Pediatric Brain Tumors Research Articles

Recurrent choroid plexus carcinoma treated with CyberKnife radiosurgery: illustrative case.

Choroid plexus carcinomas (CPCs) are rare malignant brain tumors primarily affecting children younger than 2 years old. These tumors originate from the choroid plexus epithelium and are a subtype of choroid plexus tumors, which account for 1%-4% of pediatric brain tumors. Although CPCs often show a notably high recurrence rate after surgery, the standard treatment approach remains gross-total resection (GTR) of the tumor, given the lack of clinical data supporting the effectiveness of adjunct treatment options such as radiotherapy or chemotherapy. A 16-year-old female with a history of a recurrent cranial CPC resistant to surgery and radiotherapy was treated with CyberKnife stereotactic radiosurgery (SRS), following resection. The procedures successfully maintained local disease control for 41 months; however, there was a subsequent recurrence, ultimately leading to the death of the patient. CPC treatment remains challenging. SRS can be used as a viable adjunct to surgery, which remains the gold standard, although it can also be considered for nonsurgical candidates or when GTR cannot be achieved. Nevertheless, it is crucial to conduct additional research to explore diverse approaches for radiosurgery, including its role as the primary treatment modality versus its combination with surgery, radiotherapy, or chemotherapy. https://thejns.org/doi/10.3171/CASE23748.

Diagnosis of pediatric central nervous system tumors using methylation profiling of cfDNA from cerebrospinal fluid

Pediatric central nervous system tumors remain challenging to diagnose. Imaging approaches do not provide sufficient detail to discriminate between different tumor types, while the histopathological examination of tumor tissue shows high inter-observer variability. Recent studies have demonstrated the accurate classification of central nervous system tumors based on the DNA methylation profile of a tumor biopsy. However, a brain biopsy holds significant risk of bleeding and damaging the surrounding tissues. Liquid biopsy approaches analyzing circulating tumor DNA show high potential as an alternative and less invasive tool to study the DNA methylation pattern of tumors. Here, we explore the potential of classifying pediatric brain tumors based on methylation profiling of the circulating cell-free DNA (cfDNA) in cerebrospinal fluid (CSF). For this proof-of-concept study, we collected cerebrospinal fluid samples from 19 pediatric brain cancer patients via a ventricular drain placed for reasons of increased intracranial pressure. Analyses on the cfDNA showed high variability of cfDNA quantities across patients ranging from levels below the limit of quantification to 40 ng cfDNA per milliliter of CSF. Classification based on methylation profiling of cfDNA from CSF was correct for 7 out of 20 samples in our cohort. Accurate results were mostly observed in samples of high quality, more specifically those with limited high molecular weight DNA contamination. Interestingly, we show that centrifugation of the CSF prior to processing increases the fraction of fragmented cfDNA to high molecular weight DNA. In addition, classification was mostly correct for samples with high tumoral cfDNA fraction as estimated by computational deconvolution (> 40%). In summary, analysis of cfDNA in the CSF shows potential as a tool for diagnosing pediatric nervous system tumors especially in patients with high levels of tumoral cfDNA in the CSF. Further optimization of the collection procedure, experimental workflow and bioinformatic approach is required to also allow classification for patients with low tumoral fractions in the CSF.

Perioperative Outcomes Following Surgery for Pediatric Brain Tumors: Assessment of Eight-year Single-center Short-term Results

Perioperative Outcomes Following Surgery for Pediatric Brain Tumors: Assessment of Eight-year Single-center Short-term Results

Stepwise Transfer Learning for Expert-level Pediatric Brain Tumor MRI Segmentation in a Limited Data Scenario.

