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Updated: Apr 15, 2026

Genome-Wide Analysis of DNA Methylation in Gastrointestinal Cancer
Published on: September 18, 2020
Quantitative methodology is critical for assessing DNA methylation and impacts on correlation with patient outcome
Annette M Lim1, Ida Lm Candiloro2, Nicholas Wong3
1Department of Medical Oncology, Peter MacCallum Cancer Centre, Locked Bag 1 A'Beckett Street, Melbourne, Victoria 8006 Australia ; The University of Melbourne, Parkville, Victoria 3010 Australia ; Research Division, Peter MacCallum Cancer Centre, Locked Bag 1 A'Beckett Street, Melbourne, Victoria 8006 Australia.
Background:
DNA hypermethylation is reported as a frequent event and prognostic marker in head and neck squamous cell carcinomas (HNSCC). Methylation has been commonly assessed with non-quantitative methodologies, such as methylation-specific PCR (MSP). We investigated previously reported hypermethylated genes with quantitative methodology in oral tongue squamous cell carcinomas (OTSCC).
Results:
The methylation status of 12 genes in 115 OTSCC samples was assessed by one or more of three quantitative analyses: methylation sensitive high resolution melting (MS-HRM), sensitive-melting analysis after real time-methylation specific PCR (SMART-MSP), and bisulfite pyrosequencing. In contrast to much of the literature, either no or infrequent locus-specific methylation was identified by MS-HRM for DAPK1, RASSF1A, MGMT, MLH1, APC, CDH1, CDH13, BRCA1, ERCC1, and ATM. The most frequently methylated loci were RUNX3 (18/108 methylated) and ABO (22/107 methylated). Interrogation of the Cancer Genome Atlas (TCGA) HNSCC cohort confirmed the frequency of significant methylation for the loci investigated. Heterogeneous methylation of RUNX3 (18/108) and ABO (22/107) detected by MS-HRM, conferred significantly worse survival (P = 0.01, and P = 0.03). However, following quantification of methylation levels using pyrosequencing, only four tumors had significant quantities (>15%) of RUNX3 methylation which correlated with a worse patient outcome (P <0.001), while the prognostic significance of ABO hypermethylation was lost. RUNX3 methylation was not prognostic for the TCGA cohort (P = 0.76).
Conclusions:
We demonstrated the critical need for quantification of methylation levels and its impact on correlative analyses. In OTSCC, we found little evidence of significant or frequent hypermethylation of many loci reported to be commonly methylated. It is likely that previous reports have overestimated the frequency of significant methylation events as a consequence of the use of non-quantitative methodology.
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