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DNA methylation, microRNAs, and their crosstalk as potential biomarkers in hepatocellular carcinoma
Author(s) -
Sumadi Lukman Anwar,
Ulrich Lehmann
Publication year - 2014
Publication title -
world journal of gastroenterology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.427
H-Index - 155
eISSN - 2219-2840
pISSN - 1007-9327
DOI - 10.3748/wjg.v20.i24.7894
Subject(s) - epigenetics , dna methylation , microrna , biology , carcinogenesis , cancer research , methylation , hepatocellular carcinoma , cancer epigenetics , cancer , genetics , gene expression , gene
Epigenetic alterations have been identified as a major characteristic in human cancers. Advances in the field of epigenetics have contributed significantly in refining our knowledge of molecular mechanisms underlying malignant transformation. DNA methylation and microRNA expression are epigenetic mechanisms that are widely altered in human cancers including hepatocellular carcinoma (HCC), the third leading cause of cancer related mortality worldwide. Both DNA methylation and microRNA expression patterns are regulated in developmental stage specific-, cell type specific- and tissue-specific manner. The aberrations are inferred in the maintenance of cancer stem cells and in clonal cell evolution during carcinogenesis. The availability of genome-wide technologies for DNA methylation and microRNA profiling has revolutionized the field of epigenetics and led to the discovery of a number of epigenetically silenced microRNAs in cancerous cells and primary tissues. Dysregulation of these microRNAs affects several key signalling pathways in hepatocarcinogenesis suggesting that modulation of DNA methylation and/or microRNA expression can serve as new therapeutic targets for HCC. Accumulative evidence shows that aberrant DNA methylation of certain microRNA genes is an event specifically found in HCC which correlates with unfavorable outcomes. Therefore, it can potentially serve as a biomarker for detection as well as for prognosis, monitoring and predicting therapeutic responses in HCC.

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