A Hematogenous Route for Medulloblastoma Leptomeningeal Metastases.

While the preponderance of morbidity and mortality in medulloblastoma patients are due to metastatic disease, most research focuses on the primary tumor due to a dearth of metastatic tissue samples and model systems. Medulloblastoma metastases are found almost exclusively on the leptomeningeal surface of the brain and spinal cord; dissemination is therefore thought to occur through shedding of primary tumor cells into the cerebrospinal fluid followed by distal re-implantation on the leptomeninges. We present evidence for medulloblastoma circulating tumor cells (CTCs) in therapy-naive patients and demonstrate in vivo, through flank xenografting and parabiosis, that medulloblastoma CTCs can spread through the blood to the leptomeningeal space to form leptomeningeal metastases. Medulloblastoma leptomeningeal metastases express high levels of the chemokine CCL2, and expression of CCL2 in medulloblastoma in vivo is sufficient to drive leptomeningeal dissemination. Hematogenous dissemination of medulloblastoma offers a new opportunity to diagnose and treat lethal disseminated medulloblastoma.

Microbiota-Induced TNF-like Ligand 1A Drives Group 3 Innate Lymphoid Cell-Mediated Barrier Protection and Intestinal T Cell Activation during Colitis.

Inflammatory bowel disease (IBD) results from a dysregulated interaction between the microbiota and a genetically susceptible host. Genetic studies have linked TNFSF15 polymorphisms and its protein TNF-like ligand 1A (TL1A) with IBD, but the functional role of TL1A is not known. Here, we found that adherent IBD-associated microbiota induced TL1A release from CX3CR1+ mononuclear phagocytes (MNPs). Using cell-specific genetic deletion models, we identified an essential role for CX3CR1+MNP-derived TL1A in driving group 3 innate lymphoid cell (ILC3) production of interleukin-22 and mucosal healing during acute colitis. In contrast to this protective role in acute colitis, TL1A-dependent expression of co-stimulatory molecule OX40L in MHCII+ ILC3s during colitis led to co-stimulation of antigen-specific T cells that was required for chronic T cell colitis. These results identify a role for ILC3s in activating intestinal T cells and reveal a central role for TL1A in promoting ILC3 barrier immunity during colitis.

Genome sequencing of pediatric medulloblastoma links catastrophic DNA rearrangements with TP53 mutations.

Genomic rearrangements are thought to occur progressively during tumor development. Recent findings, however, suggest an alternative mechanism, involving massive chromosome rearrangements in a one-step catastrophic event termed chromothripsis. We report the whole-genome sequencing-based analysis of a Sonic-Hedgehog medulloblastoma (SHH-MB) brain tumor from a patient with a germline TP53 mutation (Li-Fraumeni syndrome), uncovering massive, complex chromosome rearrangements. Integrating TP53 status with microarray and deep sequencing-based DNA rearrangement data in additional patients reveals a striking association between TP53 mutation and chromothripsis in SHH-MBs. Analysis of additional tumor entities substantiates a link between TP53 mutation and chromothripsis, and indicates a context-specific role for p53 in catastrophic DNA rearrangements. Among these, we observed a strong association between somatic TP53 mutations and chromothripsis in acute myeloid leukemia. These findings connect p53 status and chromothripsis in specific tumor types, providing a genetic basis for understanding particularly aggressive subtypes of cancer.

Developing deep learning-based strategies to predict the risk of hepatocellular carcinoma among patients with nonalcoholic fatty liver disease from electronic health records.

