Pleomorphic xanthoastrocytoma (PXA) in its classic manifestation exhibits distinct morphological features and is assigned to CNS WHO grade 2 or grade 3. Distinction from glioblastoma variants and lower grade glial and glioneuronal tumors is a common diagnostic challenge. We compared a morphologically defined set of PXA (histPXA) with an independent set, defined by DNA methylation analysis (mcPXA). HistPXA encompassed 144 tumors all subjected to DNA methylation array analysis. Sixty-two histPXA matched to the methylation class mcPXA. These were combined with the cases that showed the mcPXA signature but had received a histopathological diagnosis other than PXA. This cohort constituted a set of 220 mcPXA. Molecular and clinical parameters were analyzed in these groups. Morphological parameters were analyzed in a subset of tumors with FFPE tissue available. HistPXA revealed considerable heterogeneity in regard to methylation classes, with methylation classes glioblastoma and ganglioglioma being the most frequent mismatches. Similarly, the mcPXA cohort contained tumors of diverse histological diagnoses, with glioblastoma constituting the most frequent mismatch. Subsequent analyses demonstrated the presence of canonical pTERT mutations to be associated with unfavorable prognosis among mcPXA. Based on these data, we consider the tumor type PXA to be histologically more varied than previously assumed. Histological approach to diagnosis will predominantly identify cases with the established archetypical morphology. DNA methylation analysis includes additional tumors in the tumor class PXA that share similar DNA methylation profile but lack the typical morphology of a PXA. DNA methylation analysis also assist in separating other tumor types with morphologic overlap to PXA. Our data suggest the presence of canonical pTERT mutations as a robust indicator for poor prognosis in methylation class PXA.

Alzheimer's disease (AD) is the most common cause of dementia with advancing age as its strongest risk factor. AD neuropathologic change (ADNC) is known to be associated with numerous DNA methylation changes in the human brain, but the oldest old (> 90 years) have so far been underrepresented in epigenetic studies of ADNC. Our study participants were individuals aged over 90 years (n = 47) from The 90+ Study. We analyzed DNA methylation from bulk samples in eight precisely dissected regions of the human brain: middle frontal gyrus, cingulate gyrus, entorhinal cortex, dentate gyrus, CA1, substantia nigra, locus coeruleus and cerebellar cortex. We deconvolved our bulk data into cell-type-specific (CTS) signals using computational methods. CTS methylation differences were analyzed across different levels of ADNC. The highest amount of ADNC related methylation differences was found in the dentate gyrus, a region that has so far been underrepresented in large scale multi-omic studies. In neurons of the dentate gyrus, DNA methylation significantly differed with increased burden of amyloid beta (Aβ) plaques at 5897 promoter regions of protein-coding genes. Amongst these, higher Aβ plaque burden was associated with promoter hypomethylation of the Presenilin enhancer 2 (PEN-2) gene, one of the rate limiting genes in the formation of gamma-secretase, a multicomponent complex that is responsible in part for the endoproteolytic cleavage of amyloid precursor protein into Aβ peptides. In addition to novel ADNC related DNA methylation changes, we present the most detailed array-based methylation survey of the old aged human brain to date. Our open-sourced dataset can serve as a brain region reference panel for future studies and help advance research in aging and neurodegenerative diseases.

The introduction of the classification of brain tumours based on their DNA methylation profile has significantly changed the diagnostic approach for cases with ambiguous histology, non-informative or contradictory molecular profiles or for entities where methylation profiling provides useful information for patient risk stratification, for example in medulloblastoma and ependymoma. We present our experience that combines a conventional molecular diagnostic approach with the complementary use of a DNA methylation-based classification tool, for adult brain tumours originating from local as well as national referrals. We report the frequency of IDH mutations in a large cohort of nearly 1550 patients, EGFR amplifications in almost 1900 IDH-wildtype glioblastomas, and histone mutations in 70 adult gliomas. We demonstrate how additional methylation-based classification has changed and improved our diagnostic approach. Of the 325 cases referred for methylome testing, 179 (56%) had a calibrated score of 0.84 and higher and were included in the evaluation. In these 179 samples, the diagnosis was changed in 45 (25%), refined in 86 (48%) and confirmed in 44 cases (25%). In addition, the methylation arrays contain copy number information that usefully complements the methylation profile. For example, EGFR amplification which is 95% concordant with our Real-Time PCR-based copy number assays. We propose here a diagnostic algorithm that integrates histology, conventional molecular tests and methylation arrays.

Craniopharyngiomas (CP) are rare epithelial tumors of the sellar region. Two subtypes, adamantinomatous (adaCP) and papillary CP (papCP), were previously identified based on histomorphological and epidemiological aspects. Recent data indicates that both variants are defined by specific genetic alterations, and influenced by distinct molecular pathways and particular origins. The fact that CP is an uncommon tumor entity renders studies on large cohorts difficult and exceptional. In order to achieve further insights distinguishing CP variants, we conducted whole genome methylation (450 k array) and microarray-based gene expression studies in addition to CTNNB1 and BRAF mutation analysis using a comprehensive cohort of 80 adaCP and 35 papCP.

In this multi-institutional study we compiled a retrospective cohort of 86 posterior fossa tumors having received the diagnosis of cerebellar glioblastoma (cGBM). All tumors were reviewed histologically and subjected to array-based methylation analysis followed by algorithm-based classification into distinct methylation classes (MCs). The single MC containing the largest proportion of 25 tumors diagnosed as cGBM was MC anaplastic astrocytoma with piloid features representing a recently-described molecular tumor entity not yet included in the WHO Classification of Tumours of the Central Nervous System (WHO classification). Twenty-nine tumors molecularly corresponded to either of 6 methylation subclasses subsumed in the MC family GBM IDH wildtype. Further we identified 6 tumors belonging to the MC diffuse midline glioma H3 K27 M mutant and 6 tumors allotted to the MC IDH mutant glioma subclass astrocytoma. Two tumors were classified as MC pilocytic astrocytoma of the posterior fossa, one as MC CNS high grade neuroepithelial tumor with BCOR alteration and one as MC control tissue, inflammatory tumor microenvironment. The methylation profiles of 16 tumors could not clearly be assigned to one distinct MC. In comparison to supratentorial localization, the MC GBM IDH wildtype subclass midline was overrepresented, whereas the MCs GBM IDH wildtype subclass mesenchymal and subclass RTK II were underrepresented in the cerebellum. Based on the integration of molecular and histological findings all tumors received an integrated diagnosis in line with the WHO classification 2016. In conclusion, cGBM does not represent a molecularly uniform tumor entity, but rather comprises different brain tumor entities with diverse prognosis and therapeutic options. Distinction of these molecular tumor classes requires molecular analysis. More than 30% of tumors diagnosed as cGBM belong to the recently described molecular entity of anaplastic astrocytoma with piloid features.

Medulloblastoma (MB) is the most frequent malignant brain tumor in children. Four subgroups with distinct genetic, epigenetic and clinical characteristics have been identified. Survival remains particularly poor in patients with Group 3 tumors harbouring a MYC amplification. We herein explore the molecular mechanisms and translational implications of class I histone deacetylase (HDAC) inhibition in MYC driven MBs.