Purpose To develop, externally test, and evaluate clinical acceptability of a deep learning pediatric brain tumor segmentation model using stepwise transfer learning. Materials and Methods In this retrospective study, the authors leveraged two T2-weighted MRI datasets (May 2001 through December 2015) from a national brain tumor consortium (n = 184; median age, 7 years [range, 1-23 years]; 94 male patients) and a pediatric cancer center (n = 100; median age, 8 years [range, 1-19 years]; 47 male patients) to develop and evaluate deep learning neural networks for pediatric low-grade glioma segmentation using a stepwise transfer learning approach to maximize performance in a limited data scenario. The best model was externally tested on an independent test set and subjected to randomized blinded evaluation by three clinicians, wherein they assessed clinical acceptability of expert- and artificial intelligence (AI)-generated segmentations via 10-point Likert scales and Turing tests. Results The best AI model used in-domain stepwise transfer learning (median Dice score coefficient, 0.88 [IQR, 0.72-0.91] vs 0.812 [IQR, 0.56-0.89] for baseline model; P = .049). With external testing, the AI model yielded excellent accuracy using reference standards from three clinical experts (median Dice similarity coefficients: expert 1, 0.83 [IQR, 0.75-0.90]; expert 2, 0.81 [IQR, 0.70-0.89]; expert 3, 0.81 [IQR, 0.68-0.88]; mean accuracy, 0.82). For clinical benchmarking (n = 100 scans), experts rated AI-based segmentations higher on average compared with other experts (median Likert score, 9 [IQR, 7-9] vs 7 [IQR 7-9]) and rated more AI segmentations as clinically acceptable (80.2% vs 65.4%). Experts correctly predicted the origin of AI segmentations in an average of 26.0% of cases. Conclusion Stepwise transfer learning enabled expert-level automated pediatric brain tumor autosegmentation and volumetric measurement with a high level of clinical acceptability. Keywords: Stepwise Transfer Learning, Pediatric Brain Tumors, MRI Segmentation, Deep Learning Supplemental material is available for this article. © RSNA, 2024.

Intracerebellar administration of the chemokine Cxcl3 reduces the volume of medulloblastoma lesions at an advanced stage by promoting the migration and differentiation of preneoplastic precursor cells

AbstractThe prognosis for many pediatric brain tumors, including cerebellar medulloblastoma (MB), remains dismal but there is promise in new therapies. We have previously generated a mouse model developing spontaneous MB at high frequency, Ptch1+/−/Tis21−/−. In this model, reproducing human tumorigenesis, we identified the decline of the Cxcl3 chemokine in cerebellar granule cell precursors (GCPs) as responsible for a migration defect, which causes GCPs to stay longer in the proliferative area rather than differentiate and migrate internally, making them targets of transforming insults. We demonstrated that 4‐week Cxcl3 infusion in cerebella of 1‐month‐old mice, at the initial stage of MB formation, forces preneoplastic GCPs (pGCPs) to leave lesions and differentiate, with a complete suppression of MB development. In this study, we sought to verify the effect of 4‐week Cxcl3 treatment in 3‐month‐old Ptch1+/−/Tis21−/− mice, when MB lesions are at an advanced, irreversible stage. We found that Cxcl3 treatment reduces tumor volumes by sevenfold and stimulates the migration and differentiation of pGCPs from the lesion to the internal cerebellar layers. We also tested whether the pro‐migratory action of Cxcl3 favors metastases formation, by xenografting DAOY human MB cells in the cerebellum of immunosuppressed mice. We showed that DAOY cells express the Cxcl3 receptor, Cxcr2, and that Cxcl3 triggers their migration. However, Cxcl3 did not significantly affect the frequency of metastases or the growth of DAOY‐generated MBs. Finally, we mapped the expression of the Cxcr2 receptor in human MBs, by evaluating a well‐characterized series of 52 human MBs belonging to different MB molecular subgroups. We found that Cxcr2 was variably expressed in all MB subgroups, suggesting that Cxcl3 could be used for therapy of different MBs.

Longitudinal risk prediction for pediatric glioma with temporal deep learning.

Pediatric glioma recurrence can cause morbidity and mortality; however, recurrence pattern and severity are heterogeneous and challenging to predict with established clinical and genomic markers. Resultingly, almost all children undergo frequent, long-term, magnetic resonance (MR) brain surveillance regardless of individual recurrence risk. Deep learning analysis of longitudinal MR may be an effective approach for improving individualized recurrence prediction in gliomas and other cancers but has thus far been infeasible with current frameworks. Here, we propose a self-supervised, deep learning approach to longitudinal medical imaging analysis, temporal learning, that models the spatiotemporal information from a patient's current and prior brain MRs to predict future recurrence. We apply temporal learning to pediatric glioma surveillance imaging for 715 patients (3,994 scans) from four distinct clinical settings. We find that longitudinal imaging analysis with temporal learning improves recurrence prediction performance by up to 41% compared to traditional approaches, with improvements in performance in both low- and high-grade glioma. We find that recurrence prediction accuracy increases incrementally with the number of historical scans available per patient. Temporal deep learning may enable point-of-care decision-support for pediatric brain tumors and be adaptable more broadly to patients with other cancers and chronic diseases undergoing surveillance imaging.

