Aims: Paediatric brain tumours are rare, and establishing a precise diagnosis can be challenging. Analysis of DNA methylation profiles has been shown to be a reliable method to classify central nervous system (CNS) tumours with high accuracy. We aimed to prospectively analyse CNS tumours diagnosed in Sweden, to assess the clinical impact of adding DNA methylation-based classification to standard paediatric brain tumour diagnostics in an unselected cohort.Methods: All CNS tumours diagnosed in children (0-18 years) during 2017-2020 were eligible for inclusion provided sufficient tumour material was available. Tumours were analysed using genome-wide DNA methylation profiling and classified by the MNP brain

DNA methylation is increasingly used for tumour classification and has expanded upon the > 100 currently known brain tumour entities. A correct diagnosis is the basis for suitable treatment for patients with brain tumours, which is the leading cause of cancer-related death in children. DNA methylation profiling is required for diagnosis of certain tumours, and used clinically for paediatric brain tumours in several countries. We therefore evaluated if the methylation-based classification is robust in different locations of the same tumour, and determined how the methylation pattern changed over time to relapse. We sampled 3–7 spatially separated biopsies per patient, and collected samples from paired primary and relapse brain tumours from children. Altogether, 121 samples from 46 paediatric patients with brain tumours were profiled with EPIC methylation arrays. The methylation-based classification was mainly homogeneous for all included tumour types that were successfully classified, which is promising for clinical diagnostics. There were indications of multiple subclasses within tumours and switches in the relapse setting, but not confirmed as the classification scores were below the threshold. Site-specific methylation alterations did occur within the tumours and varied significantly between tumour types for the temporal samples, and as a trend in spatial samples. More alterations were present in high-grade tumours compared to low-grade, and significantly more alterations with longer relapse times. The alterations in the spatial and temporal samples were significantly depleted in CpG islands, exons and transcription start sites, while enriched in OpenSea and regions not affiliated with a gene, suggesting a random location of the alterations in less conserved regions. In conclusion, more DNA methylation changes accumulated over time and more alterations occurred in high-grade tumours. The alterations mainly occurred in regions without gene affiliation, and did not affect the methylation-based classification, which largely remained homogeneous in paediatric brain tumours.

Background Molecular analyses have shown that tumours diagnosed as supratentorial primitive neuro-ectodermal tumours of the central nervous system (CNS-PNETs) in the past represent a heterogenous group of rare childhood tumours including high-grade gliomas (HGG), ependymomas, atypical teratoid/rhabdoid tumours (AT/RT), CNS neuroblastoma with forkhead box R2 (FOXR2) activation and embryonal tumour with multi-layered rosettes (ETMR). All these tumour types are rare and long-term clinical follow-up data are sparse. We retrospectively re-evaluated all children (0–18 years old) diagnosed with a CNS-PNET in Sweden during 1984–2015 and collected clinical data. Methods In total, 88 supratentorial CNS-PNETs were identified in the Swedish Childhood Cancer Registry and from these formalin-fixed paraffin-embedded tumour material was available for 71 patients. These tumours were histopathologically re-evaluated and, in addition, analysed using genome-wide DNA methylation profiling and classified by the MNP brain tumour classifier. Results The most frequent tumour types, after histopathological re-evaluation, were HGG (35%) followed by AT/RT (11%), CNS NB-FOXR2 (10%) and ETMR (8%). DNA methylation profiling could further divide the tumours into specific subtypes and with a high accuracy classify these rare embryonal tumours. The 5 and 10-year overall survival (OS) for the whole CNS-PNET cohort was 45% ± 12% and 42% ± 12%, respectively. However, the different groups of tumour types identified after re-evaluation displayed very variable survival patterns, with a poor outcome for HGG and ETMR patients with 5-year OS 20% ± 16% and 33% ± 35%, respectively. On the contrary, high PFS and OS was observed for patients with CNS NB-FOXR2 (5-year 100% for both). Survival rates remained stable even after 15-years of follow-up. Conclusions Our findings demonstrate, in a national based setting, the molecular heterogeneity of these tumours and show that DNA methylation profiling of these tumours provides an indispensable tool in distinguishing these rare tumours. Long-term follow-up data confirms previous findings with a favourable outcome for CNS NB-FOXR2 tumours and poor chances of survival for ETMR and HGG.

AIMS: Paediatric brain tumours are rare and establishing a precise diagnosis can be challenging. Analysis of DNA methylation profiles has been shown to be a reliable method to classify central nervous system (CNS) tumours with high accuracy. We aimed to prospectively analyse CNS tumours diagnosed in Sweden, to assess the clinical impact of adding DNA methylation-based classification to standard paediatric brain tumour diagnostics in an unselected cohort. Methods: All CNS tumours diagnosed in children (0-18 years) during 2017-2020 were eligible for inclusion provided sufficient tumour material was available. Tumours were analysed using genome-wide DNA methylation profiling and classified by the MNP brain tumour classifier. The initial histopathological diagnosis was compared to the DNA methylation-based classification. For incongruent results, a blinded re-evaluation was performed by an experienced neuropathologist. Results: 240 tumours with a histopathology-based diagnosis were profiled. A high-confidence methylation score of 0.84 or more was reached in 78% of the cases. In 69%, the histopathological diagnosis was confirmed and for some of these also refined, 6% were incongruent and the re-evaluation favoured the methylation-based classification. In the remaining 3% of cases, the methylation class was non-contributory or could not be predicted. The change in diagnosis would have had a direct impact on the clinical management in 5% of all patients.Conclusions: Integrating DNA methylation-based tumour classification into routine clinical analysis improves diagnostics and molecular information important for treatment decisions. The results from methylation profiling should be interpreted in the context of clinical and histopathological information.

Background Elevated serum levels of serum amyloid A (SAA) are associated with increased risk of cardiovascular disease. In this study, we examine associations between allelic variation in the rs11024595 single nucleotide polymorphism (SNP) in the 5’ flanking region of the SAA1 gene and adipose tissue gene expression, serum levels of SAA and cardiovascular risk factors. Methods DNA samples from 729 participants in the SibPair study, comprising weight discordant siblings and their biological parents, and 3542 participants (1783 patients treated with bariatric surgery and 1759 controls) from the Swedish Obese Subjects (SOS) study were used. The rs11024595 SNP was genotyped in both cohorts using Pyrosequencing or the Sequenom MassARRAY platform, respectively. Blood chemistry and anthropometry were assessed at study start. Adipose tissue SAA1 gene expression and serum levels of SAA in the SibPair study were analyzed with DNA microarray or immunoassay, respectively. Results In the SibPair study, the rs11024595 SNP was associated with serum levels of SAA (P = 0.0050) where T allele carriers displayed lower levels of SAA (P = 0.0025) but no association between genotype and adipose tissue SAA1 gene expression was found. In the SOS study, the rs11024595 SNP was associated with serum levels of HDL cholesterol (P = 0.0045), triglycerides (P = 0.025) and apolipoprotein E (P = 0.026). Moreover, T allele carriers had lower levels of HDL cholesterol (P = 0.0148), but higher levels of triglycerides (P = 0.0418) and apolipoprotein E (P = 0.028) compared to C allele homozygotes. The rs11024595 SNP was also associated with plasma glucose (P = 0.044). Conclusions The rs11024595 SNP in the 5’ flanking region of the SAA1 gene is associated with both serum levels of SAA and other cardiovascular risk factors. Future studies are required to elucidate whether the rs11024595 SNP can affect the risk of cardiovascular events. Trial registration ClinicalTrials.gov Identifier: NCT01479452 Registered 24 November 2011 - retrospectively registered.