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Abstract Medulloblastomas (MBs) are malignant pediatric brain tumors that are molecularly and clinically heterogenous. The application of omics technologies—mainly studying nucleic acids—has significantly improved MB classification and stratification, but treatment options are still unsatisfactory. The proteome and their N-glycans hold the potential to discover clinically relevant phenotypes and targetable pathways. We compile a harmonized proteome dataset of 167 MBs and integrate findings with DNA methylome, transcriptome and N-glycome data. We show six proteome MB subtypes, that can be assigned to two main molecular programs: transcription/translation (pSHHt, pWNT and pG3myc), and synapses/immunological processes (pSHHs, pG3 and pG4). Multiomic analysis reveals different conservation levels of proteome features across MB subtypes at the DNA methylome level. Aggressive pGroup3myc MBs and favorable pWNT MBs are most similar in cluster hierarchies concerning overall proteome patterns but show different protein abundances of the vincristine resistance-associated multiprotein complex TriC/CCT and of N-glycan turnover-associated factors. The N-glycome reflects proteome subtypes and complex-bisecting N-glycans characterize pGroup3myc tumors. Our results shed light on targetable alterations in MB and set a foundation for potential immunotherapies targeting glycan structures.

Abstract Background Pediatric-type diffuse high-grade glioma (pHGG) is the most frequent malignant brain tumor in children and can be subclassified into multiple entities. Fusion genes activating the MET receptor tyrosine kinase often occur in infant-type hemispheric glioma (IHG) but also in other pHGG and are associated with devastating morbidity and mortality. Methods To identify new treatment options, we established and characterized two novel orthotopic mouse models harboring distinct MET fusions. These included an immunocompetent, murine allograft model and patient-derived orthotopic xenografts (PDOX) from a MET-fusion IHG patient who failed conventional therapy and targeted therapy with cabozantinib. With these models, we analyzed the efficacy and pharmacokinetic properties of three MET inhibitors, capmatinib, crizotinib and cabozantinib, alone or combined with radiotherapy. Results Capmatinib showed superior brain pharmacokinetic properties and greater in vitro and in vivo efficacy than cabozantinib or crizotinib in both models. The PDOX models recapitulated the poor efficacy of cabozantinib experienced by the patient. In contrast, capmatinib extended survival and induced long-term progression-free survival when combined with radiotherapy in two complementary mouse models. Capmatinib treatment increased radiation-induced DNA double-strand breaks and delayed their repair. Conclusions We comprehensively investigated the combination of MET inhibition and radiotherapy as a novel treatment option for MET-driven pHGG. Our seminal preclinical data package includes pharmacokinetic characterization, recapitulation of clinical outcomes, coinciding results from multiple complementing in vivo studies, and insights into molecular mechanism underlying increased efficacy. Taken together, we demonstrate the groundbreaking efficacy of capmatinib and radiation as a highly promising concept for future clinical trials.

Tumours of the central nervous system (CNS) represent the most common group of solid tumours in children and adolescents up to the age of 18 years. They comprise several biological entities, subgroups, and subtypes. These subtypes and additional factors, including age at diagnosis, location, stage, or genetic characteristics of the tumours result in a very heterogeneous spectrum of treatment-relevant strata for risk-adapted multimodal treatment recommendations, clinical courses, and long-term outcomes. Multidisciplinary teams with highly experienced members are needed to treat these children and adolescents to achieve the best possible outcome in the short and long-term. This is particularly important for the new CNS tumour entities with no established standard of care. On behalf of the Brain Tumour Group of the European Society for Paediatric Oncology, we summarize the key statements of the involved disciplines that need to cooperate in the diagnosis and risk-adapted treatment of children with CNS tumours: neuroradiology, neurosurgery, neuropathology, radiotherapy, endocrinology, neuro-ophthalmology, and quality of survival professionals, covering what should be considered standard clinical practice for diagnostic assessments, treatment modalities, and follow-up of children with CNS-tumours.

Abstract Medulloblastomas with extensive nodularity are cerebellar tumors characterized by two distinct compartments and variable disease progression. The mechanisms governing the balance between proliferation and differentiation in MBEN remain poorly understood. Here, we employ a multi-modal single cell transcriptome analysis to dissect this process. In the internodular compartment, we identify proliferating cerebellar granular neuronal precursor-like malignant cells, along with stromal, vascular, and immune cells. In contrast, the nodular compartment comprises postmitotic, neuronally differentiated malignant cells. Both compartments are connected through an intermediate cell stage resembling actively migrating CGNPs. Notably, we also discover astrocytic-like malignant cells, found in proximity to migrating and differentiated cells at the transition zone between the two compartments. Our study sheds light on the spatial tissue organization and its link to the developmental trajectory, resulting in a more benign tumor phenotype. This integrative approach holds promise to explore intercompartmental interactions in other cancers with varying histology.