Synergy of retinoic acid and BH3 mimetics in MYC(N)-driven embryonal nervous system tumours

BackgroundCertain paediatric nervous system malignancies have dismal prognoses. Retinoic acid (RA) is used in neuroblastoma treatment, and preclinical data indicate potential benefit in selected paediatric brain tumour entities. However, limited single-agent efficacy necessitates combination treatment approaches.MethodsWe performed drug sensitivity profiling of 76 clinically relevant drugs in combination with RA in 16 models (including patient-derived tumouroids) of the most common paediatric nervous system tumours. Drug responses were assessed by viability assays, high-content imaging, and apoptosis assays and RA relevant pathways by RNAseq from treated models and patient samples obtained through the precision oncology programme INFORM (n = 2288). Immunoprecipitation detected BCL-2 family interactions, and zebrafish embryo xenografts were used for in vivo efficacy testing.ResultsGroup 3 medulloblastoma (MBG3) and neuroblastoma models were highly sensitive to RA treatment. RA induced differentiation and regulated apoptotic genes. RNAseq analysis revealed high expression of BCL2L1 in MBG3 and BCL2 in neuroblastomas. Co-treatments with RA and BCL-2/XL inhibitor navitoclax synergistically decreased viability at clinically achievable concentrations. The combination of RA with navitoclax disrupted the binding of BIM to BCL-XL in MBG3 and to BCL-2 in neuroblastoma, inducing apoptosis in vitro and in vivo.ConclusionsRA treatment primes MBG3 and NB cells for apoptosis, triggered by navitoclax cotreatment.

Advanced MRI imaging techniques in pediatric brain tumors.

There is a diverse array of pediatric brain tumors with considerable associated morbidity. Like adult brain tumors, MRI serves as the primary imaging modality for pediatric brain tumors. In addition to standard sequences, more advanced MRI techniques can enhance the precision of diagnosis and assist in prognostication, and treatment planning. This paper discusses these various advanced techniques categorizing them into those that assist in identifying tissue characteristics, and those that evaluate the functional impact of tumors to aid in treatment planning.

METB-12. GIFT FROM A CHILD POSTMORTEM SPECIMEN DATASET EXTENSION OF THE PEDIATRIC BRAIN TUMOR ATLAS EMPOWERS PEDIATRIC BRAIN TUMOR RESEARCH

Abstract BACKGROUND Pediatric brain and spinal cord tumors are the leading cause of cancer-related mortality in children. An incomplete understanding of brain tumor biology and associated limited access to high-quality biological samples for research are the main factors driving the lack of clinical therapeutic development for pediatric brain tumors that recur or progress. Post-mortem tissue donation provides an unprecedented resource for addressing some of these limitations. METHODS The Gift from a Child (GFAC) program by the Swifty Foundation has a unique mission to increase post-mortem pediatric brain tissue donations through advocacy as well as the education of clinicians and families. Through GFAC’s strategic collaboration with the Children’s Brain Tumor Network (CBTN), CBTN has leveraged postmortem tissue to expand the Pediatric Brain Tumor Atlas (PBTA), a cross-histology multi-omics atlas resource. As part of the effort CBTN has sequenced and released data for over 350 post-mortem pediatric brain tumor specimens including multiple brain region sampling cases with specimen and sequencing quality metrics. RESULTS Here we present an assessment of postmortem samples and available multi-omic data on postmortem samples within the PBTA dataset. Data have been harmonized and released with no publication embargo. To access data, researchers can utilize existing open source data resources and platforms including PedCbioPortal and OpenPedCan to: (1) Identify tumor spatial and temporal specific alterations (2) Establish tumor evolution trajectory leading to therapeutic resistance and tumor progression; (3) Understand tumor heterogeneity longitudinally across multiple ‘omics layers; and (4) Identify and request specimens and derived tumor models. CONCLUSIONS Together, we present the largest deeply characterized cohort of postmortem pediatric brain tumor samples as powerful expansion of the PBTA cohort of >3,000 pediatric brain tumors. CBTN’s open-science model supported by the GFAC mission highlights the value and utility of autopsy-based specimen collection on behalf of improving outcomes for children with brain tumors.

TRLS-05. A PILOT STUDY TO ASSESS THE SAFETY, FEASIBILITY, AND PRELIMINARY EFFICACY OF A NEOEPITOPE-BASED PERSONALIZED DNA VACCINE APPROACH IN PEDIATRIC PATIENTS WITH RECURRENT BRAIN TUMORS

