Methylation of the O(6)-Methylguanine-DNA methyltransferase ( MGMT ) promoter is predictive for treatment response in glioblastoma patients. However, precise predictive cutoff values to distinguish “ MGMT methylated” from “ MGMT unmethylated” patients remain highly debated in terms of pyrosequencing (PSQ) analysis. We retrospectively analyzed a clinically and molecularly very well-characterized cohort of 111 IDH wildtype glioblastoma patients, who underwent gross total tumor resection and received standard Stupp treatment. Detailed clinical parameters were obtained. Predictive cutoff values for MGMT promoter methylation were determined using ROC curve analysis and survival curve comparison using Log-rank (Mantel-Cox) test. MGMT status was analyzed using pyrosequencing (PSQ), semi-quantitative methylation specific PCR (sqMSP) and direct bisulfite sequencing (dBiSeq). Highly methylated (> 20%) MGMT correlated with significantly improved progression-free survival (PFS) and overall survival (OS) in our cohort. Median PFS was 7.2 months in the unmethylated group (UM, < 10% mean methylation), 10.4 months in the low methylated group (LM, 10-20% mean methylation) and 19.83 months in the highly methylated group (HM, > 20% mean methylation). Median OS was 13.4 months for UM, 17.9 months for LM and 29.93 months for HM. Within the LM group, correlation of PSQ and sqMSP or dBiSeq was only conclusive in 51.5% of our cases. ROC curve analysis revealed superior test precision for survival if additional sqMSP results were considered (AUC = 0.76) compared to PSQ (cutoff 10%) alone (AUC = 0.67). We therefore challenge the widely used, strict PSQ cutoff at 10% which might not fully reflect the clinical response to alkylating agents and suggest applying a second method for MGMT testing (e.g. MSP) to confirm PSQ results for patients with LM MGMT levels if therapeutically relevant. Electronic supplementary material The online version of this article (10.1186/s40478-019-0745-z) contains supplementary material, which is available to authorized users.

Primary lymphomas of the central nervous system (PCNSL) are mainly diffuse large B-cell lymphomas (DLBCLs) confined to the central nervous system (CNS). Despite extensive research, the molecular alterations leading to PCNSL have not been fully elucidated. In order to provide a comprehensive description of the genomic and transcriptional landscape of PCNSL, we here performed whole-genome and transcriptome sequencing and integrative analysis of 51 lymphomas presenting in the CNS, including 42 EBV-negative PCNSL, 6 secondary CNS lymphomas (SCNSL) and 3 EBV+ CNSL and matched controls. The results were compared to an independent validation cohort of 31 FFPE CNSL specimens (PCNSL, n = 19; SCNSL, n = 9; EBV+ CNSL, n = 3) as well as 39 FL and 36 systemic DLBCL cases outside the CNS. Somatic genomic alterations in PCNSL mainly affect the JAK-STAT, NFkB, and B-cell receptor signaling pathways, with hallmark recurrent mutations including MYD88 L265P (67%) and CD79B (63%), CDKN2A deletions (83%) and also non-coding RNA genes such as MALAT1 (70%), NEAT (60%), and MIR142 (80%). Kataegis events, which affected 15 of 50 identified driver genes and 21 of the top 50 mutated ncRNAs, played a decisive role in shaping the mutational repertoire of PCNSL. Compared to systemic DLBCL, PCNSLs exhibited significantly more focal deletions in 6p21 targeting the HLA-D locus that encodes for MHC class II molecules as a potential mechanism of immune evasion. Mutational signatures correlating with DNA replication and mitosis (SBS1, ID1 and ID2) were significantly enriched in PCNSL (SBS1: p = 0.0027, ID1/ID2: p < 1x10-4). Furthermore, TERT gene expression was significantly higher in PCNSL compared to ABC-DLBCL (p = 0.027). Although PCNSL share many genetic alterations with systemic ABC-DLBCL in the same signaling pathways, transcriptome analysis clearly distinguished both into distinct molecular subtypes. EBV+ CNSL cases may be distinguished by lack of recurrent mutational hotspots apart from IG and HLA-DRB loci.