Alternative splicing is frequently dysregulated in pediatric central nervous system (CNS) tumors, including high-grade gliomas (HGGs) and diffuse midline gliomas (DMGs) which have poor survival outcomes and urgently need new therapeutic strategies. Aberrant splicing events are increasingly being explored as sources of tumor-specific antigens (TSAs) for immunotherapy, yet the tumor-specific splicing landscape in pediatric CNS cancers remains critically underexplored. In this study, we quantified alternative splice events in primary CNS tumors from the Pediatric Brain Tumor Atlas (PBTA) and compared expression to that in healthy brain tissue to identify tumor-enriched splice events (TESEs). Events were detected from RNA-seq data of PBTA CNS tumors (n=1,375) and healthy brain samples from GTEx (<40 years, n=2,642), the Evo-Devo atlas (n=228), and pediatric brain tissue (n=7) using replicate Multivariate Analysis of Transcript Splicing (rMATS-turbo). We limited analysis to exon inclusion (SE), retained introns (RI), and alternative 3’ and 5’ splice site (A3SS, A5SS) events involving annotated splice sites in GENCODE v39. TESEs were defined by an absolute difference in percent spliced-in (|ΔPSI|) > 0.3 between tumors and all healthy brain samples, while oncofetal TESEs were defined as those meeting the same |ΔPSI| threshold compared to postnatal brain samples only. TESEs were annotated with Pfam protein domains and UniProt topological domains to identify those encoding functional and extracellular (EC) domains, respectively. We identified 3,315 recurrent TESEs (>10% of tumors), most of which (77.1%) involved increased exon skipping (n=1,451) or inclusion (n=1,105) in tumors. Of these, 1,483 (44.7%) were classified as oncofetal, and comprised the majority of TESEs in medulloblastoma (MB, 65.9%), other CNS embryonal tumors (65.3%), and oligodendrogliomas (52.2%). Clustering of tumors by TESE PSI values grouped samples broadly into tumor histologies (i.e., MB, ependymoma, HGG) or distinct molecular subtypes (e.g. within Atypical Teratoid Rhabdoid Tumor), suggesting conserved patterns of splicing aberrations. 113 recurrent TESEs encoded protein extracellular domains in 71 unique genes, including 28 genes in HGG and DMG tumors. Overall, we identified hundreds of pan-pediatric CNS cancer, histology-, and subtype-specific splicing aberrations affecting protein domains, and a subset with predicted cell surface localization, nominating candidate TSAs. Future work will seek to validate the protein expression of TESE-derived EC peptides as well as predict presentation of intracellular TESE-derived peptides by MHC molecules. Ryan J Corbett, Patricia J Sullivan, Ammar S Naqvi, Alex Sickler, Bicna Song, Chao Di, Bo Zhang, Chuwei Zhong, Brian Rood, Jo Lynne Rokita. Tumor-enriched splicing events exhibit histology-specific prevalence in pediatric CNS tumors and encode tumor-specific antigens with immunotherapeutic potential [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Discovery and Innovation in Pediatric Cancer— From Biology to Breakthrough Therapies; 2025 Sep 25-28; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2025;85(18_Suppl_2):Abstract nr B022.

