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MR imaging is central to the assessment of tumor burden and changes over time in neuro-oncology. Several response assessment guidelines have been set forth by the Response Assessment in Pediatric Neuro-Oncology (RAPNO) working groups in different tumor histologies; however, the visual delineation of tumor components using MRIs is not always straightforward, and complexities not currently addressed by these criteria can introduce inter- and intra-observer variability in manual assessments. Differentiation of non-enhancing tumors from peritumoral edema, mild enhancement from absence of enhancement, and various cystic components can be challenging; particularly given a lack of sufficient and uniform imaging protocols in clinical practice. Automated tumor segmentation with artificial intelligence (AI) may be able to provide more objective delineations, but rely on accurate and consistent training data created manually (ground truth). Herein, this paper reviews existing challenges and potential solutions to identifying and defining subregions of pediatric brain tumors (PBTs) that are not explicitly addressed by current guidelines. The goal is to assert the importance of defining and adopting criteria for addressing these challenges, as it will be critical to achieving standardized tumor measurements and reproducible response assessment in PBTs, ultimately leading to more precise outcome metrics and accurate comparisons among clinical studies., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Pediatric brain cancer is the leading cause of disease-related mortality in children, and many aggressive tumors still lack effective treatment strategies. Despite extensive studies characterizing these tumor genomes, alternative transcriptional splicing patterns remain underexplored. Here, we systematically characterized aberrant alternative splicing across pediatric brain tumors, identifying pediatric high-grade gliomas (HGGs) among the most heterogeneous. Through integration with UniProt Knowledgebase annotations, we identified 12,145 splice events in 5,424 genes, leading to functional changes in protein activation, folding, and localization. We discovered that the master splicing factor and cell-cycle modulator, CDC-like kinase 1 ( CLK1 ), is aberrantly spliced in HGGs to include exon 4, resulting in a gain of two phosphorylation sites and subsequent activation of CLK1. Inhibition of CLK1 with Cirtuvivint in the pediatric HGG KNS-42 cell line significantly decreased both cell viability and proliferation in a dose-dependent manner. Morpholino-mediated depletion of CLK1 exon 4 splicing reduced RNA expression, protein abundance, and cell viability. Notably, KNS-42 cells treated with the CLK1 exon 4 morpholino demonstrated differential expression 78 genes and differential splicing with loss or gain of a functional site in 193 genes annotated as oncogene or tumor suppressor genes (TSGs). These genes were enriched for cancer-associated pathways, with 20 identified as significant gene dependencies in pediatric HGGs. Our findings highlight a dependency of pediatric HGGs on CLK1 and its roles contributing to tumor splicing heterogeneity through transcriptional dysregulation of splicing factors and transcriptional modulation of oncogenes. Overall, aberrant splicing in HGGs and other pediatric brain tumors represents a potentially targetable oncogenic pathway contributing to tumor growth and maintenance., Competing Interests: Conflicts of Interest The authors declare no conflicts of interest.

The availability of data from profiling of cancer patients with multiomics is rapidly increasing. However, integrative analysis of such data for personalized target identification is not trivial. Multiomics2Targets is a platform that enables users to upload transcriptomics, proteomics, and phosphoproteomics data matrices collected from the same cohort of cancer patients. After uploading the data, Multiomics2Targets produces a report that resembles a research publication. The uploaded matrices are processed, analyzed, and visualized using the tools Enrichr, KEA3, ChEA3, Expression2Kinases, and TargetRanger to identify and prioritize proteins, genes, and transcripts as potential targets. Figures and tables, as well as descriptions of the methods and results, are automatically generated. Reports include an abstract, introduction, methods, results, discussion, conclusions, and references and are exportable as citable PDFs and Jupyter Notebooks. Multiomics2Targets is applied to analyze version 3 of the Clinical Proteomic Tumor Analysis Consortium (CPTAC3) pan-cancer cohort, identifying potential targets for each CPTAC3 cancer subtype. Multiomics2Targets is available from https://multiomics2targets.maayanlab.cloud/., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Background: Patients with sinonasal malignancy (SNM) present with significant sinonasal quality of life (QOL) impairment. Global sinonasal QOL as measured by the 22-item Sinonasal Outcomes Test (SNOT-22) has been shown to improve with treatment. This study aims to characterize SNOT-22 subdomain outcomes in SNM., Methods: Patients diagnosed with SNM were prospectively enrolled in a multi-center patient registry. SNOT-22 scores were collected at the time of diagnosis and through the post-treatment period for up to 5 years. Multivariable regression analysis was used to identify drivers of variation in SNOT-22 subdomains., Results: Note that 234 patients were reviewed, with a mean follow-up of 22 months (3 months-64 months). Rhinologic, psychological, and sleep subdomains significantly improved versus baseline (all p < 0.05). Subanalysis of 40 patients with follow-up at all timepoints showed statistically significant improvement in rhinologic, extra-nasal, psychological, and sleep subdomains, with minimal clinically important difference met between 2 and 5 years in sleep and psychological subdomains. Adjuvant chemoradiation was associated with worse outcomes in rhinologic (adjusted odds ratio (5.22 [1.69-8.66])), extra-nasal (2.21 [0.22-4.17]) and ear/facial (5.53 [2.10-8.91]) subdomains. Pterygopalatine fossa involvement was associated with worse outcomes in rhinologic (3.22 [0.54-5.93]) and ear/facial (2.97 [0.32-5.65]) subdomains. Positive margins (5.74 [2.17-9.29]) and surgical approach-combined versus endoscopic (3.41 [0.78-6.05])-were associated with worse psychological outcomes. Adjuvant radiation (2.28 [0.18-4.40]) was associated with worse sleep outcomes., Conclusions: Sinonasal QOL improvements associated with treatment of SNM are driven by rhinologic, extra-nasal, psychological, and sleep subdomains., (© 2024 ARS‐AAOA, LLC.)

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 extend the OpenPBTA to create the Open Pediatric Cancer (OpenPedCan) Project, a harmonized open-source multi-omic dataset from 6,112 pediatric cancer patients with 7,096 tumor events across more than 100 histologies. Combined with RNA-Seq from the Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA), OpenPedCan contains nearly 48,000 total biospecimens (24,002 tumor and 23,893 normal specimens)., Findings: We utilized Gabriella Miller Kids First (GMKF) workflows to harmonize WGS, WXS, RNA-seq, and Targeted Sequencing datasets to include somatic SNVs, InDels, CNVs, SVs, RNA expression, fusions, and splice variants. We integrated summarized CPTAC whole cell proteomics and phospho-proteomics data, miRNA-Seq data, and have developed a methylation array harmonization workflow to include m-values, beta-vales, 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 NCI's pediatric Molecular Targets Platform. Notably, we have expanded PBTA molecular subtyping to include methylation information to align with the WHO 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., Competing Interests: Declarations of Interest The authors declare no conflicts.

Although genomic anomalies in glioblastoma (GBM) have been well studied for over a decade, its 5-year survival rate remains lower than 5%. We seek to expand the molecular landscape of high-grade glioma, composed of IDH-wildtype GBM and IDH-mutant grade 4 astrocytoma, by integrating proteomic, metabolomic, lipidomic, and post-translational modifications (PTMs) with genomic and transcriptomic measurements to uncover multi-scale regulatory interactions governing tumor development and evolution. Applying 14 proteogenomic and metabolomic platforms to 228 tumors (212 GBM and 16 grade 4 IDH-mutant astrocytoma), including 28 at recurrence, plus 18 normal brain samples and 14 brain metastases as comparators, reveals heterogeneous upstream alterations converging on common downstream events at the proteomic and metabolomic levels and changes in protein-protein interactions and glycosylation site occupancy at recurrence. Recurrent genetic alterations and phosphorylation events on PTPN11 map to important regulatory domains in three dimensions, suggesting a central role for PTPN11 signaling across high-grade gliomas., Competing Interests: Declaration of interests T.M.Y. is a co-founder, stockholder, and member of the board of directors of DESTROKE, Inc., an early stage start-up developing mobile technology for automated clinical stroke detection. J.L.J. has received consulting fees from Scorpion Therapeutics and Volastra Therapeutics. L.C.C. is a founder and member of the board of directors of Agios Pharmaceuticals and is a founder of Petra Pharmaceuticals. L.C.C. is an inventor on patents (pending) for Combination Therapy for PI3K-associated Disease or Disorder, and The Identification of Therapeutic Interventions to Improve Response to PI3K Inhibitors for Cancer Treatment. L.C.C. is a co-founder and shareholder in Faeth Therapeutics. P.W. is a statistical consultant for Sema4. M.G.C. receives research support from Merck, Orbus Therapeutics, and NeoimmuneTech Inc, and royalties from UpToDate., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

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.

