The large diversity of central nervous system (CNS) tumor types in children and adolescents results in disparate patient outcomes and renders accurate diagnosis challenging. In this study, we prospectively integrated DNA methylation profiling and targeted gene panel sequencing with blinded neuropathological reference diagnostics for a population-based cohort of more than 1,200 newly diagnosed pediatric patients with CNS tumors, to assess their utility in routine neuropathology. We show that the multi-omic integration increased diagnostic accuracy in a substantial proportion of patients through annotation to a refining DNA methylation class (50%), detection of diagnostic or therapeutically relevant genetic alterations (47%) or identification of cancer predisposition syndromes (10%). Discrepant results by neuropathological WHO-based and DNA methylation-based classification (30%) were enriched in histological high-grade gliomas, implicating relevance for current clinical patient management in 5% of all patients. Follow-up (median 2.5 years) suggests improved survival for patients with histological high-grade gliomas displaying lower-grade molecular profiles. These results provide preliminary evidence of the utility of integrating multi-omics in neuropathology for pediatric neuro-oncology.

Diffuse intrinsic pontine glioma is a uniformly lethal malignant tumor of infancy with no effective therapies. A new study reveals that inhibition of JMJD3 has robust antitumor activity in diffuse intrinsic pontine glioma xenografts.

Medulloblastoma, the most common malignant childhood brain tumor, exhibits distinct molecular subtypes and cellular origins. Genetic alterations driving medulloblastoma initiation and progression remain poorly understood. Herein, we identify GNAS, encoding the G protein Gαs, as a potent tumor suppressor gene that, when expressed at low levels, defines a subset of aggressive Sonic hedgehog (SHH)-driven human medulloblastomas. Ablation of the single Gnas gene in anatomically distinct progenitors in mice is sufficient to induce Shh-associated medulloblastomas, which recapitulate their human counterparts. Gαs is highly enriched at the primary cilium of granule neuron precursors and suppresses Shh signaling by regulating both the cAMP-dependent pathway and ciliary trafficking of Hedgehog pathway components. Elevation in levels of a Gαs effector, cAMP, effectively inhibits tumor cell proliferation and progression in Gnas-ablated mice. Thus, our gain- and loss-of-function studies identify a previously unrecognized tumor suppressor function for Gαs that can be found consistently across Shh-group medulloblastomas of disparate cellular and anatomical origins, highlighting G protein modulation as a potential therapeutic avenue.

Recurrent medulloblastoma and ependymoma are universally lethal, with no approved targeted therapies and few candidates presently under clinical evaluation. Nearly all recurrent medulloblastomas and posterior fossa group A (PFA) ependymomas are located adjacent to and bathed by the cerebrospinal fluid, presenting an opportunity for locoregional therapy, bypassing the blood-brain barrier. We identify three cell-surface targets, EPHA2, HER2 and interleukin 13 receptor α2, expressed on medulloblastomas and ependymomas, but not expressed in the normal developing brain. We validate intrathecal delivery of EPHA2, HER2 and interleukin 13 receptor α2 chimeric antigen receptor T cells as an effective treatment for primary, metastatic and recurrent group 3 medulloblastoma and PFA ependymoma xenografts in mouse models. Finally, we demonstrate that administration of these chimeric antigen receptor T cells into the cerebrospinal fluid, alone or in combination with azacytidine, is a highly effective therapy for multiple metastatic mouse models of group 3 medulloblastoma and PFA ependymoma, thereby providing a rationale for clinical trials of these approaches in humans.

The causes of pediatric cancers' distinctiveness compared to adult-onset tumors of the same type are not completely clear and not fully explained by their genomes. In this study, we used an optimized multilevel RNA clustering approach to derive molecular definitions for most childhood cancers. Applying this method to 13,313 transcriptomes, we constructed a pediatric cancer atlas to explore age-associated changes. Tumor entities were sometimes unexpectedly grouped due to common lineages, drivers or stemness profiles. Some established entities were divided into subgroups that predicted outcome better than current diagnostic approaches. These definitions account for inter-tumoral and intra-tumoral heterogeneity and have the potential of enabling reproducible, quantifiable diagnostics. As a whole, childhood tumors had more transcriptional diversity than adult tumors, maintaining greater expression flexibility. To apply these insights, we designed an ensemble convolutional neural network classifier. We show that this tool was able to match or clarify the diagnosis for 85% of childhood tumors in a prospective cohort. If further validated, this framework could be extended to derive molecular definitions for all cancer types.