Validation of target‐enriched enzymatic methylation sequencing for brain tumor classification from formalin‐fixed paraffin embedded‐derived <scp>DNA</scp>

DNA methylation profiling by Illumina methylation array-based methods has revolutionized the molecular classification and diagnosis of brain tumors. A significant barrier to adopting these methods in a clinical environment is the requirement for specialized scanners, which results in high additional costs and a larger laboratory footprint. DNA sequencing-based alternatives are attractive because most clinical molecular pathology laboratories already use sequencers for other molecular assays. This study aimed to compare the utility of the newly developed sequencing-based enzymatic methyl sequencing (EM-seq) method paired with the Twist Human Methylome panel for brain tumor classification with standard Infinium Methylation BeadChip-based methods. We used DNA from fresh-frozen or formalin-fixed, paraffin-embedded (FFPE) brain cancer samples from 19 patients and 1 control sample to construct DNA libraries covering 3.98 million CpG sites. We developed and validated a bioinformatics pipeline to analyze target-enriched EM-seq (TEEM-seq) data in comparison with standard array-based methods for tumor classification and copy number profiling. We found high concordance between TEEM-seq and traditional methods, with high correlation coefficients (>0.98) between FFPE replicates. We successfully classified tumor samples into the expected molecular classes with robust prediction scores (>0.82). We observed that FFPE samples required a sequencing depth of at least 35x to achieve consistently high and reliable prediction scores. The TEEM-seq method has the potential to complement existing tumor classification methods and lower the barriers for the adoption of methylation profiling in routine clinical use.

Authors

Institutions

Publication Details

Journal
Brain Pathology
Published
2025-02-28
DOI
https://doi.org/10.1111/bpa.70000
Citations
3
Primary Topic
Epigenetics and DNA Methylation
Type
article
Field-Weighted Citation Impact
2.42

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Validation of target‐enriched enzymatic methylation sequencing for brain tumor classification from formalin‐fixed paraffin embedded‐derived DNA

Quynh T. Tran, Brent A. Orr, Charles Grenfell Mullighan, Ruth Tatevossian et al.
3 citations
Brain Pathology
Epigenetics and DNA Methylation
2.42
article

Validation of target‐enriched enzymatic methylation sequencing for brain tumor classification from formalin‐fixed paraffin embedded‐derived DNA

Quynh T. Tran, Brent A. Orr, Charles Grenfell Mullighan, Ruth Tatevossian, Md Zahangir Alom, Lu Wang, Sujuan Jia
article en
3 citations

Abstract

DNA methylation profiling by Illumina methylation array-based methods has revolutionized the molecular classification and diagnosis of brain tumors. A significant barrier to adopting these methods in a clinical environment is the requirement for specialized scanners, which results in high additional costs and a larger laboratory footprint. DNA sequencing-based alternatives are attractive because most clinical molecular pathology laboratories already use sequencers for other molecular assays. This study aimed to compare the utility of the newly developed sequencing-based enzymatic methyl sequencing (EM-seq) method paired with the Twist Human Methylome panel for brain tumor classification with standard Infinium Methylation BeadChip-based methods. We used DNA from fresh-frozen or formalin-fixed, paraffin-embedded (FFPE) brain cancer samples from 19 patients and 1 control sample to construct DNA libraries covering 3.98 million CpG sites. We developed and validated a bioinformatics pipeline to analyze target-enriched EM-seq (TEEM-seq) data in comparison with standard array-based methods for tumor classification and copy number profiling. We found high concordance between TEEM-seq and traditional methods, with high correlation coefficients (>0.98) between FFPE replicates. We successfully classified tumor samples into the expected molecular classes with robust prediction scores (>0.82). We observed that FFPE samples required a sequencing depth of at least 35x to achieve consistently high and reliable prediction scores. The TEEM-seq method has the potential to complement existing tumor classification methods and lower the barriers for the adoption of methylation profiling in routine clinical use.

Brain PathologyVol. 35(5)
St. Jude Children's Research Hospital (US)
American Lebanese Syrian Associated Charities
Openalex Percentile: Top 13%
Epigenetics and DNA Methylation
2.42
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.