Analysis of DNA Methylation in Gliomas: Assessment of Preanalytical Variables.

Autor:	Bomsztyk K; UW Medicine South Lake Union, University of Washington, Seattle, Washington; Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, Washington; Matchstick Technologies, Inc, Kirkland, Washington. Electronic address: karolb@uw.edu., Mar D; UW Medicine South Lake Union, University of Washington, Seattle, Washington; Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, Washington., Denisenko O; UW Medicine South Lake Union, University of Washington, Seattle, Washington., Powell S; Department of Neuropathology, Houston Methodist Hospital, Houston, Texas., Vishnoi M; Department of Neurosurgery, Houston Methodist Research Institute, Houston, Texas., Yin Z; Department of Systems Medicine and Bioengineering, Houston Methodist Neil Cancer Center, Houston, Texas., Delegard J; Department of Neurological Surgery, University of Washington, Seattle, Washington., Hadley C; Department of Neurosurgery, University of New Mexico, Albuquerque, New Mexico., Tandon N; Department of Neurosurgery, McGovern Medical School at UT Health, Houston, Texas., Patel AJ; Department of Neurosurgery, Baylor College of Medicine, Houston, Texas., Patel AP; Department of Neurosurgery, Duke University, Durham, North Carolina., Ellenbogen RG; Department of Neurological Surgery, University of Washington, Seattle, Washington., Ramakrishna R; Department of Neurological Surgery, Weill Cornell Medicine, New York, New York., Rostomily RC; Department of Neurosurgery, Houston Methodist Research Institute, Houston, Texas; Department of Neurological Surgery, University of Washington, Seattle, Washington; Department of Neurological Surgery, Weill Cornell Medicine, New York, New York.
Jazyk:	angličtina
Zdroj:	Laboratory investigation; a journal of technical methods and pathology [Lab Invest] 2024 Dec; Vol. 104 (12), pp. 102160. Date of Electronic Publication: 2024 Oct 18.
DOI:	10.1016/j.labinv.2024.102160
Abstrakt:	Precision oncology is driven by biomarkers. For glioblastoma multiforme (GBM), the most common malignant adult primary brain tumor, O 6 -methylguanine-DNA methyltransferase (MGMT) gene promoter methylation is an important prognostic and treatment clinical biomarker. Time-consuming preanalytical steps such as biospecimen storage, fixation, sampling, and processing are sources of data irreproducibility, and all these preanalytical variables are confounded by intratumor heterogeneity of MGMT promoter methylation. To assess the effect of preanalytical variables on GBM DNA methylation, tissue storage/sampling (CryoGrid), sample preparation multisonicator (PIXUL), and 5-methylcytosine DNA immunoprecipitation (Matrix-MeDIP-qPCR/seq) platforms were used. MGMT promoter methylation status assayed by MeDIP-qPCR was validated with methylation-specific polymerase chain reaction. MGMT promoter methylation levels in frozen and formalin-fixed paraffin-embedded sample pairs were not statistically different, confirming the reliability of formalin-fixed paraffin-embedded for MGMT promoter methylation analysis. Warm ex vivo ischemia (up to 4 hours at 37 °C) and 3 cycles of repeated sample thawing and freezing did not statistically impact 5-methylcytosine at MGMT promoter, exon, and enhancer regions, indicating the resistance of DNA methylation to common variations in sample processing conditions that might be encountered in research and clinical settings. Twenty-six percent to 34% of specimens exhibited intratumor heterogeneity in the MGMT DNA promoter methylation. These data demonstrate that variations in sample fixation, ischemia duration and temperature, and DNA methylation assay technique do not have a statistically significant impact on MGMT promoter methylation assessment. However, intratumor methylation heterogeneity underscores the value of multiple biopsies at different GBM geographic tumor sites in the evaluation of MGMT promoter methylation status. Matrix-MeDIP-seq analysis revealed that MGMT promoter methylation status clustered with other differentially methylated genomic loci (eg, HOXA and lncRNAs) that are resilient to variation in the above preanalytical conditions. These observations offer new opportunities to develop more granular data-based epigenetic GBM biomarkers. In this regard, the high-throughput CryoGrid-PIXUL-Matrix toolbox could be useful. (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)
Databáze:	MEDLINE
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