Purpose: Sinonasal malignancies (SNMs) adversely impact patients' quality of life (QOL) and are frequently identified at an advanced stage. Because these tumors are rare, there are few studies that examine the specific QOL areas that are impacted. This knowledge would help improve the care of these patients., Methods: In this prospective, multi-institutional study, 273 patients with SNMs who underwent definitive treatment with curative intent were evaluated. We used the University of Washington Quality of Life (UWQOL) instrument over 5 years from diagnosis to identify demographic, treatment, and disease-related factors that influence each of the 12 UWQOL subdomains from baseline to 5 -years post-treatment., Results: Multivariate models found endoscopic resection predicted improved pain (vs. nonsurgical treatment CI 2.4, 19.4, p = 0.01) and appearance versus open (CI 27.0, 35.0, p < 0.001) or combined (CI 10.4, 17.1, p < 0.001). Pterygopalatine fossa involvement predicted worse swallow (CI -10.8, -2.4, p = 0.01) and pain (CI -17.0, -4.0, p < 0.001). Neck dissection predicted worse swallow (CI -14.8, -2.8, p < 0.001), taste (CI -31.7, -1.5, p = 0.02), and salivary symptoms (CI -28.4, -8.6, p < 0.001). Maxillary involvement predicted worse chewing (CI 9.8, 33.2; p < 0.001) and speech (CI -21.8, -5.4, p < 0.001) relative to other sites. Advanced T stage predicted worse anxiety (CI -13.0, -2.0, p = 0.03)., Conclusions: Surgical approach, management of cervical disease, tumor extent, and site of involvement impacted variable UWQOL symptom areas. Endoscopic resection predicted better pain, appearance, and chewing compared with open. These results may aid in counseling patients regarding potential QOL expectations in their SNM treatment and recovery course., (© 2024 The Author(s). International Forum of Allergy & Rhinology published by Wiley Periodicals LLC on behalf of American Academy of Otolaryngic Allergy and American Rhinologic Society.)

Purpose To develop and externally test a scan-to-prediction deep learning pipeline for noninvasive, MRI-based BRAF mutational status classification for pediatric low-grade glioma. Materials and Methods This retrospective study included two pediatric low-grade glioma datasets with linked genomic and diagnostic T2-weighted MRI data of patients: Dana-Farber/Boston Children's Hospital (development dataset, n = 214 [113 (52.8%) male; 104 (48.6%) BRAF wild type, 60 (28.0%) BRAF fusion, and 50 (23.4%) BRAF V600E]) and the Children's Brain Tumor Network (external testing, n = 112 [55 (49.1%) male; 35 (31.2%) BRAF wild type, 60 (53.6%) BRAF fusion, and 17 (15.2%) BRAF V600E]). A deep learning pipeline was developed to classify BRAF mutational status ( BRAF wild type vs BRAF fusion vs BRAF V600E) via a two-stage process: (a) three-dimensional tumor segmentation and extraction of axial tumor images and (b) section-wise, deep learning-based classification of mutational status. Knowledge-transfer and self-supervised approaches were investigated to prevent model overfitting, with a primary end point of the area under the receiver operating characteristic curve (AUC). To enhance model interpretability, a novel metric, center of mass distance, was developed to quantify the model attention around the tumor. Results A combination of transfer learning from a pretrained medical imaging-specific network and self-supervised label cross-training (TransferX) coupled with consensus logic yielded the highest classification performance with an AUC of 0.82 (95% CI: 0.72, 0.91), 0.87 (95% CI: 0.61, 0.97), and 0.85 (95% CI: 0.66, 0.95) for BRAF wild type, BRAF fusion, and BRAF V600E, respectively, on internal testing. On external testing, the pipeline yielded an AUC of 0.72 (95% CI: 0.64, 0.86), 0.78 (95% CI: 0.61, 0.89), and 0.72 (95% CI: 0.64, 0.88) for BRAF wild type, BRAF fusion, and BRAF V600E, respectively. Conclusion Transfer learning and self-supervised cross-training improved classification performance and generalizability for noninvasive pediatric low-grade glioma mutational status prediction in a limited data scenario. Keywords: Pediatrics, MRI, CNS, Brain/Brain Stem, Oncology, Feature Detection, Diagnosis, Supervised Learning, Transfer Learning, Convolutional Neural Network (CNN) Supplemental material is available for this article. © RSNA, 2024.

Background: The impact of sinonasal malignancies (SNMs) on quality of life (QOL) at presentation is poorly understood. The Sinonasal Outcome Test (SNOT-22) and University of Washington Quality of Life (UWQOL) are validated QOL instruments with distinctive subdomains. This study aims to identify factors impacting pretreatment QOL in SNM patients to personalize multidisciplinary management and counseling., Methods: Patients with previously untreated SNMs were prospectively enrolled (2015-2022) in a multicenter observational study. Baseline pretreatment QOL instruments (SNOT-22, UWQOL) were obtained along with demographics, comorbidities, histopathology/staging, tumor involvement, and symptoms. Multivariable regression models identified factors associated with reduced baseline QOL., Results: Among 204 patients, presenting baseline QOL was significantly reduced. Multivariable regression showed worse total SNOT-22 QOL in patients with skull base erosion (p = 0.02). SNOT-rhinologic QOL was worse in women (p = 0.009), patients with epistaxis (p = 0.036), and industrial exposure (p = 0.005). SNOT extranasal QOL was worse in patients with industrial exposure (p = 0.016); worse SNOT ear/facial QOL if perineural invasion (PNI) (p = 0.027). Squamous cell carcinoma pathology (p = 0.037), palate involvement (p = 0.012), and pain (p = 0.017) were associated with worse SNOT sleep QOL scores. SNOT psychological subdomain scores were significantly worse in patients with palate lesions (p = 0.022), skull base erosion (p = 0.025), and T1 staging (p = 0.023). Low QOL was more likely in the presence of PNI on UW health (p = 0.019) and orbital erosion on UW overall (p = 0.03). UW social QOL was worse if palatal involvement (p = 0.023) or PNI (p = 0.005)., Conclusions: Our findings demonstrate a negative impact on baseline QOL in patients with SNMs and suggest sex-specific and symptom-related lower QOL scores, with minimal histopathology association. Anatomical tumor involvement may be more reflective of QOL than T-staging, as orbital and skull base erosion, PNI, and palate lesions are significantly associated with reduced baseline QOL., (© 2023 ARS‐AAOA, LLC.)

Summary: With the increasing rates of exome and whole genome sequencing, the ability to classify large sets of germline sequencing variants using up-to-date American College of Medical Genetics-Association for Molecular Pathology (ACMG-AMP) criteria is crucial. Here, we present Automated Germline Variant Pathogenicity (AutoGVP), a tool that integrates germline variant pathogenicity annotations from ClinVar and sequence variant classifications from a modified version of InterVar (PVS1 strength adjustments, removal of PP5/BP6). This tool facilitates large-scale, clinically focused classification of germline sequence variants in a research setting., Availability and Implementation: AutoGVP is an open source dockerized workflow implemented in R and freely available on GitHub at https://github.com/diskin-lab-chop/AutoGVP., (© The Author(s) 2024. Published by Oxford University Press.)

