breast cancer risk in Asian American women. Cancer Epidemiol Biomarkers Prev 18, 10501059.CrossRefGoogle ScholarPubMed
128Thanos, J, Cotterchio, M, Boucher, BA, et al. . (2006) Adolescent dietary phytoestrogen intake and breast cancer risk (Canada). Cancer Causes Control 17, 12531261.CrossRefGoogle ScholarPubMed
129Shu, XO, Jin, F, Dai, Q, et al. . (2001) Soyfood intake during adolescence and subsequent risk of breast cancer among Chinese women. Cancer Epidemiol Biomarkers Prev 10, 483488.Google ScholarPubMed
130Dong, JY & Qin, LQ (2011) Soy isoflavones consumption and risk of breast cancer incidence or recurrence: a meta-analysis of prospective studies. Breast Cancer Res Treat 125, 315323.CrossRefGoogle ScholarPubMed
131Lamartiniere, CA, Moore, JB, Brown, NM, et al. . (1995) Genistein suppresses mammary cancer in rats. Carcinogenesis 16, 28332840.CrossRefGoogle ScholarPubMed
132Barnes, S, Peterson, TG & Coward, L (1995) Rationale for the use of genistein-containing soy matrices in chemoprevention trials for breast and prostate cancer. J Cell Biochem Suppl 22, 181187.CrossRefGoogle ScholarPubMed
133Barnes, S (1997) The chemopreventive properties of soy isoflavonoids in animal models of breast cancer. Breast Cancer Res Treat 46, 169179.CrossRefGoogle ScholarPubMed
134Constantinou, AI, Mehta, RG & Vaughan, A (1996) Inhibition of N-methyl-N-nitrosourea-induced mammary tumors in rats by the soybean isoflavones. Anticancer Res 16, 32933298.Google ScholarPubMed
135Constantinou, AI, White, BE, Tonetti, D, et al. . (2005) The soy isoflavone daidzein improves the capacity of tamoxifen to prevent mammary tumours. Eur J Cancer 41, 647654.CrossRefGoogle ScholarPubMed
136Constantinou, AI, Lantvit, D, Hawthorne, M, et al. . (2001) Chemopreventive effects of soy protein and purified soy isoflavones on DMBA-induced mammary tumors in female Sprague–Dawley rats. Nutr Cancer 41, 7581.CrossRefGoogle ScholarPubMed
137Gotoh, T, Yamada, K, Yin, H, et al. . (1998) Chemoprevention of N-nitroso-N-methylurea-induced rat mammary carcinogenesis by soy foods or biochanin A. Jpn J Cancer Res 89, 137142.CrossRefGoogle ScholarPubMed
138Lamartiniere, CA, Cotroneo, MS, Fritz, WA, et al. . (2002) Genistein chemoprevention: timing and mechanisms of action in murine mammary and prostate. J Nutr 132, 552S558S.CrossRefGoogle ScholarPubMed
139Lamartiniere, CA, Wang, J, Smith-Johnson, M, et al. . (2002) Daidzein: bioavailability, potential for reproductive toxicity, and breast cancer chemoprevention in female rats. Toxicol Sci 65, 228238.CrossRefGoogle ScholarPubMed
140Hsieh, CY, Santell, RC, Haslam, SZ, et al. . (1998) Estrogenic effects of genistein on the growth of estrogen receptor-positive human breast cancer (MCF-7) cells in vitro and in vivo. Cancer Res 58, 38333838.Google ScholarPubMed
141Cohen, LA, Zhao, Z, Pittman, B, et al. . (2000) Effect of intact and isoflavone-depleted soy protein on NMU-induced rat mammary tumorigenesis. Carcinogenesis 21, 929935.CrossRefGoogle ScholarPubMed
142Wood, CE, Kaplan, JR, Stute, P, et al. . (2006) Effects of soy on the mammary glands of premenopausal female monkeys. Fertil Steril 85, Suppl. 1, 11791186.CrossRefGoogle ScholarPubMed
143Kim, H, Hall, P, Smith, M, et al. . (2004) Chemoprevention by grape seed extract and genistein in carcinogen-induced mammary cancer in rats is diet dependent. J Nutr 134, 3445S3452S.CrossRefGoogle ScholarPubMed
144Stedman, L, Nickel, KP, Castillo, SS, et al. . (2003) 1,25-dihydroxyvitamin D inhibits vitamin E succinate-induced apoptosis in C3H10T1/2 cells but not Harvey ras-transfected cells. Nutr Cancer 45, 93100.CrossRefGoogle Scholar
145de Souza, PL, Russell, PJ, Kearsley, JH, et al. . (2010) Clinical pharmacology of isoflavones and its relevance for potential prevention of prostate cancer. Nutr Rev 68, 542555.CrossRefGoogle ScholarPubMed
146Pavese, JM, Farmer, RL & Bergan, RC (2010) Inhibition of cancer cell invasion and metastasis by genistein. Cancer Metastasis Rev 29, 465482.CrossRefGoogle ScholarPubMed
147Hooper, L, Madhavan, G, Tice, JA, et al. . (2010) Effects of isoflavones on breast density in pre- and post-menopausal women: a systematic review and meta-analysis of randomized controlled trials. Hum Reprod Update 16, 745760.CrossRefGoogle ScholarPubMed
148Maskarinec, G, Verheus, M, Steinberg, FM, et al. . (2009) Various doses of soy isoflavones do not modify mammographic density in postmenopausal women. J Nutr 139, 981986.CrossRefGoogle Scholar
149Verheus, M, van Gils, CH, Kreijkamp-Kaspers, S, et al. . (2008) Soy protein containing isoflavones and mammographic density in a randomized controlled trial in postmenopausal women. Cancer Epidemiol Biomarkers Prev 17, 26322638.CrossRefGoogle Scholar
150Powles, TJ, Howell, A, Evans, DG, et al. . (2008) Red clover isoflavones are safe and well tolerated in women with a family history of breast cancer. Menopause Int 14, 612.CrossRefGoogle ScholarPubMed
151Maskarinec, G, Takata, Y, Franke, AA, et al. . (2004) A 2-year soy intervention in premenopausal women does not change mammographic densities. J Nutr 134, 30893094.CrossRefGoogle Scholar
