Citations

Abstract Oncogenic BRAF alterations occur in a subset of diffuse gliomas across WHO grades and are increasingly identified through modern molecular diagnostics. In addition to standard glioma therapies, targeted treatments are available for patients with BRAF-altered glioma supported by variable evidence spanning randomized trials, single-arm studies, and real-world evidence. This joint consensus review from the Society for Neuro-Oncology (SNO) and the European Association of Neuro-Oncology (EANO) synthesizes current knowledge on the diagnosis and management of BRAF-altered gliomas across age groups, tumor grades, and lines of therapy. Particular emphasis is placed on expert consensus in clinical scenarios where high-quality trial evidence remains limited. The review addresses rationale testing for BRAF alterations, selection, and monitoring of targeted therapies, management of treatment-related toxicities, approaches to resistance, and priorities for future research. It aims to provide practical, evidence-based guidance for clinicians while highlighting gaps to inform prospective studies.

Abstract Background DNA methylation profiling can be used to robustly predict postsurgical outcomes and response to radiotherapy (RT) for meningioma patients. To allow for seamless integration of these complementary models into clinical practice, a practical framework is needed. Methods We leveraged a cohort of nearly 2000 surgically-treated meningiomas with DNA methylation profiling and clinical outcomes data. Existing methylation-based prediction models were dichotomized to yield four risk groups: low and high recurrent risk, each with RT sensitive and resistant subgroups. Risk groups were correlated with progression-free survival in the context of existing biomarkers including extent of resection and WHO grade. Results We first demonstrated that all risk groups benefit from gross total resection. All “high-risk, RT sensitive” tumors (n = 306, 15.7%) also benefited from adjuvant RT: after GTR, median PFS increased from 4.68 (4.13-9.48) years to not reached (P = .003); after subtotal resection (STR), from 2.12 (1.59-3.02) to 4.09 (3.41-not reached) years (P = .004). “Low-risk, RT sensitive cases” (n = 1207, 61.8%) also benefited from RT after STR (median PFS 7.39 (6.66-12.8) vs. 16.53 (10.35-not reached) years, P = .03), suggesting that RT be considered in these patients. Neither “low-risk RT resistant” (n = 84, 4.3%) nor “high-risk RT resistant” (n = 356, 18.2%) cases benefited from RT, and the latter group was associated with universally poor outcomes. Conclusions We identify methylation-defined risk groups of meningioma for which additional benefit is gained from adjuvant RT, leading to a clinical decision-making framework for straightforward integration of molecular models into clinical practice.

PURPOSE Recent studies reveal that 5%-18% of children with cancer harbor pathogenic variants in known cancer-predisposing genes. However, DNA damage repair (DDR) genes, which are frequently somatically altered in pediatric tumors, have not been systematically examined as a source of novel cancer-predisposing signals. METHODS To address this gap, we interrogated 189 DDR genes for presence of germline predisposing variants (PV) among 5,993 childhood cancer cases and 14,477 adult noncancer controls (discovery cohort). PV were determined using a tiered approach incorporating ClinVar annotations, InterVar classification, and in silico tools (REVEL, CADD, and MetaSVM). Using logistic and firth regression, we identified genes with PV statistically enriched in the germline of children with tumors and replicated findings among 1,497 additional childhood cancer cases across three independent cohorts. RESULTS Analysis across all cases with cancer revealed enrichment of TP53 PV. Cancer-specific analyses confirmed known associations including germline TP53 PV in adrenocortical carcinoma, high-grade glioma (HGG), and medulloblastoma (MB), PMS2 in HGG and non-Hodgkin lymphoma (NHL), MLH1 in HGG, BRCA2 in NHL, and BARD1 in neuroblastoma. In addition, four novel associations were uncovered, including BRCA1 in ependymoma, SPIDR in HGG, SMC5 in MB, and SMARCAL1 in osteosarcoma (OS). Importantly, the SMARCAL1 :OS association was significant in the discovery (6/230, 2.6%, false discovery rate [FDR] logistic = 0.0189) as well as all three replication cohorts (Childhood Cancer Survivor Study: 8/275, 2.9%; P Fisher < .0001; Cancer Predisposition Syndrome-German Childhood Cancer Registry: 4/135, 3%, P Fisher = .002; Individualized Therapy for Relapsed Malignancies in Childhood: 4/217, 1.8%, P Fisher = .012). The remaining wild-type SMARCAL1 allele was deleted in three of four OS tumors with available data. CONCLUSION Our study confirms the relevance DDR genetic variation in pediatric cancer risk and establishes SMARCAL1 as a novel OS predisposing gene, providing insights into tumor biology and creating opportunities to optimize care for patients with this challenging tumor.

