Maternal exposures to environmental factors during pregnancy influence the risk of many chronic adult-onset diseases in the offspring. Here we investigate whether feeding pregnant rats a high-fat (HF)- or ethinyl-oestradiol (EE2)-supplemented diet affects carcinogen-induced mammary cancer risk in daughters, granddaughters and great-granddaughters. We show that mammary tumourigenesis is higher in daughters and granddaughters of HF rat dams and in daughters and great-granddaughters of EE2 rat dams. Outcross experiments suggest that the increase in mammary cancer risk is transmitted to HF granddaughters equally through the female or male germ lines, but it is only transmitted to EE2 granddaughters through the female germ line. The effects of maternal EE2 exposure on offspring's mammary cancer risk are associated with changes in the DNA methylation machinery and methylation patterns in mammary tissue of all three EE2 generations. We conclude that dietary and oestrogenic exposures in pregnancy increase breast cancer risk in multiple generations of offspring, possibly through epigenetic means.

Parental environmental experiences affect disease susceptibility in the progeny through epigenetic inheritance. Pesticides are substances or mixtures of chemicals—some of which are persistent environmental pollutants—that are used to control pests. This review explores the evidence linking parental exposure to pesticides and endocrine disruptors to intergenerational and transgenerational susceptibility of cancer in population studies and animal models. We also discuss the impact of pesticides and other endocrine disruptors on the germline epigenome as well as the emerging evidence for how epigenetic information is transmitted between generations. Finally, we discuss the importance of this mode of inheritance in the context of cancer prevention and the challenges ahead.

While many studies have shown that maternal factors in pregnancy affect the cancer risk for offspring, few studies have investigated the impact of paternal exposures on their progeny’s risk of this disease. Population studies generally show a U-shaped association between birthweight and breast cancer risk, with both high and low birthweight increasing the risk compared with average birthweight. Here, we investigated whether paternal malnutrition would modulate the birthweight and later breast cancer risk of daughters. Male mice were fed AIN93G-based diets containing either 17.7% (control) or 8.9% (low-protein (LP)) energy from protein from 3 to 10 weeks of age. Males on either group were mated to females raised on a control diet. Female offspring from control and LP fathers were treated with 7,12-dimethylbenz[a]anthracene (DMBA) to initiate mammary carcinogenesis. Mature sperm from fathers and mammary tissue and tumors from female offspring were used for epigenetic and other molecular analyses. We found that paternal malnutrition reduces the birthweight of daughters and leads to epigenetic and metabolic reprogramming of their mammary tissue and tumors. Daughters of LP fathers have higher rates of mammary cancer, with tumors arising earlier and growing faster than in controls. The energy sensor, the AMP-activated protein kinase (AMPK) pathway, is suppressed in both mammary glands and tumors of LP daughters, with consequent activation of mammalian target of rapamycin (mTOR) signaling. Furthermore, LP mammary tumors show altered amino-acid metabolism with increased glutamine utilization. These changes are linked to alterations in noncoding RNAs regulating those pathways in mammary glands and tumors. Importantly, we detect alterations in some of the same microRNAs/target genes found in our animal model in breast tumors of women from populations where low birthweight is prevalent. Our study suggests that ancestral paternal malnutrition plays a role in programming offspring cancer risk and phenotype by likely providing a metabolic advantage to cancer cells.

Elevated pregnancy hormone levels, such as oestrogen and progesterone, may increase the risk of developing breast cancer both in mothers and offspring. However, the reasons for large inter-individual variations in estrogen and progesterone levels during pregnancy remain unknown. The objectives of this study were to investigate whether a) intakes of total dietary fat, types of fat (monounsaturated: MUFA, polyunsaturated: n-3 and n-6 PUFA, and saturated) and b) gestational weight gain are associated with estradiol and progesterone levels in plasma during pregnancy. We measured body weight as well as estradiol and progesterone in plasma among 226 healthy pregnant Swedish women on gestation weeks 12, 25 and 33. At the same time points, dietary intake of total fat and types of fat (MUFA, PUFA, SFA, n-3 and n-6 PUFA) were estimated using 3-day food diaries. A large variation in estradiol and progesterone levels was evident. Nulliparous women had 37%, 12% and 30% higher mean estradiol levels on gestation weeks 12, 25 and 33 compared to parous women (P = 0.008). No associations were found between dietary intake of total fat or fat subtypes (including n-3 PUFA and n-6 PUFA) and plasma estradiol or progesterone levels. Gestational weight gain was associated with progesterone levels (P = 0.03) but the effect was very small (20% increase in progesterone levels between gestational weeks 12 and 33 per kg body weight/week). No associations among gestational weight gain, maternal dietary fat intake (total or subtypes including n-3 PUFA and n-6 PUFA) and plasma estradiol levels were found. However, pregnancy progesterone levels correlated with weight gain during pregnancy. Identification of other possible determinants of pregnancy estradiol and progesterone levels, important for the development of breast cancer in both mothers and offspring, are needed.

While many studies have shown that maternal weight and nutrition in pregnancy affects offspring’s breast cancer risk, no studies have investigated the impact of paternal body weight on daughters’ risk of this disease. Here, we show that diet-induced paternal overweight around the time of conception can epigenetically reprogram father’s germ-line and modulate their daughters’ birth weight and likelihood of developing breast cancer, using a mouse model. Increased body weight was associated with changes in the miRNA expression profile in paternal sperm. Daughters of overweight fathers had higher rates of carcinogen-induced mammary tumors which were associated with delayed mammary gland development and alterations in mammary miRNA expression. The hypoxia signaling pathway, targeted by miRNAs down-regulated in daughters of overweight fathers, was activated in their mammary tissues and tumors. This study provides evidence that paternal peri-conceptional body weight may affect daughters’ mammary development and breast cancer risk and warrants further studies in other animal models and humans.

Studies in rodent models of breast cancer show that exposures to dietary/hormonal factors during the in utero and pubertal periods, when the mammary gland undergoes extensive modeling and re-modeling, alter susceptibility to carcinogen-induced mammary tumors. Similar findings have been described in humans: for example, high birthweight increases later risk of developing breast cancer, and dietary intake of soy during childhood decreases breast cancer risk. It is thought that these prenatal and postnatal dietary modifications induce persistent morphological changes in the mammary gland that in turn modify breast cancer risk later in life. These morphological changes likely reflect epigenetic modifications, such as changes in DNA methylation, histones and miRNA expression that then affect gene transcription . In this article we describe how changes in mammary gland morphology can predict mammary cancer risk in rats. Our protocol specifically describes how to dissect and remove the rat abdominal mammary gland and how to prepare mammary gland whole mounts. It also describes how to analyze mammary gland morphology according to three end-points (number of terminal end buds, epithelial elongation and differentiation) and to use the data to predict risk of developing mammary cancer.