152Hilakivi-Clarke, L, Cho, E, Raygada, M, et al. . (1997) Alterations in mammary gland development following neonatal exposure to estradiol, transforming growth factor α, and estrogen receptor antagonist ICI 182,780. J Cell Physiol 170, 279289.3.0.CO;2-L>CrossRefGoogle ScholarPubMed
153Hilakivi-Clarke, L, Onojafe, I, Raygada, M, et al. . (1999) Prepubertal exposure to zearalenone or genistein reduces mammary tumorigenesis. Br J Cancer 80, 16821688.CrossRefGoogle ScholarPubMed
154Hilakivi-Clarke, L, Cho, E, Onojafe, I, et al. . (1999) Maternal exposure to genistein during pregnancy increases carcinogen-induced mammary tumorigenesis in female rat offspring. Oncol Rep 6, 10891095.Google ScholarPubMed
155Petersen, OW & Polyak, K (2010) Stem cells in the human breast. Cold Spring Harb Perspect Biol 2, a003160.CrossRefGoogle ScholarPubMed
156Dolinoy, DC, Weidman, JR, Waterland, RA, et al. . (2006) Maternal genistein alters coat color and protects Avy mouse offspring from obesity by modifying the fetal epigenome. Environ Health Perspect 114, 567572.CrossRefGoogle ScholarPubMed
157Dolinoy, DC, Huang, D & Jirtle, RL (2007) Maternal nutrient supplementation counteracts bisphenol A-induced DNA hypomethylation in early development. Proc Natl Acad Sci U S A 104, 1305613061.CrossRefGoogle ScholarPubMed
158Qin, W, Zhu, W, Shi, H, et al. . (2009) Soy isoflavones have an antiestrogenic effect and alter mammary promoter hypermethylation in healthy premenopausal women. Nutr Cancer 61, 238244.CrossRefGoogle ScholarPubMed
159Berner, C, Aumuller, E, Gnauck, A, et al. . (2010) Epigenetic control of estrogen receptor expression and tumor suppressor genes is modulated by bioactive food compounds. Ann Nutr Metab 57, 183189.CrossRefGoogle ScholarPubMed
160Kabat, GC, Kim, M, Shikany, JM, et al. . (2010) Alcohol consumption and risk of ductal carcinoma in situ of the breast in a cohort of postmenopausal women. Cancer Epidemiol Biomarkers Prev 19, 20662072.CrossRefGoogle Scholar
161Engeset, D, Dyachenko, A, Ciampi, A, et al. . (2009) Dietary patterns and risk of cancer of various sites in the Norwegian European Prospective Investigation into Cancer and Nutrition cohort: the Norwegian Women and Cancer study. Eur J Cancer Prev 18, 6975.CrossRefGoogle ScholarPubMed
162Smith-Warner, SA, Spiegelman, D, Yaun, SS, et al. . (1998) Alcohol and breast cancer in women: a pooled analysis of cohort studies. JAMA 279, 535540.CrossRefGoogle ScholarPubMed
163Viel, JF, Perarnau, JM, Challier, B, et al. . (1997) Alcoholic calories, red wine consumption and breast cancer among premenopausal women. Eur J Epidemiol 13, 639643.CrossRefGoogle ScholarPubMed
164Zhang, SM, Lee, IM, Manson, JE, et al. . (2007) Alcohol consumption and breast cancer risk in the Women's Health Study. Am J Epidemiol 165, 667676.CrossRefGoogle ScholarPubMed
165Vachon, CM, Kuni, CC, Anderson, K, et al. . (2000) Association of mammographically defined percent breast density with epidemiologic risk factors for breast cancer (United States). Cancer Causes Control 11, 653662.CrossRefGoogle ScholarPubMed
166Newcomb, PA, Nichols, HB, Beasley, JM, et al. . (2009) No difference between red wine or white wine consumption and breast cancer risk. Cancer Epidemiol Biomarkers Prev 18, 10071010.CrossRefGoogle ScholarPubMed
167Berstad, P, Ma, H, Bernstein, L, et al. . (2008) Alcohol intake and breast cancer risk among young women. Breast Cancer Res Treat 108, 113120.CrossRefGoogle ScholarPubMed
168Ellison, RC, Zhang, Y, McLennan, CE, et al. . (2001) Exploring the relation of alcohol consumption to risk of breast cancer. Am J Epidemiol 154, 740747.CrossRefGoogle ScholarPubMed
169Key, J, Hodgson, S, Omar, RZ, et al. . (2006) Meta-analysis of studies of alcohol and breast cancer with consideration of the methodological issues. Cancer Causes Control 17, 759770.CrossRefGoogle ScholarPubMed
170Tjonneland, A, Christensen, J, Olsen, A, et al. . (2007) Alcohol intake and breast cancer risk: the European Prospective Investigation into Cancer and Nutrition (EPIC). Cancer Causes Control 18, 361373.CrossRefGoogle ScholarPubMed
171Lew, JQ, Freedman, ND, Leitzmann, MF, et al. . (2009) Alcohol and risk of breast cancer by histologic type and hormone receptor status in postmenopausal women: the NIH-AARP Diet and Health Study. Am J Epidemiol 170, 308317.CrossRefGoogle ScholarPubMed
172Poschl, G & Seitz, HK (2004) Alcohol and cancer. Alcohol Alcohol 39, 155165.CrossRefGoogle ScholarPubMed
173Boffetta, P & Hashibe, M (2006) Alcohol and cancer. Lancet Oncol 7, 149156.CrossRefGoogle ScholarPubMed
174Seitz, HK & Stickel, F (2007) Molecular mechanisms of alcohol-mediated carcinogenesis. Nat Rev Cancer 7, 599612.CrossRefGoogle ScholarPubMed
175Reichman, ME, Judd, JT, Longcope, C, et al. . (1993) Effects of alcohol consumption on plasma and urinary hormone concentrations in premenopausal women. J Natl Cancer Inst 85, 722727.CrossRefGoogle ScholarPubMed
176Ginsburg, ES, Walsh, BW, Gao, X, et al. . (1995) The effect of acute ethanol ingestion on estrogen levels in postmenopausal women using transdermal estradiol. J Soc Gynecol Investig 2, 2629.CrossRefGoogle ScholarPubMed