The morphological patterns leading to the diagnosis of glioblastoma may also commonly be observed in several other distinct tumor entities, which can result in a mixed bag of tumors subsumed under this diagnosis. The 2021 WHO Classification of CNS Tumors has separated several of these entities from the diagnosis of glioblastoma, IDH-wildtype. This study determines the DNA methylation classes most likely receiving the diagnosis glioblastoma, IDH wildtype according to the definition by the WHO 2021 Classification and provides comparative copy number analyses. We identified 10782 methylome datasets uploaded to the web page www.molecularneuropathology.org with a calibrated score of ≥0.9 by the Heidelberg Brain Tumor Classifier version v12.8. These methylation classes were characterized by the diagnosis glioblastoma being the most frequent classification encountered in each of the classes according to the WHO 2021 definition. Further, methylation classes selected for this study predominantly contained adult patients. Unsupervised clustering confirmed the presence of nine methylation classes containing tumors most likely receiving the diagnosis glioblastoma, IDH-wildtype according to the WHO 2021 definition. Copy number analysis and a focus on genes with typical numerical alterations in glioblastoma revealed clear differences between the nine methylation classes. Although great progress in diagnostic precision has been achieved over the last decade, our data clearly demonstrate that glioblastoma, IDH-wildtype still is a heterogeneous group in need of further stratification.

Abstract Background Cancer immunotherapies including immune checkpoint inhibitors and Chimeric Antigen Receptor (CAR) T-cell therapy have shown variable response rates in paediatric patients highlighting the need to establish robust biomarkers for patient selection. While the tumour microenvironment in adults has been widely studied to delineate determinants of immune response, the immune composition of paediatric solid tumours remains relatively uncharacterized calling for investigations to identify potential immune biomarkers. Methods To inform immunotherapy approaches in paediatric cancers with embryonal origin, we performed an immunogenomic analysis of RNA-seq data from 925 treatment-naïve paediatric nervous system tumours (pedNST) spanning 12 cancer types from three publicly available data sets. Results Within pedNST, we uncovered four broad immune clusters: Paediatric Inflamed (10%), Myeloid Predominant (30%), Immune Neutral (43%) and Immune Desert (17%). We validated these clusters using immunohistochemistry, methylation immune inference and segmentation analysis of tissue images. We report shared biology of these immune clusters within and across cancer types, and characterization of specific immune cell frequencies as well as T- and B-cell repertoires. We found no associations between immune infiltration levels and tumour mutational burden, although molecular cancer entities were enriched within specific immune clusters. Conclusions Given the heterogeneity of immune infiltration within pedNST, our findings suggest personalized immunogenomic profiling is needed to guide selection of immunotherapeutic strategies.

Abstract Pediatric low-grade gliomas (pLGG) show heterogeneous responses to MAPK inhibitors (MAPKi) in clinical trials. Thus, more complex stratification biomarkers are needed to identify patients likely to benefit from MAPKi therapy. Here, we identify MAPK-related genes enriched in MAPKi-sensitive cell lines using the GDSC dataset and apply them to calculate class-specific MAPKi sensitivity scores (MSSs) via single-sample gene set enrichment analysis. The MSSs discriminate MAPKi-sensitive and non-sensitive cells in the GDSC dataset and significantly correlate with response to MAPKi in an independent PDX dataset. The MSSs discern gliomas with varying MAPK alterations and are higher in pLGG compared to other pediatric CNS tumors. Heterogenous MSSs within pLGGs with the same MAPK alteration identify proportions of potentially sensitive patients. The MEKi MSS predicts treatment response in a small set of pLGG patients treated with trametinib. High MSSs correlate with a higher immune cell infiltration, with high expression in the microglia compartment in single-cell RNA sequencing data, while low MSSs correlate with low immune infiltration and increased neuronal score. The MSSs represent predictive tools for the stratification of pLGG patients and should be prospectively validated in clinical trials. Our data supports a role for microglia in the response to MAPKi.

Abstract To date, several studies on genomic events underlying medulloblastoma (MB) biology have expanded our understanding of this tumour entity and led to its division into four groups—WNT, SHH, group 3 (G3) and group 4 (G4). However, there is little information about the relevance of pathogenic mitochondrial DNA (mtDNA) mutations and their consequences across these. In this report, we describe the case of a female patient with MB and a mitochondriopathy, followed by a study of mtDNA variants in MB groups. After being diagnosed with G4 MB, the index patient was treated in line with the HIT 2000 protocol with no indications of relapse after five years. Long-term side effects of treatment were complemented by additional neurological symptoms and elevated lactate levels ten years later, resulting in suspected mitochondrial disease. This was confirmed by identifying a mutation in the MT-TS1 gene which appeared homoplasmic in patient tissue and heteroplasmic in the patient’s mother. Motivated by this case, we explored mtDNA mutations across 444 patients from ICGC and HIT cohorts. While there was no statistically significant enrichment of mutations in one MB group, both cohorts encompassed a small group of patients harbouring potentially deleterious mtDNA variants. The case presented here highlights the possible similarities between sequelae caused by MB treatment and neurological symptoms of mitochondrial dysfunction, which may apply to patients across all MB groups. In the context of the current advances in characterising and interpreting mtDNA aberrations, recognising affected patients could enhance our future knowledge regarding the mutations’ impact on carcinogenesis and cancer treatment.