OBJECTIVE: The accuracy of deep learning models for many disease prediction problems is affected by time-varying covariates, rare incidence, covariate imbalance and delayed diagnosis when using structured electronic health records data. The situation is further exasperated when predicting the risk of one disease on condition of another disease, such as the hepatocellular carcinoma risk among patients with nonalcoholic fatty liver disease due to slow, chronic progression, the scarce of data with both disease conditions and the sex bias of the diseases. The goal of this study is to investigate the extent to which the aforementioned issues influence deep learning performance, and then devised strategies to tackle these challenges. These strategies were applied to improve hepatocellular carcinoma risk prediction among patients with nonalcoholic fatty liver disease. METHODS: We evaluated two representative deep learning models in the task of predicting the occurrence of hepatocellular carcinoma in a cohort of patients with nonalcoholic fatty liver disease (n = 220,838) from a national EHR database. The disease prediction task was carefully formulated as a classification problem while taking censorship and the length of follow-up into consideration. RESULTS: We developed a novel backward masking scheme to deal with the issue of delayed diagnosis which is very common in EHR data analysis and evaluate how the length of longitudinal information after the index date affects disease prediction. We observed that modeling time-varying covariates improved the performance of the algorithms and transfer learning mitigated reduced performance caused by the lack of data. In addition, covariate imbalance, such as sex bias in data impaired performance. Deep learning models trained on one sex and evaluated in the other sex showed reduced performance, indicating the importance of assessing covariate imbalance while preparing data for model training. CONCLUSIONS: The strategies developed in this work can significantly improve the performance of hepatocellular carcinoma risk prediction among patients with nonalcoholic fatty liver disease. Furthermore, our novel strategies can be generalized to apply to other disease risk predictions using structured electronic health records, especially for disease risks on condition of another disease.

CNGPLD: case-control copy-number analysis using Gaussian process latent difference.

MOTIVATION: Cross-sectional analyses of primary cancer genomes have identified regions of recurrent somatic copy-number alteration, many of which result from positive selection during cancer formation and contain driver genes. However, no effective approach exists for identifying genomic loci under significantly different degrees of selection in cancers of different subtypes, anatomic sites or disease stages. RESULTS: CNGPLD is a new tool for performing case-control somatic copy-number analysis that facilitates the discovery of differentially amplified or deleted copy-number aberrations in a case group of cancer compared with a control group of cancer. This tool uses a Gaussian process statistical framework in order to account for the covariance structure of copy-number data along genomic coordinates and to control the false discovery rate at the region level. AVAILABILITY AND IMPLEMENTATION: CNGPLD is freely available at https://bitbucket.org/djhshih/cngpld as an R package. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Incorporating COVID-19 into Acute Febrile Illness Surveillance Systems, Belize, Kenya, Ethiopia, Peru, and Liberia, 2020-2021.

Existing acute febrile illness (AFI) surveillance systems can be leveraged to identify and characterize emerging pathogens, such as SARS-CoV-2, which causes COVID-19. The US Centers for Disease Control and Prevention collaborated with ministries of health and implementing partners in Belize, Ethiopia, Kenya, Liberia, and Peru to adapt AFI surveillance systems to generate COVID-19 response information. Staff at sentinel sites collected epidemiologic data from persons meeting AFI criteria and specimens for SARS-CoV-2 testing. A total of 5,501 patients with AFI were enrolled during March 2020-October 2021; >69% underwent SARS-CoV-2 testing. Percentage positivity for SARS-CoV-2 ranged from 4% (87/2,151, Kenya) to 19% (22/115, Ethiopia). We show SARS-CoV-2 testing was successfully integrated into AFI surveillance in 5 low- to middle-income countries to detect COVID-19 within AFI care-seeking populations. AFI surveillance systems can be used to build capacity to detect and respond to both emerging and endemic infectious disease threats.

Divergent clonal selection dominates medulloblastoma at recurrence.

