Preprint
Article

Clinical Validation of a Novel Quantitative Assay for the Detection of MGMT Methylation in Glioblastoma Patients

Altmetrics

Downloads

239

Views

159

Comments

0

Submitted:

03 August 2020

Posted:

04 August 2020

You are already at the latest version

Alerts
Abstract
The promoter hypermethylation of the methylguanine-DNA methyltransferase (MGMT) gene is a frequently used biomarker in daily clinical practice as it is associated with a favorable prognosis in glioblastoma patients treated with temozolamide. In this study we carried out a clinical validation of a quantitative assay for MGMT methylation detection by comparing a novel MSP custom assay using double-probe characteristics (dp_qMSP) with the conventional MSP in 100 FFPE glioblastoma samples collected from a prospective study in La Paz University Hospital. We realized both determinations and established the best cutoff for the identification of positive-methylated samples using the quantitative data obtained from dp_qMSP. Kaplan-Meier curves and ROC time dependent or ROC(t) curves were employed for the comparison of both methodologies. Our results indicate that the optimal cutoff to categorize the MGMTm positive samples by using dp_qMSP is 3.75% methylation value. We obtained similar results using both assays in the same cohort of patients, in terms of progression free survival (PFS) and overall survival (OS) when analyzing the Kaplan-Meier curves. The results of ROC(t) curves showed that dp_qMSP increases the AUC (t) in comparison with MSP for predicting PFS and OS over time. We conclude that dp_qMSP is an alternative methodology compatible with the results obtained with the conventional MSP. This easy-to-use, objective and reliable methodology provides quantitative results and improves the diagnostic precision of patients with glioblastoma in terms of PFS and OS, making it a more competitive assay, suitable for clinical practice.
Keywords: 
Subject: Biology and Life Sciences  -   Biochemistry and Molecular Biology
Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
Prerpints.org logo

Preprints.org is a free preprint server supported by MDPI in Basel, Switzerland.

Subscribe

© 2024 MDPI (Basel, Switzerland) unless otherwise stated