Body mass index associated with genome-wide methylation in breast tissue

Tumor purity adjusted beta values improve biological interpretability of high-dimensional DNA methylation data

A common issue affecting DNA methylation analysis in tumor tissue is the presence of a substantial amount of non-tumor methylation signal derived from the surrounding microenvironment. Although approaches for quantifying and correcting for the infiltration component have been proposed previously, we believe these have not fully addressed the issue in a comprehensive and universally applicable way. We present a multi-population framework for adjusting DNA methylation beta values on the Illumina 450/850K platform using generic purity estimates to account for non-tumor signal. Our approach also provides an indirect estimate of the aggregate methylation state of the surrounding normal tissue. Using whole exome sequencing derived purity estimates and Illumina 450K methylation array data generated by The Cancer Genome Atlas project (TCGA), we provide a demonstration of this framework in breast cancer illustrating the effect of beta correction on the aggregate methylation beta value distribution, clustering accuracy, and global methylation profiles.

Integrative Analysis of Gene Expression and DNA Methylation Depicting the Impact of Obesity on Breast Cancer

Obesity has been reported to be a risk factor for breast cancer, but how obesity affects breast cancer (BC) remains unclear. Although body mass index (BMI) is the most commonly used reference for obesity, it is insufficient to evaluate the obesity-related pathophysiological changes in breast tissue. The purpose of this study is to establish a DNA-methylation-based biomarker for BMI (DM-BMI) and explore the connection between obesity and BC. Using DNA methylation data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), we developed DM-BMI to evaluate the degree of obesity in breast tissues. In tissues from non-BC and BC population, the DM-BMI model exhibited high accuracy in BMI prediction. In BC tissues, DM-BMI correlated with increased adipose tissue content and BC tissues with increased DM-BMI exhibited higher expression of pro-inflammatory adipokines. Next, we identified the gene expression profile relating to DM-BMI. Using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, we observed that the DM-BMI-related genes were mostly involved in the process of cancer immunity. DM-BMI is positively correlated with T cell infiltration in BC tissues. Furthermore, we observed that DM-BMI was positively correlated with immune checkpoint inhibitors (ICI) response markers in BC. Collectively, we developed a new biomarker for obesity and discovered that BC tissues from obese individuals exhibit an increased degree of immune cell infiltration, indicating that obese BC patients might be the potential beneficiaries for ICI treatment.

Can the epigenome contribute to risk stratification for cancer onset?

The increasing burden of cancer requires identifying and protecting individuals at highest risk. The epigenome provides an indispensable complement to genetic alterations for a risk stratification approach for the following reasons: gene transcription necessary for cancer onset is directed by epigenetic modifications and many risk factors studied so far have been associated with alterations related to the epigenome. The risk level depends on the plasticity of the epigenome during phases of life particularly sensitive to environmental and dietary impacts. Modifications in the activity of DNA regulatory regions and altered chromatin compaction may accumulate, hence leading to the increase of cancer risk. Moreover, tissue architecture directs the unique organization of the epigenome for each tissue and cell type, which allows the epigenome to control cancer risk in specific organs. Investigations of epigenetic signatures of risk should help identify a continuum of alterations leading to a threshold beyond which the epigenome cannot maintain homeostasis. We propose that this threshold may be similar in the population for a given tissue, but the pace to reach this threshold will depend on the combination of germline inheritance and the risk and protective factors encountered, particularly during windows of epigenetic susceptibility, by individuals.

Ten Years of EWAS

Epigenome-wide association study (EWAS) has been applied to analyze DNA methylation variation in complex diseases for a decade, and epigenome as a research target has gradually become a hot topic of current studies. The DNA methylation microarrays, next-generation, and third-generation sequencing technologies have prepared a high-quality platform for EWAS. Here, the progress of EWAS research is reviewed, its contributions to clinical applications, and mainly describe the achievements of four typical diseases. Finally, the challenges encountered by EWAS and make bold predictions for its future development are presented.

