Mariëtte E. G. Kranendonk

DNA methylation-based classification is increasingly a cornerstone of CNS tumor diagnostics. Recently,nanopore sequencing enables very rapid methylation profiling to support surgical decision making. Time-constrained sequencing yields sparse methylation profiles, necessitating specialized classifiers for accurate predictions. All publicly available sparse-profile classifiers rely on a single reference set of only 2,801 samples published in 2018 and its accompanying classification system. Here we present Sturgeon V2, trained on nearly 10,000 methylation profiles assembled from a range of public repositories and collaborations. To harmonize differences in tumor class labels, we developed an iterative semi-supervised relabeling strategy with a two-tiered concordance filter. We demonstrate that this filtering is essential for optimal performance. Compared to Sturgeon V1, we further redesigned the classifier architecture to provide more stable, and consistent confidence estimates while accumulating sequencing data and we introduce an updated class system including new classes, such as meningioma subtypes, PATZ-fusion neuroepithelial tumors and PLAG1/2-amplified embryonal tumors. In a retrospective intraoperative cohort of 94 pediatric cases, Sturgeon V2 was confidently correct in 85 cases (Sturgeon V1: 78) with one confident misclassification, and in simulated sequencing runs (n=1880) reduced the error rate among confident calls from 7.1% to 2.8%, outperforming publicly available alternatives. Sturgeon V2 is the first openly available, locally executable classifier for sparse methylation profiles trained beyond the 2018 reference era.

Background: Central nervous system (CNS) tumors represent the leading cause of pediatric cancer-related deaths. Primary treatment often involves neurosurgical tumor resection. Accurate diagnosis is crucial to perform the best-suited extent of resection. Recently, we published Sturgeon, an AI-based validated intraoperative nanopore sequencing tool, delivering accurate methylation-based diagnoses during surgery. Although several other nanopore sequencing strategies have been described, clear evidence of clinical impact remains critically absent. Here, we report a care evaluation analyzing the impact of Sturgeon on real-time pediatric neurosurgical decision-making. Methods: Since May 2023, a dual diagnostic neuro-oncological workflow incorporating intraoperative frozen section analyses and ultra-fast nanopore sequencing using Sturgeon has been fully implemented as standard of care at the Princess Máxima Center for Pediatric Oncology in the Netherlands. This intraoperative diagnostic workflow has been applied to all pediatric patients (<19 years of age) with primary CNS tumors and the multidisciplinary indication for tumor resection surgery. Results: Sturgeon delivered correct diagnoses in 82 out of 94 consecutive patients (87.2%, <90 minutes), no diagnosis in 11.7% and one incorrect diagnosis (1.1%). The diagnosis obtained by Sturgeon supported the intended surgical strategy (85.7%) or changed the strategy (14.3%) toward a more aggressive or limited resection. This contributed to a low complication rate and less second-look surgeries. Earlier communication of the histomolecular diagnosis to patients and their families was observed. Conclusions: Intraoperative use of Sturgeon provides essential guidance toward the most optimal neurosurgical strategy for pediatric CNS tumors and thereby has great potential to contribute to better clinical outcome.

Meningiomas in pediatric and adolescent/young adult patients are poorly characterized biologically and clinically, and risk stratification is largely extrapolated from adult tumors. We analyze 293 tumors from patients aged 0-39 years using integrated histopathological and molecular profiling. Youth-onset meningiomas are enriched for NF2 and SMARCE1 alterations and exhibit a gain-dominated copy-number landscape, including recurrent chr17q gain, whereas canonical adult high-risk features, such as chr1p loss, lack prognostic significance. Adult-derived prognostic frameworks, including WHO grade, methylation-based stratification and integrated risk scores, fail to predict progression in patients ≤21 years of age. Tumors segregate into age-enriched epigenetic clusters defined by SMARCE1, NF2 and BAP1 alterations. Among NF2-altered tumors, patterns of Merlin inactivation, shaped by germline status and co-occurring copy-number variations, delineate biologically divergent subsets. In patients ≤21 years, extent of resection is the dominant predictor of outcome, while molecular features further refine risk assessment. These findings define pediatric and young adult meningiomas as a distinct molecular entity and support age-adapted risk refinement that integrates molecular features with strong clinical determinants.