BACKGROUND:In 2019, the Open Pediatric Brain Tumor Atlas (OpenPBTA) was created as a global, collaborative open-science initiative to genomically characterize 1,074 pediatric brain tumors and 22 patient-derived cell lines. Here, we present an extension of the OpenPBTA called the Open Pediatric Cancer (OpenPedCan) Project, a harmonized open-source multiomic dataset from 6,112 pediatric cancer patients with 7,096 tumor events across more than 100 histologies. Combined with RNA sequencing (RNA-seq) from the Genotype-Tissue Expression and The Cancer Genome Atlas projects, OpenPedCan contains nearly 48,000 total biospecimens (24,002 tumor and 23,893 normal specimens). FINDINGS:We utilized Gabriella Miller Kids First workflows to harmonize whole-genome sequencing (WGS), whole exome sequencing (WXS), RNA-seq, and Targeted Sequencing datasets to include somatic SNVs, indels, copy number variants, structural variants, RNA expression, fusions, and splice variants. We integrated summarized Clinical Proteomic Tumor Analysis Consortium whole-cell proteomics and phospho-proteomics data and miRNA sequencing data, as well as developed a methylation array harmonization workflow to include m-values, beta-values, and copy number calls. OpenPedCan contains reproducible, dockerized workflows in GitHub, CAVATICA, and Amazon Web Services (AWS) to deliver harmonized and processed data from over 60 scalable modules, which can be leveraged both locally and on AWS. The processed data are released in a versioned manner and accessible through CAVATICA or AWS S3 download (from GitHub) and queryable through PedcBioPortal and the National Cancer Institute's pediatric Molecular Targets Platform. Notably, we have expanded Pediatric Brain Tumor Atlas molecular subtyping to include methylation information to align with the World Health Organization 2021 Central Nervous System Tumor classifications, allowing us to create research-grade integrated diagnoses for these tumors. CONCLUSIONS:OpenPedCan data and its reproducible analysis module framework are openly available and can be utilized and/or adapted by researchers to accelerate discovery, validation, and clinical translation.

Abstract Medulloblastoma is a cerebellar tumor for which relapses are associated with poor survival rates of less than 5%. Molecular heterogeneity and dose-limiting toxicities that occur with standard of care approaches, which include surgical resection, craniospinal irradiation, and chemotherapy, complicate the treatment of both primary and recurrent medulloblastoma due to adverse long-term sequela. While the integration of molecular analyses into the histopathology of pediatric medulloblastomas has changed the way these diseases are diagnosed, classified, and treated, there remains an unmet need to further understand the underpinnings of the disease to improve clinical outcomes and minimize neuronal, cognitive, and hormonal toxicities that occur with standard-of-care therapies. We therefore aimed to investigate novel subgroups of pediatric medulloblastoma as a basis for further defining biological properties and targets for the disease through multi-omic characterization. We derived single-nucleotide variant, copy number variant, expression, alternative splicing, and methylation array data from pediatric medulloblastomas profiled as part of the Children’s Brain Tumor Network (CBTN) and the Open Pediatric Cancer (OpenPedCan) projects. Using non-negative matrix factorization across the five datasets derived from genomic, transcriptomic, and epigenomic profiling, we identified 14 clusters found to be prognostically significant by Kaplan-Meier analysis of overall survival (p < 0.0001). Our model further subdivided sonic hedgehog (SHH) and Group 3/4 tumors, but not Wnt-driven tumors, suggesting that the latter forms a homogeneous molecular subgroup. Among our subgroups, we recapitulated the four classically defined medulloblastoma subtypes known to be associated with mutations in KDM6A, KMT2C, CTNNB1, PTCH1, TP53, KBTBD4, MYC, and MYCN. Cascading biological relationships across the copy number, methylation, and expression domains were observed among novel subgroups, potentially driving migratory, immuno-regulatory, GPCR-related, growth factor-related, and histone methylation biological programs. A comparison of subgroup expression profiles to transcriptional signatures from the Library of Integrated Network-Based Cellular Signatures (LINCS) program identified canonical oncogenic pathways unique to each subgroup as potentially targetable, including, but not limited to, MAPK, VEGFA, inflammatory, fatty acid metabolic, and PI3K/AKT signaling. Our work uncovers novel biological entities in pediatric medulloblastoma potentially driven by higher order mechanisms across the genome, transcriptome, and epigenome, with the possibility of informing novel precision medicine approaches for the disease. Citation Format: Komal Rathi, Varun Kesherwani, Ammar S. Naqvi, Yuankun Zhu, Alex Sickler, Xiaoyan Huang, Bo Zhang, Brian Rood, Adam C. Resnick, Adam A. Kraya. Integrative multi-omic analysis reveals novel prognostic biological entities in pediatric medulloblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4889.