Examining the association between adiposity and DNA methylation: A systematic review and meta-analysis

Obesity is associated with widespread differential DNA methylation (DNAm) patterns, though there have been limited overlap in the obesity-associated cytosine-guanine nucleotide pair (CpG) sites that have been identified in the literature. We systematically searched four databases for studies published until January 2020. Eligible studies included cross-sectional, longitudinal, or intervention studies examining adiposity and genome-wide DNAm in non-pregnant adults aged 18-75 in all tissue types. Study design and results were extracted in the descriptive review. Blood-based DNAm results in body mass index (BMI) and waist circumference (WC) were meta-analyzed using weighted sum of Z-score meta-analysis. Of the 10,548 studies identified, 46 studies were included in the systematic review with 18 and nine studies included in the meta-analysis of BMI and WC, respectively. In the blood, 77 and four CpG sites were significant in three or more studies of BMI and WC, respectively. Using a genome-wide threshold for significance, 52 blood-based CpG sites were significantly associated with BMI. These sites have previously been associated with many obesity-related diseases including type 2 diabetes, cardiovascular disease, Crohn's disease, and depression. Our study shows that DNAm at 52 CpG sites represent potential mediators of obesity-associated chronic diseases and may be novel intervention or therapeutic targets to protect against obesity-associated chronic diseases.

A genome-wide methylation study of body fat traits in the Norfolk Island isolate

BACKGROUND AND AIMS

Natural variation in body fat is explained by both genetic and environmental effects. Epigenetic mechanisms such as DNA methylation can mediate these effects causing changes in gene expression leading to onset of obesity. Studies of genetic isolates have the potential to provide new epigenetic insights with advantages such as reduced genetic diversity and environmental exposures.

METHODS AND RESULTS

This was an exploratory study of genome-wide DNA methylation in relation to body fat traits in 47 healthy adults from the genetic isolate of Norfolk Island. Quantitative body fat traits (body fat percentage, body mass index, hip circumference, waist circumference, waist-hip-ratio and weight) were carefully measured. DNA methylation data was obtained from peripheral blood using Illumina 450K arrays. Multi-trait analysis was performed using Principal Component Analysis (PCA). CpG by trait association testing was performed using stepwise linear regressions. Two components were identified that explained approximately 89% of the phenotypic variance. In total, 5 differential methylated positions (DMPs) were identified at genome-wide significance (P≤ 2.4 × 10^-7), which mapped to GOT2-CDH8, LYSMD3, HIBADH, ADGRD1 and EBF4 genes. Gene set enrichment analysis of 848 genes containing suggestive DMPs (P≤ 1.0 × 10^-4) implicated the Cadherin (28 genes, P_adj = 6.76 × 10^-7) and Wnt signaling pathways (38 genes, P_adj = 7.78 × 10^-6).

CONCLUSION

This study provides new insights into the epigenetically influenced genes and pathways underlying body fat variation in a healthy cohort and provides targets for consideration in future studies of obesity risk.

The methylation landscape and its role in domestication and gene regulation in the chicken

Domestication is one of the strongest examples of artificial selection and has produced some of the most extreme within-species phenotypic variation known. In the case of the chicken, it has been hypothesized that DNA methylation may play a mechanistic role in the domestication response. By inter-crossing wild-derived red junglefowl with domestic chickens, we mapped quantitative trait loci for hypothalamic methylation (methQTL), gene expression (eQTL) and behaviour. We find large, stable methylation differences, with 6,179 cis and 2,973 trans methQTL identified. Over 46% of the trans effects were genotypically controlled by five loci, mainly associated with increased methylation in the junglefowl genotype. In a third of eQTL, we find that there is a correlation between gene expression and methylation, while statistical causality analysis reveals multiple instances where methylation is driving gene expression, as well as the reverse. We also show that methylation is correlated with some aspects of behavioural variation in the inter-cross. In conclusion, our data suggest a role for methylation in the regulation of gene expression underlying the domesticated phenotype of the chicken.

