Methylation-specific ligation detection reaction (msLDR): a new approach for multiplex evaluation of methylation patterns View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2011-10

AUTHORS

Felix Bormann, Christine Sers, Barbara Seliger, Diana Handke, Thomas Bergmann, Stephanie Seibt, Hans Lehrach, Andreas Dahl

ABSTRACT

A new sensitive method for multiplex gene-specific methylation analysis was developed using a ligation-based approach combined with a TaqMan-based detection and readout employing universal reporter probes. The approach, termed methylation-specific Ligation Detection Reaction (msLDR), was applied to test 16 loci in 8 different colorectal cancer cells in parallel. These loci encode immune regulatory genes involved in T-cell and natural killer cell activation, whose silencing is associated with the development or progression of colorectal cancer. Parallel analysis of HLA-A, HLA-B, STAT1, B2M, LMP2, LMP7, PA28α, TAP1, TAP2, TAPBP, ULBP2 and ULBP3 by msLDR in eight colorectal cancer cell lines showed preferential methylation at the HLA-B, ULBP2 and ULBB3 loci, but not at the other loci. MsLDR was found to represent a suitable and sensitive method for the detection of distinct methylation patterns as validated by conventional bisulphite Sanger sequencing and COBRA analysis. Since gene silencing by epigenetic mechanisms plays a central role during transformation of a normal differentiated somatic cell into a cancer cell, characterization of the gene methylation status in tumours is a major topic not only in basic research, but also in clinical diagnostics. Due to a very simple workflow, msLDR is likely to be applicable to clinical samples and thus comprises a potential diagnostic tool for clinical purposes. More... »

PAGES

279

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00438-011-0645-9

DOI

http://dx.doi.org/10.1007/s00438-011-0645-9

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1023645244

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/21879293


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Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s00438-011-0645-9'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s00438-011-0645-9'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s00438-011-0645-9'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s00438-011-0645-9'


 

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