Abstract BACKGROUND Pediatric brain tumors present a heterogeneous group of neoplasms with limited treatment options, especially at relapse. Hence, innovative therapeutic strategies are imperative. Immunotherapy, specifically immunogenomics, utilizing personalized vaccines based on tumor-specific neoantigens, has emerged as a promising option in other tumors. However, the feasibility of this approach in pediatric brain tumors remain largely unexplored. METHODS This single institution feasibility study focuses on sequencing analyses of pediatric brain tumors to identify mutant tumor-specific antigens. The study employs tumor/normal exome sequencing and cDNA-capture sequencing to identify and confirm mutant antigens, respectively. An epitope prediction algorithm prioritizes these antigens with subsequent confirmation of binding to HLA class I molecules. The neoantigen DNA vaccine strategy, utilizing a polyepitope DNA vaccine, is designed to target up to 20 prioritized antigens. The TDS-IM v2.0 device facilitates the administration of the vaccine. The primary objective of the study is to determine the feasibility of adjuvant personalized neoantigen DNA vaccine administration in patients with recurrent or refractory pediatric brain tumors. RESULTS We anticipate the identification of actionable neoantigens in pediatric brain tumors to support the potential efficacy of personalized DNA vaccines. The proposed sequencing strategies, epitope prediction algorithm, and in vitrobinding studies aim to establish a comprehensive methodology for neoantigen identification and prioritization. During the meeting, we will present the study background, rationale, detailed methodology, and design to inform the brain tumor community of this study. CONCLUSION This feasibility study is poised to provide essential insights into the development of personalized neoantigen DNA vaccines for recurrent or refractory pediatric brain tumors and aims to demonstrate safety, feasibility, and potential efficacy in targeting mutant tumor-specific antigens. The findings from this study will lay the groundwork for future clinical trials, evaluating the impact of personalized immunotherapy on progression-free and overall survival rates in this challenging patient population.

NURS-13. NEUROCOGNITIVE SIDE EFFECTS OF PEDIATRIC BRAIN TUMORS: A CONTINUING CHALLENGE

Abstract BACKGROUND Pediatric brain tumors pose a considerable challenge in clinical oncology, necessitating multimodal treatment approaches. Many of these have the potential to impact cognition on vulnerable, young brains. While advancements in therapies have improved survival rates, neurocognitive outcomes continue to be one of the most challenging late effects that affect quality of life for pediatric brain tumor survivors. METHODS We conducted a literature review to identify 1) current treatment approaches for pediatric brain tumors, 2) the neurocognitive effects that survivors of pediatric brain tumors experience, and 3) appropriate interventions that can be implemented to mitigate those neurocognitive effects. RESULTS Novel chemotherapeutic agents, such as molecularly targeted therapies, are increasingly implemented in a personalized approach to treatment. New approaches to radiation therapy, particularly proton therapy, have shown promise in minimizing cognitive decline compared to traditional photon therapy. Advances in neuroimaging techniques have enabled a more detailed understanding of structural and functional brain changes associated with treatment. While these newer treatment modalities are promising, their long-term side effects are mostly unknown and bear close monitoring over time. Because neurocognitive side effects continue to underscore the impact of pediatric brain tumor treatments, recent studies often specifically evaluate the cognitive side effects as well as attempt to personalize treatments to reduce cognitive damage. CONCLUSIONS Recent research findings reinforce the enduring concern of neurocognitive side effects in pediatric brain tumor survivors. The integration of advanced therapeutic modalities and targeted supportive care interventions may hold the key to optimizing treatment outcomes while minimizing cognitive morbidity. Continued research efforts are essential for refining treatment protocols and developing personalized strategies to safeguard neurocognitive function in this vulnerable population. Additionally, studies exploring the role of supportive care interventions, such as cognitive rehabilitation and neuroprotective strategies, demonstrate potential avenues for mitigating cognitive sequelae but require ongoing research.

PATH-01. ACCURATE AND RAPID PAEDIATRIC BRAIN TUMOR CLASSIFICATION (PBT) BY METHYLATION PROFILING USING NOVEL NATIVE REAL TIME OXFORD NANOPORE TECHNOLOGY SEQUENCING TECHNOLOGY