Abstract Despite standard-of-care therapy, pediatric brain tumors are now the leading cause of cancer-related death in children, highlighting an urgent need for the development of new treatments. Immunotherapy is actively being evaluated as a therapeutic approach to pediatric brain tumors, however, more research is needed to reveal additional antigenic targets that exist in these malignancies. In this study, our team performed a transcriptomic analysis of pediatric brain tumor RNA sequencing data within the Children’s Brain Tumor Network (CBTN) to identify intra and extracellular antigens that are highly expressed across major tumor types. Interestingly, our team observed that most tumors had high gene expression of a group of antigens that were unique to that specific tumor type. Specifically, our analysis revealed that diffuse midline gliomas (DMGs) highly expressed the extracellular antigens CA9, CTCFL, and ST8SIA1, whereas atypical rhabdoid tumors (ATRTs) highly expressed MUC1 and TEK. Other tumors that displayed high gene expression for a variety of antigenic targets included H3-wildtype high-grade gliomas (HGGs), and ependymomas (EPNs). Strikingly, we observed minimal difference in antigen expression in primary tumors when compared to patient-matched recurrences. Beyond antigen expression, we evaluated the expression of antigen processing machinery (APM) which includes major histocompatibility complexes (MHCs). Our findings revealed that DMGs had the lowest level of APM expression, however, these tumors uniquely expressed high levels of the immune checkpoints ADORA2A, CD276, and KLRC1. Contrarily, ATRTs showed a high expression of immune checkpoints CD274 (PD-L1), PVR, and CD80. Other tumors included in our analysis had unique expression patterns of antigen, as well as APM and immune checkpoints. Our findings illustrate that pediatric brain tumors have distinct expression patterns of antigens, APM, and immune checkpoints that are specific to tumor type, emphasizing diverse, rather than general, immunotherapeutic approaches must be considered for childhood brain tumors.

Pediatric tumors of the central nervous system are the most common cause of cancer-related death in children. The five-year survival rate for high-grade gliomas in children is less than 20%. Due to their rarity, the diagnosis of these entities is often delayed, their treatment is mainly based on historic treatment concepts, and clinical trials require multi-institutional collaborations. The MICCAI Brain Tumor Segmentation (BraTS) Challenge is a landmark community benchmark event with a successful history of 12 years of resource creation for the segmentation and analysis of adult glioma. Here we present the CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs 2023 challenge, which represents the first BraTS challenge focused on pediatric brain tumors with data acquired across multiple international consortia dedicated to pediatric neuro-oncology and clinical trials. The BraTS-PEDs 2023 challenge focuses on benchmarking the development of volumentric segmentation algorithms for pediatric brain glioma through standardized quantitative performance evaluation metrics utilized across the BraTS 2023 cluster of challenges. Models gaining knowledge from the BraTS-PEDs multi-parametric structural MRI (mpMRI) training data will be evaluated on separate validation and unseen test mpMRI dataof high-grade pediatric glioma. The CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs 2023 challenge brings together clinicians and AI/imaging scientists to lead to faster development of automated segmentation techniques that could benefit clinical trials, and ultimately the care of children with brain tumors.

Pediatric central nervous system tumors are the leading cause of cancer-related deaths in children. The five-year survival rate for high-grade glioma in children is less than 20%. The development of new treatments is dependent upon multi-institutional collaborative clinical trials requiring reproducible and accurate centralized response assessment. We present the results of the BraTS-PEDs 2023 challenge, the first Brain Tumor Segmentation (BraTS) challenge focused on pediatric brain tumors. This challenge utilized data acquired from multiple international consortia dedicated to pediatric neuro-oncology and clinical trials. BraTS-PEDs 2023 aimed to evaluate volumetric segmentation algorithms for pediatric brain gliomas from magnetic resonance imaging using standardized quantitative performance evaluation metrics employed across the BraTS 2023 challenges. The top-performing AI approaches for pediatric tumor analysis included ensembles of nnU-Net and Swin UNETR, Auto3DSeg, or nnU-Net with a self-supervised framework. The BraTS-PEDs 2023 challenge fostered collaboration between clinicians (neuro-oncologists, neuroradiologists) and AI/imaging scientists, promoting faster data sharing and the development of automated volumetric analysis techniques. These advancements could significantly benefit clinical trials and improve the care of children with brain tumors.

