Breast cancer is the most frequent cancer in women and represents the second leading cause of cancer death among women (after lung cancer). The etiology of breast cancer is still poorly understood with known breast cancer risk factors explaining only a small proportion of cases. Risk factors that modulate the development of breast cancer discussed in this review include: age, geographic location (country of origin) and socioeconomic status, reproductive events, exogenous hormones, lifestyle risk factors (alcohol, diet, obesity and physical activity), familial history of breast cancer, mammographic density, history of benign breast disease, ionizing radiation, bone density, height, IGF-1 and prolactin levels, chemopreventive agents. Additionally, we summarized breast cancer risk associated with the following genetic factors: breast cancer susceptibility high-penetrance genes (BRCA1, BRCA2, p53, PTEN, ATM, NBS1 or LKB1) and low-penetrance genes such as cytochrome P450 genes (CYP1A1, CYP2D6, CYP19), glutathione S-transferase family (GSTM1, GSTP1), alcohol and one-carbon metabolism genes (ADH1C and MTHFR), DNA repair genes (XRCC1, XRCC3, ERCC4/XPF) and genes encoding cell signaling molecules (PR, ER, TNFα or HSP70). All these factors contribute to a better understanding of breast cancer risk. Nonetheless, in order to evaluate more accurately the overall risk of breast tumorigenesis, novel genetic and phenotypic traits need to be identified. Keywords

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DNA alterations in mitochondria are believed to play a role in carcinogenesis and are found in smoking-related cancers. We sought to replicate earlier findings for the association of smoking with increased mitochondrial DNA (mtDNA) content in buccal cells and further hypothesized that there would be an increased number of somatic mtDNA mutations in smokers. Buccal cells and blood lymphocytes were studied from 42 healthy smokers and 30 non-smokers. Temporal temperature gradient electrophoresis screening and sequencing was used to identify mtDNA mutations. The relative mtDNA content was determined by real-time polymerase chain reaction. Assuming that mtDNA in lymphocytes represents the inherited sequence, it was found that 31% of smokers harbored at least one somatic mtDNA mutation in buccal cells with a total of 39 point mutations and 8 short deletions/insertions. In contrast, only 23% of non-smokers possessed mutations with a total of 10 point mutations and no insertions/deletions detected. mtDNA somatic mutation density was higher in smokers (0.68/10 000 bp per person) than in non-smokers (0.2/10 000 bp per person). There was a statistically significant difference in the pattern of homoplasmy and heteroplasmy mutation changes between smokers and non-smokers. Whereas non-smokers had the most mutations in D-loop region (70%), smokers had mutations in both messenger RNA encoding gene (36%) and D-loop region (49%). The mean ratio of buccal cells to lymphocytes of mtDNA content in smokers was increased (2.81) when compared with non-smokers (0.46). These results indicate that cigarette smoke exposure affects mtDNA in buccal cells of smokers. Additional studies are needed to determine if mitochondrial mutation assays provide new or complementary information for estimating cigarette smoke exposure at the cellular level or as a cancer risk biomarker.

Cancer patients' outcome and survival depends on the early diagnosis of malignant lesions. Several investigation methods used for the prevention and early detection strategies have specific limitations. More recently, epigenetic changes have been considered one of the most promising tools for the early diagnosis of cancer. Some of these epigenetic alterations including promoter hypermethylation of genes like P16INK4a, BRCA1, BRCA2, ERα and RARβ2, APC, and RASSF1A have been associated with early stages of mammary gland tumorigenesis and have been suggested to be included in the models that evaluate individual breast cancer risk. In lung cancer, P16INK4a and MGMT gene hypermethylation was observed in sputum years before clinical manifestation of the squamous cell carcinoma among smokers. Loss of GSTP1 function by DNA hypermethylation together with changes in the methylation levels of repetitive elements like LINE-1 and Sat2 was reported in prostatic preneoplastic lesions. Also, DNA hypermethylation for hMLH1 and MGMT DNA repair genes was reported in precursor lesions to colorectal cancer. These epigenetic alterations may be influenced by factors such as xenoestrogens, folate, and multivitamins. Detection of these changes may help determining cancer susceptibility and early diagnosis.

Background Blood adipokines are associated with breast cancer risk; however, blood–breast adipokine correlations and factors that explain variation in adipokines are unknown. Methods Plasma (n = 155) and breast (n = 85) leptin and adiponectin were assessed by immunoassays in women with no history of cancer. Multivariable-adjusted regression models were used to determine breast adipokine associations. Results Through body mass index (BMI)-adjusted analyses, we initially observed positive plasma–breast correlations for leptin (r = 0.41, P = 0.0002) and adiponectin (r = 0.23, P = 0.05). The positive plasma–breast correlation for leptin was strongest among normal weight women (r = 0.62), whereas the correlation for adiponectin was strongest among obese women (r = 0.31). In multivariable models, adjusting for BMI, demographic, reproductive, and lifestyle factors, plasma leptin was not associated with breast leptin, and only the highest quartile of plasma adiponectin was associated with tissue levels. Of the risk factors investigated, those that contributed most to the variation in breast tissue adipokines were BMI and race for leptin, oral contraceptive use and smoking status for adiponectin. Conclusions Although we report positive plasma–breast adipokine correlations overall, plasma adipokine concentrations may not be good surrogates for breast concentrations among all women. Predictors of breast adipokines vary, depending on subject characteristics, possibly explaining inconsistent epidemiologic results and they implicate differing pathways toward carcinogenesis. Impact A clearer understanding of the relationships between plasma adipokines and their levels within the target organ is necessary to better understand the impact of these hormones on breast cancer risk. Future studies are needed to identify additional factors associated with breast adipokines in target tissues.

