Tumors of the pineal region comprise several different entities with distinct clinical and histopathological features. Whereas some entities predominantly affect adults, pineoblastoma (PB) constitutes a highly aggressive malignancy of childhood with a poor outcome. PBs mainly arise sporadically, but may also occur in the context of cancer predisposition syndromes including DICER1 and RB1 germline mutation. With this study, we investigate clinico-pathological subgroups of pineal tumors and further characterize their biological features.We performed genome-wide DNA methylation analysis in 195 tumors of the pineal region and 20 normal pineal gland controls. Copy-number profiles were obtained from DNA methylation data; gene panel sequencing was added for 93 tumors and analysis was further complemented by miRNA sequencing for 22 tumor samples.Unsupervised clustering based on DNA methylation profiling separated known subgroups, like pineocytoma, pineal parenchymal tumor of intermediate differentiation, papillary tumor of the pineal region and PB, and further distinct subtypes within these groups, including three subtypes within the core PB subgroup. The novel molecular subgroup Pin-RB includes cases of trilateral retinoblastoma as well as sporadic pineal tumors with RB1 alterations, and displays similarities with retinoblastoma. Distinct clinical associations discriminate the second novel molecular subgroup PB-MYC from other PB cases. Alterations within the miRNA processing pathway (affecting DROSHA, DGCR8 or DICER1) are found in about two thirds of cases in the three core PB subtypes.Methylation profiling revealed biologically distinct groups of pineal tumors with specific clinical and molecular features. Our findings provide a foundation for further clinical as well as molecular and functional characterization of PB and other pineal tumors, including the role of miRNA processing defects in oncogenesis.

Cancer driving mutations are difficult to identify especially in the non-coding part of the genome. Here, we present sigDriver, an algorithm dedicated to call driver mutations. Using 3813 whole-genome sequenced tumors from International Cancer Genome Consortium, The Cancer Genome Atlas Program, and a childhood pan-cancer cohort, we employ mutational signatures based on single-base substitution in the context of tri- and penta-nucleotide motifs for hotspot discovery. Knowledge-based annotations on mutational hotspots reveal enrichment in coding regions and regulatory elements for 6 mutational signatures, including APOBEC and somatic hypermutation signatures. APOBEC activity is associated with 32 hotspots of which 11 are known and 11 are putative regulatory drivers. Somatic single nucleotide variants clusters detected at hypermutation-associated hotspots are distinct from translocation or gene amplifications. Patients carrying APOBEC induced PIK3CA driver mutations show lower occurrence of signature SBS39. In summary, sigDriver uncovers mutational processes associated with known and putative tumor drivers and hotspots particularly in the non-coding regions of the genome.

Background Pilocytic astrocytoma (PA) is the most common pediatric brain tumor. While genome and transcriptome landscapes are well studied, data of the complete methylome, tumor cell composition, and immune infiltration are scarce. Methods We generated whole genome bisulfite sequence (WGBS) data of 9 PAs and 16 control samples and integrated available 154 PA and 57 control methylation array data. RNA sequence data of 49 PAs and 11 control samples as well as gene expression arrays of 248 PAs and 28 controls were used to assess transcriptional activity. Results DNA-methylation patterns of partially methylated domains suggested high stability of the methylomes during tumorigenesis. Comparing tumor and control tissues of infra- and supratentorial location using methylation arrays revealed a site specific pattern. Analysis of WGBS data revealed 9381 significantly differentially methylated regions (DMRs) in PA versus control tissue. Enhancers and transcription factor (TF) motifs of five distinct TF families were found to be enriched in DMRs. Methylation together with gene expression data–based in silico tissue deconvolution analysis indicated a striking variation in the immune cell infiltration in PA. A TF network analysis showed a regulatory relation between basic leucine zipper (bZIP) transcription factors and genes involved in immune-related processes. Conclusion We provide evidence for a link of focal methylation differences and differential gene expression to immune infiltration.