Abstract BACKGROUND Pediatric brain tumors (PBTs) pose a significant challenge being the leading cause of cancer related mortality in children. The existing classification process is time-consuming and fails to capture the heterogeneity of PBTs. Urgent advancements in diagnostic and therapeutic approaches are needed. The WHO classification 5th edition for CNS tumors introduced DNA methylation analysis into the diagnostic process, especially for difficult-to-diagnose cases. However, the currently available DNA methylation array-based methods are laborious, costly, &require large amounts of DNA METHODS Nanopore methylation analysis is rapid, accurate, and inexpensive & requires minimal tissue. We applied this technology on 24 PBT samples that were classified into ten molecular subgroups. RESULTS Our results were compatible with those obtained through Heidelberg methylation analysis, standard histopathological examination, and molecular tests and were in concordance with the final neuro-pathological diagnosis. Moreover, for five prospective cases, that would have challenged standard methods, Nanopore yielded same-day results, guiding additional tests and providing a significant diagnostic advantage. In one case, a 2.2-year-old male, with a large left parieto-temporal tumor and a suprasellar lesioninitially treated elsewhere with upfront chemotherapy without biopsy, developed clinical deterioration. We resected the temporal lesion and frozen tissue diagnosis suggested low-grade glioma. However, same day Nanopore sequencing analysis indicated a high score for ‘Meningioma’. Final pathology examination 10 days later confirmed ‘‘Atypical meningioma, WHO grade 2” – an extremely rare diagnosis in this age group. Visual deterioration prompted immediate resection of the second lesion before final pathological confirmation. Thus, early Nanopore classification played a vital role in diagnosis and management. CONCLUSIONS Our preliminary results underscore the potential of Nanopore potential for accurate and rapid PBT classification from small brain biopsies, with DNA input as low as 100 nanograms. This cutting-edge technology promises to substantially reduce time to diagnosis, shaping future neurosurgical strategies for individualized PBT patient management.

LMIC-22. TOWARD A COMPREHENSIVE PEDIATRIC BRAIN TUMOR REGISTRY: ESTABLISHING FUNDAMENTAL VALUE IN INDONESIA TERTIARY HOSPITAL

Abstract BACKGROUND Systematic documentation and research on pediatric brain tumor (PBT) have been underreported in Indonesia. Precise and readily available epidemiological data hold significant value in enhancing the PBT service of any center, each with its own distinctive characteristics. We aim to evaluate our PBT registry and service after Cipto Mangunkusumo National General Hospital utilized the St. Jude (SJ) Cares Registry program. METHODS A retrospective observational longitudinal study, carried out at Cipto Mangunkusumo National General Hospital, utilizing primary registry data encompassing patients’ profiles, diagnoses, and follow-up issues from January 2022 to December 2023, was performed. An evaluative review was then carried out to delineate our center’s unique problems and solutions to improve the overall PBT health services. RESULTS A total of 103 patients participated, dominated by females (55.3%), with a median age of 8 (IQR 4-12). The most identified diagnoses were gliomas (48.6%), germ cells (16.5%), and medulloblastomas (8.7%), with high-grade gliomas contributing to the most death (48.4%). The main symptoms contributing to the most extended diagnosis delay (from onset to diagnosis) were puberty issues, motoric paresis, vertigo, macrocephaly, proptosis, disequilibrium, and headache. Some critical findings from this registry evaluation were the mapping of patients’ key clinical symptoms and most diagnoses to be anticipated, factors related to diagnosis delay, and the numerous ineffective yet revisable health service systems that led to incomplete patient data and loss of follow-up. These led to our team’s effort to implement more effective multidiscipline communication (through regular synchronous and asynchronous meetings), orbit the pediatrician to become the St. Jude virtual fellow and recruit more trained data registry specialists. CONCLUSION In conclusion, as each center has unique problems in its own PBT health services, it is essential to have accurate registry data to be the fundamental value and starting point for comprehensively delineating and improving PBT service.

IMG-27. ASSESSMENT OF VARIABILITY OF PEDIATRIC BRAIN TUMOR IMAGING PROTOCOLS ACROSS INSTITUTIONS: ARE WE FOLLOWING RECOMMENDATIONS?

Abstract BACKGROUND Evaluating pediatric brain tumors requires imaging children with tailored MRI protocols. Considerable variation in pediatric brain tumor imaging protocols exist across institutions, which can cause inaccuracies in staging. Although recently consensus guidelines for pediatric brain tumor imaging protocols have been established, adherence to these guidelines across institutions is unknown. Institutions may perceive guidelines as applicable for research purposes rather than routine clinical practice. We aim to explore variability in pediatric brain tumor imaging protocols across institutions and determine the factors influencing guideline divergence. METHODS AND METHODOLOGY Faculty at institutions routinely imaging pediatric patients with brain tumors were invited to share brain tumor MRI protocols and complete a structured survey. The survey included multiple choice and open-ended queries concerning practice type, the presence of an institutional imaging protocol for pediatric brain tumors and if the protocol was based on specific consensus recommendations. We assessed if protocols included the 7 minimum recommended MRI sequences by the Children’s Oncology Group (COG) guidelines, including slice thickness and gap. RESULTS Twenty emails were sent and responses were received from 12 institutions (the data collection is still ongoing). 2 institutions did not have dedicated protocols for pediatric brain tumors. On average, institutions had 5.7 out of the 7 minimum COG-recommended sequences. All 10 institutions included 3D T1 IR-GRE/TSE, DWI or DTI, and SWI sequences in their protocols. 9 (90%) included post-contrast 3D T1 IR-GRE/TSE, 7 (70%) included T2 TSE/FSE, 7 (70%) included either 3D T2 FLAIR or T2 FLAIR TSE/FSE, and 4 (40%) included T1/TSE/FSE. Across all sequences in all protocols, adherence to recommended imaging parameters was 87% for plane, 71% for slice thickness, and 85% for gap. CONCLUSION Significant variability in pediatric brain tumor imaging protocols exists across institutions Standardizing imaging protocols through collaboration is vital in ensuring uniformity in care.