177Brooks, PJ (1997) DNA damage, DNA repair, and alcohol toxicity – a review. Alcohol Clin Exp Res 21, 10731082.Google ScholarPubMed
178Christensen, BC, Kelsey, KT, Zheng, S, et al. . (2010) Breast cancer DNA methylation profiles are associated with tumor size and alcohol and folate intake. PLoS Genet 6, e1001043.CrossRefGoogle ScholarPubMed
179Hursting, SD, Thornquist, M & Henderson, MM (1990) Types of dietary fat and the incidence of cancer at five sites. Prev Med 19, 242253.CrossRefGoogle ScholarPubMed
180Armstrong, B & Doll, R (1975) Environmental factors and cancer incidence and mortality in different countries, with special reference to dietary practices. Int J Cancer 15, 617631.CrossRefGoogle ScholarPubMed
181Lea, AJ (1966) Dietary factors associated with death-rates from certain neoplasms in man. Lancet ii, 332333.CrossRefGoogle Scholar
182Rose, DP, Boyar, AP & Wynder, EL (1986) International comparisons of mortality rates for cancer of the breast, ovary, prostate, and colon, and per capita food consumption. Cancer 58, 23632371.3.0.CO;2-#>CrossRefGoogle ScholarPubMed
183Howe, GR, Hirohata, T, Hislop, TG, et al. . (1990) Dietary factors and risk of breast cancer: combined analysis of 12 case–control studies. J Natl Cancer Inst 82, 561569.CrossRefGoogle ScholarPubMed
184Smith-Warner, SA, Spiegelman, D, Adami, HO, et al. . (2001) Types of dietary fat and breast cancer: a pooled analysis of cohort studies. Int J Cancer 92, 767774.3.0.CO;2-0>CrossRefGoogle ScholarPubMed
185Willett, WC (1990) Epidemiologic studies of diet and cancer. Prog Clin Biol Res 346, 159168.Google ScholarPubMed
186Willett, WC, Hunter, DJ, Stampfer, MJ, et al. . (1992) Dietary fat and fiber in relation to risk of breast cancer. An 8-year follow-up. JAMA 268, 20372044.CrossRefGoogle Scholar
187Schulz, M, Hoffmann, K, Weikert, C, et al. . (2008) Identification of a dietary pattern characterized by high-fat food choices associated with increased risk of breast cancer: the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam Study. Br J Nutr 100, 942946.CrossRefGoogle ScholarPubMed
188Alexander, DD, Morimoto, LM, Mink, PJ, et al. . (2010) A review and meta-analysis of red and processed meat consumption and breast cancer. Nutr Res Rev 23, 349365.CrossRefGoogle ScholarPubMed
189Bougnoux, P, Hajjaji, N & Couet, C (2008) The lipidome as a composite biomarker of the modifiable part of the risk of breast cancer. Prostaglandins Leukot Essent Fatty Acids 79, 9396.CrossRefGoogle ScholarPubMed
190Chajes, V, Thiebaut, AC, Rotival, M, et al. . (2008) Association between serum trans-monounsaturated fatty acids and breast cancer risk in the E3N-EPIC Study. Am J Epidemiol 167, 13121320.CrossRefGoogle ScholarPubMed
191Kim, EH, Willett, WC, Colditz, GA, et al. . (2006) Dietary fat and risk of postmenopausal breast cancer in a 20-year follow-up. Am J Epidemiol 164, 990997.CrossRefGoogle Scholar
192Linos, E, Willett, WC, Cho, E, et al. . (2010) Adolescent diet in relation to breast cancer risk among premenopausal women. Cancer Epidemiol Biomarkers Prev 19, 689696.CrossRefGoogle ScholarPubMed
193Fay, MP & Freedman, LS (1997) Meta-analyses of dietary fats and mammary neoplasms in rodent experiments. Breast Cancer Res Treat 46, 215223.CrossRefGoogle ScholarPubMed
194Freedman, LS, Clifford, C & Messina, M (1990) Analysis of dietary fat, calories, body weight, and the development of mammary tumors in rats and mice: a review. Cancer Res 50, 57105719.Google ScholarPubMed
195Welsch, CW, House, JL, Herr, BL, et al. . (1990) Enhancement of mammary carcinogenesis by high levels of dietary fat: a phenomenon dependent on ad libitum feeding. J Natl Cancer Inst 82, 16151620.CrossRefGoogle ScholarPubMed
196Welsch, CW (1992) Dietary fat, calories, and mammary gland tumorigenesis. Adv Exp Med Biol 322, 203222.CrossRefGoogle ScholarPubMed
197Kritchevsky, D, Weber, MM & Klurfeld, DM (1984) Dietary fat versus caloric content in initiation and promotion of 7,12-dimethylbenz(a)anthracene-induced mammary tumorigenesis in rats. Cancer Res 44, 31743177.Google Scholar
198Klurfeld, DM, Weber, MM & Kritchevsky, D (1987) Inhibition of chemically induced mammary and colon tumor promotion by caloric restriction in rats fed increased dietary fat. Cancer Res 47, 27592762.Google ScholarPubMed
199Woutersen, RA, Appel, MJ, Van Garderen-Hoetmer, A, et al. . (1999) Dietary fat and carcinogenesis. Mutat Res 443, 111127.CrossRefGoogle ScholarPubMed
200Chapkin, RS, Wang, N, Fan, YY, et al. . (2008) Docosahexaenoic acid alters the size and distribution of cell surface microdomains. Biochim Biophys Acta 1778, 466471.CrossRefGoogle ScholarPubMed
201Simopoulos, AP (2010) Genetic variants in the metabolism of omega-6 and omega-3 fatty acids: their role in the determination of nutritional requirements and chronic disease risk. Exp Biol Med (Maywood) 235, 785795.CrossRefGoogle Scholar
