Literature DB >> 17998806

DNA methylation analysis as a tool for cell typing.

Udo Baron1, Ivana Türbachova, Alexander Hellwag, Florian Eckhardt, Kurt Berlin, Ulrich Hoffmuller, Paul Gardina, Sven Olek.   

Abstract

Cell therapeutic approaches currently lack definitive quality control measures which guarantee safety in clinical applications and create consistent standards for regulatory approval. These approaches rely on isolation, purification and possibly ex vivo manipulation of donor cells. Since such cells are exposed to artificial environments, there is potential for deviations from natural growth processes. The resulting heterogeneity of cell cultures is an inherent problem. Therefore, verification of cell identity and quantification of subpopulations is mandatory. Focusing on cultured human primary cells, we tested whether DNA methylation patterns serve as distinctive cell type markers. We identified panels of cell type specific differentially methylated gene regions (CDMs) which produce unambiguous profiles for these cell types. Applying methylation sensitive single nucleotide primer extension generated binary cell type descriptors ("barcodes") which allow quantification of cell mixtures. Thus, methylation based analytics suggest themselves as promising tools for the characterization and quality control of ex vivo manipulated cells.

Entities:  

Mesh:

Year:  2006        PMID: 17998806     DOI: 10.4161/epi.1.1.2643

Source DB:  PubMed          Journal:  Epigenetics        ISSN: 1559-2294            Impact factor:   4.528


  30 in total

1.  Blood-based profiles of DNA methylation predict the underlying distribution of cell types: a validation analysis.

Authors:  Devin C Koestler; Brock Christensen; Margaret R Karagas; Carmen J Marsit; Scott M Langevin; Karl T Kelsey; John K Wiencke; E Andres Houseman
Journal:  Epigenetics       Date:  2013-06-25       Impact factor: 4.528

2.  Clinical epigenomics for cardiovascular disease: Diagnostics and therapies.

Authors:  Matthew A Fischer; Thomas M Vondriska
Journal:  J Mol Cell Cardiol       Date:  2021-02-06       Impact factor: 5.000

3.  Epigenetic quantification of tumor-infiltrating T-lymphocytes.

Authors:  Jalid Sehouli; Christoph Loddenkemper; Tatjana Cornu; Tim Schwachula; Ulrich Hoffmüller; Andreas Grützkau; Philipp Lohneis; Thorsten Dickhaus; Jörn Gröne; Martin Kruschewski; Alexander Mustea; Ivana Turbachova; Udo Baron; Sven Olek
Journal:  Epigenetics       Date:  2011-02-01       Impact factor: 4.528

Review 4.  FOXP3+ Tregs: heterogeneous phenotypes and conflicting impacts on survival outcomes in patients with colorectal cancer.

Authors:  Changhua Zhuo; Ye Xu; Mingang Ying; Qingguo Li; Liyong Huang; Dawei Li; Sanjun Cai; Bin Li
Journal:  Immunol Res       Date:  2015-03       Impact factor: 2.829

5.  Multigenerational effects of maternal undernutrition.

Authors:  Francine H Einstein
Journal:  Cell Metab       Date:  2014-06-03       Impact factor: 27.287

6.  T regulatory cells in cord blood--FOXP3 demethylation as reliable quantitative marker.

Authors:  Jing Liu; Anna Lluis; Sabina Illi; Laura Layland; Sven Olek; Erika von Mutius; Bianca Schaub
Journal:  PLoS One       Date:  2010-10-12       Impact factor: 3.240

7.  Replication timing: a fingerprint for cell identity and pluripotency.

Authors:  Tyrone Ryba; Ichiro Hiratani; Takayo Sasaki; Dana Battaglia; Michael Kulik; Jinfeng Zhang; Stephen Dalton; David M Gilbert
Journal:  PLoS Comput Biol       Date:  2011-10-20       Impact factor: 4.475

8.  Epigenetic control of the foxp3 locus in regulatory T cells.

Authors:  Stefan Floess; Jennifer Freyer; Christiane Siewert; Udo Baron; Sven Olek; Julia Polansky; Kerstin Schlawe; Hyun-Dong Chang; Tobias Bopp; Edgar Schmitt; Stefan Klein-Hessling; Edgar Serfling; Alf Hamann; Jochen Huehn
Journal:  PLoS Biol       Date:  2007-02       Impact factor: 8.029

Review 9.  Epi-fingerprinting and epi-interventions for improved crop production and food quality.

Authors:  Carlos M Rodríguez López; Mike J Wilkinson
Journal:  Front Plant Sci       Date:  2015-06-05       Impact factor: 5.753

10.  DNA methylation arrays as surrogate measures of cell mixture distribution.

Authors:  Eugene Andres Houseman; William P Accomando; Devin C Koestler; Brock C Christensen; Carmen J Marsit; Heather H Nelson; John K Wiencke; Karl T Kelsey
Journal:  BMC Bioinformatics       Date:  2012-05-08       Impact factor: 3.169

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.