Eugène T. P. Verwiel

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.

Whole genome sequencing (WGS) is increasingly accessible in clinical practice, enabling pharmacogenomics (PGx) integration, including in pediatric oncology. However, the lack of validated software to accurately annotate clinically actionable PGx variants from WGS limits routine implementation. We therefore aimed to identify and validate a PGx annotation tool suitable for clinical use in pediatric oncology. We evaluated several tools for technical performance and clinical integration. The Pharmacogenomics Clinical Annotation Tool (PharmCAT) was selected for its alignment with expert‐reviewed PGx guidelines, inclusion of relevant gene‐drug pairs and prescribing recommendations. PharmCAT was validated using an in silico dataset by introducing known diplotypes into the Genome in a Bottle (GIAB) reference sample, complemented by four clinically confirmed diplotypes from three patients. Diplotype and phenotype outputs from WGS were compared against the GIAB and patient reference data. We tested 71 diplotypes across seven genes ( TPMT , NUDT15 , CYP3A5 , CYP2C9 , CYP2C19 , DPYD , UGT1A1 ), using ≥ 95% sensitivity and specificity as validation criteria. CYP2D6 was excluded from this validation due to genotyping limitations from the input data used by PharmCAT. The tool was integrated into our WGS analysis pipeline using containerization for consistent, reproducible execution. Diplotype and phenotype results from PharmCAT fully matched the in silico GIAB set and patient samples, achieving 100% sensitivity and specificity. These findings confirm PharmCAT as a reliable tool for preemptive PGx annotation, supporting implementation in pediatric oncology. Its clinical integration supports individualized dosing, reducing adverse effects and improving efficacy. Further validation of additional gene‐drug pairs will broaden its clinical utility.

In pediatric oncology, pharmacogenetic guidelines are underutilized and the potential impact of pre‐emptive pharmacogenetic screening remains largely unexplored despite this field's need for individualized approaches. While comprehensive pharmacogenetic guidelines are not yet available for all anticancer drugs, evidence‐based recommendations exist for a subset of supportive care drugs and anticancer drugs, including thiopurines, irinotecan, capecitabine, and 5‐fluorouracil. In this study, we evaluate the potential impact of pre‐emptive pharmacogenetic screening by retrospectively identifying opportunities for dose or treatment adjustments within a national pediatric oncology cohort. Our analysis focused on ten genes and 28 drugs relevant to pediatric oncology, which are included in the Clinical Pharmacogenetics Implementation Consortium and the Dutch Pharmacogenetics Working Group guidelines. In a cohort of 1,151 pediatric oncology subjects, we identified that 16% of individuals could have benefited from altered drug dosing or treatment. These include dose and treatment recommendations for allopurinol, nonsteroidal anti‐inflammatory drugs, phenytoin, amitriptyline, proton pump inhibitors, voriconazole, tramadol, codeine, paroxetine, tacrolimus, rasburicase, and 6‐mercaptopurine. As genetic data increasingly becomes available through molecular diagnostics in pediatric oncology, there is a unique opportunity to re‐utilize this data for pre‐emptive pharmacogenetic screening. Leveraging genetic profiles to guide clinicians in drug selection and dose optimization can improve patient outcomes by enhancing the safety and efficacy of treatments. We therefore recommend incorporating pharmacogenetic screening into clinical workflows to advance personalized medicine in pediatric oncology.

With many rare tumor types, acquiring the correct diagnosis is a challenging but crucial process in pediatric oncology. Here, we present M&M, a pan-cancer ensemble-based machine learning algorithm tailored towards inclusion of rare tumor types. The RNA-seq based algorithm can classify 52 different tumor types (precision ∼ 99%, recall ∼ 80%), plus the underlying 96 tumor subtypes (precision ∼ 96%, recall ∼ 70%). For low-confidence classifications, a comparable precision is achieved when including the three highest-scoring labels. M&M’s pan-cancer setup allows for easy clinical implementation, requiring only one classifier for all incoming diagnostic samples, including samples from different tumor stages and treatment statuses. Simultaneously, its performance is comparable to existing tumor- and tissue-specific classifiers. The introduction of an extensive pan-cancer classifier in diagnostics has the potential to increase diagnostic accuracy for many pediatric cancer cases, thereby contributing towards optimal patient survival and quality of life.