The development of targeted anti-cancer therapies through the study of cancer genomes is intended to increase survival rates and decrease treatment-related toxicity. We treated a transposon-driven, functional genomic mouse model of medulloblastoma with 'humanized' in vivo therapy (microneurosurgical tumour resection followed by multi-fractionated, image-guided radiotherapy). Genetic events in recurrent murine medulloblastoma exhibit a very poor overlap with those in matched murine diagnostic samples (<5%). Whole-genome sequencing of 33 pairs of human diagnostic and post-therapy medulloblastomas demonstrated substantial genetic divergence of the dominant clone after therapy (<12% diagnostic events were retained at recurrence). In both mice and humans, the dominant clone at recurrence arose through clonal selection of a pre-existing minor clone present at diagnosis. Targeted therapy is unlikely to be effective in the absence of the target, therefore our results offer a simple, proximal, and remediable explanation for the failure of prior clinical trials of targeted therapy.

The LHC Olympics 2020 a community challenge for anomaly detection in high energy physics.

A new paradigm for data-driven, model-agnostic new physics searches at colliders is emerging, and aims to leverage recent breakthroughs in anomaly detection and machine learning. In order to develop and benchmark new anomaly detection methods within this framework, it is essential to have standard datasets. To this end, we have created the LHC Olympics 2020, a community challenge accompanied by a set of simulated collider events. Participants in these Olympics have developed their methods using an R&D dataset and then tested them on black boxes: datasets with an unknown anomaly (or not). Methods made use of modern machine learning tools and were based on unsupervised learning (autoencoders, generative adversarial networks, normalizing flows), weakly supervised learning, and semi-supervised learning. This paper will review the LHC Olympics 2020 challenge, including an overview of the competition, a description of methods deployed in the competition, lessons learned from the experience, and implications for data analyses with future datasets as well as future colliders.

Effect and Mechanism of TL1A Expression on Epithelial-Mesenchymal Transition during Chronic Colitis-Related Intestinal Fibrosis.

BACKGROUND AND AIMS: Recent evidences reveal that epithelial to mesenchymal transition (EMT) exacerbates the process of intestinal fibrosis. Tumor necrosis factor-like ligand 1A (TL1A) is a member of the tumor necrosis family (TNF), which can take part in the development of colonic inflammation and fibrosis by regulating immune response or inflammatory factors. The purpose of this study was to elucidate the possible contribution of TL1A in onset and progression of intestinal inflammation and fibrosis through EMT. METHODS: Colonic specimens were obtained from patients with inflammatory bowel disease (IBD) and control individuals. The expression levels of TL1A and EMT-related markers in intestinal tissues were evaluated. Furthermore, the human colorectal adenocarcinoma cell line, HT-29, was stimulated with TL1A, anti-TL1A antibody, or BMP-7 to assess EMT process. In addition, transgenic mice expressing high levels of TL1A in lymphoid cells were used to further investigate the mechanism of TL1A in intestinal fibrosis. RESULTS: High levels of TL1A expression were detected in the intestinal specimens of patients with ulcerative colitis and Crohn's disease and were negatively associated with the expression of an epithelial marker (E-cadherin), while it was positively associated with the expression of interstitial markers (FSP1 and α-SMA). Transgenic mice with high expression of TL1A were more sensitive to dextran sodium sulfate and exhibited severe intestinal inflammation and fibrosis. Additionally, the TGF-ß1/Smad3 pathway may be involved in TL1A-induced EMT, and the expression of IL-13 and EMT-related transcriptional molecules (e.g., ZEB1 and Snail1) was increased in the intestinal specimens of the transgenic mice. Furthermore, TL1A-induced EMT can be influenced by anti-TL1A antibody or BMP-7 in vitro. CONCLUSIONS: TL1A participates in the formation and process of EMT in intestinal fibrosis. This new knowledge enables us to better understand the pathogenesis of intestinal fibrosis and identify new therapeutic targets for its treatment.

A Gene Expression Signature to Predict Nucleotide Excision Repair Defects and Novel Therapeutic Approaches.

