ArticleOral oncology2025
Optimization of methylation capture sequencing workflow in formalin fixed tissue from oral squamous cell carcinoma patients.
Article in Oral oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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10 authors.
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Abstract
backgroundOral squamous cell carcinoma (OSCC) is typically diagnosed at advanced stages, resulting in poor survival rates. Epigenetic alterations, especially DNA methylation, are important early and key contributors to OSCC pathogenesis, but comprehensive epigenetic analysis has traditionally been confounded by cancer tissue availability, with fresh-frozen tissues being the gold standard but difficult to obtain.
methodsThis study established and optimized a new workflow for the use of methylation capture sequencing (MC-seq) to analyze DNA methylation profiles in formalin-fixed paraffin-embedded (FFPE) tissues. Twelve OSCC patients were randomly selected from a prospective, multi-institutional study. Paired fresh-frozen and FFPE tissues were collected and processed for DNA extraction and MC-seq. Data were pre-processed using Bismark and methylKit pipelines. Methylation concordance between FFPE and fresh-frozen samples was assessed by comparing β-value correlation.
resultsDNA from FFPE and fresh-frozen OSCC samples showed minimal differences in fragmentation, with FFPE achieving high mapping efficiency (average 71.6%) and retaining an average of about 5 million CpG sites at 10× depth. The distributions of CpG in the methylome region, including promoter, exonic, intronic, and intergenic regions, showed similar patterns between sample types. Additionally, the methylation levels of all matched CpG sites in our 12-gene prognostic panel showed a strong correlation (r ≥ 0.97) between FFPE and fresh-frozen samples.
conclusionOur findings indicate that FFPE samples are reliable for methylation capture sequencing, offering a new, scalable and reliable alternative to fresh-frozen samples for large-scale OSCC research.
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