ObjectivesDespite surgical resection, chemoradiation, and targeted therapy, brain tumors remain a leading cause of cancer-related death in children. Immunotherapy has shown some promise and is actively being investigated for treating childhood brain tumors. However, a critical step in advancing immunotherapy for these patients is to uncover targets that can be effectively translated into therapeutic interventions.MethodsIn this study, our team performed a transcriptomic analysis across pediatric brain tumor types to identify potential targets for immunotherapy. Additionally, we assessed components that may impact patient response to immunotherapy, including the expression of genes essential for antigen processing and presentation, inhibitory ligands and receptors, interferon signature, and overall predicted T cell infiltration.ResultsWe observed distinct expression patterns across tumor types. These included elevated expression of antigen genes and antigen processing machinery in some tumor types while other tumors had elevated inhibitory checkpoint receptors, known to be associated with response to checkpoint inhibitor immunotherapy.ConclusionThese findings suggest that pediatric brain tumors exhibit distinct potential for specific immunotherapies. We believe our findings can guide investigators in their assessment of appropriate immunotherapy classes and targets in pediatric brain tumors.

Abstract BACKGROUND Medulloblastoma (MB) is a common malignant pediatric brain tumor with significant heterogeneity among its four molecular subgroups: WNT, SHH, groups 3 and 4. There is a significant rate of disease recurrence with group 3/4 MB indicating a need for novel therapeutic targets. Since transcriptomic profiling of MB has not identified novel targets, we focused on a proteomic approach. We selected 157 proteins significantly over-expressed in Group 3/4 MB and performed a targeted loss-of-function CRISPR-Cas9 screen in four MB cell lines. We identified 17 essential genes shared by at least 2 of the cell lines. The PTBP2 splicing factor was essential for all cell lines. PTBP2 is an RNA-binding protein involved in splicing regulation that plays an important role during neuronal maturation. We hypothesize that persistent expression of PTBP2 results in a differentiation arrest and preservation of proliferative potential. METHODS We stably knocked-out PTBP2 expression in D556 and MB002 MB cells. We performed bulk RNA-seq and quantitative proteomics of these KO clones along with CLIP-seq to map PTBP2 targeted transcripts. We also performed phenotype assays, qPCR array and single-cell RNA-seq in KO clones to validate proliferation and neuronal differentiation. RESULTS RNA-seq in PTBP2 KO MB cells revealed 2,213 differentially expressed genes predominantly involved in neuronal differentiation. These genes were cross-referenced with quantitative proteomic and eCLIP data. Using RNAseq from clinical samples, splice inclusion analysis based upon PTBP2 bound transcripts neatly segregated Group 3/4 MB from SHH and WNT. PTBP2 KO cells exhibited reduced proliferation and, upon stimulation, increased differentiated morphology compared to controls. This latter observation was further supported by qPCR array and single-cell RNA-seq. CONCLUSIONS The results suggests that the loss of PTBP2 expression stimulates MB differentiation with a subsequent reduction of proliferation activity and nominates PTBP2 and its downstream effectors as potential therapeutic targets in group 3/4 MB.

Neuroblastoma (NB) can be a highly aggressive malignancy in children. However, the precise mechanisms driving NB tumorigenesis remain elusive. This study revealed the critical role of CREB phosphorylation in NB cell proliferation. By employing a CRISPR-Cas9 knockout screen targeting calcium/calmodulin-dependent protein kinase (CaMK) family members, we identified the CaM kinase-like vesicle-associated (CAMKV) protein as a kinase that mediates direct phosphorylation of CREB to promote NB cell proliferation. CAMKV was found to be a transcriptional target of MYCN/MYC in NB cells. CAMKV knockout and knockdown effectively suppressed NB cell proliferation and tumor growth both in vitro and in vivo. Bioinformatic analysis revealed that high CAMKV expression is significantly correlated with poor patient survival. High-risk NB frequently had high CAMKV protein levels by Immunohistochemical staining. Integrated transcriptomic and proteomic analyses of CAMKV knockdown cells unveiled downstream targets involved in CAMKV-regulated phosphorylation and signaling pathways, many of which are linked to neural development and cancer progression. We identified small molecule inhibitors targeting CAMKV and further demonstrated the efficacy of one inhibitor in suppressing NB tumor growth and prolonging the survival of mice bearing xenografted tumors. These findings reveal a critical role for CAMKV kinase signaling in NB growth and identified CAMKV kinase as a potential therapeutic target and prognostic marker for patients with NB.

