OS05.5.A Methylation analysis of matched primary and recurrent IDHmt astrocytoma; an update from the Glioma Longitudinal Analysis NL (GLASS-NL) consortium

Abstract

Abstract BACKGROUND The evolutionary processes that drive progression in patients with IDH-mutant astrocytoma remain unclear. The GLASS-NL consortium, as part of the larger worldwide GLASS consortium, was initiated to gain insight into the molecular mechanisms underlying glioma evolution and to identify markers of progression in IDH-mutant astrocytomas. Such markers can ultimately assist clinical decision making. Here, we present the first results of genome wide methylation profiling of samples included in the GLASS-NL study. MATERIAL AND METHODS 110 adult patients were identified with an IDH-mutant astrocytoma at first diagnosis. All patients underwent a surgical resection of the tumor at least twice, separated by at least 6 months with a median of 40.9 months (IQR: 24.0, 64.7), in 37% and 18% of the cases, patients were treated with radiotherapy or chemotherapy respectively, before surgical resection of the recurrent tumor. Methylation profiling was done on (macro dissected) DNA isolated of 235 samples from 103 patients (102 1st, 101 2nd, 29 3rd, and 3 4th resection), using the Infinium MethylationEPIC BeadChip array. Copy number variations were also derived from these data. Methylation classes were determined according to Capper et al. (2018). Overall survival (OS) was measured from date of first surgery. RESULTS Of all primary tumors, the methylation-classifier assigned 85 (87%) to the A_IDH (‘low grade’) subclass and 10 (10%) to the A_IDH_HG (‘high grade’) subclass. The relative proportion of high grade tumors increased ~three-fold at tumor recurrence (32/101, 32%) and even further in the second recurrence (15/29, 52%). The overall DNA-methylation levels of recurrent samples was lower than that of primary samples. This difference is explained by the increased number of high grade samples at recurrence, since near identical DNA-methylation levels were observed in samples that remained low grade. In an unsupervised analysis, methylation data derived from first and second resections of individual patients mostly (79%) cluster together. This indicates that variability between tumors is larger than temporal heterogeneity within tumors. Recurrent samples that do not cluster with their primary tumor, form a separate cluster and have relatively low genome-wide DNA-methylation. CONCLUSION Our data demonstrate that methylation profiling identifies a shift towards a higher grade at tumor progression coinciding with reduced genome-wide DNA-methylation levels.