Abstract A founder variant is a genetic alteration, that is inherited from a common ancestor together with a surrounding chromosomal segment, and is observed at a high frequency in a defined population. This founder effect occurs as a consequence of long-standing inbreeding of isolated populations. For high-risk cancer predisposition genes, such as BRCA1/2, the identification of founder variants in a certain population could help designing customized cost-effective cancer screening panels. This advantage has been best utilized in designing a customized breast cancer BRCA screening panel for the Ashkenazi Jews (AJ) population, composed of the three BRCA founder variants which account for approximately 90% of identified BRCA alterations. Indeed, the high prevalence of pathogenic BRCA1/2 variants among AJ (~ 2%) has additionally contributed to make population-based screening cost-effective in comparison to family-history-based screening. In Jordan there are multiple demographic characteristics supporting the proposal of a founder effect. A high consanguinity rate of ~ 57% in the nineties of the last century and ~ 30% more recently is a prominent factor, in addition to inbreeding which is often practiced by different sub-populations of the country. This review explains the concept of founder effect, then applies it to analyze published Jordanian BRCA variants, and concludes that nine pathogenic (P) and likely pathogenic (LP) BRCA2 variants together with one pathogenic BRCA1 variant are potential founder variants. Together they make up 43% and 55% of all identified BRCA1/2 alterations in the two largest studied cohorts of young patients and high-risk patients respectively. These variants were identified based on being recurrent and either specific to ethnic groups or being novel. In addition, the report highlights the required testing methodologies to validate these findings, and proposes a health economic evaluation model to test cost-effectiveness of a population-based customized BRCA screening panel for the Jordanian population. The aim of this report is to highlight the potential utilization of founder variants in establishing customized cancer predisposition services, in order to encourage more population-based genomic studies in Jordan and similar populations.

Abstract Background Cancer metabolism influences multiple aspects of tumorigenesis and causes diversity across malignancies. Although comprehensive research has extended our knowledge of molecular subgroups in medulloblastoma (MB), discrete analysis of metabolic heterogeneity is currently lacking. This study seeks to improve our understanding of metabolic phenotypes in MB and their impact on patients’ outcomes. Methods Data from four independent MB cohorts encompassing 1,288 patients were analysed. We explored metabolic characteristics of 902 patients (ICGC and MAGIC cohorts) on bulk RNA level. Moreover, data from 491 patients (ICGC cohort) were searched for DNA alterations in genes regulating cell metabolism. To determine the role of intratumoral metabolic differences, we examined single-cell RNA-sequencing (scRNA-seq) data from 34 additional patients. Findings on metabolic heterogeneity were correlated to clinical data. Results Established MB groups exhibit substantial differences in metabolic gene expression. By employing unsupervised analyses, we identified three clusters of group 3 and 4 samples with distinct metabolic features in ICGC and MAGIC cohorts. Analysis of scRNA-seq data confirmed our results of intertumoral heterogeneity underlying the according differences in metabolic gene expression. On DNA level, we discovered clear associations between altered regulatory genes involved in MB development and lipid metabolism. Additionally, we determined the prognostic value of metabolic gene expression in MB and showed that expression of genes involved in metabolism of inositol phosphates and nucleotides correlates with patient survival. Conclusion Our research underlines the biological and clinical relevance of metabolic alterations in MB. Thus, distinct metabolic signatures presented here might be the first step towards future metabolism-targeted therapeutic options. Graphical Abstract

Abstract Ependymoma is a tumor of the brain or spinal cord. The two most common and aggressive molecular groups of ependymoma are the supratentorial ZFTA-fusion associated and the posterior fossa ependymoma group A. In both groups, tumors occur mainly in young children and frequently recur after treatment. Although molecular mechanisms underlying these diseases have recently been uncovered, they remain difficult to target and innovative therapeutic approaches are urgently needed. Here, we use genome-wide chromosome conformation capture (Hi-C), complemented with CTCF and H3K27ac ChIP-seq, as well as gene expression and DNA methylation analysis in primary and relapsed ependymoma tumors, to identify chromosomal conformations and regulatory mechanisms associated with aberrant gene expression. In particular, we observe the formation of new topologically associating domains (‘neo-TADs’) caused by structural variants, group-specific 3D chromatin loops, and the replacement of CTCF insulators by DNA hyper-methylation. Through inhibition experiments, we validate that genes implicated by these 3D genome conformations are essential for the survival of patient-derived ependymoma models in a group-specific manner. Thus, this study extends our ability to reveal tumor-dependency genes by 3D genome conformations even in tumors that lack targetable genetic alterations.

Abstract Pediatric neoplasms in the central nervous system (CNS) show extensive clinical and molecular heterogeneity and are fundamentally different from those occurring in adults. Molecular genetic testing contributes to accurate diagnosis and enables an optimal clinical management of affected children. Here, we investigated a rare, molecularly distinct type of pediatric high-grade neuroepithelial tumor (n = 18), that was identified through unsupervised visualization of genome-wide DNA methylation array data, together with copy number profiling, targeted next-generation DNA sequencing, and RNA transcriptome sequencing. DNA and/or RNA sequencing revealed recurrent fusions involving the capicua transcriptional repressor (CIC) gene in 10/10 tumor samples analyzed, with the most common fusion being CIC::LEUTX (n = 9). In addition, a CIC::NUTM1 fusion was detected in one of the tumors. Apart from the detected fusion events, no additional oncogenic alteration was identified in these tumors. The histopathological review demonstrated a morphologically heterogeneous group of high-grade neuroepithelial tumors with positive immunostaining for markers of glial differentiation in combination with weak and focal expression of synaptophysin, CD56 and CD99. All tumors were located in the supratentorial compartment, occurred during childhood (median age 8.5 years) and typically showed early relapses. In summary, we expand the spectrum of pediatric-type tumors of the CNS by reporting a previously uncharacterized group of rare high-grade neuroepithelial tumors that share a common DNA methylation signature and recurrent gene fusions involving the transcriptional repressor CIC. Downstream functional consequences of the fusion protein CIC::LEUTX and potential therapeutic implications need to be further investigated.