Abstract To unravel the molecular mechanisms underlying high-grade glioma (HGG) in adolescent and young adult (AYA) patients, we conducted a comprehensive proteogenomic analysis for 34 AYA (age 15-40) and 59 pediatric (age 0-15) HGG cases. Our approach involved whole genome sequencing, methylation profiling, RNA sequencing, and a suite of mass spectrometry-based proteomic experiments, including global proteomic, phosphoproteomic, and glycoproteomic profiling. The proteomics study successfully identified and quantified approximately 11,000 proteins, 33,000 phosphosites, and 3000 glycopeptides with a 50% missing filtering threshold. To identify the unique characteristics of AYA HGG in contrast to both pediatric and adult HGG, we further integrated a proteogenomic dataset of 99 adult GBM tumors previously published by CPTAC and collaborators (PMID: 33577785). Our study unveiled a collection of mutations, copy number variations, epigenetic modifications and gene fusions that exhibited different frequencies across tumors from pediatric, AYA, and adult patients. Moreover, the influence of these genetic variations on RNA/protein activities also varied across different age groups. Clustering analysis using age-dependent molecular profiles revealed striking differences in RNA/protein/phosphosite activities between patients aged 15-26 and 26-40. Additionally, significantly better overall survival (OS) was observed in the 26-40 age group compared to all other age groups, highlighting distinct biological characteristics within the AYA category that differentiate adolescents from young adults.By leveraging proteogenomic datasets from normal brain tissues (PMID: 30518843), we identified genes, proteins, and pathways with differential age-dependent molecular profiles between tumor and normal brain tissues. Notably, this analysis highlighted significant alterations in proteins from the oxidative phosphorylation, tricarboxylic acid (TCA) cycle, and myelin sheath pathways in tumors compared to normal tissues, some of which were found to be sex-specific.To search for prognostic markers, we introduced a novel approach called Trans-Population Survival Analysis through Interpolation of Age-Dependent Tumor Molecular Profiles. Applying this method on the kinase activity scores derived from the phosphoproteomic data, we identified 150 kinases whose activities were significantly associated with OS among AYA patients. Additionally, employing a causal network analysis tool, we pinpointed six kinases causally linked to OS, suggesting their potential as treatment targets. This study not only characterizes the molecular landscape of AYA HGG but also explores the disease trajectory across the lifespan. Our findings shed light on the intricate interplay of various factors influencing glioma etiology and patient outcomes, paving the way for a deeper understanding of HGG in the AYA population. Citation Format: Nicole Tignor, Mateusz P. Koptyra, Shrabanti Chowdhury, Weiping Ma, Jo Lynne Rokita, Marina Gritsenko, Xiaoyu Song, Giacomo B. Marino, Eden Z. Deng, Francesca Petralia, Azra Krek, Dmitry Rykunov, Felipe da Veiga Leprevost, Noshad Hosseini, Komal S. Rathi, Yingwei Hu, Simona Migliozzi, Tomer Yaron, Weijia Fu, Bo Zhang, Yuankun Zhu, Miguel A. Brown, Jeffrey R. Whiteaker, Clinical Proteomics Tumor Analysis Consortium (CPTAC), Children’s Brain Tumor Network (CBTN), Mehdi Mesri, Ana I. Robles, Karin Rodland, Lewis C. Cantley, Antonio Iavarone, Kenneth Aldape, Marcin Cieślik, Alexey I. Nesvizhskii, Joseph E. Ippolito, Joshua B. Rubin, Amanda G. Paulovich, Hui Zhang, Avi Ma'ayan, Tao Liu, Phillip B. Storm, Adam C. Resnick, Brian R. Rood, Pei Wang. A proteogenomic study of high-grade glioma among adolescents and young adults [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3955.