202Larsson, SC, Kumlin, M, Ingelman-Sundberg, M, et al. . (2004) Dietary long-chain n-3 fatty acids for the prevention of cancer: a review of potential mechanisms. Am J Clin Nutr 79, 935945.CrossRefGoogle Scholar
203de Assis, S, Khan, G & Hilakivi-Clarke, L (2006) High birth weight increases mammary tumorigenesis in rats. Int J Cancer 119, 15371546.CrossRefGoogle ScholarPubMed
204Vucetic, Z, Kimmel, J, Totoki, K, et al. . (2010) Maternal high-fat diet alters methylation and gene expression of dopamine and opioid-related genes. Endocrinology 151, 47564764.CrossRefGoogle ScholarPubMed
205Yenbutr, P, Hilakivi-Clarke, L & Passaniti, A (1998) Hypomethylation of an exon I estrogen receptor CpG island in spontaneous and carcinogen-induced mammary tumorigenesis in the rat. Mech Ageing Dev 106, 93102.CrossRefGoogle ScholarPubMed
206Mahoney, MC, Bevers, T, Linos, E, et al. . (2008) Opportunities and strategies for breast cancer prevention through risk reduction. CA Cancer J Clin 58, 347371.CrossRefGoogle ScholarPubMed
207Romieu, I, Lazcano-Ponce, E, Sanchez-Zamorano, LM, et al. . (2004) Carbohydrates and the risk of breast cancer among Mexican women. Cancer Epidemiol Biomarkers Prev 13, 12831289.CrossRefGoogle ScholarPubMed
208Gomez, LM, Hernandez-Prado, B, Morales, MC, et al. . (2009) Physical activity and overweight/obesity in adult Mexican population: the Mexican National Health and Nutrition Survey 2006. Salud Publica Mex 51, Suppl. 4, S621S629.CrossRefGoogle ScholarPubMed
209Frazier, AL, Li, L, Cho, E, et al. . (2004) Adolescent diet and risk of breast cancer. Cancer Causes Control 15, 7382.CrossRefGoogle ScholarPubMed
210Larsson, SC, Bergkvist, L & Wolk, A (2009) Glycemic load, glycemic index and breast cancer risk in a prospective cohort of Swedish women. Int J Cancer 125, 153157.CrossRefGoogle Scholar
211Lajous, M, Boutron-Ruault, MC, Fabre, A, et al. . (2008) Carbohydrate intake, glycemic index, glycemic load, and risk of postmenopausal breast cancer in a prospective study of French women. Am J Clin Nutr 87, 13841391.CrossRefGoogle Scholar
212Nielsen, TG, Olsen, A, Christensen, J, et al. . (2005) Dietary carbohydrate intake is not associated with the breast cancer incidence rate ratio in postmenopausal Danish women. J Nutr 135, 124128.CrossRefGoogle Scholar
213Yanochko, GM & Eckhart, W (2006) Type I insulin-like growth factor receptor over-expression induces proliferation and anti-apoptotic signaling in a three-dimensional culture model of breast epithelial cells. Breast Cancer Res 8, R18.CrossRefGoogle Scholar
214Key, TJ, Appleby, PN, Reeves, GK, et al. . (2010) Insulin-like growth factor 1 (IGF1), IGF binding protein 3 (IGFBP3), and breast cancer risk: pooled individual data analysis of 17 prospective studies. Lancet Oncol 11, 530542.Google ScholarPubMed
215Lewis, SJ, Harbord, RM, Harris, R, et al. . (2006) Meta-analyses of observational and genetic association studies of folate intakes or levels and breast cancer risk. J Natl Cancer Inst 98, 16071622.CrossRefGoogle ScholarPubMed
216Zhang, S, Hunter, DJ, Hankinson, SE, et al. . (1999) A prospective study of folate intake and the risk of breast cancer. JAMA 281, 16321637.CrossRefGoogle ScholarPubMed
217Larsson, SC, Giovannucci, E & Wolk, A (2007) Folate and risk of breast cancer: a meta-analysis. J Natl Cancer Inst 99, 6476.CrossRefGoogle ScholarPubMed
218Mason, JB & Choi, SW (2000) Folate and carcinogenesis: developing a unifying hypothesis. Adv Enzyme Regul 40, 127141.CrossRefGoogle ScholarPubMed
219Stolzenberg-Solomon, RZ, Chang, SC & Leitzmann, MF (2006) Folate intake, alcohol use, and postmenopausal breast cancer risk in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. Am J Clin Nutr 83, 895904.CrossRefGoogle ScholarPubMed
220Chen, J, Gammon, MD, Chan, W, et al. . (2005) One-carbon metabolism, MTHFR polymorphisms, and risk of breast cancer. Cancer Res 65, 16061614.CrossRefGoogle ScholarPubMed
221Lajous, M, Lazcano-Ponce, E, Hernandez-Avila, M, et al. . (2006) Vitamin B6, and vitamin B12 intake and the risk of breast cancer among Mexican women. Cancer Epidemiol Biomarkers Prev 15, 443448.CrossRefGoogle ScholarPubMed
222Levi, F, Pasche, C, Lucchini, F, et al. . (2001) Dietary intake of selected micronutrients and breast-cancer risk. Int J Cancer 91, 260263.3.0.CO;2-#>CrossRefGoogle ScholarPubMed
223Negri, E, La Vecchia, C & Franceschi, S (2000) Re: dietary folate consumption and breast cancer risk. J Natl Cancer Inst 92, 12701271.CrossRefGoogle ScholarPubMed
224Ronco, A, de Stefani, E, Boffetta, P, et al. . (1999) Vegetables, fruits, and related nutrients and risk of breast cancer: a case–control study in Uruguay. Nutr Cancer 35, 111119.CrossRefGoogle ScholarPubMed
225Shrubsole, MJ, Gao, YT, Cai, Q, et al. . (2004) MTHFR polymorphisms, dietary folate intake, and breast cancer risk: results from the Shanghai Breast Cancer Study. Cancer Epidemiol Biomarkers Prev 13, 190196.CrossRefGoogle ScholarPubMed
226Lajous, M, Romieu, I, Sabia, S, et al. . (2006) Folate, vitamin B12 and postmenopausal breast cancer in a prospective study of French women. Cancer Causes Control 17, 12091213.CrossRefGoogle Scholar