QOL-45. SOCIAL DETERMINANTS OF HEALTH PREDICT NEUROPSYCHOLOGICAL OUTCOMES IN PEDIATRIC BRAIN TUMOR SURVIVORS

Abstract BACKGROUND Pediatric brain tumors and their treatment impact cognition including intellectual functioning (IQ), attention, working memory, and processing speed. Few studies have examined the role of social determinants of health (SDoH) on cognition in pediatric brain tumors. To date, studies have primarily focused on family-related SDoH factors such as insurance status or parental education as predictors of cognition. To our knowledge, no study has examined multiple indicators of SDoH to determine which family-based and community-based predict cognition. METHODS Participants included 151 pediatric brain tumor patients (M diagnosis age=8.82) seen for a clinical neuropsychological evaluation (M evaluation age=13.71). IQ, brief attention (WISC/DAS-II Digits Forward), working memory (WISC/DAS-II Digits Backwards), and processing speed (WISC Coding) were obtained from age-appropriate measures (WISC>6 years, DAS-II<6 years). Family-based SDoH indicators include insurance type (public, private) and maternal education (<high school degree, some college, ≥college degree). Community-based SDoH include the Area Deprivation Index (ADI) and Childhood Opportunity Index (COI). Multiple regressions examined variance in IQ, attention, working memory, and processing speed accounted for by the SDoH measures, after controlling for treatment exposures using the Neurological Predictor Scale. RESULTS Insurance accounted for 14.9% of the IQ variance [β=-.316, t(151)=-4.18; p<.001]; COI accounted for 18.3% of the IQ variance [β=.202, t(151)=2.70; p=.008]. Insurance accounted for 12% of the variance in attention [β=-.324, t(152)=-4.22; p<.001], and 17.5% of the variance in processing speed [F(2,134)=15.399, p<.001]. In the working memory model, insurance [β=-.179, t(148)=-2.19; p=.03] and ADI [β=-.171, t(148)=-2.11; p=.04], accounted for 5.3% and 7.5% of the variance, respectively. CONCLUSIONS Findings highlight the important contribution of both family and community factors on neuropsychological outcomes in pediatric brain tumors. Nuances of the data will be discussed as they relate to clinical care and research.

BIOM-14. UTILITY OF MIRNA-BASED LIQUID BIOPSY AND RADIOGRAPHIC IMAGING IN PEDIATRIC BRAIN TUMOR PATIENTS

Abstract BACKGROUND MRI is the current gold standard imaging technique for diagnostic evaluation and monitoring of pediatric CNS tumors; however, MRI measures can only provide inference into tumor biology and molecular stratification. miRNAs are an abundant and stable nucleic acid found circulating in blood and cerebrospinal fluid (CSF) and can be utilized as a tumor biomarker. METHODS We hypothesized that correlating miRNA biomarkers with radiological tumor measurements may provide improved diagnostic and monitoring for patients with pediatric brain tumors. Using a cohort of 54 pediatric brain tumors including low grade glioma, ependymoma, germ cell tumor, medulloblastoma, atypical teratoid rhabdoid tumor and high-grade glioma we attempted to combine MRI findings and circulating miRNA data. The miRNA expression was profiled in 33 CSF and 52 plasma samples using the HTG EdgeSeq platform. Clinically acquired, multi-parametric MRI scans at time-points close to liquid biopsy collection were collected retrospectively and used to generate volumetric tumor segmentations. Machine learning methods were implemented to evaluate combinatory features. RESULTS We identified unique miRNA targets that significantly correlated with MRI features, clinical findings, and patient outcomes. In both CSF and plasma, miRNA expression was found to correlate with diagnosis and clinical features including tumor grade and disease burden (p < 0.05). In CSF, miRNA expression was correlated with MRI features including cystic core presence, edema, leptomeningeal disease and tumor location (p <0.05). In plasma, differences in miRNA expression were related to MRI measurements including cystic core volume, location, and leptomeningeal disease (p < 0.05). Combination of miRNA targets for plasma or CSF with imaging-based features significantly improved histology specific multimodal diagnosis predictions. CONCLUSIONS These results demonstrate the potential utility of miRNAs as a pediatric brain tumor biomarker which when combined with imaging features can improve minimally and non-invasive diagnostics and the subsequent management of pediatric brain tumor patients.