AbstractPurpose: Patients with MYC-amplified medulloblastoma (MB) have poor prognosis and frequently develop recurrence, thus new therapeutic approaches to prevent recurrence are needed. Experimental Design: We evaluated OLIG2 expression in a panel of mouse Myc-driven MB tumors, patient MB samples, and patient-derived xenograft (PDX) tumors and analyzed radiation sensitivity in OLIG2–high and OLIG2–low tumors in PDX lines. We assessed the effect of inhibition of OLIG2 by OLIG2-CRISPR or the small molecule inhibitor CT-179 combined with radiotherapy on tumor progression in PDX models. Results: We found that MYC-associated MB can be stratified into OLIG2–high and OLIG2–low tumors based on OLIG2 protein expression. In MYC-amplified MB PDX models, OLIG2–low tumors were sensitive to radiation and rarely relapsed, whereas OLIG2–high tumors were resistant to radiation and consistently developed recurrence. In OLIG2–high tumors, irradiation eliminated the bulk of tumor cells; however, a small number of tumor cells comprising OLIG2– tumor cells and rare OLIG2+ tumor cells remained in the cerebellar tumor bed when examined immediately post-irradiation. All animals harboring residual-resistant tumor cells developed relapse. The relapsed tumors mirrored the cellular composition of the primary tumors with enriched OLIG2 expression. Further studies demonstrated that OLIG2 was essential for recurrence, as OLIG2 disruption with CRISPR-mediated deletion or with the small molecule inhibitor CT-179 prevented recurrence from the residual radioresistant tumor cells. Conclusions: Our studies reveal that OLIG2 is a biomarker and an effective therapeutic target in a high-risk subset of MYC-amplified MB, and OLIG2 inhibitor combined with radiotherapy represents a novel effective approach for treating this devastating disease.

Molecular characteristics of pediatric brain tumors have not only allowed for tumor subgrouping but have introduced novel treatment options for patients with specific tumor alterations. Therefore, an accurate histologic and molecular diagnosis is critical for optimized management of all pediatric patients with brain tumors, including central nervous system embryonal tumors. We present a case where optical genome mapping identified a ZNF532-NUTM1 fusion in a patient with a unique tumor best characterized histologically as a central nervous system embryonal tumor with rhabdoid features. Additional analyses including immunohistochemistry for NUT protein, methylation array, whole genome, and RNA-sequencing was done to confirm the presence of the fusion in the tumor. This is the first description of a pediatric patient with a ZNF532-NUTM1 fusion, yet the histology of this tumor is similar to that of adult cancers with ZNF-NUTM1 fusions and other NUTM1- fusion positive brain tumors reported in literature. Although rare, the distinct pathology and underlying molecular characteristics of these tumors separate them from other embryonal tumors. Therefore, the NUTM- rearrangement appears to define a novel subgroup of pediatric central nervous system embryonal tumors with rhabdoid/epithelioid features that may have a unique response to treatment. Screening for a NUTM1- rearrangement should be considered for all patients with unclassified central nervous system tumors with rhabdoid features to ensure accurate diagnosis so this can ultimately inform therapeutic management for these patients.