227Shrubsole, MJ, Jin, F, Dai, Q, et al. . (2001) Dietary folate intake and breast cancer risk: results from the Shanghai Breast Cancer Study. Cancer Res 61, 71367141.Google ScholarPubMed
228Zhang, SM, Willett, WC, Selhub, J, et al. . (2003) Plasma folate, vitamin B6, vitamin B12, homocysteine, and risk of breast cancer. J Natl Cancer Inst 95, 373380.CrossRefGoogle ScholarPubMed
229Ericson, U, Borgquist, S, Ivarsson, MI, et al. . (2010) Plasma folate concentrations are positively associated with risk of estrogen receptor β negative breast cancer in a Swedish nested case control study. J Nutr 140, 16611668.CrossRefGoogle Scholar
230Kim, YI (2005) Nutritional epigenetics: impact of folate deficiency on DNA methylation and colon cancer susceptibility. J Nutr 135, 27032709.CrossRefGoogle ScholarPubMed
231Kim, YI (2004) Will mandatory folic acid fortification prevent or promote cancer? Am J Clin Nutr 80, 11231128.CrossRefGoogle ScholarPubMed
232Choi, SW & Mason, JB (2000) Folate and carcinogenesis: an integrated scheme. J Nutr 130, 129132.CrossRefGoogle ScholarPubMed
233Kotsopoulos, J, Medline, A, Renlund, R, et al. . (2005) Effects of dietary folate on the development and progression of mammary tumors in rats. Carcinogenesis 26, 16031612.CrossRefGoogle ScholarPubMed
234Kotsopoulos, J, Sohn, KJ, Martin, R, et al. . (2003) Dietary folate deficiency suppresses N-methyl-N-nitrosourea-induced mammary tumorigenesis in rats. Carcinogenesis 24, 937944.CrossRefGoogle ScholarPubMed
235Baggott, JE, Vaughn, WH, Juliana, MM, et al. . (1992) Effects of folate deficiency and supplementation on methylnitrosourea-induced rat mammary tumors. J Natl Cancer Inst 84, 17401744.CrossRefGoogle ScholarPubMed
236Mason, JB & Choi, SW (2005) Effects of alcohol on folate metabolism: implications for carcinogenesis. Alcohol 35, 235241.CrossRefGoogle ScholarPubMed
237Lin, J, Lee, IM, Cook, NR, et al. . (2008) Plasma folate, vitamin B-6, vitamin B-12, and risk of breast cancer in women. Am J Clin Nutr 87, 734743.CrossRefGoogle ScholarPubMed
238Williams, KT & Schalinske, KL (2007) New insights into the regulation of methyl group and homocysteine metabolism. J Nutr 137, 311314.CrossRefGoogle ScholarPubMed
239Mehedint, MG, Niculescu, MD, Craciunescu, CN, et al. . (2010) Choline deficiency alters global histone methylation and epigenetic marking at the Re1 site of the calbindin 1 gene. FASEB J 24, 184195.CrossRefGoogle Scholar
240Ly, A, Lee, H, Chen, J, et al. . (2011) Effect of maternal and postweaning folic acid supplementation on mammary tumor risk in the offspring. Cancer Res 71, 988997.CrossRefGoogle ScholarPubMed
241Sie, KK, Chen, J, Sohn, KJ, et al. . (2009) Folic acid supplementation provided in utero and during lactation reduces the number of terminal end buds of the developing mammary glands in the offspring. Cancer Lett 280, 7277.CrossRefGoogle ScholarPubMed
242Steegers-Theunissen, RP, Obermann-Borst, SA, Kremer, D, et al. . (2009) Periconceptional maternal folic acid use of 400 microg per day is related to increased methylation of the IGF2 gene in the very young child. PLoS One 4, e7845.CrossRefGoogle Scholar
243Lelievre, SA (2009) Contributions of extracellular matrix signaling and tissue architecture to nuclear mechanisms and spatial organization of gene expression control. Biochim Biophys Acta 1790, 925935.CrossRefGoogle ScholarPubMed
244Stempak, JM, Sohn, KJ, Chiang, EP, et al. . (2005) Cell and stage of transformation-specific effects of folate deficiency on methionine cycle intermediates and DNA methylation in an in vitro model. Carcinogenesis 26, 981990.CrossRefGoogle ScholarPubMed
245Song, J, Medline, A, Mason, JB, et al. . (2000) Effects of dietary folate on intestinal tumorigenesis in the apcMin mouse. Cancer Res 60, 54345440.Google ScholarPubMed
246Garland, CF, Gorham, ED, Mohr, SB, et al. . (2007) Vitamin D and prevention of breast cancer: pooled analysis. J Steroid Biochem Mol Biol 103, 708711.CrossRefGoogle ScholarPubMed
247Cui, Y & Rohan, TE (2006) Vitamin D, calcium, and breast cancer risk: a review. Cancer Epidemiol Biomarkers Prev 15, 14271437.CrossRefGoogle ScholarPubMed
248Garland, FC, Garland, CF, Gorham, ED, et al. . (1990) Geographic variation in breast cancer mortality in the United States: a hypothesis involving exposure to solar radiation. Prev Med 19, 614622.CrossRefGoogle ScholarPubMed
249Lowe, LC, Guy, M, Mansi, JL, et al. . (2005) Plasma 25-hydroxy vitamin D concentrations, vitamin D receptor genotype and breast cancer risk in a UK Caucasian population. Eur J Cancer 41, 11641169.CrossRefGoogle Scholar
250Chen, P, Hu, P, Xie, D, et al. . (2010) Meta-analysis of vitamin D, calcium and the prevention of breast cancer. Breast Cancer Res Treat 121, 469477.CrossRefGoogle ScholarPubMed
251Lin, J, Manson, JE, Lee, IM, et al. . (2007) Intakes of calcium and vitamin D and breast cancer risk in women. Arch Intern Med 167, 10501059.CrossRefGoogle ScholarPubMed
252Shin, MH, Holmes, MD, Hankinson, SE, et al. . (2002) Intake of dairy products, calcium, and vitamin D and risk of breast cancer. J Natl Cancer Inst 94, 13011311.CrossRefGoogle ScholarPubMed