Development of Tissue-Specific Age Predictors Using DNA Methylation Data

DNA methylation patterns have been shown to change throughout the normal aging process. Several studies have found epigenetic aging markers using age predictors, but these studies only focused on blood-specific or tissue-common methylation patterns. Here, we constructed nine tissue-specific age prediction models using methylation array data from normal samples. The constructed models predict the chronological age with good performance (mean absolute error of 5.11 years on average) and show better performance in the independent test than previous multi-tissue age predictors. We also compared tissue-common and tissue-specific aging markers and found that they had different characteristics. Firstly, the tissue-common group tended to contain more positive aging markers with methylation values that increased during the aging process, whereas the tissue-specific group tended to contain more negative aging markers. Secondly, many of the tissue-common markers were located in Cytosine-phosphate-Guanine (CpG) island regions, whereas the tissue-specific markers were located in CpG shore regions. Lastly, the tissue-common CpG markers tended to be located in more evolutionarily conserved regions. In conclusion, our prediction models identified CpG markers that capture both tissue-common and tissue-specific characteristics during the aging process.

Alcohol and DNA Methylation: An Epigenome-Wide Association Study in Blood and Normal Breast Tissue

The biological mechanisms driving associations between alcohol consumption and chronic diseases might include epigenetic modification of DNA methylation. We explored the hypothesis that alcohol consumption is associated with methylation in an epigenome-wide association study of blood and normal breast tissue DNA. Infinium HumanMethylation450 BeadChip (Illumina Inc., San Diego, California) array data on blood DNA methylation was examined in a discovery set of 2,878 non-Hispanic white women from the Sister Study (United States, 2004-2015) who provided detailed questionnaire information on lifetime alcohol use. Robust linear regression modeling was used to identify significant associations (false discovery rate of Q < 0.05) between the number of alcoholic drinks per week and DNA methylation at 5,458 cytosine-phosphate-guanine (CpG) sites. Associations were replicated (P < 0.05) for 677 CpGs in an independent set of 187 blood DNA samples from the Sister Study and for 628 CpGs in an independent set of 171 normal breast DNA samples; 1,207 CpGs were replicated in either blood or normal breast, with 98 CpGs replicated in both tissues. Individual gene effects were notable for phosphoglycerate dehydrogenase (PGHDH), peptidyl-prolyl cis-trans isomerase (PPIF), solute carrier 15 (SLC15), solute carrier family 43 member 1 (SLC43A1), and solute carrier family 7 member 11 (SLC7A11). We also found that high alcohol consumption was associated with significantly lower global methylation as measured by the average of CpGs on the entire array.

Hormone therapy use and breast tissue DNA methylation: analysis of epigenome wide data from the normal breast study

Hormone therapy (HT) is associated with increased risk of breast cancer, strongly dependent on type, duration, and recency of use. HT use could affect cancer risk by changing breast tissue transcriptional programs. We hypothesize that these changes are preceded by changes in DNA methylation. To explore this hypothesis we used histologically normal-appearing breast tissue from the Normal Breast Study (NBS). DNA methylation β-values were obtained using the Illumina HumanMethylation 450 BeadChips for 90 samples including all NBS-participants who used HT within 5 y before surgery. Data were analyzed using the reference-free cell mixture method. Cancer Genome Atlas (TCGA) mRNA-Seq data were used to assess correlation between DNA methylation and gene expression. We identified 527 CpG sites in 403 genes that were associated with ever using HT at genome wide significance (FDR q < 0.05), of these, 68 sites were also significantly associated with duration of use or recency of use. Twelve sites reached significance in all analyses one of which was cg01382688 in ARHGEF4 (p < 1.2x10⁻⁷). Mutations in ARHGEF4 have been reported in breast tumors, but this is the first report of possible breast cancer-related DNA methylation changes. In addition, 22 genes included more than one significant CpG site and a majority of these sites were significantly correlated with gene expression. Although based on small numbers, these findings support the hypothesis that HT is associated with epigenetic alterations in breast tissue, and identifies genes with altered DNA methylation states which could be linked to breast cancer development.