Pleomorphic xanthoastrocytoma (PXA) poses a diagnostic challenge. The present study relies on methylation-based predictions and focuses on copy number variations (CNV) in PXA. We identified 551 tumors from patients having received the histologic diagnosis or differential diagnosis pleomorphic xanthoastrocytoma (PXA) uploaded to the web page www.molecularneuropathology.org. Of these 551 tumors, 165 received the prediction “methylation class (anaplastic) pleomorphic xanthoastrocytoma” with a calibrated score >=0.9 by the brain tumor classifier version v12.8 and, therefore, were defined the PXA reference set designated mcPXAref. In addition to these 165 mcPXAref, 767 other tumors received the prediction mcPXA with a calibrated score >=0.9 but without a histological PXA diagnosis. The total number of individual tumors predicted by histology and/or by methylome based classification as PXA, mcPXA or both was 1318, and these were designated the study cohort. The selection of a control cohort was guided by methylation-based predictions recurrently observed for the other 386/551 tumors diagnosed as histologic PXA. 131/386 received predictions for another entity besides PXA with a score >=0.9. Control tumors corresponding to the 11 most common other predictions were selected, adding up to 1100 reference cases. CNV profiles were calculated from all methylation datasets of the study and control cohorts. Special attention was given to the 7/10 signature, gene amplifications and homozygous deletion of CDKN2A/B. Comparison of CNV in the subsets of the study cohort and the control cohort were used to establish relations independent of histological diagnoses. Tumors in mcPXA were highly homogenous in regard to CNV alterations, irrespective of the histological diagnoses. The 7/10 signature commonly present in glioblastoma, IDH-wildtype, was present in 15-20% of mcPXA, whereas amplification of oncogenes (likewise common in glioblastoma) was very rare in mcPXA (

Group 3 medulloblastomas (MBs) have the worst prognosis amongst the subtypes of MBs and are associated with MYC amplifications. Here the authors identify that mutations in CTDNEP1 cause MYC activation, amplification, and genomic instability in this subtype of MBs.

Abstract Nowadays medulloblastoma (MB) tumors can be treated with risk-stratified approaches with up to 80% success rate. However, disease relapses occur in approximately 30% of patients and successful salvage treatment strategies at relapse remain scarce. Acquired copy number changes or TP53 mutations are known to occur frequently in relapses, while methylation profiles usually remain highly similar to those of the matching primary tumors, indicating that in general molecular subgrouping does not change during the course of the disease. In the current study, we have used RNA sequencing data to analyze the transcriptome profiles of 43 primary-relapse MB pairs in order to identify specific molecular features of relapses within various tumor groups. Gene variance analysis between primary and relapse samples demonstrated the impact of age in SHH-MB: the changes in gene expression relapse profiles were more pronounced in the younger patients (

Abstract The international precision oncology program INFORM enrolls relapsed/refractory pediatric cancer patients for comprehensive molecular analysis. We report a two-year pilot study implementing ex vivo drug sensitivity profiling (DSP) using a library of 75–78 clinically relevant drugs. We included 132 viable tumor samples from 35 pediatric oncology centers in seven countries. DSP was conducted on multicellular fresh tumor tissue spheroid cultures in 384-well plates with an overall mean processing time of three weeks. In 89 cases (67%), sufficient viable tissue was received; 69 (78%) passed internal quality controls. The DSP results matched the identified molecular targets, including BRAF, ALK, MET, and TP53 status. Drug vulnerabilities were identified in 80% of cases lacking actionable (very) high-evidence molecular events, adding value to the molecular data. Striking parallels between clinical courses and the DSP results were observed in selected patients. Overall, DSP in clinical real-time is feasible in international multicenter precision oncology programs.

Sinonasal tumour diagnosis can be complicated by the heterogeneity of disease and classification systems. Here, the authors use machine learning to classify sinonasal undifferentiated carcinomas into 4 molecular classe with differences in differentiation state and clinical outcome.

Abstract Atypical teratoid/rhabdoid tumor (AT/RT) is a highly malignant brain tumor in infants that is characterized by loss of nuclear expression of SMARCB1 or SMARCA4 proteins. Recent studies show that AT/RTs comprise three molecular subgroups, namely AT/RT-TYR, AT/RT-MYC and AT/RT-SHH. The subgroups show distinct expression patterns of genes involved in ciliogenesis, however, little is known about the functional roles of primary cilia in the biology of AT/RT. Here, we show that primary cilia are present across all AT/RT subgroups with specific enrichment in AT/RT-TYR patient samples. Furthermore, we demonstrate that primary ciliogenesis contributes to AT/RT biology in vitro and in vivo. Specifically, we observed a significant decrease in proliferation and clonogenicity following disruption of primary ciliogenesis in AT/RT cell line models. Additionally, apoptosis was significantly increased via the induction of STAT1 and DR5 signaling, as detected by proteogenomic profiling. In a Drosophila model of SMARCB1 deficiency, concomitant knockdown of several cilia-associated genes resulted in a substantial shift of the lethal phenotype with more than 20% of flies reaching adulthood. We also found significantly extended survival in an orthotopic xenograft mouse model of AT/RT upon disruption of primary ciliogenesis. Taken together, our findings indicate that primary ciliogenesis or its downstream signaling contributes to the aggressiveness of AT/RT and, therefore, may constitute a novel therapeutic target.