Breast cancer is more common in European Americans (EAs) than in African Americans (AAs) but mortality from breast cancer is higher among AAs. While there are racial differences in DNA methylation and gene expression in breast tumors, little is known whether such racial differences exist in breast tissues of healthy women. Genome-wide DNA methylation and gene expression profiling was performed in histologically normal breast tissues of healthy women. Linear regression models were used to identify differentially-methylated CpG sites (CpGs) between EAs (n D 61) and AAs (n D 22). Correlations for methylation and expression were assessed. Biological functions of the differentially-methylated genes were assigned using the Ingenuity Pathway Analysis. Among 485 differentially-methylated CpGs by race, 203 were hypermethylated in EAs, and 282 were hypermethylated in AAs. Promoter-related differentially-methylated CpGs were more frequently hypermethylated in EAs (52%) than AAs (27%) while gene body and intergenic CpGs were more frequently hypermethylated in AAs. The differentially-methylated CpGs were enriched for cancer-associated genes with roles in cell death and survival, cellular development, and cell-to-cell signaling. In a separate analysis for correlation in EAs and AAs, different patterns of correlation were found between EAs and AAs. The correlated genes showed different biological networks between EAs and AAs; networks were connected by Ubiquitin C. To our knowledge, this is the first comprehensive genome-wide study to identify differences in methylation and gene expression between EAs and AAs in breast tissues from healthy women. These findings may provide further insights regarding the contribution of epigenetic differences to racial disparities in breast cancer.

Purpose To determine the hypermethylation status of the promoter regions of tumor suppressor genes in normal breast tissues and identify the determinants of these epigenetic changes. Experimental design Questionnaires and breast tissues were collected from healthy women without a history of cancer and undergoing reduction mammoplasty (N=141). Methylation for p16INK4, BRCA1, ERα and RAR-β promoter regions from normal breast tissues were determined by methylation specific PCR. Associations were examined with chi-square and Fisher’s exact test as well as logistic regression. All statistical tests were two-sided. Results p16INK4, BRCA1, ERα and RAR-β hypermethylation were identified in 31%, 17% 9% and 0% of the women, respectively. Women with BRCA1 hypermethylation had an eight-fold increase in the risk of ERα hypermethylation (p=0.007). p16INK4 hypermethylation was present in 28% of African-Americans, but 65% in European-Americans (p=0.02). There was an increased likelihood of p16INK4 or BRCA1 hypermethylation for women with family history of cancer (OR 2.3; 95%CI: 1.05–4.85 and OR 5.0; 95%CI: 1.55–15.81, respectively). ERα hypermethylation was associated with family history of breast cancer (OR 6.6; 95%CI: 1.58–27.71). After stratification by race, p16INK4 in European-Americans and BRCA1 hypermethylation in African-Americans were associated with family history of cancer (OR 3.8; 95%CI: 1.21–12.03 and OR 6.5; 95%CI: 1.33–31.32, respectively). Conclusions Gene promoter hypermethylation was commonly found in healthy breast tissues from women without cancer, indicating that these events are frequent and early lesions. Race and family history of cancer increase the likelihood of these early events.

Single nucleotide polymorphisms (SNPs) in one-carbon metabolism genes and lifestyle factors (alcohol drinking and breast folate) may be determinants of whole-genome methylation in the breast. DNA methylation profiling was performed using the Illumina Infinium HumanMethylation450 BeadChip in 81 normal breast tissues from women undergoing reduction mammoplasty and no history of cancer. ANCOVA, adjusting for age, race and BMI, was used to identify differentially-methylated (DM) CpGs. Gene expression, by the Affymetrix GeneChip Human Transcriptome Array 2.0, was correlated with DM. Biological networks of DM genes were assigned using Ingenuity Pathway Analysis. Fifty-seven CpG sites were DM in association with eight SNPs in FTHFD, MTHFD1, MTHFR, MTR, MTRR, and TYMS (P <5.0 x 10); 56% of the DM CpGs were associated with FTHFD SNPs, including DM within FTHFD. Gene expression was negatively correlated with FTHFD methylation (r=-0.25, P=0.017). Four DM CpGs identified by SNPs in MTRR, MTHFR, and FTHFD were significantly associated with alcohol consumption and/or breast folate. The top biological network of DM CpGs was associated with Energy Production, Molecular Transportation, and Nucleic Acid Metabolism. This is the first comprehensive study of the association between SNPs in one-carbon metabolism genes and genome-wide DNA methylation in normal breast tissues. These SNPs, especially FTHFD, as well as alcohol intake and folate exposure, appear to affect DM in breast tissues of healthy women. The finding that SNPs in FTHFD and MTR are associated with their own methylation is novel and highlights a role for these SNPs as cis-methylation quantitative trait loci.