Surgery is the mainstay of treatment for meningioma, the most common primary intracranial tumor, but improvements in meningioma risk stratification are needed and indications for postoperative radiotherapy are controversial. Here we develop a targeted gene expression biomarker that predicts meningioma outcomes and radiotherapy responses. Using a discovery cohort of 173 meningiomas, we developed a 34-gene expression risk score and performed clinical and analytical validation of this biomarker on independent meningiomas from 12 institutions across 3 continents ( N = 1,856), including 103 meningiomas from a prospective clinical trial. The gene expression biomarker improved discrimination of outcomes compared with all other systems tested ( N = 9) in the clinical validation cohort for local recurrence (5-year area under the curve (AUC) 0.81) and overall survival (5-year AUC 0.80). The increase in AUC compared with the standard of care, World Health Organization 2021 grade, was 0.11 for local recurrence (95% confidence interval 0.07 to 0.17, P < 0.001). The gene expression biomarker identified meningiomas benefiting from postoperative radiotherapy (hazard ratio 0.54, 95% confidence interval 0.37 to 0.78, P = 0.0001) and suggested postoperative management could be refined for 29.8% of patients. In sum, our results identify a targeted gene expression biomarker that improves discrimination of meningioma outcomes, including prediction of postoperative radiotherapy responses.

Pediatric brain and spinal cancers remain the leading cause of cancer-related death in children. Advancements in clinical decision-support in pediatric neuro-oncology utilizing the wealth of radiology imaging data collected through standard care, however, has significantly lagged other domains. Such data is ripe for use with predictive analytics such as artificial intelligence (AI) methods, which require large datasets. To address this unmet need, we provide a multi-institutional, large-scale pediatric dataset of 23,101 multi-parametric MRI exams acquired through routine care for 1,526 brain tumor patients, as part of the Children's Brain Tumor Network. This includes longitudinal MRIs across various cancer diagnoses, with associated patient-level clinical information, digital pathology slides, as well as tissue genotype and omics data. To facilitate downstream analysis, treatment-naïve images for 370 subjects were processed and released through the NCI Childhood Cancer Data Initiative via the Cancer Data Service. Through ongoing efforts to continuously build these imaging repositories, our aim is to accelerate discovery and translational AI models with real-world data, to ultimately empower precision medicine for children.

Pediatric brain tumors are the leading cause of cancer-related death in children in the United States and contribute a disproportionate number of potential years of life lost compared to adult cancers. Moreover, survivors frequently suffer long-term side effects, including secondary cancers. The Children's Brain Tumor Network (CBTN) is a multi-institutional international clinical research consortium created to advance therapeutic development through the collection and rapid distribution of biospecimens and data via open-science research platforms for real-time access and use by the global research community. The CBTN's 32 member institutions utilize a shared regulatory governance architecture at the Children's Hospital of Philadelphia to accelerate and maximize the use of biospecimens and data. As of August 2022, CBTN has enrolled over 4700 subjects, over 1500 parents, and collected over 65,000 biospecimen aliquots for research. Additionally, over 80 preclinical models have been developed from collected tumors. Multi-omic data for over 1000 tumors and germline material are currently available with data generation for > 5000 samples underway. To our knowledge, CBTN provides the largest open-access pediatric brain tumor multi-omic dataset annotated with longitudinal clinical and outcome data, imaging, associated biospecimens, child-parent genomic pedigrees, and in vivo and in vitro preclinical models. Empowered by NIH-supported platforms such as the Kids First Data Resource and the Childhood Cancer Data Initiative, the CBTN continues to expand the resources needed for scientists to accelerate translational impact for improved outcomes and quality of life for children with brain and spinal cord tumors.

Pediatric brain and spinal cancers are collectively the leading disease-related cause of death in children; thus, we urgently need curative therapeutic strategies for these tumors. To accelerate such discoveries, the Children's Brain Tumor Network (CBTN) and Pacific Pediatric Neuro-Oncology Consortium (PNOC) created a systematic process for tumor biobanking, model generation, and sequencing with immediate access to harmonized data. We leverage these data to establish OpenPBTA, an open collaborative project with over 40 scalable analysis modules that genomically characterize 1,074 pediatric brain tumors. Transcriptomic classification reveals universal TP53 dysregulation in mismatch repair-deficient hypermutant high-grade gliomas and TP53 loss as a significant marker for poor overall survival in ependymomas and H3 K28-mutant diffuse midline gliomas. Already being actively applied to other pediatric cancers and PNOC molecular tumor board decision-making, OpenPBTA is an invaluable resource to the pediatric oncology community.