Detection of epigenetic field defects using a weighted epigenetic distance-based method

Identifying epigenetic field defects, notably early DNA methylation alterations, is important for early cancer detection. Research has suggested these early methylation alterations are infrequent across samples and identifiable as outlier samples. Here we developed a weighted epigenetic distance-based method characterizing (dis)similarity in methylation measures at multiple CpGs in a gene or a genetic region between pairwise samples, with weights to up-weight signal CpGs and down-weight noise CpGs. Using distance-based approaches, weak signals that might be filtered out in a CpG site-level analysis could be accumulated and therefore boost the overall study power. In constructing epigenetic distances, we considered both differential methylation (DM) and differential variability (DV) signals. We demonstrated the superior performance of the proposed weighted epigenetic distance-based method over non-weighted versions and site-level EWAS (epigenome-wide association studies) methods in simulation studies. Application to breast cancer methylation data from Gene Expression Omnibus (GEO) comparing normal-adjacent tissue to tumor of breast cancer patients and normal tissue of independent age-matched cancer-free women identified novel epigenetic field defects that were missed by EWAS methods, when majority were previously reported to be associated with breast cancer and were confirmed the progression to breast cancer. We further replicated some of the identified epigenetic field defects.

Vitamin D, DNA methylation, and breast cancer

BACKGROUND

Vitamin D has anticarcinogenic and immune-related properties and may protect against some diseases, including breast cancer. Vitamin D affects gene transcription and may influence DNA methylation.

METHODS

We studied the relationships between serum vitamin D, DNA methylation, and breast cancer using a case-cohort sample (1070 cases, 1277 in subcohort) of non-Hispanic white women. For our primary analysis, we used robust linear regression to examine the association between serum 25-hydroxyvitamin D (25(OH)D) and methylation within a random sample of the cohort ("subcohort"). We focused on 198 CpGs in or near seven vitamin D-related genes. For these 198 candidate CpG loci, we also examined how multiplicative interactions between methylation and 25(OH)D were associated with breast cancer risk. This was done using Cox proportional hazards models and the full case-cohort sample. We additionally conducted an exploratory epigenome-wide association study (EWAS) of the association between 25(OH)D and DNA methylation in the subcohort.

RESULTS

Of the CpGs in vitamin D-related genes, cg21201924 (RXRA) had the lowest p value for association with 25(OH)D (p = 0.0004). Twenty-two other candidate CpGs were associated with 25(OH)D (p < 0.05; RXRA, NADSYN1/DHCR7, GC, or CYP27B1). We observed an interaction between 25(OH)D and methylation at cg21201924 in relation to breast cancer risk (ratio of hazard ratios = 1.22, 95% confidence interval 1.10-1.34; p = 7 × 10-5), indicating a larger methylation-breast cancer hazard ratio in those with high serum 25(OH)D concentrations. We also observed statistically significant (p < 0.05) interactions for six other RXRA CpGs and CpGs in CYP24A1, CYP27B1, NADSYN1/DHCR7, and VDR. In the EWAS of the subcohort, 25(OH)D was associated (q < 0.05) with methylation at cg24350360 (EPHX1; p = 3.4 × 10-8), cg06177555 (SPN; p = 9.8 × 10-8), and cg13243168 (SMARCD2; p = 2.9 × 10-7).

CONCLUSIONS

25(OH)D concentrations were associated with DNA methylation of CpGs in several vitamin D-related genes, with potential links to immune function-related genes. Methylation of CpGs in vitamin D-related genes may interact with 25(OH)D to affect the risk of breast cancer.