Abstract Li-Fraumeni syndrome (LFS) is a cancer predisposition syndrome caused by pathogenic TP53 variants. The condition represents one of the most relevant genetic causes of cancer in children and adults due to its frequency and high cancer risk. The term Li-Fraumeni spectrum reflects the evolving phenotypic variability of the condition. Within this spectrum, patients who meet specific LFS criteria are diagnosed with LFS, while patients who do not meet these criteria are diagnosed with attenuated LFS. To explore genotype–phenotype correlations we analyzed 141 individuals from 94 families with pathogenic TP53 variants registered in the German Cancer Predisposition Syndrome Registry. Twenty-one (22%) families had attenuated LFS and 73 (78%) families met the criteria of LFS. NULL variants occurred in 32 (44%) families with LFS and in two (9.5%) families with attenuated LFS (P value

Long non-coding RNAs (lncRNAs) can contribute to cancers that are driven by Sonic hedgehog (SHH) signaling. Here the authors report that lncRNA HHIP-AS1 stabilises the mRNA of dynein complex 1, thereby, promoting the pro-mitotic effects of SHH-driven tumors.

Abstract Background Pediatric low-grade gliomas (pLGGs), particularly incompletely resected supratentorial tumours, can undergo progression after surgery. However to date, there are no predictive biomarkers for progression. Here, we aimed to identify pLGG-specific microRNA signatures and evaluate their value as a prognostic tool. Methods We identified and validated supratentorial incompletey resected pLGG-specific microRNAs in independent cohorts from four European Pediatric Neuro-Oncology Centres. Results These microRNAs demonstrated high accuracy in differentiating patients with or without progression. Specifically, incompletely resected supratentorial pLGGs with disease progression showed significantly higher miR-1248 combined with lower miR-376a-3p and miR-888-5p levels than tumours without progression. A significant (p

Abstract 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.

Josephine Daub, Saman Amini, et al. developed a genetic interaction map of childhood cancers by analyzing over 2,500 tumors from 23 types of childhood cancer. Their results provide a valuable resource for investigating the biological underpinnings of pediatric cancer.

Radiation-induced gliomas (RIGs) have been reported in patients after treatment with cranial irradiation for various primary malignancies but their origin are still unclear. Here, the authors define the genomic, epigenetic and transcriptional landscape of 32 RIGs cases.

Transcriptomic analysis may provide information about the differentiation state and cell of origin of a cancer. Here, the authors assess mRNA signals in 1300 childhood and adult renal tumors and report a fetal origin of childhood tumors and no dedifferentiation of adult tumors.

Persistent mortality rates of medulloblastoma (MB) and severe side effects of the current therapies require the definition of the molecular mechanisms that contribute to tumor progression. Using cultured MB cancer stem cells and xenograft tumors generated in mice, we show that low expression of miR‐326 and its host gene β‐arrestin1 (ARRB1) promotes tumor growth enhancing the E2F1 pro‐survival function. Our models revealed that miR‐326 and ARRB1 are controlled by a bivalent domain, since the H3K27me3 repressive mark is found at their regulatory region together with the activation‐associated H3K4me3 mark. High levels of EZH2, a feature of MB, are responsible for the presence of H3K27me3. Ectopic expression of miR‐326 and ARRB1 provides hints into how their low levels regulate E2F1 activity. MiR‐326 targets E2F1 mRNA, thereby reducing its protein levels; ARRB1, triggering E2F1 acetylation, reverses its function into pro‐apoptotic activity. Similar to miR‐326 and ARRB1 overexpression, we also show that EZH2 inhibition restores miR‐326/ARRB1 expression, limiting E2F1 pro‐proliferative activity. Our results reveal a new regulatory molecular axis critical for MB progression.

Abstract Primitive neuroectodermal tumors of the central nervous system (CNS-PNETs) are highly malignant neoplasms posing diagnostic challenge due to a lack of defining molecular markers. CNS neuroblastoma with forkhead box R2 (FOXR2) activation (CNS_NBL) emerged as a distinct pediatric brain tumor entity from a pool previously diagnosed as primitive neuroectodermal tumors of the central nervous system (CNS-PNETs). Current standard of identifying CNS_NBL relies on molecular analysis. We set out to establish immunohistochemical markers allowing safely distinguishing CNS_NBL from morphological mimics. To this aim we analyzed a series of 84 brain tumors institutionally diagnosed as CNS-PNET. As expected, epigenetic analysis revealed different methylation groups corresponding to the (1) CNS-NBL (24%), (2) glioblastoma IDH wild-type subclass H3.3 G34 (26%), (3) glioblastoma IDH wild-type subclass MYCN (21%) and (4) ependymoma with RELA_C11orf95 fusion (29%) entities. Transcriptome analysis of this series revealed a set of differentially expressed genes distinguishing CNS_NBL from its mimics. Based on RNA-sequencing data we established SOX10 and ANKRD55 expression as genes discriminating CNS_NBL from other tumors exhibiting CNS-PNET. Immunohistochemical detection of combined expression of SOX10 and ANKRD55 clearly identifies CNS_NBL discriminating them to other hemispheric CNS neoplasms harboring “PNET-like” microscopic appearance. Owing the rarity of CNS_NBL, a confirmation of the elaborated diagnostic IHC algorithm will be necessary in prospective patient series.

Alternative lengthening of telomeres (ALT) is associated with a poor outcome in neuroblastoma. Here, the authors find that ALT is associated with mutated ATRX and/or reduced protein abundance, frequent telomeric repeat loci and heterochromatic telomeric chromatin.