Background: Diffuse intrinsic pontine glioma (DIPG) is a uniformly lethal brainstem tumor of childhood, driven by histone H3 K27M mutation and resultant epigenetic dysregulation. Epigenomic analyses of DIPG have shown global loss of repressive chromatin marks accompanied by DNA hypomethylation. However, studies providing a static view of the epigenome do not adequately capture the regulatory underpinnings of DIPG cellular heterogeneity and plasticity., Methods: To address this, we performed whole-genome bisulfite sequencing on a large panel of primary DIPG specimens and applied a novel framework for analysis of DNA methylation variability, permitting the derivation of comprehensive genome-wide DNA methylation potential energy landscapes that capture intrinsic epigenetic variation., Results: We show that DIPG has a markedly disordered epigenome with increasingly stochastic DNA methylation at genes regulating pluripotency and developmental identity, potentially enabling cells to sample diverse transcriptional programs and differentiation states. The DIPG epigenetic landscape was responsive to treatment with the hypomethylating agent decitabine, which produced genome-wide demethylation and reduced the stochasticity of DNA methylation at active enhancers and bivalent promoters. Decitabine treatment elicited changes in gene expression, including upregulation of immune signaling such as the interferon response, STING, and MHC class I expression, and sensitized cells to the effects of histone deacetylase inhibition., Conclusions: This study provides a resource for understanding the epigenetic instability that underlies DIPG heterogeneity. It suggests the application of epigenetic therapies to constrain the range of epigenetic states available to DIPG cells, as well as the use of decitabine in priming for immune-based therapies., Competing Interests: The authors declare that they have no competing interests., (© The Author(s) 2024. Published by Oxford University Press, the Society for Neuro-Oncology and the European Association of Neuro-Oncology.)

Purpose: The PNOC001 phase II single-arm trial sought to estimate progression-free survival (PFS) associated with everolimus therapy for progressive/recurrent pediatric low-grade glioma (pLGG) on the basis of phosphatidylinositol 3-kinase (PI3K)/AKT/mammalian target of rapamycin (mTOR) pathway activation as measured by phosphorylated-ribosomal protein S6 and to identify prognostic and predictive biomarkers., Patients and Methods: Patients, age 3-21 years, with progressive/recurrent pLGG received everolimus orally, 5 mg/m 2 once daily. Frequency of driver gene alterations was compared among independent pLGG cohorts of newly diagnosed and progressive/recurrent patients. PFS at 6 months (primary end point) and median PFS (secondary end point) were estimated for association with everolimus therapy., Results: Between 2012 and 2019, 65 subjects with progressive/recurrent pLGG (median age, 9.6 years; range, 3.0-19.9; 46% female) were enrolled, with a median follow-up of 57.5 months. The 6-month PFS was 67.4% (95% CI, 60.0 to 80.0) and median PFS was 11.1 months (95% CI, 7.6 to 19.8). Hypertriglyceridemia was the most common grade ≥3 adverse event. PI3K/AKT/mTOR pathway activation did not correlate with clinical outcomes (6-month PFS, active 68.4% v nonactive 63.3%; median PFS, active 11.2 months v nonactive 11.1 months; P = .80). Rare/novel KIAA1549::BRAF fusion breakpoints were most frequent in supratentorial midline pilocytic astrocytomas, in patients with progressive/recurrent disease, and correlated with poor clinical outcomes (median PFS, rare/novel KIAA1549::BRAF fusion breakpoints 6.1 months v common KIAA1549::BRAF fusion breakpoints 16.7 months; P < .05). Multivariate analysis confirmed their independent risk factor status for disease progression in PNOC001 and other, independent cohorts. Additionally, rare pathogenic germline variants in homologous recombination genes were identified in 6.8% of PNOC001 patients., Conclusion: Everolimus is a well-tolerated therapy for progressive/recurrent pLGGs. Rare/novel KIAA1549::BRAF fusion breakpoints may define biomarkers for progressive disease and should be assessed in future clinical trials.

International cancer registries make real-world genomic and clinical data available, but their joint analysis remains a challenge. AACR Project GENIE, an international cancer registry collecting data from 19 cancer centers, makes data from >130,000 patients publicly available through the cBioPortal for Cancer Genomics (https://genie.cbioportal.org). For 25,000 patients, additional real-world longitudinal clinical data, including treatment and outcome data, are being collected by the AACR Project GENIE Biopharma Collaborative using the PRISSMM data curation model. Several thousand of these cases are now also available in cBioPortal. We have significantly enhanced the functionalities of cBioPortal to support the visualization and analysis of this rich clinico-genomic linked dataset, as well as datasets generated by other centers and consortia. Examples of these enhancements include (i) visualization of the longitudinal clinical and genomic data at the patient level, including timelines for diagnoses, treatments, and outcomes; (ii) the ability to select samples based on treatment status, facilitating a comparison of molecular and clinical attributes between samples before and after a specific treatment; and (iii) survival analysis estimates based on individual treatment regimens received. Together, these features provide cBioPortal users with a toolkit to interactively investigate complex clinico-genomic data to generate hypotheses and make discoveries about the impact of specific genomic variants on prognosis and therapeutic sensitivities in cancer., Significance: Enhanced cBioPortal features allow clinicians and researchers to effectively investigate longitudinal clinico-genomic data from patients with cancer, which will improve exploration of data from the AACR Project GENIE Biopharma Collaborative and similar datasets., (©2023 The Authors; Published by the American Association for Cancer Research.)

Lean muscle mass (LMM) is an important aspect of human health. Temporalis muscle thickness is a promising LMM marker but has had limited utility due to its unknown normal growth trajectory and reference ranges and lack of standardized measurement. Here, we develop an automated deep learning pipeline to accurately measure temporalis muscle thickness (iTMT) from routine brain magnetic resonance imaging (MRI). We apply iTMT to 23,876 MRIs of healthy subjects, ages 4 through 35, and generate sex-specific iTMT normal growth charts with percentiles. We find that iTMT was associated with specific physiologic traits, including caloric intake, physical activity, sex hormone levels, and presence of malignancy. We validate iTMT across multiple demographic groups and in children with brain tumors and demonstrate feasibility for individualized longitudinal monitoring. The iTMT pipeline provides unprecedented insights into temporalis muscle growth during human development and enables the use of LMM tracking to inform clinical decision-making., (© 2023. The Author(s).)

Introduction: Inverted papilloma (IP) is a sinonasal tumor with a well-known potential for malignant transformation. The role of human papillomavirus (HPV) in its pathogenesis has been controversial. The purpose of this study was to determine the virome associated with IP, with progression to carcinoma in situ (CIS), and invasive carcinoma., Methods: To determine the HPV-specific types, a metagenomics assay that contains 62,886 probes targeting viral genomes in a microarray format was used. The platform screens DNA and RNA from fixed tissues from eight controls, 16 IP without dysplasia, five IP with CIS, and 13 IP-associated squamous cell carcinoma (IPSCC). Paired with next-generation sequencing, 48 types of HPV with 857 region-specific probes were interrogated against the tumors., Results: The prevalence of HPV-16 was 14%, 42%, 70%, and 73% in control tissue, IP without dysplasia, IP with CIS, and IPSCC, respectively. The prevalence of HPV-18 had a similar progressive increase in prevalence, with 14%, 27%, 67%, and 74%, respectively. The assay allowed region-specific analysis, which identified the only oncogenic HPV-18 E6 to be statistically significant when compared with control tissue. The prevalence of HPV-18 E6 was 0% in control tissue, 25% in IP without dysplasia, 60% in IP with CIS, and 77% in IPSCC., Conclusions: There are over 200 HPV types that infect human epithelial cells, of which only a few are known to be high-risk. Our study demonstrated a trend of increasing prevalence of HPV-18 E6 that correlated with histologic severity, which is novel and supports a potential role for HPV in the pathogenesis of IP., (© 2023 ARS-AAOA, LLC.)

