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Systematic identification of DNA methylation biomarkers for tumor-type-specific detection

Arbona, J. S.; Garcia Samartino, C.; Angeloni, A. R.; Vaquer, C. C.; Wetten, P. A.; Bocanegra, V.; Militello, R. D.; Sanguinetti, G.; Correa, A.; Pellegrini, P.; Carlen, M.; Minatti, W. R.; Vaschalde, G. A.; Perez, R.; Manzino, R. N.; Rodriguez, J. D.; Valdemoros, P.; Sarrio, L.; Ledesma, A.; Campoy, E. M.

2026-02-24 bioinformatics
10.64898/2026.02.20.706794 bioRxiv
Show abstract

DNA methylation biomarkers for cancer diagnostics often underperform when tumor and background tissues share epigenetic programs, or when complex specimens with mixed cellular composition dilute tumor-derived signals and increase variability. To address these limitations, we developed a gene-centric, browser-based discovery platform that integrates genome-wide methylomes with matched transcriptomes and reference layers spanning pan-cancer tissues and leukocytes, enabling background-aware filtering beyond binary tumor-normal contrasts. Candidate loci are prioritized using combined thresholds on methylation effect size and intra-group variability to penalize stochastic and heterogeneous variation. In colorectal cancer, methylation-sensitive restriction enzyme quantitative PCR (MSRE-qPCR) validation in independent tissue cohorts confirmed multiple candidate loci with AUCs of 0.81-1.00. Using the same framework, MSRE-qPCR validation distinguished hepatocellular carcinoma from cirrhotic liver, and analysis of public tumor methylomes identified subtype-specific markers in lung adenocarcinoma and squamous-cell carcinoma. This resource bridges genome-scale epigenomic discovery with clinically accessible PCR-based methylation assays.

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