DNA Methylation Patterns in Normal Tissue Correlate more Strongly with Breast Cancer Status than Copy-Number Variants

Normal tissue at risk of neoplastic transformation is characterized by somatic mutations, copy-number variation and DNA methylation changes. It is unclear however, which type of alteration may be more informative of cancer risk. We analyzed genome-wide DNA methylation and copy-number calls from the same DNA assay in a cohort of healthy breast samples and age-matched normal samples collected adjacent to breast cancer. Using statistical methods to adjust for cell type heterogeneity, we show that DNA methylation changes can discriminate normal-adjacent from normal samples better than somatic copy-number variants. We validate this important finding in an independent dataset. These results suggest that DNA methylation alterations in the normal cell of origin may offer better cancer risk prediction and early detection markers than copy-number changes.

A link between expression level of long-non-coding RNA ZFAS1 in breast tissue of healthy women and obesity

BACKGROUND

Epidemiological and experimental literature indicates that the risk of breast cancer incidence is strongly linked to hormone-dependent factors, including reproductive history and obesity. However, the molecular mechanisms underlying the association between these factors and breast cancer risk are poorly understood. The aim of this study, therefore, was to determine whether obesity and reproductive history are associated with expression levels of two breast cancer-related long non-coding RNAs (lncRNAs), namely ZFAS1 and SRA1 in cancer-free breast tissues of women.

METHODS

In the current research, 145 healthy women were recruited, and the quantitative expression levels of the two lncRNAs were determined through qPCR assay after gathering the mammoplasty breast tissue samples.

RESULTS

It was found that women with body mass index (BMI)≥30 kg/m² and BMI 25-29 kg/m² show a low expression of ZFAS1 compared to the BMI<25 kg/m² (P=0.031 and P=0.027, respectively). Then, the correlation analysis disclosed a negative correlation of ZFAS1 low expression with increasing BMI (r=-0.194, P=0.019). Interestingly, this analysis demonstrated a negative correlation between low expression of the ZFAS1 and high BMI in women with menarche age below 14 (r=-221; P=0.028). Lastly, it was also revealed that there was a negative association of the low expression level of ZFAS1 with increasing BMI in women through regression models (B=-0.048, P=0.019).

CONCLUSIONS

These findings suggest interesting clues about the links between high BMI and the expression levels of ZFAS1 in non-diseased breasts that may help us better understand the underlying mechanisms through which obesity contributes to breast carcinogenesis. However, such results need more validations in future research.

The potential role of leptin in tumor invasion and metastasis

The adipocyte-released hormone-like cytokine/adipokine leptin behaves differently in obesity compared to its functions in the normal healthy state. In obese individuals, elevated leptin levels act as a pro-inflammatory adipokine and are associated with certain types of cancers. Further, a growing body of evidence suggests that higher circulating leptin concentrations and/or elevated expression of leptin receptors (Ob-R) in tumors may be poor prognostic factors. Although the underlying pathological mechanisms of leptin's association with poor prognosis are not clear, leptin can impact the tumor microenvironment in several ways. For example, leptin is associated with a number of biological components that could lead to tumor cell invasion and distant metastasis. This includes interactions with carcinoma-associated fibroblasts, tumor promoting effects of infiltrating macrophages, activation of matrix metalloproteinases, transforming growth factor-β signaling, etc. Recent studies also have shown that leptin plays a role in the epithelial-mesenchymal transition, an important phenomenon for cancer cell migration and/or metastasis. Furthermore, leptin's potentiating effects on insulin-like growth factor-I, epidermal growth factor receptor and HER2/neu have been reported. Regarding unfavorable prognosis, leptin has been shown to influence both adenocarcinomas and squamous cell carcinomas. Features of poor prognosis such as tumor invasion, lymph node involvement and distant metastasis have been recorded in several cancer types with higher levels of leptin and/or Ob-R. This review will describe the current scenario in a precise manner. In general, obesity indicates poor prognosis in cancer patients.