Background: Quality of life (QOL) for individuals with sinonasal malignancy (SNM) is significantly under-studied, yet it is critical for counseling and may impact treatment. In this study we evaluated how patient, treatment, and disease factors impact sinonasal-specific and generalized QOL using validated metrics in a large cohort over a 5-year posttreatment time frame., Methods: Patients with SNM who underwent definitive treatment with curative intent were enrolled in a prospective, multisite, longitudinal observational study. QOL was assessed using the 22-item Sino-Nasal Outcome Test (SNOT-22) and University of Washington Quality of Life Questionnaire (UWQOL) instruments at pretreatment baseline and multiple follow-ups through 5 years posttreatment. Multivariable modeling was used to determine demographic, disease, and treatment factors associated with disease-specific and generalized physical and social/emotional function QOL., Results: One hundred ninety-four patients with SNM were analyzed. All QOL indices were impaired at pretreatment baseline and improved after treatment. SNOT-22 scores improved 3 months and UWQOL scores improved 6 to 9 months posttreatment. Patients who underwent open compared with endoscopic tumor resection had worse generalized QOL (p < 0.001), adjusted for factors including T stage. Pterygopalatine fossa (PPF) involvement was associated with worse QOL (SNOT-22, p < 0.001; UWQOL Physical dimension, p = 0.02). Adjuvant radiation was associated with worse disease-specific QOL (p = 0.03). Neck dissection was associated with worse generalized physical function QOL (p = 0.01). Positive margins were associated with worse generalized social/emotional function QOL (p = 0.01)., Conclusion: Disease-specific and generalized QOL is impaired at baseline in patients with SNM and improves after treatment. Endoscopic resection is associated with better QOL. PPF involvement, adjuvant radiation, neck dissection, and positive margins were associated with worse QOL posttreatment., (© 2023 ARS-AAOA, LLC.)

With medical software platforms moving to cloud environments with scalable storage and computing, the translation of predictive artificial intelligence (AI) models to aid in clinical decision-making and facilitate personalized medicine for cancer patients is becoming a reality. Medical imaging, namely radiologic and histologic images, has immense analytical potential in neuro-oncology, and models utilizing integrated radiomic and pathomic data may yield a synergistic effect and provide a new modality for precision medicine. At the same time, the ability to harness multi-modal data is met with challenges in aggregating data across medical departments and institutions, as well as significant complexity in modeling the phenotypic and genotypic heterogeneity of pediatric brain tumors. In this paper, we review recent pathomic and integrated pathomic, radiomic, and genomic studies with clinical applications. We discuss current challenges limiting translational research on pediatric brain tumors and outline technical and analytical solutions. Overall, we propose that to empower the potential residing in radio-pathomics, systemic changes in cross-discipline data management and end-to-end software platforms to handle multi-modal data sets are needed, in addition to embracing modern AI-powered approaches. These changes can improve the performance of predictive models, and ultimately the ability to advance brain cancer treatments and patient outcomes through the development of such models., Competing Interests: None declared., (© The Author(s) 2023. Published by Oxford University Press, the Society for Neuro-Oncology and the European Association of Neuro-Oncology.)

Background: Cancer immunotherapies including immune checkpoint inhibitors and Chimeric Antigen Receptor (CAR) T-cell therapy have shown variable response rates in paediatric patients highlighting the need to establish robust biomarkers for patient selection. While the tumour microenvironment in adults has been widely studied to delineate determinants of immune response, the immune composition of paediatric solid tumours remains relatively uncharacterized calling for investigations to identify potential immune biomarkers., Methods: To inform immunotherapy approaches in paediatric cancers with embryonal origin, we performed an immunogenomic analysis of RNA-seq data from 925 treatment-naïve paediatric nervous system tumours (pedNST) spanning 12 cancer types from three publicly available data sets., Results: Within pedNST, we uncovered four broad immune clusters: Paediatric Inflamed (10%), Myeloid Predominant (30%), Immune Neutral (43%) and Immune Desert (17%). We validated these clusters using immunohistochemistry, methylation immune inference and segmentation analysis of tissue images. We report shared biology of these immune clusters within and across cancer types, and characterization of specific immune cell frequencies as well as T- and B-cell repertoires. We found no associations between immune infiltration levels and tumour mutational burden, although molecular cancer entities were enriched within specific immune clusters., Conclusions: Given the heterogeneity of immune infiltration within pedNST, our findings suggest personalized immunogenomic profiling is needed to guide selection of immunotherapeutic strategies., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Background: To achieve replicative immortality, most cancers develop a telomere maintenance mechanism, such as reactivation of telomerase or alternative lengthening of telomeres (ALT). There are limited data on the prevalence and clinical significance of ALT in pediatric brain tumors, and ALT-directed therapy is not available., Methods: We performed C-circle analysis (CCA) on 579 pediatric brain tumors that had corresponding tumor/normal whole genome sequencing through the Open Pediatric Brain Tumor Atlas (OpenPBTA). We detected ALT in 6.9% (n = 40/579) of these tumors and completed additional validation by ultrabright telomeric foci in situ on a subset of these tumors. We used CCA to validate TelomereHunter for computational prediction of ALT status and focus subsequent analyses on pediatric high-grade gliomas (pHGGs) Finally, we examined whether ALT is associated with recurrent somatic or germline alterations., Results: ALT is common in pHGGs (n = 24/63, 38.1%), but occurs infrequently in other pediatric brain tumors (<3%). Somatic ATRX mutations occur in 50% of ALT+ pHGGs and in 30% of ALT- pHGGs. Rare pathogenic germline variants in mismatch repair (MMR) genes are significantly associated with an increased occurrence of ALT., Conclusions: We demonstrate that ATRX is mutated in only a subset of ALT+ pHGGs, suggesting other mechanisms of ATRX loss of function or alterations in other genes may be associated with the development of ALT in these patients. We show that germline variants in MMR are associated with the development of ALT in patients with pHGG., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Society for Neuro-Oncology.)

Increasing evidence suggests that besides mutational and molecular alterations, the immune component of the tumor microenvironment also substantially impacts tumor behavior and complicates treatment response, particularly to immunotherapies. Although the standard method for characterizing tumor immune profile is through performing integrated genomic analysis on tissue biopsies, the dynamic change in the immune composition of the tumor microenvironment makes this approach not feasible, especially for brain tumors. Radiomics is a rapidly growing field that uses advanced imaging techniques and computational algorithms to extract numerous quantitative features from medical images. Recent advances in machine learning methods are facilitating biological validation of radiomic signatures and allowing them to "mine" for a variety of significant correlates, including genetic, immunologic, and histologic data. Radiomics has the potential to be used as a non-invasive approach to predict the presence and density of immune cells within the microenvironment, as well as to assess the expression of immune-related genes and pathways. This information can be essential for patient stratification, informing treatment decisions and predicting patients' response to immunotherapies. This is particularly important for tumors with difficult surgical access such as gliomas. In this review, we provide an overview of the glioma microenvironment, describe novel approaches for clustering patients based on their tumor immune profile, and discuss the latest progress on utilization of radiomics for immune profiling of glioma based on current literature., (© 2023. The Author(s).)

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., Competing Interests: C.S.G.’s spouse was an employee of Alex’s Lemonade Stand Foundation, which was a sponsor of this research. J.A.S., C.L.S., C.J.B., S.J.S., and J.N.T. are or were employees of Alex’s Lemonade Stand Foundation, a sponsor of this research. A.J.W. is a member of the Scientific Advisory boards for Alexion and DayOne Biopharmaceuticals., (© 2023 The Author(s).)

Background: Brain tumors are the most common solid tumors and the leading cause of cancer-related death among all childhood cancers. Tumor segmentation is essential in surgical and treatment planning, and response assessment and monitoring. However, manual segmentation is time-consuming and has high interoperator variability. We present a multi-institutional deep learning-based method for automated brain extraction and segmentation of pediatric brain tumors based on multi-parametric MRI scans., Methods: Multi-parametric scans (T1w, T1w-CE, T2, and T2-FLAIR) of 244 pediatric patients ( n = 215 internal and n = 29 external cohorts) with de novo brain tumors, including a variety of tumor subtypes, were preprocessed and manually segmented to identify the brain tissue and tumor subregions into four tumor subregions, i.e., enhancing tumor (ET), non-enhancing tumor (NET), cystic components (CC), and peritumoral edema (ED). The internal cohort was split into training ( n = 151), validation ( n = 43), and withheld internal test ( n = 21) subsets. DeepMedic, a three-dimensional convolutional neural network, was trained and the model parameters were tuned. Finally, the network was evaluated on the withheld internal and external test cohorts., Results: Dice similarity score (median ± SD) was 0.91 ± 0.10/0.88 ± 0.16 for the whole tumor, 0.73 ± 0.27/0.84 ± 0.29 for ET, 0.79 ± 19/0.74 ± 0.27 for union of all non-enhancing components (i.e., NET, CC, ED), and 0.98 ± 0.02 for brain tissue in both internal/external test sets., Conclusions: Our proposed automated brain extraction and tumor subregion segmentation models demonstrated accurate performance on segmentation of the brain tissue and whole tumor regions in pediatric brain tumors and can facilitate detection of abnormal regions for further clinical measurements., Competing Interests: None to declare., (© The Author(s) 2023. Published by Oxford University Press, the Society for Neuro-Oncology and the European Association of Neuro-Oncology.)