BIOM-13. THE MIR-17/92 CO-EXPRESSED NETWORK IS ENRICHED IN AGGRESSIVE PEDIATRIC BRAIN TUMORS

Abstract BACKGROUND Over the past two decades, the understanding of miRNA biology has drastically increased as miRNAs have been found to pervade most aspects of molecular biology–from cellular growth to apoptosis. Nevertheless, there has been little understanding of the role of miRNAs in pediatric brain tumors. In this study, we sought to correlate miRNA expression with pediatric brain tumor histologies. METHODS Weighted gene co-expression network analysis (WGCNA) was performed to determine co-expressed miRNA networks that correlated with distinct brain tumor histologies. Our study cohort consisted of miRNA-sequencing of 262 pediatric brain tumor histologies consisting of Atypical Teratoid/Rhabdoid tumors, Craniopharyngioma, Ependymomas, Ganglioglioma, Low-grade astrocytic tumors, High-grade astrocytic tumors, and Medulloblastoma. We utilized associated multi-omics data from the Open Pediatric Brain Tumor Atlas to validate the results. RESULTS WGCNA analysis revealed a distinct miRNA network consisting of 32 miRNAs with miR-17-5p as the hub miRNA that was markedly upregulated in the aggressive brain tumor group (p<0.001). Interestingly, the majority of the miRNA network consisted of the miR-17/92 family of miRNAs, which are known for their oncogenic role in various cancers. To determine the transcriptional regulatory mechanism of miR-17/92 miRNAs, we first looked at sample-matched RNA-sequencing data. The gene encoding for the miR-17/92 miRNAs, MIR17HG, was significantly overexpressed (p<0.001). Further upstream, we observed that E2F1/2/3, known transcriptional regulators of MIR17HG, gene and protein expressions were significantly overexpressed (p<0.01). Sample-matched phospho-proteomics data indicated the E2F regulator, RB1, being hyperphosphorylated–additionally supporting the E2F activity in these samples. CONCLUSION These findings reveal a network of oncogenic miRNAs consisting of the miR-17/92 family that are distinctly overexpressed in aggressive pediatric brain tumors. Moreover, we suggest that the E2F-RB1 axis is the upstream regulator of the miR-17/92 family of miRNAs.

QOL-43. COMPARISON OF SOCIAL DETERMINANTS OF HEALTH MEASURES ON IQ AND ACADEMIC OUTCOMES IN PEDIATRIC BRAIN TUMORS

Abstract BACKGROUND Treatment for pediatric brain tumors impacts IQ and academic achievement; fewer studies have examined the role of social determinants of health (SDoH). To date, studies have primarily focused on family-based SDoH such as insurance type or parental education as predictors of cognition. Limited studies have examined community factors, though our work highlighted the role of education quality on IQ and academics in pediatric brain tumors. To our knowledge, no study has examined the predictive value of family and community-based SDoH. METHODS Participants included 151 pediatric brain tumor patients (M age at diagnosis=8.82) seen for a clinical neuropsychological evaluation (M age at evaluation=13.71). IQ was obtained from age-appropriate intelligence measures (WISC>6 years, DAS-II<6 years); untimed reading and math calculation were examined via WIAT/KTEA/WJ subtests. Family-based SDoH included insurance type (public, private) and maternal education (<high school degree, some college, >college degree). Community-based SDoH included the Area Deprivation Index (ADI) and Education, Health-Environment, and Social-Economic indices from the Childhood Opportunity Index (COI). Multiple regressions examined variance in IQ, reading, and math accounted for by each of the SDoH measures, after controlling for treatment exposures using the Neurological Predictor Scale (NPS). RESULTS Insurance [β=-.302, t(151)=-4.00; p<001] and Education [β=.235, t(151)=3.14; p=.002] accounted for 14.9% and 19.7% of the IQ variance, respectively. Education also accounted for 12.8% of the reading variance (β=.304, t(109)=3.40; p<.001). Both the Education [β=.570, t(107)=3.41; p<.001] and Social-Economic [β=-.381, t(107)=-2.28; p=.03] indices accounted for 7.7% and 11.3% of the math calculation variance, respectively. CONCLUSIONS Community, particularly those related to education and social & economic resources, and family factors (e.g., insurance status) were associated with IQ and academic performance. Findings indicate the importance of investigating both family and community factors that may contribute to outcomes in pediatric brain tumors.