253Robien, K, Cutler, GJ & Lazovich, D (2007) Vitamin D intake and breast cancer risk in postmenopausal women: the Iowa Women's Health Study. Cancer Causes Control 18, 775782.CrossRefGoogle ScholarPubMed
254Blot, WJ, Fraumeni, JF Jr & Stone, BJ (1977) Geographic patterns of breast cancer in the United States. J Natl Cancer Inst 59, 14071411.CrossRefGoogle ScholarPubMed
255McCullough, ML, Rodriguez, C, Diver, WR, et al. . (2005) Dairy, calcium, and vitamin D intake and postmenopausal breast cancer risk in the Cancer Prevention Study II Nutrition Cohort. Cancer Epidemiol Biomarkers Prev 14, 28982904.CrossRefGoogle ScholarPubMed
256Zierold, C, Mings, JA & Deluca, HF (2003) Regulation of 25-hydroxyvitamin D3-24-hydroxylase mRNA by 1,25-dihydroxyvitamin D3 and parathyroid hormone. J Cell Biochem 88, 234237.CrossRefGoogle ScholarPubMed
257Armbrecht, HJ, Boltz, MA & Hodam, TL (2003) PTH increases renal 25(OH)D3-1α-hydroxylase (CYP1α) mRNA but not renal 1,25(OH)2D3 production in adult rats. Am J Physiol Renal Physiol 284, F1032F1036.CrossRefGoogle ScholarPubMed
258Li, J, Byrne, ME, Chang, E, et al. . (2008) 1α,25-Dihydroxyvitamin D hydroxylase in adipocytes. J Steroid Biochem Mol Biol 112, 122126.CrossRefGoogle Scholar
259Kemmis, CM, Salvador, SM, Smith, KM, et al. . (2006) Human mammary epithelial cells express CYP27B1 and are growth inhibited by 25-hydroxyvitamin D-3, the major circulating form of vitamin D-3. J Nutr 136, 887892.CrossRefGoogle ScholarPubMed
260Zehnder, D, Bland, R, Williams, MC, et al. . (2001) Extrarenal expression of 25-hydroxyvitamin D3-1α-hydroxylase. J Clin Endocrinol Metab 86, 888894.Google Scholar
261Norman, AW (2008) From vitamin D to hormone D: fundamentals of the vitamin D endocrine system essential for good health. Am J Clin Nutr 88, 491S499S.CrossRefGoogle ScholarPubMed
262Haussler, MR, Haussler, CA, Bartik, L, et al. . (2008) Vitamin D receptor: molecular signaling and actions of nutritional ligands in disease prevention. Nutr Rev 66, S98S112.CrossRefGoogle ScholarPubMed
263Bernardi, RJ, Johnson, CS, Modzelewski, RA, et al. . (2002) Antiproliferative effects of 1α,25-dihydroxyvitamin D3 and vitamin D analogs on tumor-derived endothelial cells. Endocrinology 143, 25082514.CrossRefGoogle Scholar
264Wali, RK, Baum, CL, Bolt, MJ, et al. . (1992) 1,25-Dihydroxyvitamin D3 inhibits Na(+)-H+ exchange by stimulating membrane phosphoinositide turnover and increasing cytosolic calcium in CaCo-2 cells. Endocrinology 131, 11251133.CrossRefGoogle ScholarPubMed
265Wali, RK, Baum, CL, Sitrin, MD, et al. . (1992) Effect of vitamin D status on the rapid actions of 1,25-dihydroxycholecalciferol in rat colonic membranes. Am J Physiol 262, G945G953.Google ScholarPubMed
266Li, W & Farach-Carson, MC (2001) Parathyroid hormone-stimulated resorption in calvaria cultured in serum-free medium is enhanced by the calcium-mobilizing activity of 1,25-dihydroxyvitamin D3. Bone 29, 231235.CrossRefGoogle Scholar
267Norman, AW, Okamura, WH, Bishop, JE, et al. . (2002) Update on biological actions of 1α,25(OH)2-vitamin D3 (rapid effects) and 24R,25(OH)2-vitamin D3. Mol Cell Endocrinol 197, 113.CrossRefGoogle Scholar
268Matthews, D, LaPorta, E, Zinser, GM, et al. . (2010) Genomic vitamin D signaling in breast cancer: insights from animal models and human cells. J Steroid Biochem Mol Biol 121, 362367.CrossRefGoogle ScholarPubMed
269Zinser, GM & Welsh, J (2004) Vitamin D receptor status alters mammary gland morphology and tumorigenesis in MMTV-neu mice. Carcinogenesis 25, 23612372.CrossRefGoogle ScholarPubMed
270Zinser, GM, Suckow, M & Welsh, J (2005) Vitamin D receptor (VDR) ablation alters carcinogen-induced tumorigenesis in mammary gland, epidermis and lymphoid tissues. J Steroid Biochem Mol Biol 97, 153164.CrossRefGoogle ScholarPubMed
271Kurihara, N, Fan, K, Thaler, HT, et al. . (2008) Effect of a Western-style diet fortified with increased calcium and vitamin D on mammary gland of C57BL/6 mice. J Med Food 11, 201206.CrossRefGoogle ScholarPubMed
272Jacobson, EA, James, KA, Newmark, HL, et al. . (1989) Effects of dietary fat, calcium, and vitamin D on growth and mammary tumorigenesis induced by 7,12-dimethylbenz(a)anthracene in female Sprague-Dawley rats. Cancer Res 49, 63006303.Google ScholarPubMed
273Welsh, J (2007) Vitamin D and prevention of breast cancer. Acta Pharmacol Sin 28, 13731382.CrossRefGoogle ScholarPubMed
274Chlebowski, RT, Johnson, KC, Kooperberg, C, et al. . (2008) Calcium plus vitamin D supplementation and the risk of breast cancer. J Natl Cancer Inst 100, 15811591.CrossRefGoogle ScholarPubMed
275Lappe, JM, Travers-Gustafson, D, Davies, KM, et al. . (2007) Vitamin D and calcium supplementation reduces cancer risk: results of a randomized trial. Am J Clin Nutr 85, 15861591.CrossRefGoogle ScholarPubMed
276Banwell, CM, MacCartney, DP, Guy, M, et al. . (2006) Altered nuclear receptor corepressor expression attenuates vitamin D receptor signaling in breast cancer cells. Clin Cancer Res 12, 20042013.CrossRefGoogle ScholarPubMed