How abnormal neurodevelopment relates to the tumour aggressiveness of medulloblastoma (MB), the most common type of embryonal tumour, remains elusive. Here we uncover a neurodevelopmental epigenomic programme that is hijacked to induce MB metastatic dissemination. Unsupervised analyses of integrated publicly available datasets with our newly generated data reveal that SMARCD3 (also known as BAF60C) regulates Disabled 1 (DAB1)-mediated Reelin signalling in Purkinje cell migration and MB metastasis by orchestrating cis-regulatory elements at the DAB1 locus. We further identify that a core set of transcription factors, enhancer of zeste homologue 2 (EZH2) and nuclear factor I X (NFIX), coordinates with the cis-regulatory elements at the SMARCD3 locus to form a chromatin hub to control SMARCD3 expression in the developing cerebellum and in metastatic MB. Increased SMARCD3 expression activates Reelin-DAB1-mediated Src kinase signalling, which results in a MB response to Src inhibition. These data deepen our understanding of how neurodevelopmental programming influences disease progression and provide a potential therapeutic option for patients with MB., (© 2023. The Author(s).)

Pediatric CNS tumors are responsible for the majority of cancer-related deaths in children and have poor prognoses, despite advancements in chemotherapy and radiotherapy. As many tumors lack efficacious treatments, there is a crucial need to develop more promising therapeutic options, such as immunotherapies; the use of chimeric antigen receptor (CAR) T cell therapy directed against CNS tumors is of particular interest. Cell surface targets such as B7-H3, IL13RA2, and the disialoganglioside GD2 are highly expressed on the surface of several pediatric and adult CNS tumors, raising the opportunity to use CAR T cell therapy against these and other surface targets. To evaluate the repeated locoregional delivery of CAR T cells in preclinical murine models, an indwelling catheter system that recapitulates indwelling catheters currently being used in human clinical trials was established. Unlike stereotactic delivery, the indwelling catheter system allows for repeated dosing without the use of multiple surgeries. This protocol describes the intratumoral placement of a fixed guide cannula that has been used to successfully test serial CAR T cell infusions in orthotopic murine models of pediatric brain tumors. Following orthotopic injection and engraftment of the tumor cells in mice, intratumoral placement of a fixed guide cannula is completed on a stereotactic apparatus and secured with screws and acrylic resin. Treatment cannulas are then inserted through the fixed guide cannula for repeated CAR T cell delivery. Stereotactic placement of the guide cannula can be adjusted to deliver CAR T cells directly into the lateral ventricle or other locations in the brain. This platform offers a reliable mechanism for the preclinical testing of repeated intracranial infusions of CAR T cells and other novel therapeutics for these devastating pediatric tumors.

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., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. David S. Ziegler is a consultant, or on the advisory board, of Bayer, AstraZeneca, Accendatech, Novartis, Day One, FivePhusion, Amgen, Alexion, and Norgine. Angela J. Waanders is on the advisory board of Alexion and Day One., (Copyright © 2022. Published by Elsevier Inc.)

Background: Pediatric brain tumors are the leading cause of cancer death in children with an urgent need for innovative therapies. Glypican 2 (GPC2) is a cell surface oncoprotein expressed in neuroblastoma for which targeted immunotherapies have been developed. This work aimed to characterize GPC2 expression in pediatric brain tumors and develop an mRNA CAR T cell approach against this target., Methods: We investigated GPC2 expression across a cohort of primary pediatric brain tumor samples and cell lines using RNA sequencing, immunohistochemistry, and flow cytometry. To target GPC2 in the brain with adoptive cellular therapies and mitigate potential inflammatory neurotoxicity, we used optimized mRNA to create transient chimeric antigen receptor (CAR) T cells. We developed four mRNA CAR T cell constructs using the highly GPC2-specific fully human D3 single chain variable fragment for preclinical testing., Results: We identified high GPC2 expression across multiple pediatric brain tumor types including medulloblastomas, embryonal tumors with multilayered rosettes, other central nervous system embryonal tumors, as well as definable subsets of highly malignant gliomas. We next validated and prioritized CAR configurations using in vitro cytotoxicity assays with GPC2-expressing neuroblastoma cells, where the light-to-heavy single chain variable fragment configurations proved to be superior. We expanded the testing of the two most potent GPC2-directed CAR constructs to GPC2-expressing medulloblastoma and high-grade glioma cell lines, showing significant GPC2-specific cell death in multiple models. Finally, biweekly locoregional delivery of 2-4 million GPC2-directed mRNA CAR T cells induced significant tumor regression in an orthotopic medulloblastoma model and significantly prolonged survival in an aggressive orthotopic thalamic diffuse midline glioma xenograft model. No GPC2-directed CAR T cell related neurologic or systemic toxicity was observed., Conclusion: Taken together, these data show that GPC2 is a highly differentially expressed cell surface protein on multiple malignant pediatric brain tumors that can be targeted safely with local delivery of mRNA CAR T cells, laying the framework for the clinical translation of GPC2-directed immunotherapies for pediatric brain tumors., Competing Interests: Competing interests: TS is currently employed by Spark Therapeutics. KK is currently employed by BioNTech and is an inventor on a patent related to use of nucleoside-modified mRNA. DMB is currently employed by Tmunity Therapeutics. JBF, DMB, JMM, and KRB hold patents for the discovery and development of immunotherapies for cancer, including patents related to glypican 2 (GPC2)-directed immunotherapies. KRB and JMM receive research funding from Tmunity for research on GPC2-directed immunotherapies and JBF, DMB, JMM, and KRB receive royalties from Tmunity for licensing of GPC2-related intellectual property. JMM is a founder of both Tantigen Bio and Hula Therapeutics, focused on cellular therapies for childhood cancers, but neither are working on GPC2-directed therapeutics. All other authors have nothing to disclose., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Neurotrophins and their related tyrosine kinase receptors (TRKs), encoded by the neurotrophic tyrosine receptor kinase genes NTRKs, play a crucial role in central nervous system development. Oncogenic NTRK gene fusion events have been identified in several cancer subtypes and cause constitutive activation of the TRK receptor, promoting tumorigenesis. While NTRK fusions are rare in cancers overall, they have been identified in appreciable frequency in certain CNS tumors subtypes recently. In other non-CNS neoplasms, the development of NTRK fusion directed therapies has been developed with TRK inhibitors showing promise in clinical trials. Given the difficulty in treating certain pediatric CNS tumors such as high grade gliomas, understanding NTRK fusions in pediatric CNS tumors may lead to more directed treatment and subsequent therapeutic benefit. This review examines the biology of NTRK fusions, the frequency and clinical significance in pediatric CNS tumors, and methods for detection of NTRK fusion in CNS tumors., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Background: Inverted papilloma (IP) is a sinonasal tumor with a well-known potential for malignant transformation. The purpose of this study was to identify the genes and pathways associated with IP, with progression to carcinoma-in-situ and invasive carcinoma., Methods: To determine genes and molecular pathways that may indicate progression and correlate with histologic changes, we analyzed six IP without dysplasia, five IP with carcinoma-in-situ, and 13 squamous cell carcinoma ex-IP by targeted sequencing. The HTG EdgeSeq Oncology Biomarker Panel coupled with next-generation sequencing was used to evaluate 2560 transcripts associated with solid tumors., Results: Progressive upregulation of 11 genes were observed (CALD1, COL1A1, COL3A1, COL4A2, COL5A2, FN1, ITGA5, LGALS1, MMP11, SERPINH1, SPARC) in the order of invasive carcinoma > carcinoma-in-situ > IP without dysplasia. When compared with IP without dysplasia, more genes are differentially expressed in invasive carcinoma than carcinoma-in-situ samples (341 downregulated/333 upregulated vs. 195 downregulated/156 upregulated). Gene set enrichment analysis determined three gene sets in common between the cohorts (epithelial mesenchymal transition, extracellular matrix organization, and coagulation)., Conclusions: Progressive upregulation of genes specific to IP malignant degeneration has significant clinical implications. This panel of 11 genes will improve concordance of histologic classification, which can directly impact treatment and patient outcomes. Additionally, future studies on larger tumor sets may observe upregulation in the gene panel that preceded histologic changes, which may be useful for further risk stratification., (© 2021 ARS-AAOA, LLC.)