Nucleotide excision repair (NER) resolves DNA adducts, such as those caused by ultraviolet light. Deficient NER (dNER) results in a higher mutation rate that can predispose to cancer development and premature ageing phenotypes. Here, we used isogenic dNER model cell lines to establish a gene expression signature that can accurately predict functional NER capacity in both cell lines and patient samples. Critically, none of the identified NER deficient cell lines harbored mutations in any NER genes, suggesting that the prevalence of NER defects may currently be underestimated. Identification of compounds that induce the dNER gene expression signature led to the discovery that NER can be functionally impaired by GSK3 inhibition, leading to synergy when combined with cisplatin treatment. Furthermore, we predicted and validated multiple novel drugs that are synthetically lethal with NER defects using the dNER gene signature as a drug discovery platform. Taken together, our work provides a dynamic predictor of NER function that may be applied for therapeutic stratification as well as development of novel biological insights in human tumors.

Robust Jet Classifiers through Distance Correlation.

While deep learning has proven to be extremely successful at supervised classification tasks at the LHC and beyond, for practical applications, raw classification accuracy is often not the only consideration. One crucial issue is the stability of network predictions, either versus changes of individual features of the input data or against systematic perturbations. We present a new method based on a novel application of "distance correlation," a measure quantifying nonlinear correlations, that achieves equal performance to state-of-the-art adversarial decorrelation networks but is much simpler and more stable to train. To demonstrate the effectiveness of our method, we carefully recast a recent ATLAS study of decorrelation methods as applied to boosted, hadronic W tagging. We also show the feasibility of regularization with distance correlation for more powerful convolutional neural networks, as well as for the problem of hadronic top tagging.

Enhancer hijacking activates GFI1 family oncogenes in medulloblastoma.

Medulloblastoma is a highly malignant paediatric brain tumour currently treated with a combination of surgery, radiation and chemotherapy, posing a considerable burden of toxicity to the developing child. Genomics has illuminated the extensive intertumoral heterogeneity of medulloblastoma, identifying four distinct molecular subgroups. Group 3 and group 4 subgroup medulloblastomas account for most paediatric cases; yet, oncogenic drivers for these subtypes remain largely unidentified. Here we describe a series of prevalent, highly disparate genomic structural variants, restricted to groups 3 and 4, resulting in specific and mutually exclusive activation of the growth factor independent 1 family proto-oncogenes, GFI1 and GFI1B. Somatic structural variants juxtapose GFI1 or GFI1B coding sequences proximal to active enhancer elements, including super-enhancers, instigating oncogenic activity. Our results, supported by evidence from mouse models, identify GFI1 and GFI1B as prominent medulloblastoma oncogenes and implicate 'enhancer hijacking' as an efficient mechanism driving oncogene activation in a childhood cancer.

Myeloid ATG16L1 Facilitates Host-Bacteria Interactions in Maintaining Intestinal Homeostasis.

Intact ATG16L1 plays an essential role in Paneth cell function and intestinal homeostasis. However, the functional consequences of ATG16L1 deficiency in myeloid cells, particularly macrophages, are not fully characterized. We generated mice with Atg16l1 deficiency in myeloid and dendritic cells and showed that mice with myeloid Atg16l1 deficiency had exacerbated colitis in two acute and one chronic model of colitis with increased proinflammatory to anti-inflammatory macrophage ratios, production of proinflammatory cytokines, and numbers of IgA-coated intestinal microbes. Mechanistic analyses using primary murine macrophages showed that Atg16l1 deficiency led to increased reactive oxygen species production, impaired mitophagy, reduced microbial killing, impaired processing of MHC class II Ags, and altered intracellular trafficking to the lysosomal compartments. Increased production of reactive oxygen species and reduced microbial killing may be general features of the myeloid compartment, as they were also observed in Atg16l1-deficient primary murine neutrophils. A missense polymorphism (Thr300Ala) in the essential autophagy gene ATG16L1 is associated with Crohn disease (CD). Previous studies showed that this polymorphism leads to enhanced cleavage of ATG16L1 T300A protein and thus reduced autophagy. Similar findings were shown in primary human macrophages from controls and a population of CD patients carrying the Atg16l1 T300A risk variant and who were controlled for NOD2 CD-associated variants. This study revealed that ATG16L1 deficiency led to alterations in macrophage function that contribute to the severity of CD.