IMG-08. SYNTHESIZING MISSING MRI SEQUENCES IN PEDIATRIC BRAIN TUMORS USING GENERATIVE ADVERSARIAL NETWORKS; TOWARDS IMPROVED VOLUMETRIC TUMOR ASSESSMENT

Abstract BACKGROUND Standard MRI sequences, such as pre- and post-contrast T1w, T2w, and FLAIR images, are essential for optimizing segmentation of tumor subregions and evaluating treatment responses in pediatric brain tumors (PBTs). However, MRI sets are often incomplete due to imaging artifacts or inconsistent acquisition protocols across various centers. Generative Adversarial Networks (GANs) have been effectively utilized to generate missing MRI sequences for adult brain tumors. This study applies image-to-image translation models using GANs to synthesize missing FLAIR images from T2w images in PBTs. METHODS This retrospective study developed two GAN models, pix2pix in both 2D and 3D, trained and validated on T2w and FLAIR image pairs from 79 and 19 patients, respectively, with pediatric-type diffuse high-grade gliomas (diffuse midline glioma (DMG) including diffuse intrinsic pontine glioma (DIPG)), collected from the Children’s Brain Tumor Network (CBTN). The 2D pix2pix model processes each T2w MRI volume slice-by-slice, generating corresponding FLAIR slices to reconstruct the complete image volume. The 3D pix2pix model allows translation of 3D FLAIR volumes directly from T2w volumes without the need for individual slice processing and reconstruction. The quality of the generated FLAIR volumes was evaluated using Structural Similarity Index (SSI; best closer to 1) and Mean Squared Error (MSE; best near 0) on the validation set. RESULTS The 2D and 3D models achieved robust performance with median SSI, MSE of 0.88, 0.004, and 0.92, 0.002, respectively. CONCLUSIONS The GAN models developed in this study effectively generate missing FLAIR MRI volumes from corresponding T2w images in PBTs. The 3D model, outperforming 2D, speeds the overall processing pipeline by eliminating volume slicing and reconstruction. Future work includes assessing the impact of these synthesized images on the accuracy of our pretrained autosegmentation models in differentiating tumor subregions and measuring tumor volumes in longitudinal MRIs.

MODL-08. PATIENT-DERIVED ORGANOIDS RECAPITULATE THE MOLECULAR LANDSCAPE OF PEDIATRIC BRAIN TUMORS

Abstract BACKGROUND Pediatric brain tumors (PBT) are the leading cause of non-accidental death in pediatric age. These tumors are rare and lack adequate experimental models capable of accurately capturing their complex molecular landscape. METHODS AND RESULTS Our team has established specific protocols for the generation and expansion of ex-vivo patient-derived organoids (PDO) from fresh surgical material of a variety of PBT, within a clinically relevant timeframe. These include pilocytic astrocytomas, a pleomorphic xanthoastrocytoma, a rosette-forming glioneuronal tumor, a supratentorial ependymoma, diffuse high-grade gliomas, a medulloblastoma, an atypical teratoid rhabdoid tumor, and a meningioma. The PDO cultures were set within 7-15 days, with organoids reaching 200-800 μm in diameter. Immunofluorescence analysis using confocal high-content microscopy imaging revealed that PDO kept the protein markers typically found in the corresponding primary tumors. Likewise, at a genomic level, PDO recapitulated the molecular landscape of corresponding primary tumors, as denoted by the maintenance of NF1, PIK3CA, and FGFR1mutations (rosette-forming glioneuronal tumor), KIAA1549::BRAF fusions (pilocytic astrocytomas), ZFTA::RELA fusion(supratentorial ependymoma) or gene amplifications, such as KRAS, CDK4, MDM2, GLI1, PTPN11 and PI3KCA. Additionally, PDO exhibited minimal genetic drift after over one month in culture. In three PBT cases from a medulloblastoma, an atypical teratoid rhabdoid tumor, and a meningioma, where no molecular alterations were detected using a comprehensive NGS panel, we are running DNA methylation arrays and copy number variations. CONCLUSIONS Our results underscore the potential of PDO as a robust ex-vivo experimental model. The generated PDO cultures can be rapidly established and retain key molecular features of corresponding primary tumors. This preclinical model presents versatile applications, serving as a valuable molecular tool for precision medicine approaches in PBT patients, the study of PBT biology, and the acceleration of drug development processes within the context of PBT.