The clinical trial landscape of molecularly targeted treatments for pediatric low-grade glioma (pLGG) has created an exciting and hopeful era for both patients and clinicians alike. Despite numerous clinical trials investigating the use of targeted agents for pLGG, only two oral precision-based regimens for pLGG have received federal agency approval. However, enthusiasm surrounding recently completed early phase clinical trials has resulted in increased off-label prescribing practices beyond the federally-approved indications, despite a lack of phase 3 clinical trial data and an incomplete understanding of the long-term radiographic, functional outcomes, and toxicity for both approved and experimental therapies. These gaps in knowledge are critically important to consider when selecting therapies for patients with pLGG, as the prevention and reduction of late effects in pLGG survivors is crucial to prevent long-term morbidity. In this editorial by the clinical working group of the International pLGG Coalition, we discuss the landscape of molecularly targeted therapies for pLGG, outline the unanswered questions for the use of novel therapies in the management of pLGG, review the risks and benefits of early off-label use of targeted agents, and discuss the importance of patience and evidence-based clinical practice in the rapidly evolving era of precision medicine.

Diffuse midline glioma (DMG) is a highly aggressive and untreatable pediatric cancer primarily arising in the pontine brainstem region, necessitating the development of representative models for treatment advance. Here we developed an FGF4-driven human brainstem organoid model, which we used to genetically engineer H3.3K27M-altered DMG. We demonstrated that brainstem pontine glial specification is critical for DMG tumorigenesis, yielding infiltrative tumors that recapitulate patient-representative intratumoral heterogeneity. Prolonged GD2 chimeric antigen receptor (CAR) T cell treatment mirrored clinical outcomes and revealed extensive transcriptional heterogeneity, from which both potent effector and dysfunctional CAR T cell populations could be identified. Furthermore, incorporation of myeloid cells generated DMG-specific microglia that reduced treatment efficacy and revealed CAR T cell functional states most vulnerable to microglia-mediated immunosuppression. Thus, we present a representative DMG model offering a months-long experimental window in vitro, which we leveraged to delineate CAR T cell functionality and microglial impact, aiding therapy development for this devastating disease.

For pediatric patients with central nervous system (CNS) tumors, primary treatment often involves neurosurgical tumor resection. Accurate diagnosis is crucial to perform the best-suited extent of resection. Since two years, Sturgeon, an AI-based validated intraoperative nanopore sequencing tool, has been fully integrated with frozen section analyses as standard of care in our nationwide centralized pediatric oncology hospital. This care evaluation is the first to demonstrate the impact of Sturgeon on neurosurgical decision-making. Sturgeon delivered correct diagnoses in 82 out of 94 consecutive patients (87.2%, <90 minutes), no diagnosis in 11.7% and 1 incorrect diagnosis. The diagnosis obtained by Sturgeon supported the intended surgical strategy (85.7%) or changed the strategy (14.3%) toward a more aggressive or limited resection. This resulted in only 3.2% second-look surgeries. In conclusion, intraoperative use of Sturgeon provides essential guidance toward the most optimal neurosurgical strategy and thereby has great potential to contribute to better clinical outcome.

Background: Pilocytic astrocytomas (PAs) are the most common pediatric central nervous system tumors, which present with limited genetic but significant clinical heterogeneity. Current treatment strategies are partly effective, but tumors often progress, and patients experience long-term side effects, highlighting the need for additional novel therapeutic approaches. A promising alternative approach could be targeting the tumor immune microenvironment (TIME); however, a comprehensive overview of the TIME of PAs across different anatomical tumor locations is currently lacking. The aim of this study was to comprehensively characterize the cellular and transcriptional landscape of pediatric PAs. Methods: We employed a multimodal, integrative approach using single-nucleus and bulk RNA-sequencing alongside high-dimensional immunofluorescence imaging and flow cytometry to elucidate the transcriptional landscape and cellular composition of pediatric PAs across tumor locations. Results: Our analysis uncovered neoplastic cell transcriptional heterogeneity reflective of aberrant glial differentiation. Moreover, we provided a detailed characterization of the TIME, revealing pro-inflammatory brain-resident microglia and abundant activated monocyte-derived macrophages and T cells. Deconvolution of bulk RNA-sequencing data revealed variation in tumor and TIME composition across anatomical tumor locations. Suprasellar tumors additionally exhibited increased expression of immune-related genes compared to tumors arising in other anatomical locations. Conclusions: Together, our multimodal in-depth characterization provides detailed insights into the transcriptional and cellular heterogeneity of pediatric PAs across distinct anatomical tumor locations, which could aid in the development of novel (immuno)therapeutic approaches.