Effects and Mechanism of Constitutive TL1A Expression on Intestinal Mucosal Barrier in DSS-Induced Colitis.

OBJECTIVE: The role of TL1A in the intestinal mucosa barrier in inflammatory bowel disease (IBD) is still unclear. This study was aimed to investigate the expression levels of tight junction protein (TJ), myosin light chain kinase (MLCK), MyD88 and tumor necrosis factor (TNF) receptor-associated factor-6 (TRAF6) and how TL1A influences the intestinal barrier in IBD. METHODS: The mouse models of IBD were built using FMS-TL1A-GFP-transgenic mice and wild-type mice. The morphological and histopathological changes, bacterial translocation, permeability of colonic mucosa, and LPS level were assessed. Caco-2 cells were used to further investigate the association between TL1A and TNF-α and LPS. The protein level and mRNA changes of TJ proteins including ZO-1, occluding, JAMA, claudin-1, claudin-2, and claudin-3 were investigated using Western blot and real-time PCR. Protein changes of MLCK, MyD88 and TNF receptor-associated factor-6 (TRAF6), and TNF-α mRNA in the mouse colon were further assessed. RESULTS: The IBD models were successfully built. Cooper HS score and histopathological score of the colon were higher in DSS/WT group than in control/WT group (P < 0.05), higher in DSS/Tg group than in control/Tg group (P < 0.05), and higher in DSS/Tg group than in DSS/WT group. PAS, colonic permeability of the colon, and FITC-D examination showed the similar results and trends. Compared with control/WT group, the levels of TL1A and claudin-2 were higher and the levels of ZO-1, occludin, JAMA, claudin-1, and claudin-3 were lower in DSS/WT group (P < 0.05). Compared with control/Tg group, the levels of TL1A and claudin-2 were higher and the levels of ZO-1, occludin, JAMA, claudin-1, and claudin-3 were lower in DSS/Tg group. Compared with Caco-2 + TNF-α group, the expression level of occludin and claudin-1 in Caco-2 + LV-TNFSF15 + TNF-α group was significantly lower (P < 0.05); p-MLC level was significantly higher. Compared with Caco-2 + LPS group, the expression level of occludin and claudin-1 significantly decreased in Caco-2 + LV-TNFSF15 + LPS group; MyD88 and TRAF6 expression level significantly increased. CONCLUSION: The results suggested that TL1A could impair intestinal epithelial barrier in the mouse model of IBD and might regulate TJ expression via MLCK/p-MLC pathway and LPS-mediated MyD88/TRAF6 pathway.

Heterogeneity within the PF-EPN-B ependymoma subgroup.

Posterior fossa ependymoma comprise three distinct molecular variants, termed PF-EPN-A (PFA), PF-EPN-B (PFB), and PF-EPN-SE (subependymoma). Clinically, they are very disparate and PFB tumors are currently being considered for a trial of radiation avoidance. However, to move forward, unraveling the heterogeneity within PFB would be highly desirable. To discern the molecular heterogeneity within PFB, we performed an integrated analysis consisting of DNA methylation profiling, copy-number profiling, gene expression profiling, and clinical correlation across a cohort of 212 primary posterior fossa PFB tumors. Unsupervised spectral clustering and t-SNE analysis of genome-wide methylation data revealed five distinct subtypes of PFB tumors, termed PFB1-5, with distinct demographics, copy-number alterations, and gene expression profiles. All PFB subtypes were distinct from PFA and posterior fossa subependymomas. Of the five subtypes, PFB4 and PFB5 are more discrete, consisting of younger and older patients, respectively, with a strong female-gender enrichment in PFB5 (age: p = 0.011, gender: p = 0.04). Broad copy-number aberrations were common; however, many events such as chromosome 2 loss, 5 gain, and 17 loss were enriched in specific subtypes and 1q gain was enriched in PFB1. Late relapses were common across all five subtypes, but deaths were uncommon and present in only two subtypes (PFB1 and PFB3). Unlike the case in PFA ependymoma, 1q gain was not a robust marker of poor progression-free survival; however, chromosome 13q loss may represent a novel marker for risk stratification across the spectrum of PFB subtypes. Similar to PFA ependymoma, there exists a significant intertumoral heterogeneity within PFB, with distinct molecular subtypes identified. Even when accounting for this heterogeneity, extent of resection remains the strongest predictor of poor outcome. However, this biological heterogeneity must be accounted for in future preclinical modeling and personalized therapies.