277Kim, MS, Fujiki, R, Kitagawa, H, et al. . (2007) 1α,25(OH)2D3-induced DNA methylation suppresses the human CYP27B1 gene. Mol Cell Endocrinol 265–266, 168173.CrossRefGoogle Scholar
278Novakovic, B, Sibson, M, Ng, HK, et al. . (2009) Placenta-specific methylation of the vitamin D 24-hydroxylase gene: implications for feedback autoregulation of active vitamin D levels at the fetomaternal interface. J Biol Chem 284, 1483814848.CrossRefGoogle ScholarPubMed
279Luo, W, Karpf, AR, Deeb, KK, et al. . (2010) Epigenetic regulation of vitamin D 24-hydroxylase/CYP24A1 in human prostate cancer. Cancer Res 70, 59535962.CrossRefGoogle ScholarPubMed
280Deeb, KK, Luo, W, Karpf, AR, et al. . (2011) Differential vitamin D 24-hydroxylase/CYP24A1 gene promoter methylation in endothelium from benign and malignant human prostate. Epigenetics 6, 9941000.CrossRefGoogle ScholarPubMed
281Margolis, RN & Christakos, S (2010) The nuclear receptor superfamily of steroid hormones and vitamin D gene regulation. An update. Ann N Y Acad Sci 1192, 208214.CrossRefGoogle ScholarPubMed
282Giovannucci, E (1999) Tomatoes, tomato-based products, lycopene, and cancer: review of the epidemiologic literature. J Natl Cancer Inst 91, 317331.CrossRefGoogle ScholarPubMed
283Rohan, TE (2001) Invited Commentary: serum carotenoids and breast cancer. Am J Epidemiol 153, 11481150.CrossRefGoogle ScholarPubMed
284Toniolo, P, Van Kappel, AL, Akhmedkhanov, A, et al. . (2001) Serum carotenoids and breast cancer. Am J Epidemiol 153, 11421147.CrossRefGoogle ScholarPubMed
285Zhang, S, Hunter, DJ, Forman, MR, et al. . (1999) Dietary carotenoids and vitamins A, C, and E and risk of breast cancer. J Natl Cancer Inst 91, 547556.CrossRefGoogle Scholar
286Hulten, K, Van Kappel, AL, Winkvist, A, et al. . (2001) Carotenoids, α-tocopherols, and retinol in plasma and breast cancer risk in northern Sweden. Cancer Causes Control 12, 529537.CrossRefGoogle ScholarPubMed
287Nissen, SB, Tjonneland, A, Stripp, C, et al. . (2003) Intake of vitamins A, C, and E from diet and supplements and breast cancer in postmenopausal women. Cancer Causes Control 14, 695704.CrossRefGoogle Scholar
288Wald, NJ, Boreham, J, Hayward, JL, et al. . (1984) Plasma retinol, β-carotene and vitamin E levels in relation to the future risk of breast cancer. Br J Cancer 49, 321324.CrossRefGoogle Scholar
289Epplein, M, Shvetsov, YB, Wilkens, LR, et al. . (2009) Plasma carotenoids, retinol, and tocopherols and postmenopausal breast cancer risk in the Multiethnic Cohort Study: a nested case–control study. Breast Cancer Res 11, R49.CrossRefGoogle ScholarPubMed
290Mignone, LI, Giovannucci, E, Newcomb, PA, et al. . (2009) Dietary carotenoids and the risk of invasive breast cancer. Int J Cancer 124, 29292937.CrossRefGoogle ScholarPubMed
291Sato, R, Helzlsouer, KJ, Alberg, AJ, et al. . (2002) Prospective study of carotenoids, tocopherols, and retinoid concentrations and the risk of breast cancer. Cancer Epidemiol Biomarkers Prev 11, 451457.Google ScholarPubMed
292Kabat, GC, Kim, M, Adams-Campbell, LL, et al. . (2009) Longitudinal study of serum carotenoid, retinol, and tocopherol concentrations in relation to breast cancer risk among postmenopausal women. Am J Clin Nutr 90, 162169.CrossRefGoogle ScholarPubMed
293Rabi, T & Bishayee, A (2009) Terpenoids and breast cancer chemoprevention. Breast Cancer Res Treat 115, 223239.CrossRefGoogle ScholarPubMed
294Okuno, M, Kojima, S, Matsushima-Nishiwaki, R, et al. . (2004) Retinoids in cancer chemoprevention. Curr Cancer Drug Targets 4, 285298.CrossRefGoogle ScholarPubMed
295Black, HS (2004) Pro-carcinogenic activity of β-carotene, a putative systemic photoprotectant. Photochem Photobiol Sci 3, 753758.CrossRefGoogle ScholarPubMed
296Valko, M, Izakovic, M, Mazur, M, et al. . (2004) Role of oxygen radicals in DNA damage and cancer incidence. Mol Cell Biochem 266, 3756.CrossRefGoogle ScholarPubMed
297King-Batoon, A, Leszczynska, JM & Klein, CB (2008) Modulation of gene methylation by genistein or lycopene in breast cancer cells. Environ Mol Mutagen 49, 3645.CrossRefGoogle ScholarPubMed
298Bistulfi, G, Pozzi, S, Ren, M, et al. . (2006) A repressive epigenetic domino effect confers susceptibility to breast epithelial cell transformation: implications for predicting breast cancer risk. Cancer Res 66, 1030810314.CrossRefGoogle ScholarPubMed
299Ndiaye, M, Kumar, R & Ahmad, N (2011) Resveratrol in cancer management: where are we and where we go from here? Ann N Y Acad Sci 1215, 144149.CrossRefGoogle Scholar
300Koo, SH & Montminy, M (2006) In vino veritas: a tale of two sirt1s? Cell 127, 10911093.CrossRefGoogle ScholarPubMed
301Binda, O, Nassif, C & Branton, PE (2008) SIRT1 negatively regulates HDAC1-dependent transcriptional repression by the RBP1 family of proteins. Oncogene 27, 33843392.CrossRefGoogle ScholarPubMed
302Miller, A, Chen, J, Takasuka, TE, et al. . (2010) Proliferating cell nuclear antigen (PCNA) is required for cell-cycle regulated silent chromatin on replicated and nonreplicated genes. J Biol Chem 285, 3514235154.CrossRefGoogle ScholarPubMed