The growing number of next-generation sequencing (NGS) data presents a unique opportunity to study the combined impact of mitochondrial and nuclear-encoded genetic variation in complex disease. Mitochondrial DNA variants and in particular, heteroplasmic variants, are critical for determining human disease severity. While there are approaches for obtaining mitochondrial DNA variants from NGS data, these software do not account for the unique characteristics of mitochondrial genetics and can be inaccurate even for homoplasmic variants. We introduce MitoScape, a novel, big-data, software for extracting mitochondrial DNA sequences from NGS. MitoScape adopts a novel departure from other algorithms by using machine learning to model the unique characteristics of mitochondrial genetics. We also employ a novel approach of using rho-zero (mitochondrial DNA-depleted) data to model nuclear-encoded mitochondrial sequences. We showed that MitoScape produces accurate heteroplasmy estimates using gold-standard mitochondrial DNA data. We provide a comprehensive comparison of the most common tools for obtaining mtDNA variants from NGS and showed that MitoScape had superior performance to compared tools in every statistically category we compared, including false positives and false negatives. By applying MitoScape to common disease examples, we illustrate how MitoScape facilitates important heteroplasmy-disease association discoveries by expanding upon a reported association between hypertrophic cardiomyopathy and mitochondrial haplogroup T in men (adjusted p-value = 0.003). The improved accuracy of mitochondrial DNA variants produced by MitoScape will be instrumental in diagnosing disease in the context of personalized medicine and clinical diagnostics., Competing Interests: The authors have declared that no competing interests exist.

Cancer Informatics for Cancer Centers (CI4CC) is a grassroots, nonprofit 501c3 organization intended to provide a focused national forum for engagement of senior cancer informatics leaders, primarily aimed at academic cancer centers anywhere in the world but with a special emphasis on the 70 National Cancer Institute-funded cancer centers. This consortium has regularly held topic-focused biannual face-to-face symposiums. These meetings are a place to review cancer informatics and data science priorities and initiatives, providing a forum for discussion of the strategic and pragmatic issues that we faced at our respective institutions and cancer centers. Here, we provide meeting highlights from the latest CI4CC Symposium, which was delayed from its original April 2020 schedule because of the COVID-19 pandemic and held virtually over three days (September 24, October 1, and October 8) in the fall of 2020. In addition to the content presented, we found that holding this event virtually once a week for 6 hours was a great way to keep the kind of deep engagement that a face-to-face meeting engenders. This is the second such publication of CI4CC Symposium highlights, the first covering the meeting that took place in Napa, California, from October 14-16, 2019. We conclude with some thoughts about using data science to learn from every child with cancer, focusing on emerging activities of the National Cancer Institute's Childhood Cancer Data Initiative., Competing Interests: Anne C. KirchhoffStock and Other Ownership Interests: Medtronic Kara L. DavisHonoraria: NovartisResearch Funding: Jazz Pharmaceuticals Karlyne ReillyConsulting or Advisory Role: Saul Ewing LLCPatents, Royalties, Other Intellectual Property: I hold a patent to a potential therapeutic: Reilly KM, Beutler JA, Turbyville T, Wiemer DF: The Natural Product Schweinfurthin A and Synthetic Schweinfurthin Analogs Specifically Inhibit Nf1-Null Cells and may be Useful as a Therapy for Neurofibromatosis Type 1. US patent 61/174,338, April 19, 2014; International patent PCT/US10/33153. There are no royalties or licensing fees from this patent at the time Richard AplencExpert Testimony: Vorys Samuel L. VolchenboumStock and Other Ownership Interests: Litmus HealthConsulting or Advisory Role: AccordantTravel, Accommodations, Expenses: Sanford Health Bruce J. AronowPatents, Royalties, Other Intellectual Property: Patents issued for some data analysis algorithms related to data mining and discovery approaches to drug repositioning for new clinical indications Olena VaskeEmployment: NantWorksStock and Other Ownership Interests: NantHealth Casey GreeneOther Relationship: Alex's Lemonade Stand Foundation Jack DiGiovannaEmployment: Biogen (I)Stock and Other Ownership Interests: Biogen Sorena NadafThis author is a member of the JCO Clinical Cancer Informatics Editorial Board. Journal policy recused the author from having any role in the peer review of this manuscript. Warren A. KibbeThis author is a member of the JCO Clinical Cancer Informatics Editorial Board. Journal policy recused the author from having any role in the peer review of this manuscript.No other potential conflicts of interest were reported.

Pediatric histiocytic neoplasms are hematopoietic disorders frequently driven by the BRAF-V600E mutation. Here, we identified two BRAF gene fusions (novel MTAP-BRAF and MS4A6A-BRAF) in two aggressive histiocytic neoplasms. In contrast to previously described BRAF fusions, MTAP-BRAF and MS4A6A-BRAF do not respond to the paradox breaker RAF inhibitor (RAFi) PLX8394 due to stable fusion dimerization mediated by the N-terminal fusion partners. This highlights a significant and clinically relevant shift from the current dogma that BRAF-fusions respond similarly to BRAF-inhibitors. As an alternative, we show suppression of fusion-driven oncogenic growth with the pan-RAFi LY3009120 and MEK inhibition., (© 2021 Wiley Periodicals LLC.)

Glioblastoma (GBM) is the most aggressive nervous system cancer. Understanding its molecular pathogenesis is crucial to improving diagnosis and treatment. Integrated analysis of genomic, proteomic, post-translational modification and metabolomic data on 99 treatment-naive GBMs provides insights to GBM biology. We identify key phosphorylation events (e.g., phosphorylated PTPN11 and PLCG1) as potential switches mediating oncogenic pathway activation, as well as potential targets for EGFR-, TP53-, and RB1-altered tumors. Immune subtypes with distinct immune cell types are discovered using bulk omics methodologies, validated by snRNA-seq, and correlated with specific expression and histone acetylation patterns. Histone H2B acetylation in classical-like and immune-low GBM is driven largely by BRDs, CREBBP, and EP300. Integrated metabolomic and proteomic data identify specific lipid distributions across subtypes and distinct global metabolic changes in IDH-mutated tumors. This work highlights biological relationships that could contribute to stratification of GBM patients for more effective treatment., Competing Interests: Declaration of interests S.Y. is employed by Sema4. A.H.K. consults for Monteris Medical. P.W. is a statistical consultant for Sema4. M.G.C. receives research support from Orbus Therapeutics and NeoimmuneTech Inc, and royalties from UpToDate., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Low-grade gliomas (LGGs) are the most common childhood brain tumor in the general population and in individuals with the Neurofibromatosis type 1 (NF1) cancer predisposition syndrome. Surgical biopsy is rarely performed prior to treatment in the setting of NF1, resulting in a paucity of tumor genomic information. To define the molecular landscape of NF1-associated LGGs (NF1-LGG), we integrated clinical data, histological diagnoses, and multi-level genetic/genomic analyses on 70 individuals from 25 centers worldwide. Whereas, most tumors harbored bi-allelic NF1 inactivation as the only genetic abnormality, 11% had additional mutations. Moreover, tumors classified as non-pilocytic astrocytoma based on DNA methylation analysis were significantly more likely to harbor these additional mutations. The most common secondary alteration was FGFR1 mutation, which conferred an additional growth advantage in multiple complementary experimental murine Nf1 models. Taken together, this comprehensive characterization has important implications for the management of children with NF1-LGG, distinct from their sporadic counterparts.

