👤 Uri Tabori

To characterize the clinical, radiological, and molecular characteristics of CNS tumors associated with Noonan syndrome (NS) and other non-Neurofibromatosis type 1 RASopathies. Twenty-four patients with concern for NS underwent clinical and central radiological review in this multi-institutional study. Whole-exome sequencing, RNA sequencing, and methylation analyses of peripheral blood and/or tumor specimens were performed. Nineteen (79%) of 24 participants had NS, 17/19 (89%) of which had a germline The online version contains supplementary material available at 10.1007/s11060-026-05478-7. Show less

To characterize the clinical, radiological, and molecular characteristics of CNS tumors associated with Noonan syndrome (NS) and other non-Neurofibromatosis type 1 RASopathies. Twenty-four patients with concern for NS underwent clinical and central radiological review in this multi-institutional study. Whole-exome sequencing, RNA sequencing, and methylation analyses of peripheral blood and/or tumor specimens were performed. Nineteen (79%) of 24 participants had NS, 17/19 (89%) of which had a germline Show less

Pediatric Low-Grade Glioma (pLGG) is the most common pediatric brain tumor, and radiomics-based machine learning (ML) models have shown promise in identifying BRAF fusion and BRAF p.V600E mutation. This bicentric retrospective study included 495 children diagnosed between 1999 and 2023. The local hospital dataset comprised Magnetic Resonance Imaging (MRI) scans of patients with BRAF fusion (n = 190), BRAF p.V600E mutation (n = 95), FGFR1 (n = 25), and other molecular subtypes (n = 144), while an external dataset included BRAF fusion (n = 32) and BRAF p.V600E mutation (n = 9) cases. Radiomics features were extracted from Fluid-Attenuated Inversion Recovery images, and Random Forest classifiers were trained using Monte Carlo data splits and leave-one-out validation. The best-performing model achieved an average one-vs-the-rest area under receiver operating characteristic curve of 0.819 (95% confidence interval [0.791, 0.848]). This study highlights the potential of radiomics-based ML models for molecular subtype differentiation in pLGG, with per-patient predictions enabling outlier identification and subgroup performance evaluation. Show less

CNS tumors are a significant cause of death in the adolescent and young adult (AYA; age 15-39 years) population; however, these patients often lack standardized treatments. In Canada, we have established national multidisciplinary virtual AYA CNS tumor board rounds (national rounds) to improve and standardize care. From November 2021 to June 2024, 185 AYA patients with CNS tumors were presented from centers nationwide, including 138 patients with glioma. Before case presentation, 5.1% of patients with glioma were taking targeted agents or were enrolled in clinical trials. However, after national rounds, 72.6% of patients with pediatric-type glioma and 45.9% of patients with adult-type glioma were recommended clinical trials and/or targeted agents. Among the 44 patients with glioma who had received radiation therapy before national rounds, only 14 were recommended further radiation. Cumulatively, 68.9% of patients analyzed received a treatment recommendation that represented a change in clinical management compared with their previous treatments. Concurrently, we performed molecular review of 174 AYA CNS tumors during the study time frame. Using TruSight, we identified gene fusions involving Our results suggest that national rounds with centralized molecular review can direct AYA patients with CNS tumors toward targeted agents and clinical trials, while deferring radiation therapy. Taken together, our work details an ongoing effort to improve and standardize care of AYA patients with CNS tumors in Canada. Show less