Abstract
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.