ALK (Anaplastic lymphoma kinase) fusion proteins are oncogenic and have been seen in various tumors. PPP1CB-ALK fusions are rare but have been reported in a few patients with low- or high-grade gliomas. However, little is known regarding the mechanism of fusion formation and genomic break points of this fusion. We performed genomic characterization of a PPP1CB-ALK fusion with fusion gene amplification in a congenital glioblastoma. The PPP1CB-ALK consists of exons 1-5 of PPP1CB and exons 20-29 of ALK. The genomic translocation breakpoints were determined by real-time quantitative PCR (RT-qPCR) and Sanger sequencing of genomic DNA. Next generation sequencing, RT-qPCR and fluorescence in situ hybridization analyses demonstrated PPP1CB-ALK amplification. Copy number analyses of genes between PPP1CB and ALK using RT-qPCR suggest that the PPP1CB-ALK is likely the result of local chromothripsis followed by episomal amplification. Transcriptome sequencing demonstrated high-level SOX2 expression and predicted WNT/β-catenin pathway activation, suggesting possible therapeutic approaches., Competing Interests: Declaration of Competing Interest None declared., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

Purpose: Neurotrophic tyrosine receptor kinase (NTRK) fusions have been described as oncogenic drivers in a variety of tumors. However, little is known about the overall frequency of NTRK fusion in unselected pediatric tumors. Here, we assessed the frequency, fusion partners, and clinical course in pediatric patients with NTRK fusion-positive tumors., Patients and Methods: We studied 1,347 consecutive pediatric tumors from 1,217 patients who underwent tumor genomic profiling using custom-designed DNA and RNA next-generation sequencing panels. NTRK fusions identified were orthogonally confirmed., Results and Discussion: NTRK fusions were identified in 29 tumors from 27 patients with a positive yield of 2.22% for all patients and 3.08% for solid tumors. Although NTRK2 fusions were found exclusively in CNS tumors and NTRK1 fusions were highly enriched in papillary thyroid carcinomas, NTRK3 fusions were identified in all tumor categories. The most canonical fusion was ETV6-NTRK3 observed in 10 patients with diverse types of tumors. Several novel NTRK fusions were observed in rare tumor types, including KCTD16-NTRK1 in ganglioglioma and IRF2BP2-NTRK3 in papillary thyroid carcinomas. The detection of an NTRK fusion confirmed the morphologic diagnosis including five cases where the final tumor diagnosis was largely based on the discovery of an NTRK fusion. In one patient, the diagnosis was changed because of the identification of an ETV6-NTRK3 fusion. One patient with infantile fibrosarcoma was treated with larotrectinib and achieved complete pathologic remission., Conclusion: NTRK fusions are more frequently seen in pediatric tumors than in adult tumors and involve a broader panel of fusion partners and a wider range of tumors than previously recognized. These results highlight the importance of screening for NTRK fusions as part of the tumor genomic profiling for patients with pediatric cancer., Competing Interests: The following represents disclosure information provided by authors of this manuscript. All relationships are considered compensated unless otherwise noted. Relationships are self-held unless noted. I = Immediate Family Member, Inst = My Institution. Relationships may not relate to the subject matter of this manuscript. For more information about ASCO’s conflict of interest policy, please refer to www.asco.org/rwc or ascopubs.org/cci/author-center. Open Payments is a public database containing information reported by companies about payments made to US-licensed physicians (Open Payments). Elizabeth FoxOther Relationship: Helsinn TherapeuticsGerald B. WertheimEmployment: Johnson & Johnson Stock and Other Ownership Interests: Johnson & JohnsonVinodh PillaiConsulting or Advisory Role: Foundation medicine Travel, Accommodations, Expenses: Foundation MedicineJennifer E. PogorilerEmployment: Bristol-Myers Squibb Stock and Other Ownership Interests: Bristol-Myers SquibbStephen P. HungerStock and Other Ownership Interests: Amgen, Merck Honoraria: Amgen Consulting or Advisory Role: NovartisAndrew J. BauerHonoraria: Sandoz-Novartis Travel, Accommodations, Expenses: SandozMarilyn M. LiConsulting or Advisory Role: Roche No other potential conflicts of interest were reported, (© 2021 by American Society of Clinical Oncology.)

We report a comprehensive proteogenomics analysis, including whole-genome sequencing, RNA sequencing, and proteomics and phosphoproteomics profiling, of 218 tumors across 7 histological types of childhood brain cancer: low-grade glioma (n = 93), ependymoma (32), high-grade glioma (25), medulloblastoma (22), ganglioglioma (18), craniopharyngioma (16), and atypical teratoid rhabdoid tumor (12). Proteomics data identify common biological themes that span histological boundaries, suggesting that treatments used for one histological type may be applied effectively to other tumors sharing similar proteomics features. Immune landscape characterization reveals diverse tumor microenvironments across and within diagnoses. Proteomics data further reveal functional effects of somatic mutations and copy number variations (CNVs) not evident in transcriptomics data. Kinase-substrate association and co-expression network analysis identify important biological mechanisms of tumorigenesis. This is the first large-scale proteogenomics analysis across traditional histological boundaries to uncover foundational pediatric brain tumor biology and inform rational treatment selection., Competing Interests: Declaration of Interests E.E.S. serves as chief executive officer for Sema4 and has an equity interest in this company., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Background: Gene fusion events are significant sources of somatic variation across adult and pediatric cancers and are some of the most clinically-effective therapeutic targets, yet low consensus of RNA-Seq fusion prediction algorithms makes therapeutic prioritization difficult. In addition, events such as polymerase read-throughs, mis-mapping due to gene homology, and fusions occurring in healthy normal tissue require informed filtering, making it difficult for researchers and clinicians to rapidly discern gene fusions that might be true underlying oncogenic drivers of a tumor and in some cases, appropriate targets for therapy., Results: We developed annoFuse, an R package, and shinyFuse, a companion web application, to annotate, prioritize, and explore biologically-relevant expressed gene fusions, downstream of fusion calling. We validated annoFuse using a random cohort of TCGA RNA-Seq samples (N = 160) and achieved a 96% sensitivity for retention of high-confidence fusions (N = 603). annoFuse uses FusionAnnotator annotations to filter non-oncogenic and/or artifactual fusions. Then, fusions are prioritized if previously reported in TCGA and/or fusions containing gene partners that are known oncogenes, tumor suppressor genes, COSMIC genes, and/or transcription factors. We applied annoFuse to fusion calls from pediatric brain tumor RNA-Seq samples (N = 1028) provided as part of the Open Pediatric Brain Tumor Atlas (OpenPBTA) Project to determine recurrent fusions and recurrently-fused genes within different brain tumor histologies. annoFuse annotates protein domains using the PFAM database, assesses reciprocality, and annotates gene partners for kinase domain retention. As a standard function, reportFuse enables generation of a reproducible R Markdown report to summarize filtered fusions, visualize breakpoints and protein domains by transcript, and plot recurrent fusions within cohorts. Finally, we created shinyFuse for algorithm-agnostic interactive exploration and plotting of gene fusions., Conclusions: annoFuse provides standardized filtering and annotation for gene fusion calls from STAR-Fusion and Arriba by merging, filtering, and prioritizing putative oncogenic fusions across large cancer datasets, as demonstrated here with data from the OpenPBTA project. We are expanding the package to be widely-applicable to other fusion algorithms and expect annoFuse to provide researchers a method for rapidly evaluating, prioritizing, and translating fusion findings in patient tumors.

Medulloblastoma is a highly heterogeneous pediatric brain tumor with five molecular subtypes, Sonic Hedgehog TP53-mutant, Sonic Hedgehog TP53-wildtype, WNT, Group 3, and Group 4, defined by the World Health Organization. The current mechanism for classification into these molecular subtypes is through the use of immunostaining, methylation, and/or genetics. We surveyed the literature and identified a number of RNA-Seq and microarray datasets in order to develop, train, test, and validate a robust classifier to identify medulloblastoma molecular subtypes through the use of transcriptomic profiling data. We have developed a GPL-3 licensed R package and a Shiny Application to enable users to quickly and robustly classify medulloblastoma samples using transcriptomic data. The classifier utilizes a large composite microarray dataset (15 individual datasets), an individual microarray study, and an RNA-Seq dataset, using gene ratios instead of gene expression measures as features for the model. Discriminating features were identified using the limma R package and samples were classified using an unweighted mean of normalized scores. We utilized two training datasets and applied the classifier in 15 separate datasets. We observed a minimum accuracy of 85.71% in the smallest dataset and a maximum of 100% accuracy in four datasets with an overall median accuracy of 97.8% across the 15 datasets, with the majority of misclassification occurring between the heterogeneous Group 3 and Group 4 subtypes. We anticipate this medulloblastoma transcriptomic subtype classifier will be broadly applicable to the cancer research and clinical communities., Competing Interests: The authors have declared that no competing interests exist.