Extrapulmonary Nontuberculous Mycobacterial Disease Surveillance - Oregon, 2014-2016.

Nontuberculous mycobacteria (NTM), ubiquitous in soil and water, usually infect immunocompromised persons. However, even healthy persons are susceptible to infection through percutaneous inoculation. Although 77% of NTM diseases manifest as primarily pulmonary illnesses (1), NTM also infect skin, bones, joints, the lymphatic system, and soft tissue. NTM infections can have incubation periods that exceed 5 years (2), often require prolonged treatment, and can lead to sepsis and death. Extrapulmonary NTM outbreaks have been reported in association with contaminated surgical gentian violet (3), nail salon pedicures (4), and tattoos received at tattoo parlors (5), although few surveillance data have been available for estimating the public health burden of NTM.* On January 1, 2014, the Oregon Health Authority designated extrapulmonary NTM disease a reportable condition. To characterize extrapulmonary NTM infection, estimate resources required for surveillance, and assess the usefulness of surveillance in outbreak detection and investigation, 2014-2016 extrapulmonary NTM surveillance data were reviewed, and interviews with stakeholders were conducted. During 2014-2016, 134 extrapulmonary NTM cases (11 per 1 million persons per year) were reported in Oregon. The age distribution was bimodal, with highest incidence among persons aged <10 years (20 per 1 million persons per year) and persons aged 60-69 years (18 per 1 million persons per year). The most frequently reported predisposing factors (occurring within 14-70 days of symptom onset) were soil exposure (41/98; 42%), immunocompromised condition (42/124; 34%), and surgery (32/120; 27%). Overall, 43 (33%) patients were hospitalized, 18 (15%) developed sepsis, and one (0.7%) died. Surveillance detected or helped to control two outbreaks at low cost. Jurisdictions interested in implementing extrapulmonary NTM surveillance can use the Council of State and Territorial Epidemiologists (CSTE) standardized case definition (6) for extrapulmonary NTM reporting or investigative guidelines maintained by the Oregon Health Authority (7).

Mesenchymal stem cell transplantation improves chronic colitis-associated complications through inhibiting the activity of toll-like receptor-4 in mice.

BACKGROUND: A variety of extra-intestinal manifestations (EIMs), including hepatobiliary complications, are associated with inflammatory bowel disease (IBD). Mesenchymal stem cells (MSCs) have been shown to play a potential role in the therapy of IBD. This study was designed to investigate the effect and mechanism of MSCs on chronic colitis-associated hepatobiliary complications using mouse chronic colitis models induced by dextran sulfate sodium (DSS). METHODS: DSS-induced mouse chronic colitis models were established and treated with MSCs. Severity of colitis was evaluated by disease activity index (DAI), body weight (BW), colon length and histopathology. Serum lipopolysaccharide (LPS) levels were detected by limulus amebocyte lysate test (LAL-test). Histology and liver function of the mice were checked correspondingly. Serum LPS levels and bacterial translocation of mesenteric lymph nodes (MLN) were detected. Pro-inflammatory cytokines including tumor necrosis factor-α (TNF-α), interferon-γ (IFN-γ), interleukin-1ß (IL-1ß), interleukin-17A (IL-17A), Toll receptor 4 (TLR4), TNF receptor-associated factor 6 (TRAF6) and nuclear factor kappa B (NF-κB) were detected by immunohistochemical staining, western blot analysis and real-time PCR, respectively. RESULTS: The DSS-induced chronic colitis model was characterized by reduced BW, high DAI, worsened histologic inflammation, and high levels of LPS and E. coli. Liver histopathological lesions, impaired liver function, enhanced proteins and mRNA levels of TNF-α, IFN-γ, IL-1ß, IL-17A, TLR4, TRAF6 and NF-κB were observed after DSS administration. MSCs transplantation markedly ameliorated the pathology of colon and liver by reduction of LPS levels and proteins and mRNA expressions of TNF-α, IFN-γ, IL-1ß, IL-17A, TLR4, TRAF6 and NF-κB. CONCLUSIONS: MSCs can improve chronic colitis-associated hepatobiliary complications, probably by inhibition of enterogenous endotoxemia and hepatic inflammation through LPS/TLR4 pathway. MSCs may represent a novel therapeutic approach for chronic colitis-associated hepatobiliary complications.