Sarcomas are morphologically heterogeneous tumours rendering their classification challenging. Here the authors developed a classifier using DNA methylation data from several soft tissue and bone sarcoma subtypes, which has the potential to improve classification for research and clinical purposes.

Summary: Pediatric renal cell carcinomas (RCC) differ from their adult counterparts not only in histologic subtypes but also in clinical characteristics and outcome. However, the underlying biology is still largely unclear. For this reason, we performed whole-exome and transcriptome sequencing analyses on a cohort of 25 pediatric RCC patients with various histologic subtypes, including 10 MiT family translocation (MiT) and 10 papillary RCCs. In this cohort of pediatric RCC, we find only limited genomic overlap with adult RCC, even within the same histologic subtype. Recurrent somatic mutations in genes not previously reported in RCC were detected, such as in CCDC168, PLEKHA1, VWF, and MAP3K9. Our papillary pediatric RCCs, which represent the largest cohort to date with comprehensive molecular profiling in this age group, appeared as a distinct genomic subtype differing in terms of gene mutations and gene expression patterns not only from MiT-RCC but also from their adult counterparts.

Abstract Background Pediatric patients with relapsed or refractory disease represent a population with a desperate medical need. The aim of the INFORM (INdividualized Therapy FOr Relapsed Malignancies in Childhood) program is to translate next generation molecular diagnostics into a biomarker driven treatment strategy. The program consists of two major foundations: the INFORM registry providing a molecular screening platform and the INFORM2 series of biomarker driven phase I/II trials. The INFORM2 NivEnt trial aims to determine the recommended phase 2 dose (RP2D) of the combination treatment of nivolumab and entinostat (phase I) and to evaluate activity and safety (phase II). Methods This is an exploratory non-randomized, open-label, multinational and multicenter seamless phase I/II trial in children and adolescents with relapsed / refractory or progressive high-risk solid tumors and CNS tumors. The phase I is divided in 2 age cohorts: 12–21 years and 6–11 years and follows a 3 + 3 design with two dose levels for entinostat (2 mg/m2 and 4 mg/m2 once per week) and fixed dose nivolumab (3 mg/kg every 2 weeks). Patients entering the trial on RP2D can seamlessly enter phase II which consists of a biomarker defined four group basket trial: high mutational load (group A), high PD-L1 mRNA expression (group B), focal MYC(N) amplification (group C), low mutational load and low PD-L1 mRNA expression and no MYC(N) amplification (group D). A Bayesian adaptive design will be used to early stop cohorts that fail to show evidence of activity. The maximum number of patients is 128. Discussion This trial intends to exploit the immune enhancing effects of entinostat on nivolumab using an innovative biomarker driven approach in order to maximize the chance of detecting signs of activity. It prevents exposure to unnecessary risks by applying the Bayesian adaptive design for early stopping for futility. The adaptive biomarker driven design provides an innovative approach accelerating drug development and reducing exposure to investigational treatments in these vulnerable children at the same time. Trial registration ClinicalTrials.gov, NCT03838042 . Registered on 12 February 2019.

Abstract Diffuse invasion is the primary cause of treatment failure of glioblastoma (GBM). Previous studies on GBM invasion have long been forced to use the resected tumor mass cells. Here, a strategy to reliably isolate matching pairs of invasive (GBMINV) and tumor core (GBMTC) cells from the brains of 6 highly invasive patient‐derived orthotopic models is described. Direct comparison of these GBMINV and GBMTC cells reveals a significantly elevated invasion capacity in GBMINV cells, detects 23/768 miRNAs over‐expressed in the GBMINV cells (miRNAINV) and 22/768 in the GBMTC cells (miRNATC), respectively. Silencing the top 3 miRNAsINV (miR‐126, miR‐369‐5p, miR‐487b) successfully blocks invasion of GBMINV cells in vitro and in mouse brains. Integrated analysis with mRNA expression identifies miRNAINV target genes and discovers KCNA1 as the sole common computational target gene of which 3 inhibitors significantly suppress invasion in vitro. Furthermore, in vivo treatment with 4‐aminopyridine (4‐AP) effectively eliminates GBM invasion and significantly prolongs animal survival times (P = 0.035). The results highlight the power of spatial dissection of functionally accurate GBMINV and GBMTC cells in identifying novel drivers of GBM invasion and provide strong rationale to support the use of biologically accurate starting materials in understanding cancer invasion and metastasis.

Abstract 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.

The molecular mechanisms driving proliferation in the pediatric brain cancer epdendymoma are poorly understood. Here the authors show that a YAP1- MAMLD1 fusion drives tumor formation in mice and show that the fusion protein can collaborate with the TEAD and NFI transcription factors.

