DNA甲基化
乳腺癌
表观遗传学
甲基化
医学
内科学
生物
肿瘤科
癌症
生物信息学
基因
遗传学
基因表达
作者
Lien Van De Voorde,Reinhart Speeckaert,Dirk Van Gestel,Marc Bracke,Wilfried De Neve,Joris Delanghe,Marijn M. Speeckaert
标识
DOI:10.1016/j.mrrev.2012.06.001
摘要
Alterations of genetic and epigenetic features can provide important insights into the natural history of breast cancer. Although DNA methylation analysis is a rapidly developing field, a reproducible epigenetic blood-based assay for diagnosis and follow-up of breast cancer has yet to be successfully developed into a routine clinical test. The aim of this study was to review multiple serum DNA methylation assays and to highlight the value of those novel biomarkers in diagnosis, prognosis and prediction of therapeutic outcome. Serum is readily accessible for molecular diagnosis in all individuals from a peripheral blood sample. The list of hypermethylated genes in breast cancer is heterogeneous and no single gene is methylated in all breast cancer types. There is increasing evidence that a panel of epigenetic markers is essential to achieve a higher sensitivity and specificity in breast cancer detection. However, the reported percentages of methylation are highly variable, which can be partly explained by the different sensitivities and the different intra-/inter-assay coefficients of variability of the analysis methods. Moreover, there is a striking lack of receiver operating characteristic (ROC) curves of the proposed biomarkers. Another point of criticism is the fact that ‘normal’ patterns of DNA methylation of some tumor suppressor and other cancer-related genes are influenced by several factors and are often poorly characterized. A relatively frequent methylation of those genes has been observed in high-risk asymptomatic women. Finally, there is a call for larger prospective cohort studies to determine methylation patterns during treatment and follow-up. Identification of patterns specific for a differential response to therapeutic interventions should be useful. Only in this way, it will be possible to evaluate the predictive and prognostic characteristics of those novel promising biomarkers.
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