The increase in speed, reliability, and cost-effectiveness of high-throughput sequencing has led to the widespread clinical application of genome (WGS), exome (WXS), and transcriptome analysis. WXS and RNA sequencing is now being implemented as the standard of care for patients and for patients included in clinical studies. To keep track of sample relationships and analyses, a platform is needed that can unify metadata for diverse sequencing strategies with sample metadata whilst supporting automated and reproducible analyses, in essence ensuring that analyses are conducted consistently and data are Findable, Accessible, Interoperable, and Reusable (FAIR).We present “Trecode”, a framework that records both clinical and research sample (meta) data and manages computational genome analysis workflows executed for both settings, thereby achieving tight integration between analysis results and sample metadata. With complete, consistent, and FAIR (meta) data management in a single platform, stacked bioinformatic analyses are performed automatically and tracked by the database, ensuring data provenance, reproducibility, and reusability, which is key in worldwide collaborative translational research. The Trecode data model, codebooks, NGS workflows, and client programs are publicly available. In addition, the complete software stack is coded in an Ansible playbook to facilitate automated deployment and adoption of Trecode by other users.

Chromosomal alterations have recurrently been identified in Wilms tumors (WTs) and some are associated with poor prognosis. Gain of 1q (1q+) is of special interest given its high prevalence and is currently actively studied for its prognostic value. However, the underlying mutational mechanisms and functional effects remain unknown. In a national unbiased cohort of 30 primary WTs, we integrated somatic SNVs, CNs and SVs with expression data and distinguished four clusters characterized by affected biological processes: muscle differentiation, immune system, kidney development and proliferation. Combined genome-wide CN and SV profiles showed that tumors profoundly differ in both their types of 1q+ and genomic stability and can be grouped into WTs with co-occurring 1p−/1q+, multiple chromosomal gains or CN neutral tumors. We identified 1q+ in eight tumors that differ in mutational mechanisms, subsequent rearrangements and genomic contexts. Moreover, 1q+ tumors were present in all four expression clusters reflecting activation of various biological processes, and individual tumors overexpress different genes on 1q. In conclusion, by integrating CNs, SVs and gene expression, we identified subgroups of 1q+ tumors reflecting differences in the functional effect of 1q gain, indicating that expression data is likely needed for further risk stratification of 1q+ WTs.

Aims: Cell regulation by signaling reactive oxygen species (sROS) is often incorrectly studied through extracellular oxidant addition. Here, we used the membrane-permeable antioxidant Trolox to examine the role of sROS in mitochondrial morphology, oxidative phosphorylation (OXPHOS), and cytosolic calcium (Ca²⁺) handling in healthy human skin fibroblasts. Results and Innovation: Trolox treatment reduced the levels of 5-(and-6)-chloromethyl-2′,7′-dichlorodihydro-fluorescein (CM-H₂DCF) oxidizing ROS, lowered cellular lipid peroxidation, and induced a less oxidized mitochondrial thiol redox state. This was paralleled by increased glutathione- and mitofusin-dependent mitochondrial filamentation, increased expression of fully assembled mitochondrial complex I, elevated activity of citrate synthase and OXPHOS enzymes, and a higher cellular O₂ consumption. In contrast, Trolox did not alter hydroethidium oxidation, cytosolic thiol redox state, mitochondrial NAD(P)H levels, or mitochondrial membrane potential. Whole genome expression profiling revealed that Trolox did not trigger significant changes in gene expression, suggesting that Trolox acts downstream of this process. Cytosolic Ca²⁺ transients, induced by the hormone bradykinin, were of a higher amplitude and decayed faster in Trolox-treated cells. These effects were dose-dependently antagonized by hydrogen peroxide. Conclusions: Our findings suggest that Trolox-sensitive sROS are upstream regulators of mitochondrial mitofusin levels, morphology, and function in healthy human skin fibroblasts. This information not only facilitates the interpretation of antioxidant effects in cell models (of oxidative-stress), but also contributes to a better understanding of ROS-related human pathologies, including mitochondrial disorders. Antioxid. Redox Signal. 17, 1657–1669.