Abstract Background With the advent of array-based techniques to measure methylation levels in primary tumor samples, systematic investigations of methylomes have widely been performed on a large number of tumor entities. Most of these approaches are not based on measuring individual cell methylation but rather the bulk tumor sample DNA, which contains a mixture of tumor cells, infiltrating immune cells and other stromal components. This raises questions about the purity of a certain tumor sample, given the varying degrees of stromal infiltration in different entities. Previous methods to infer tumor purity require or are based on the use of matching control samples which are rarely available. Here we present a novel, reference free method to quantify tumor purity, based on two Random Forest classifiers, which were trained on ABSOLUTE as well as ESTIMATE purity values from TCGA tumor samples. We subsequently apply this method to a previously published, large dataset of brain tumors, proving that these models perform well in datasets that have not been characterized with respect to tumor purity . Results Using two gold standard methods to infer purity – the ABSOLUTE score based on whole genome sequencing data and the ESTIMATE score based on gene expression data- we have optimized Random Forest classifiers to predict tumor purity in entities that were contained in the TCGA project. We validated these classifiers using an independent test data set and cross-compared it to other methods which have been applied to the TCGA datasets (such as ESTIMATE and LUMP). Using Illumina methylation array data of brain tumor entities (as published in Capper et al. (Nature 555:469-474,2018)) we applied this model to estimate tumor purity and find that subgroups of brain tumors display substantial differences in tumor purity. Conclusions Random forest- based tumor purity prediction is a well suited tool to extrapolate gold standard measures of purity to novel methylation array datasets. In contrast to other available methylation based tumor purity estimation methods, our classifiers do not need a priori knowledge about the tumor entity or matching control tissue to predict tumor purity.

BET-bromodomain inhibitors could be used to treat medulloblastoma tumors with Myc amplifications. Here, the authors show that both the response and resistance to BET inhibitors in mice is mediated by bHLH/homeobox transcription factors.

Abstract Background Establishment of telomere maintenance mechanisms is a universal step in tumor development to achieve replicative immortality. These processes leave molecular footprints in cancer genomes in the form of altered telomere content and aberrations in telomere composition. To retrieve these telomere characteristics from high-throughput sequencing data the available computational approaches need to be extended and optimized to fully exploit the information provided by large scale cancer genome data sets. Results We here present TelomereHunter, a software for the detailed characterization of telomere maintenance mechanism footprints in the genome. The tool is implemented for the analysis of large cancer genome cohorts and provides a variety of diagnostic diagrams as well as machine-readable output for subsequent analysis. A novel key feature is the extraction of singleton telomere variant repeats, which improves the identification and subclassification of the alternative lengthening of telomeres phenotype. We find that whole genome sequencing-derived telomere content estimates strongly correlate with telomere qPCR measurements (r = 0.94). For the first time, we determine the correlation of in silico telomere content quantification from whole genome sequencing and whole genome bisulfite sequencing data derived from the same tumor sample (r = 0.78). An analogous comparison of whole exome sequencing data and whole genome sequencing data measured slightly lower correlation (r = 0.79). However, this is considerably improved by normalization with matched controls (r = 0.91). Conclusions TelomereHunter provides new functionality for the analysis of the footprints of telomere maintenance mechanisms in cancer genomes. Besides whole genome sequencing, whole exome sequencing and whole genome bisulfite sequencing are suited for in silico telomere content quantification, especially if matched control samples are available. The software runs under a GPL license and is available at https://www.dkfz.de/en/applied-bioinformatics/telomerehunter/telomerehunter.html.

Abstract 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.

Medulloblastoma is one of the most prevalent malignant brain tumors in children and has very poor prognosis. In this study, the authors show, using a mouse model of medulloblastoma, that Gfi1 promotes tumor growth by recruiting Lsd1, that this interaction inhibits genes involved in neuronal differentiation, and that Lsd1 may be a therapeutic target in Gfi1-activated tumors.

Abstract Background High-throughput technologies for analyzing chromosome conformation at a genome scale have revealed that chromatin is organized in topologically associated domains (TADs). While TADs are relatively stable across cell types, intra-TAD activities are cell type specific. Epigenetic profiling of different tissues and cell-types has identified a large number of non-coding epigenetic regulatory elements (‘enhancers’) that can be located far away from coding genes. Linear proximity is a commonly chosen criterion for associating enhancers with their potential target genes. While enhancers frequently regulate the closest gene, unambiguous identification of enhancer regulated genes remains to be a challenge in the absence of sample matched chromosome conformation data. Results To associate enhancers with their target genes, we have previously developed and applied a method that tests for significant correlations between enhancer and gene expressions across a cohort of samples. To limit the number of tests, we constrain this analysis to gene-enhancer pairs embedded in the same TAD, where information on TAD boundaries is borrowed from publicly available chromosome conformation capturing (‘Hi-C’) data. We have now implemented this method as an R Bioconductor package ‘InTAD’ and verified the software package by reanalyzing available enhancer and gene expression data derived from ependymoma brain tumors. Conclusion The open-source package InTAD is an easy-to-use software tool for identifying proximal and distal enhancer target genes by leveraging information on correlated expression of enhancers and genes that are located in the same TAD. InTAD can be applied to any heterogeneous cohort of samples analyzed by a combination of gene expression and epigenetic profiling techniques and integrates either public or custom information of TAD boundaries.

Desorption/ionization (DI)-mass spectrometric (MS) methods offer considerable advantages of rapidity and low-sample input for the analysis of solid biological matrices such as tissue sections. The concept of desorption electrospray ionization (DESI) offers the possibility to ionize compounds from solid surfaces at atmospheric pressure, without the addition of organic compounds to initiate desorption. However, severe drawbacks from former DESI hardware stability made the development of assays for drug quantification difficult. In the present study, the potential of new prototype source setups (High Performance DESI Sprayer and Heated Transfer Line) for the development of drug quantification assays in tissue sections was evaluated. It was demonstrated that following dedicated optimization, new DESI XS enhancements present promising options regarding targeted quantitative analyses. As a model compound for these developments, ulixertinib, an inhibitor of extracellular signal-regulated kinase (ERK) 1 and 2 was used.