The most important questions in cancer research and clinical oncology-Question 2-5. Obesity-related cancers: more questions than answers

Obesity is recognized as the second highest risk factor for cancer. The pathogenic mechanisms underlying tobacco-related cancers are well characterized and effective programs have led to a decline in smoking and related cancers, but there is a global epidemic of obesity without a clear understanding of how obesity causes cancer. Obesity is heterogeneous, and approximately 25% of obese individuals remain healthy (metabolically healthy obese, MHO), so which fat deposition (subcutaneous versus visceral, adipose versus ectopic) is "malignant"? What is the mechanism of carcinogenesis? Is it by metabolic dysregulation or chronic inflammation? Through which chemokines/genes/signaling pathways does adipose tissue influence carcinogenesis? Can selective inhibition of these pathways uncouple obesity from cancers? Do all obesity related cancers (ORCs) share a molecular signature? Are there common (over-lapping) genetic loci that make individuals susceptible to obesity, metabolic syndrome, and cancers? Can we identify precursor lesions of ORCs and will early intervention of high risk individuals alter the natural history? It appears unlikely that the obesity epidemic will be controlled anytime soon; answers to these questions will help to reduce the adverse effect of obesity on human condition.

Epigenome-wide association studies for breast cancer risk and risk factors

There have been six epigenome-wide association studies (EWAS) for breast cancer risk using blood DNA from prospective cohorts published thus far, and the only consistent finding is a global loss of methylation observed in breast cancer cases compared with controls, with no individual CpG sites passing validation across studies. In contrast, a more successful approach has been the identification of EWAS signatures of cancer risk factors such as smoking, body mass index, age and alcohol use with numerous validated CpG sites. These signatures may be used as a molecular test to quantify cancer risk associated with these factors. It is clear from the larger EWAS of risk exposures that similar-sized large collaborative studies may be needed to robustly identify DNA methylation signatures of breast cancer risk.

Body Mass Index Influences the Prognostic Impact of Combined Nuclear Insulin Receptor and Estrogen Receptor Expression in Primary Breast Cancer

The prognostic importance of tumor-specific nuclear insulin receptor (InsR) expression in breast cancer is unclear, while membrane and cytoplasmic localization of InsR is better characterized. The insulin signaling network is influenced by obesity and may interact with the estrogen receptor α (ERα) signaling. The purpose was to investigate the interplay between nuclear InsR, ER, body mass index (BMI), and prognosis. Tumor-specific expression of nuclear InsR was evaluated by immunohistochemistry in tissue microarrays from 900 patients with primary invasive breast cancer without preoperative treatment, included in a population-based cohort in Sweden (2002-2012) in relation to prognosis. Patients were followed for up to 11 years during which 107 recurrences were observed. Nuclear InsR⁺ expression was present in 214 patients (23.8%) and increased with longer time between surgery and staining (P < 0.001). There were significant effect modifications by ER status and BMI in relation to clinical outcomes. Nuclear InsR⁺ conferred higher recurrence-risk in patients with ER⁺ tumors, but lower risk in patients with ER^- tumors (P_interaction = 0.003). Normal-weight patients with nuclear InsR⁺ tumors had higher recurrence-risk, while overweight or obese patients had half the recurrence-risk compared to patients with nuclear InsR^- tumors (P_interaction = 0.007). Normal-weight patients with a nuclear InsR^-/ER⁺ tumor had the lowest risk for recurrence compared to all other nuclear InsR/ER combinations [HR_adj 0.50, 95% confidence interval (CI): 0.25-0.97], while overweight or obese patients with nuclear InsR^-/ER^- tumors had the worst prognosis (HR_adj 7.75, 95% CI: 2.04-29.48). Nuclear InsR was more prognostic than ER among chemotherapy-treated patients. In summary, nuclear InsR may have prognostic impact among normal-weight patients with ER⁺ tumors and in overweight or obese patients with ER^- tumors. Normal-weight patients with nuclear InsR^-/ER⁺ tumors may benefit from less treatment than normal-weight patients with other nuclear InsR/ER combinations. Overweight or obese patients with nuclear InsR^-/ER^- tumors may benefit from more tailored treatment or weight management.