Dissecting the genomic complexity underlying medulloblastoma.

Medulloblastoma is an aggressively growing tumour, arising in the cerebellum or medulla/brain stem. It is the most common malignant brain tumour in children, and shows tremendous biological and clinical heterogeneity. Despite recent treatment advances, approximately 40% of children experience tumour recurrence, and 30% will die from their disease. Those who survive often have a significantly reduced quality of life. Four tumour subgroups with distinct clinical, biological and genetic profiles are currently identified. WNT tumours, showing activated wingless pathway signalling, carry a favourable prognosis under current treatment regimens. SHH tumours show hedgehog pathway activation, and have an intermediate prognosis. Group 3 and 4 tumours are molecularly less well characterized, and also present the greatest clinical challenges. The full repertoire of genetic events driving this distinction, however, remains unclear. Here we describe an integrative deep-sequencing analysis of 125 tumour-normal pairs, conducted as part of the International Cancer Genome Consortium (ICGC) PedBrain Tumor Project. Tetraploidy was identified as a frequent early event in Group 3 and 4 tumours, and a positive correlation between patient age and mutation rate was observed. Several recurrent mutations were identified, both in known medulloblastoma-related genes (CTNNB1, PTCH1, MLL2, SMARCA4) and in genes not previously linked to this tumour (DDX3X, CTDNEP1, KDM6A, TBR1), often in subgroup-specific patterns. RNA sequencing confirmed these alterations, and revealed the expression of what are, to our knowledge, the first medulloblastoma fusion genes identified. Chromatin modifiers were frequently altered across all subgroups. These findings enhance our understanding of the genomic complexity and heterogeneity underlying medulloblastoma, and provide several potential targets for new therapeutics, especially for Group 3 and 4 patients.

Clonal selection drives genetic divergence of metastatic medulloblastoma.

Medulloblastoma, the most common malignant paediatric brain tumour, arises in the cerebellum and disseminates through the cerebrospinal fluid in the leptomeningeal space to coat the brain and spinal cord. Dissemination, a marker of poor prognosis, is found in up to 40% of children at diagnosis and in most children at the time of recurrence. Affected children therefore are treated with radiation to the entire developing brain and spinal cord, followed by high-dose chemotherapy, with the ensuing deleterious effects on the developing nervous system. The mechanisms of dissemination through the cerebrospinal fluid are poorly studied, and medulloblastoma metastases have been assumed to be biologically similar to the primary tumour. Here we show that in both mouse and human medulloblastoma, the metastases from an individual are extremely similar to each other but are divergent from the matched primary tumour. Clonal genetic events in the metastases can be demonstrated in a restricted subclone of the primary tumour, suggesting that only rare cells within the primary tumour have the ability to metastasize. Failure to account for the bicompartmental nature of metastatic medulloblastoma could be a major barrier to the development of effective targeted therapies.