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Enhanced Reduced Representation Bisulfite Sequencing for Assessment of DNA Methylation at Base Pair Resolution
Published on: February 24, 2015
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MethylMeter(®): bisulfite-free quantitative and sensitive DNA methylation profiling and mutation detection in FFPE
David McCarthy1, Walter Pulverer2, Andreas Weinhaeusel2
1Ribomed Biotechnologies Inc., 3469 Kurtz St., San Diego, CA 92110, USA.
Epigenomics
|June 24, 2016
Summary
A new assay, MethylMeter, offers sensitive DNA methylation profiling and mutation detection in clinical samples. This method aids in glioma grading and predicting treatment response, proving clinically valuable.
Area of Science:
- Oncology
- Molecular Biology
- Genetics
Background:
- Clinical laboratories face challenges with insufficient DNA from formalin-fixed, paraffin-embedded tumors for methylation analysis.
- Existing methods like bisulfite or methylation-sensitive restriction enzymes require substantial DNA input.
Purpose of the Study:
- To develop a sensitive method for DNA methylation profiling and mutation detection in clinical samples.
- To establish a novel assay for analyzing challenging formalin-fixed, paraffin-embedded tumor tissues.
Main Methods:
- Developed MethylMeter assay combining methyl-CpG DNA capture and Coupled Abscription PCR Signaling detection.
- Analyzed gliomas for MGMT methylation, glioma CpG island methylator phenotype, and IDH1 R132H mutation.
- Utilized formalin-fixed and paraffin-embedded tumor tissues.
Main Results:
- MethylMeter achieved a 100% assay success rate for all five biomarkers in formalin-fixed, paraffin-embedded tissues.
- MGMT methylation results correlated with survival and mRNA expression data.
- The MethylMeter-based GliomaSTRAT assay simultaneously grades gliomas and predicts temozolomide response.
Conclusions:
- MethylMeter is a sensitive, quantitative method for multitarget DNA methylation profiling and mutation detection.
- The GliomaSTRAT assay provides clinically valuable information for glioma management.
- This assay enables simultaneous glioma grading and prediction of treatment response.