The Obesity-Breast Cancer Conundrum: An Analysis of the Issues

Breast cancer develops over a timeframe of 2-3 decades prior to clinical detection. Given this prolonged latency, it is somewhat unexpected from a biological perspective that obesity has no effect or reduces the risk for breast cancer in premenopausal women yet increases the risk for breast cancer in postmenopausal women. This conundrum is particularly striking in light of the generally negative effects of obesity on breast cancer outcomes, including larger tumor size at diagnosis and poorer prognosis in both pre- and postmenopausal women. This review and analysis identifies factors that may contribute to this apparent conundrum, issues that merit further investigation, and characteristics of preclinical models for breast cancer and obesity that should be considered if animal models are used to deconstruct the conundrum.

Obesity-Associated Alterations in Inflammation, Epigenetics, and Mammary Tumor Growth Persist in Formerly Obese Mice

Using a murine model of basal-like breast cancer, we tested the hypothesis that chronic obesity, an established breast cancer risk and progression factor in women, induces mammary gland epigenetic reprogramming and increases mammary tumor growth. Moreover, we assessed whether the obesity-induced epigenetic and protumor effects are reversed by weight normalization. Ovariectomized female C57BL/6 mice were fed a control diet or diet-induced obesity (DIO) regimen for 17 weeks, resulting in a normal weight or obese phenotype, respectively. Mice on the DIO regimen were then randomized to continue the DIO diet or were switched to the control diet, resulting in formerly obese (FOb) mice with weights comparable with control mice. At week 24, all mice were orthotopically injected with MMTV-Wnt-1 mouse mammary tumor cells. Mean tumor volume, serum IL6 levels, expression of proinflammatory genes in the mammary fat pad, and mammary DNA methylation profiles were similar in DIO and FOb mice and higher than in controls. Many of the genes found to have obesity-associated hypermethylation in mice were also found to be hypermethylated in the normal breast tissue of obese versus nonobese human subjects, and nearly all of these concordant genes remained hypermethylated after significant weight loss in the FOb mice. Our findings suggest that weight normalization may not be sufficient to reverse the effects of chronic obesity on epigenetic reprogramming and inflammatory signals in the microenvironment that are associated with breast cancer progression. Cancer Prev Res; 9(5); 339-48. ©2016 AACR.

DNA methylation outliers in normal breast tissue identify field defects that are enriched in cancer

Identifying molecular alterations in normal tissue adjacent to cancer is important for understanding cancer aetiology and designing preventive measures. Here we analyse the DNA methylome of 569 breast tissue samples, including 50 from cancer-free women and 84 from matched normal cancer pairs. We use statistical algorithms for dissecting intra- and inter-sample cellular heterogeneity and demonstrate that normal tissue adjacent to breast cancer is characterized by tens to thousands of epigenetic alterations. We show that their genomic distribution is non-random, being strongly enriched for binding sites of transcription factors specifying chromatin architecture. We validate the field defects in an independent cohort and demonstrate that over 30% of the alterations exhibit increased enrichment within matched cancer samples. Breast cancers highly enriched for epigenetic field defects, exhibit adverse clinical outcome. Our data support a model where clonal epigenetic reprogramming towards reduced differentiation in normal tissue is an important step in breast carcinogenesis.

Altered epigenetics is a feature of cancer but whether these changes occur early in tumour development is unclear. Here, the authors analyse methylation events in breast cancer and adjacent normal pairs, and show that methylation changes in the normal tissue are also found in the tumour, suggesting that some of these events occur early in cancer.