Background: Pediatric-type diffuse high-grade gliomas (pHGGs) are a leading cause of pediatric cancer-related mortality. Although immunotherapy offers a promising treatment avenue, clinical responses in pHGG patients remain limited. A detailed understanding of the tumor immune microenvironment (TIME) is essential for advancing immunotherapeutic strategies. Methods: We performed single-cell spatial analysis integrating cyclical immunofluorescence imaging and spatial molecular imaging to interrogate the proteomic and transcriptomic landscape of pHGGs. A tissue microarray comprising 32 diagnostic patient-derived pHGG samples was utilized to map the spatial distribution of immune and tumor cells. Results: Our analyses reveal that the pHGG TIME is predominantly composed of myeloid cells, including brain-­resident microglia and monocyte-derived macrophages, with only few T cells. A significant subset of these myeloid cells expresses mesenchymal (MES)-like genes and is positive for SPP1 and GPNMB. Spatial mapping further demonstrated that SPP1+/GPNMB+ myeloid cells localize in close proximity to MES-like tumor cells, and negatively correlate with the location and presence of CD8+ T cells. These cells also express genes related to immunosuppression and epithelial-to-mesenchymal transition, indicating their potential role in establishing an immunosuppressive niche. Conclusions: Our findings reveal a distinct immune landscape in pHGGs characterized by SPP1+/GPNMB+ myeloid cells which may contribute to the exclusion of CD8+ T cells. This spatially resolved insight identifies these myeloid cells as promising therapeutic targets and provides a rationale for developing novel immunotherapeutic strategies to improve outcomes in pediatric high-grade gliomas.

Background: Pediatric high-grade central nervous system (pHG-CNS) tumors are the leading cause of childhood cancer-related deaths, partly due to poor response to standard treatments. B7-H3 is reportedly expressed in pHG-CNS tumors, making antigen-targeting therapies, including anti-B7-H3 chimeric antigen receptor T-cell (CAR-T) therapy, promising. However, given substantial inter-tumoral protein expression diversity in CNS tumors, it’s unclear which patients might benefit from these treatments. Therefore, we studied B7-H3 expression in a large set of pHG-CNS tumors. Methods: We retrospectively analyzed 136 pHG-CNS tumors (embryonal tumors (n = 44), high-grade neuroepithelial tumors (n = 4), ependymomas (n = 30),high-grade gliomas (HGGs, n = 58)) from the Princess Máxima Center for Pediatric Oncology. CD276 mRNA (encoding B7-H3) and immunohistochemical (IHC) protein expression of B7-H3 was measured and correlated to clinical-molecular data. Results: Large variability of B7-H3 mRNA and protein expression was observed both between and within tumor types. Many tumors expressed B7-H3, but 30% of diffuse midline glioma H3K27-altered and ependymomas posterior fossa type A showed no or minimal expression. This variability was unrelated to patient age, tumor location, epigenetic subclass, or molecular tumor driver. B7-H3 negative cases were high in tumor cells, ruling out low tumor cell percentage as an explanation for negative staining. Conclusions: Our study of B7-H3-expression in the largest pHG-CNS tumor set to date revealed significant interpatient variability and numerous negative cases. Our results urge for tumor tissue acquisition at enrollment in B7-H3 targeting therapeutic trials (including CAR-T cells) in order to thoroughly assess the value of IHC B7-H3 expression as biomarker and, ultimately, to allow for more tailored therapy.