303Abad, PC, Lewis, J, Mian, IS, et al. . (2007) NuMA influences higher order chromatin organization in human mammary epithelium. Mol Biol Cell 18, 348361.CrossRefGoogle ScholarPubMed
304Vasanthi, D & Mishra, RK (2008) Epigenetic regulation of genes during development: a conserved theme from flies to mammals. J Genet Genomics 35, 413429.CrossRefGoogle ScholarPubMed
305Plachot, C, Chaboub, LS, Adissu, HA, et al. . (2009) Factors necessary to produce basoapical polarity in human glandular epithelium formed in conventional and high-throughput three-dimensional culture: example of the breast epithelium. BMC Biol 7, 77.CrossRefGoogle ScholarPubMed
Figure 0

Fig. 1 Epigenetic mechanisms of gene transcription. An average of 147 bp of double-stranded DNA (black thick line) are wrapped around histone octamers to form nucleosomes. Two sets of four distinct histones (3, 4, 2B and 2A) form the octamer. The loosening of DNA is obtained by triggering of histone modifications (for example, acetylation on lysine 12 of histone 4 and trimethylation on lysine 4 of histone 3) that leads to a decrease in the tightness of interactions among histones and between histones and DNA and, thus, an open chromatin stage amenable for transcription. Other histone modifications (for example, trimethylation of histone 3 on lysine 27 or on lysine 9) are conducive to gene silencing by compacting nucleosomes tightly. In certain gene promoters a stretch of DNA of several hundred bp enriched in C-phosphate-G (CpG) islands could become methylated. This chemical modification has been considered as one of the sustainable changes leading to epigenetic inheritance through cell division and is found in a number of tumour-suppressor genes when cancer develops. Note: histone octamers are shown as blocks of eight light grey barrels, each barrel representing an individual histone. This is a simplified representation of chromatin organisation. The complex orientation of histones within the octamer and the histone 1 linker are not shown; the multiple protein complexes that are necessary to chemically modify histones and DNA (for example, with methylases, histone deacetylases) as well as those involved in histone displacement (for example, chromatin remodelling complexes) are not drawn.

Figure 1

Fig. 2 Possible impact of epigenetic modifications upon dietary influence during the lifespan of the mammary gland. There is still much to be understood regarding human breast development and a lot of information is extrapolated from studies in rodents. The human mammary gland evolves constantly with the formation, on average, of twelve individual ductal systems or lobes with limited branching of ducts with blunt-ended ductal termini during fetal development. Considerable secondary branching and elongation of the ductal systems and formation of terminal ductal lobular units (TDLU) occur upon hormonal stimulation during puberty, and lobes further branch out to develop into lactating tissue followed by involution of part of the glandular tissue during pregnancy/lactation cycles. All the phases of development will encompass TDLU (these structures are present in the majority starting at puberty and until menopause), thus affecting areas of the breast where cancers develop. Therefore, epigenetic alterations occurring at different periods during the lifespan of an individual might affect the mammary gland to various extents based on the possibility to propagate permanent/long-term epigenetic marks through cell division (see grey arrows). The period between birth and puberty is not accompanied by extensive breast development; instead, it is proposed to comprise an involution phase shortly after birth and slow growth that accompanies the body's growth afterwards; this period is represented by the dashed line on the drawing (periods of times between life events are not represented to scale). Menopause is characterised by a reduction in the number of TDLU and ducts(280).

Figure 2

Fig. 3 Venn diagram of a relationship between diets/food components and factors that influence their impact on breast cancer risk. Major life characteristics share specific relationships with diets/food components when it comes to breast cancer. These characteristics include the stage of mammary gland development (which encompasses menopausal status/age) and the individual's background (race/ethnicity and lifestyle other than dietary habits). The combination of these different factors might explain why certain nutrients will have an impact on the development of a certain type of breast tumour. Such knowledge is critical for optimal primary prevention, as it suggests that (1) the study of the impact of diets/food components on breast cancer has to take into account diversity and (2) the link between the development of a certain type of breast tumour and nutrition has to be further scrutinised, notably via the identification of the early alterations in the breast specific to a given type of neoplasia. ER+, oestrogen-positive; ER–, oestrogen-negative; PR+, progesterone-positive; PR–, progesterone-negative.