Literature DB >> 22121974

The implications of heterogeneous DNA methylation for the accurate quantification of methylation.

Thomas Mikeska1, Ida L M Candiloro, Alexander Dobrovic.   

Abstract

DNA methylation based biomarkers have considerable potential for molecular diagnostics, both as tumor specific biomarkers for the early detection or post-therapeutic monitoring of cancer as well as prognostic and predictive biomarkers for therapeutic stratification. Particularly in the former, the accurate estimation of DNA methylation is of compelling importance. However, quantification of DNA methylation has many traps for the unwary, especially when heterogeneous methylation comprising multiple alleles with varied DNA methylation patterns (epialleles) is present. The frequent occurrence of heterogeneous methylation as distinct from a simple mixture of fully methylated and unmethylated alleles is generally not taken into account when DNA methylation is considered as a cancer biomarker. When heterogeneous DNA methylation is present, the proportion of methylated molecules is difficult to quantify without a method that allows the measurement of individual epialleles. In this article, we critically assess the methodologies frequently used to investigate DNA methylation, with an emphasis on the detection and measurement of heterogeneous DNA methylation. The adoption of digital approaches will enable the effective use of heterogeneous DNA methylation as a cancer biomarker.

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Year:  2010        PMID: 22121974     DOI: 10.2217/epi.10.32

Source DB:  PubMed          Journal:  Epigenomics        ISSN: 1750-192X            Impact factor:   4.778


  59 in total

1.  Concomitant aberrant methylation of p15 and MGMT genes in acute myeloid leukemia: association with a particular immunophenotype of blast cells.

Authors:  Nada Kraguljac Kurtović; Milena Krajnović; Andrija Bogdanović; Nada Suvajdžić; Jelica Jovanović; Bogomir Dimitrijević; Milica Colović; Koviljka Krtolica
Journal:  Med Oncol       Date:  2012-07-07       Impact factor: 3.064

2.  Identification and Quantification of Heterogeneously-methylated DNA Fragments Using Epiallele-sensitive Droplet Digital Polymerase Chain Reaction (EAST-ddPCR).

Authors:  Mario Menschikowski; Carsten Jandeck; Markus Friedemann; Susan Richter; Dana Thiem; Björn Sönke Lange; Meinolf Suttorp
Journal:  Cancer Genomics Proteomics       Date:  2018 Jul-Aug       Impact factor: 4.069

3.  Evaluation of INK4A promoter methylation using pyrosequencing and circulating cell-free DNA from patients with hepatocellular carcinoma.

Authors:  Gengming Huang; Joseph D Krocker; Jason L Kirk; Shehzad N Merwat; Hyunsu Ju; Roger D Soloway; Lucas R Wieck; Albert Li; Anthony O Okorodudu; John R Petersen; Nihal E Abdulla; Andrea Duchini; Luca Cicalese; Cristiana Rastellini; Peter C Hu; Jianli Dong
Journal:  Clin Chem Lab Med       Date:  2014-06       Impact factor: 3.694

4.  Facile profiling of molecular heterogeneity by microfluidic digital melt.

Authors:  Christine M O'Keefe; Thomas R Pisanic; Helena Zec; Michael J Overman; James G Herman; Tza-Huei Wang
Journal:  Sci Adv       Date:  2018-09-28       Impact factor: 14.136

5.  Eagles report: Developing cancer biomarkers from genome-wide DNA methylation analyses.

Authors:  Wolfgang A Schulz; Wolfgang Goering
Journal:  World J Clin Oncol       Date:  2011-01-10

6.  Assessing combined methylation-sensitive high resolution melting and pyrosequencing for the analysis of heterogeneous DNA methylation.

Authors:  Ida L M Candiloro; Thomas Mikeska; Alexander Dobrovic
Journal:  Epigenetics       Date:  2011-04-01       Impact factor: 4.528

7.  Rapid assessment of the heterogeneous methylation status of CEBPA in patients with acute myeloid leukemia by using high-resolution melting profile.

Authors:  Tsung-Chin Lin; Sin-Sien Jiang; Wen-Chien Chou; Hsin-An Hou; Yu-Min Lin; Chia-Ling Chang; Cherng-An Hsu; Hwei-Fang Tien; Liang-In Lin
Journal:  J Mol Diagn       Date:  2011-06-30       Impact factor: 5.568

8.  PLMET: A Novel Pseudolikelihood-Based EM Test for Homogeneity in Generalilzed Exponential Tilt Mixture Models.

Authors:  Chuan Hong; Yang Ning; Shuang Wang; Hao Wu; Raymond J Carroll; Yong Chen
Journal:  J Am Stat Assoc       Date:  2017-02-27       Impact factor: 5.033

9.  Methylomic Analysis of Ovarian Cancers Identifies Tumor-Specific Alterations Readily Detectable in Early Precursor Lesions.

Authors:  Thomas R Pisanic; Leslie M Cope; Shiou-Fu Lin; Ting-Tai Yen; Pornpat Athamanolap; Ryoichi Asaka; Kentaro Nakayama; Amanda N Fader; Tza-Huei Wang; Ie-Ming Shih; Tian-Li Wang
Journal:  Clin Cancer Res       Date:  2018-08-14       Impact factor: 12.531

10.  DREAMing: a simple and ultrasensitive method for assessing intratumor epigenetic heterogeneity directly from liquid biopsies.

Authors:  Thomas R Pisanic; Pornpat Athamanolap; Weijie Poh; Chen Chen; Alicia Hulbert; Malcolm V Brock; James G Herman; Tza-Huei Wang
Journal:  Nucleic Acids Res       Date:  2015-08-24       Impact factor: 16.971

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