Abstract. To screen candidate methylation markers for early detection of breast cancer and to explore the relationship between methylation and gene expression, we performed methylated-CpG island recovery assay (MIRA) combined with CpG island array on 61982 CpG sites across 4162 genes in 10 cancerous and 10 non-cancerous breast tissues. Direct bisulfite sequencing and combined bisulfite restriction analysis (COBRA) were carried out in independent cancerous and non-cancerous samples. Gene expression was analyzed by microarrays and validated using RT-PCR. We detected 70 significantly hypermethylated genes in breast cancer tissues, including many novel hypermethylated genes such as ITGA4, NFIX, OTX2 and FGF12. Direct bisulfite sequencing showed widespread methylation occurring in intragenic regions of the WT1, PAX6 and ITGA4 genes and in the promoter region of the OTX2 gene in breast cancer tissues. COBRA assay confirmed that the WT1, OTX2 and PAX6 genes were hypermethylated in breast cancer tissues. Clustering analysis of the gene expression of 70 significantly hypermethylated genes revealed that most hypermethylated genes in breast cancer were not expressed in breast tissues. RT-PCR assay confirmed that WT1 and PITX2 were only weakly expressed in the breast cancer tissues and were not expressed in most non-cancerous breast tissues. OTX2 and PAX6 were not expressed in either breast cancer or noncancerous tissues. In conclusion, these results will expand our knowledge of hypermethylated genes and methylation sites for early detection of breast cancer and deepen our understanding of the relationship between methylation and gene expression. The MIRA approach can screen candidate methylated genes for further clinical validation more effectively than gene expression microarray-based strategy. IntroductionWith an estimated 1.38 million new cancer cases worldwide in 2008, breast cancer is the most frequent cancer and the leading cause of cancer mortality in women (1). If breast cancer is detected and treated at an early stage, the majority of the patients survive. These facts highlight an urgent need to develop novel molecular biomarkers that can detect early stage of breast cancer so that treatment is initiated promptly.Carcinogenesis has been demonstrated to involve not only genetic but also epigenetic alterations that may suppress or activate multiple genes. The most common epigenetic alteration in cancer is DNA methylation (2), which is an early event in carcinogenesis, and may therefore serve as a biomarker for the early detection of cancer. Promoter methylation, with a methyl group to the 5-carbon position of cytosine in CpG islands, is associated with transcriptional silencing. DNA methylation also occurs in the intragenic region. To date, little attention has been paid to intragenic methylation.Recently, aberrant methylations of specific genes that involve breast carcinogenesis have been widely explored and the list of aberrant methylated genes is increasing (3,4). Due to the limitation of techniques for analysis ...

Choline and betaine are essential nutrients involved in one-carbon metabolism and have been hypothesised to affect breast cancer risk. Functional polymorphisms in genes encoding choline-related one-carbon metabolism enzymes, including phosphatidylethanolamine N-methyltransferase (PEMT), choline dehydrogenase (CHDH) and betaine-homocysteine methyltransferase (BHMT), have important roles in choline metabolism and may thus interact with dietary choline and betaine intake to modify breast cancer risk. This study aimed to investigate the interactive effect of polymorphisms in PEMT, BHMT and CHDH genes with choline/betaine intake on breast cancer risk among Chinese women. This hospital-based case-control study consecutively recruited 570 cases with histologically confirmed breast cancer and 576 age-matched (5-year interval) controls. Choline and betaine intakes were assessed by a validated FFQ, and genotyping was conducted for PEMT rs7946, CHDH rs9001 and BHMT rs3733890. OR and 95 % CI were estimated using unconditional logistic regression. Compared with the highest quartile of choline intake, the lowest intake quartile showed a significant increased risk of breast cancer. The SNP PEMT rs7946, CHDH rs9001 and BHMT rs3733890 had no overall association with breast cancer, but a significant risk reduction was observed among postmenopausal women with AA genotype of BHMT rs3733890 (OR 0·49; 95 % CI 0·25, 0·98). Significant interactions were observed between choline intake and SNP PEMT rs7946 (P interaction = 0·029) and BHMT rs3733890 (P interaction = 0·006) in relation to breast cancer risk. Our results suggest that SNP PEMT rs7946 and BHMT rs3733890 may interact with choline intake on breast cancer risk.

Mammary ductoscopy (MD) is commonly used to detect intraductal lesions associated with nipple discharge. This study investigated the relationships between ductoscopic image-based indicators and breast cancer risk, and developed a nomogram for evaluating breast cancer risk in intraductal neoplasms with nipple discharge. A total of 879 consecutive inpatients (916 breasts) with nipple discharge who underwent selective duct excision for intraductal neoplasms detected by MD from June 2008 to April 2014 were analyzed retrospectively. A nomogram was developed using a multivariate logistic regression model based on data from a training set (687 cases) and validated in an independent validation set (229 cases). A Youden-derived cut-off value was assigned to the nomogram for the diagnosis of breast cancer. Color of discharge, location, appearance, and surface of neoplasm, and morphology of ductal wall were independent predictors for breast cancer in multivariate logistic regression analysis. A nomogram based on these predictors performed well. The P value of the Hosmer-Lemeshow test for the prediction model was 0.36. Area under the curve values of 0.812 (95 % confidence interval (CI) 0.763-0.860) and 0.738 (95 % CI 0.635-0.841) was obtained in the training and validation sets, respectively. The accuracies of the nomogram for breast cancer diagnosis were 71.2 % in the training set and 75.5 % in the validation set. We developed a nomogram for evaluating breast cancer risk in intraductal neoplasms with nipple discharge based on MD image findings. This model may aid individual risk assessment and guide treatment in clinical practice.

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