PALB2 (partner and localizer of BRCA2) gene encodes a protein that colocalizes with BRCA2 in nuclear foci and likely permits the stable intranuclear localization and accumulation of BRCA2 PALB2 plays a critical role in maintaining genome integrity through its role in the Fanconi anemia and homologous recombination DNA repair pathways. It has a known loss-of-function disease mechanism. Biallelic PALB2 pathogenic variants have been described in autosomal recessive Fanconi anemia. Heterozygous pathogenic variants in PALB2 are associated with increased risk for female and male breast cancer and pancreatic cancer ( Science 324: 217; Cancer Res 71: 2222-2229; N Engl J Med 371: 497-506). Heterozygous germline PALB2 mutations have also been observed in patients with medulloblastoma ( Lancet Oncol 19: 785-798). However, PALB2 -related cancer predisposition to high-grade gliomas has not been reported. Here we report a germline PALB2 pathogenic variant (c.509&#95;510delGA, p.Arg170Ilefs*14, NM&#95;024675.3) found in a pediatric patient with high-grade glioma. This variant was first identified by tumor sequencing using the Children's Hospital of Philadelphia (CHOP) Comprehensive Solid Tumor Panel and then confirmed to be a germline change using the CHOP Comprehensive Hereditary Cancer Panel on DNA from a blood sample of this patient. Parental studies showed that this variant was paternally inherited. Further studies are needed to illustrate if pathogenic variants in PALB2 convey increased risk to developing brain tumor. This case also highlights the potential of identifying germline mutation through tumor sequencing., (© 2020 Zhong et al.; Published by Cold Spring Harbor Laboratory Press.)

Children diagnosed with brain tumors have the lowest overall survival of all pediatric cancers. Recent molecular studies have resulted in the discovery of recurrent driver mutations in many pediatric brain tumors. However, despite these molecular advances, the clinical outcomes of high grade tumors, including H3K27M diffuse midline glioma (H3K27M DMG), remain poor. To address the paucity of tissue for biological studies, we have established a comprehensive protocol for the coordination and processing of donated specimens at postmortem. Since 2010, 60 postmortem pediatric brain tumor donations from 26 institutions were coordinated and collected. Patient derived xenograft models and cell cultures were successfully created (76% and 44% of attempts respectively), irrespective of postmortem processing time. Histological analysis of mid-sagittal whole brain sections revealed evidence of treatment response, immune cell infiltration and the migratory path of infiltrating H3K27M DMG cells into other midline structures and cerebral lobes. Sequencing of primary and disseminated tumors confirmed the presence of oncogenic driver mutations and their obligate partners. Our findings highlight the importance of postmortem tissue donations as an invaluable resource to accelerate research, potentially leading to improved outcomes for children with aggressive brain tumors.

Background: Pediatric high-grade gliomas (pHGGs) are incurable malignant brain cancers. Clear somatic genetic drivers are difficult to identify in the majority of cases. We hypothesized that this may be due to the existence of germline variants that influence tumor etiology and/or progression and are filtered out using traditional pipelines for somatic mutation calling., Methods: In this study, we analyzed whole-genome sequencing (WGS) datasets of matched germlines and tumor tissues to identify recurrent germline variants in pHGG patients., Results: We identified two structural variants that were highly recurrent in a discovery cohort of 8 pHGG patients. One was a ~ 40 kb deletion immediately upstream of the NEGR1 locus and predicted to remove the promoter region of this gene. This copy number variant (CNV) was present in all patients in our discovery cohort (n = 8) and in 86.3% of patients in our validation cohort (n = 73 cases). We also identified a second recurrent deletion 55.7 kb in size affecting the BTNL3 and BTNL8 loci. This BTNL3-8 deletion was observed in 62.5% patients in our discovery cohort, and in 17.8% of the patients in the validation cohort. Our single-cell RNA sequencing (scRNA-seq) data showed that both deletions result in disruption of transcription of the affected genes. However, analysis of genomic information from multiple non-cancer cohorts showed that both the NEGR1 promoter deletion and the BTNL3-8 deletion were CNVs occurring at high frequencies in the general population. Intriguingly, the upstream NEGR1 CNV deletion was homozygous in ~ 40% of individuals in the non-cancer population. This finding was immediately relevant because the affected genes have important physiological functions, and our analyses showed that NEGR1 expression levels have prognostic value for pHGG patient survival. We also found that these deletions occurred at different frequencies among different ethnic groups., Conclusions: Our study highlights the need to integrate cancer genomic analyses and genomic data from large control populations. Failure to do so may lead to spurious association of genes with cancer etiology. Importantly, our results showcase the need for careful evaluation of differences in the frequency of genetic variants among different ethnic groups.

The environmental stress response (ESR) is critical for cell survival. Yeast cells unable to synthesize inositol pyrophosphates (PP-InsPs) are unable to induce the ESR. We recently discovered a diphosphoinositol pentakisphosphate (PP-InsP 5 ) phosphatase in Saccharomyces cerevisiae encoded by SIW14 Yeast strains deleted for SIW14 have increased levels of PP-InsPs. We hypothesized that strains with high inositol pyrophosphate levels will have an increased stress response. We examined the response of the siw14 Δ mutant to heat shock, nutrient limitation, osmotic stress, and oxidative treatment using cell growth assays and found increased resistance to each. Transcriptional responses to oxidative and osmotic stresses were assessed using microarray and reverse transcriptase quantitative PCR. The ESR was partially induced in the siw14 Δ mutant strain, consistent with the increased stress resistance, and the mutant strain further induced the ESR in response to oxidative and osmotic stresses. The levels of PP-InsPs increased in WT cells under oxidative stress but not under hyperosmotic stress, and they were high and unchanging in the mutant. Phosphatase activity of Siw14 was inhibited by oxidation that was reversible. To determine how altered PP-InsP levels affect the ESR, we performed epistasis experiments with mutations in rpd3 and msn2/4 combined with siw14 Δ. We show that mutations in msn2 Δ and msn4 Δ, but not rpd3 , are epistatic to siw14 Δ by assessing growth under oxidative stress conditions and expression of CTT1 Msn2-GFP nuclear localization was increased in the siw14 Δ. These data support a model in which the modulation of PP-InsPs influence the ESR through general stress response transcription factors Msn2/4., (© 2020 Steidle et al.)

Dysembryoplastic neuroepithelial tumors (DNT) lacking key diagnostic criteria are challenging to diagnose and sometimes fall into the broader category of mixed neuronal-glial tumors (MNGT) or the recently described polymorphous low-grade neuroepithelial tumor of the young (PLNTY). We examined 41 patients with DNT, MNGT, or PLNTY for histologic features, genomic findings, and progression-free survival (PFS). Genomic analysis included sequence and copy number variants and RNA-sequencing. Classic DNT (n = 26) was compared with those with diffuse growth without cortical nodules (n = 15), 6 of which exhibited impressive CD34 staining classifying them as PLNTY. Genomic analysis was complete in 33, with sequence alterations recurrently identified in BRAF, FGFR1, NF1, and PDGFRA, as well as 7 fusion genes involving FGFR2, FGFR1, NTRK2, and BRAF. Genetic alterations did not distinguish between MNGTs, DNTs, or PLNTYs; however, FGFR1 alterations were confined to DNT, and PLNTYs contained BRAF V600E or FGFR2 fusion genes. Analysis of PFS showed no significant difference by histology or genetic alteration; however, numbers were small and follow-up time short. Further molecular characterization of a PLNTY-related gene fusion, FGFR2-CTNNA3, demonstrated oncogenic potential via MAPK/PI3K/mTOR pathway activation. Overall, DNT-MNGT spectrum tumors exhibit diverse genomic alterations, with more than half (19/33) leading to MAPK/PI3K pathway alterations., (© 2019 American Association of Neuropathologists, Inc. All rights reserved.)