Desorption/ionization mass spectrometry (DI-MS) approaches allow for the rapid quantification of drugs in biological matrices using assays that can be validated according to regulatory guidelines. However, specific adaptations must be applied to create reliable quantification methods, depending on the approach and instrumentation used. In the present article, we demonstrate the importance of the molecular weight, the fragmentation pattern, and the purity of the internal standard for the development of matrix-assisted laser desorption/ionization (MALDI)-ion mobility (IM)-tandem MS and MS/MS methods. We present preliminary results of method development for the quantification of selinexor in microdialysis fluids with a stable isotopically labeled internal standard. In addition, we discuss the selection of internal standards for MALDI-MS assays using different instrumentations.

Chromothripsis and chromoanasynthesis lead to locally clustered rearrangements affecting one or a few chromosomes, but their impact on cancer development and progression is unclear. Here the authors analyse the role of DNA repair factors in brain tumors by whole-genome sequencing of tumors from mouse models of medulloblastoma or high grade gliomas.

Abstract Diffuse midline glioma (DMG), H3 K27M-mutant, is a new entity in the updated WHO classification grouping together diffuse intrinsic pontine gliomas and infiltrating glial neoplasms of the midline harboring the same canonical mutation at the Lysine 27 of the histones H3 tail. Two hundred and fifteen patients younger than 18 years old with centrally-reviewed pediatric high-grade gliomas (pHGG) were included in this study. Comprehensive transcriptomic (n = 140) and methylation (n = 80) profiling was performed depending on the material available, in order to assess the biological uniqueness of this new entity compared to other midline and hemispheric pHGG. Tumor classification based on gene expression (GE) data highlighted the similarity of K27M DMG independently of their location along the midline. T-distributed Stochastic Neighbor Embedding (tSNE) analysis of methylation profiling confirms the discrimination of DMG from other well defined supratentorial tumor subgroups. Patients with diffuse intrinsic pontine gliomas (DIPG) and thalamic DMG exhibited a similarly poor prognosis (11.1 and 10.8 months median overall survival, respectively). Interestingly, H3.1-K27M and H3.3-K27M primary tumor samples could be distinguished based both on their GE and DNA methylation profiles, suggesting that they might arise from a different precursor or from a different epigenetic reorganization. These differences in DNA methylation profiles were conserved in glioma stem-like cell culture models of DIPG which mimicked their corresponding primary tumor. ChIP-seq profiling of H3K27me3 in these models indicate that H3.3-K27M mutated DIPG stem cells exhibit higher levels of H3K27 trimethylation which are correlated with fewer genes expressed by RNAseq. When considering the global distribution of the H3K27me3 mark, we observed that intergenic regions were more trimethylated in the H3.3-K27M mutated cells compared to the H3.1-K27M mutated ones. H3 K27M-mutant DMG represent a homogenous group of neoplasms compared to other pediatric gliomas that could be further separated based on the type of histone H3 variant mutated and their respective epigenetic landscapes. As these characteristics drive different phenotypes, these findings may have important implication for the design of future trials in these specific types of neoplasms.

Pineoblastoma is a highly aggressive and rare childhood brain cancer, and the genetic drivers of sporadic pineoblastoma are unknown. Here, the authors genomically interrogated pediatric and adult pineoblastomas and found novel variants including recurrent homozygous deletions of DROSHA.

Soft tissue tumors in infants encompass an overlapping spectrum of diseases posing unique diagnostic and clinical challenges. Here, the authors investigate the genetic basis of cryptogenic congenital mesoblastic nephroma and infantile fibrosarcoma lacking the canonical NTRK3-ETV6 fusion gene, and identify therapeutically tractable intragenic rearrangements in EGFR and BRAF.

Abstract Genomic characterization has begun to redefine diagnostic classifications of cancers. However, it remains a challenge to infer disease phenotypes from genomic alterations alone. To help realize the promise of genomics, we have performed a quantitative proteomics investigation using Stable Isotope Labeling by Amino Acids in Cell Culture (SILAC) and 41 tissue samples spanning the 4 genomically based subgroups of medulloblastoma and control cerebellum. We have identified and quantitated thousands of proteins across these groups and find that we are able to recapitulate the genomic subgroups based upon subgroup restricted and differentially abundant proteins while also identifying subgroup specific protein isoforms. Integrating our proteomic measurements with genomic data, we calculate a poor correlation between mRNA and protein abundance. Using EPIC 850 k methylation array data on the same tissues, we also investigate the influence of copy number alterations and DNA methylation on the proteome in an attempt to characterize the impact of these genetic features on the proteome. Reciprocally, we are able to use the proteome to identify which genomic alterations result in altered protein abundance and thus are most likely to impact biology. Finally, we are able to assemble protein-based pathways yielding potential avenues for clinical intervention. From these, we validate the EIF4F cap-dependent translation pathway as a novel druggable pathway in medulloblastoma. Thus, quantitative proteomics complements genomic platforms to yield a more complete understanding of functional tumor biology and identify novel therapeutic targets for medulloblastoma.

SuFu is a tumour suppressor in medulloblastoma and regulates Gli proteins in the Sonic Hedgehog pathway; however, the molecular mechanisms behind this regulation are unclear. Here, the authors show that the Itch/β-arrestin2 complex binds and ubiquitylates SuFu, facilitating the interaction with Gli3 and its conversion into the repressive form, thus counteracting medulloblastoma formation.