Blood cell DNA methylation biomarkers in preclinical malignant pleural mesothelioma: the EPIC prospective cohort
Contributo in Atti di convegno
Data di Pubblicazione:
2022
Abstract:
Malignant pleural mesothelioma (MPM) is a rare and aggressive cancer mainly caused by asbestos exposure. Understanding the
contribution of specific and sensitive non-invasive biomarkers may facilitate and enhance screening programs for the early detection of MPM. Aim of the study: To investigate DNA methylation (DNAm) profiles in MPM pre-diagnostic blood samples in a case–control study nested in the European Prospective Investigation into Cancer and nutrition (EPIC) cohort with an aim to characterise DNAm biomarkers associated with MPM. Materials and Methods: From the EPIC cohort, we included samples from 135 participants who developed MPM during 20 years of follow up and 135 matched, cancer-free controls. For the discovery phase we selected EPIC participants who developed MPM within five years from enrolment (n=36) along with their matched controls. Results: We identified nine differentially methylated CpGs, selected by 10-fold cross-validation and correlation analyses: cg25755428 (MRI1), cg20389709 (KLF11), cg23870316, cg13862711 (LHX6), cg06417478 (HOOK2), cg00667948, cg01879420 (AMD1), cg25317025 (RPL17) and cg06205333 (RAP1A). Receiver operating characteristic (ROC) analysis showed that the model including baseline characteristics (age, sex, PC1wbc) along with the nine MPMrelated CpGs has a better predictive value for MPM occurrence than the baseline model alone, maintaining some performance also at more than five years before diagnosis [area under the curve (AUC) < 5 years=0.89; AUC 5-10 years=0.80; AUC >10 years=0.75; baseline AUC range=0.63-0.67]. Conclusion: DNAm changes as non-invasive biomarkers were investigated for the first time in pre-diagnostic blood samples of MPM cases. Their application can improve the identification of asbestos-exposed individuals at higher MPM risk and can pave the way to possibly adopt more intensive monitoring for early disease identification.
Tipologia CRIS:
04C-Slides / Presentazione a convegno
Elenco autori:
E. Casalone, A. Allione, E.J. Herman, C. Viberti, I. Cotellessa, C. Catalano, G. Cugliari, A. Russo, S. Guarrera, D. Mirabelli, C.
Sacerdote, M. Gentile, E. Weiderpass, A. Agudo, EPIC MPM WG, P. Vineis, G. Matullo
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