ImportanceThere exists substantial heterogeneity in outcomes within T stages for patients with cutaneous squamous cell carcinoma (cSCC).ObjectiveTo determine whether a customized generative pretrained transformer model, trained on a comprehensive dataset with more than 1 trillion parameters and equipped with relevant focused context and retrieval augmented generation (RAG), could excel in aggregating and interpreting vast quantities of data to develop a novel class-based risk stratification system that outperforms the current standards.Design, Setting, and ParticipantsTo build the RAG knowledge base, a systematic review of the literature was conducted that addressed risk factors for poor outcomes in cSCC. Using the RAG-enabled generative pretrained transformer (GPT) model, we developed a novel class-based risk stratification system that assigned point values for risk factors, culminating in a GPT-based prognostication system called the artificial intelligence–derived risk score (AIRIS). The system’s performance was validated on a combined prospective and retrospective cohort of 2379 primary cSCC tumors (1996-2023) with at least 36 months of follow-up, against Brigham and Women’s Hospital (BWH) and American Joint Committee on Cancer Staging Manual, eighth edition (AJCC8) systems in stratifying risk for locoregional recurrence (LR), nodal metastasis (NM), distant metastasis (DM), and disease-specific death (DSD).Main Outcomes and MeasuresPerformance metrics evaluated included distinctiveness, homogeneity, and monotonicity, as defined by the AJCC8, as well as sensitivity, specificity, positive predictive value, negative predictive value, accuracy, the area under the receiver operating characteristic curve, and concordance.ResultsThe median age at diagnosis was 73 (IQR, 64-81) years, with 38.5% female patients and 61.5% male patients. The AIRIS prognostication system demonstrated superior sensitivity across all outcomes (LR, 49.1%; NM, 73.7%; DM, 82.5%; and DSD, 72.2%) and the highest area under the receiver operating characteristic curve values (LR, 0.69; NM, 0.81; DM, 0.85; and DSD, 0.80), indicating significantly enhanced discriminative capability compared with the BWH and AJCC8 systems. While all systems were comparably distinctive, the AIRIS prognostication system consistently demonstrated the lowest proportion of tumors exhibiting poor outcomes in low-risk categories, suggesting its improved homogeneity and monotonicity.Conclusions and RelevanceThe results of this diagnostic study suggest that the AIRIS system outperforms the existing BWH and AJCC8 prognostication systems, potentially providing a more effective tool for predicting poor outcomes in cSCC. This study illustrates the potential of large language models in refining prognostic tools, offering implications for treating patients with cancer.

Abstract Background Recently, a model to predict 5-year recurrence-free survival (RFS) and melanoma-specific survival (MSS) after sentinel lymph node biopsy (SLNB) was published. The aim of this study was to validate that model in a large independent international cohort. Methods The database of the Sentinel Lymph Node Working Group (SLNWG) was analysed for patients with malignant melanoma who underwent SLNB. Patients with clinical stage III melanoma, a history of other malignancies, or receiving concomitant systemic therapies during follow-up were excluded. The model’s predictive performance was evaluated using discrimination and calibration metrics in the eligible cohort. Decision curve analysis was performed to assess the clinical value of the model. Results The external validation cohort consisted of 6174 patients of the SLNWG from the USA, Europe, and Israel. A positive sentinel node was found in 788 patients (12.8%). The area under the time-dependent receiver operating characteristic (ROC) curve of the external validation was 0.76 (95% c.i. 0.74 to 0.77) for RFS and 0.79 (95% c.i. 0.76 to 0.81) for MSS. The model was well calibrated, as the observed 5-year survival rates aligned closely with the predicted survival rates (calibration slope of 0.98 for RFS and calibration slope of 0.99 for MSS). The model provided a net benefit versus the ‘treat all’ and ‘treat none’ strategies at the predetermined probability threshold for recurrence of 45%. Conclusion The model demonstrated good performance in a large heterogeneous independent cohort, emphasizing its robustness. Decision curve analysis revealed a clear net benefit of the model over a treat all strategy, highlighting its potential for clinical use.

Abstract Background There is limited data on the clinical effectiveness of upadacitinib (UPA), an oral selective inhibitor of Janus kinase 1 (JAKi), in patients with perianal Crohn's disease (pCD). The objective of this study was to evaluate the real-world effectiveness of UPA in pCD. Methods This retrospective analysis utilized data on adults (&gt;17 years) who initiated UPA at 45 mg/day for active pCD across 10 centers in the United States and Canada. Standardized data extraction and entry protocols were followed. The primary outcome was clinical response, defined as a ≥3-point reduction in Perianal Disease Activity Index (PDAI) between baseline and follow-up. Secondary outcomes included normalization of CRP (&lt;5 mg/L) or hsCRP (&lt;1 mg/L), clinical remission (PDAI ≤4), and rates of hospitalization, antibiotic use, corticosteroid initiation, and new pCD-related surgeries. Fistula healing on MRI pelvis fistula protocol was defined as an absence of T2-weighted hyperintensity and post-contrast enhancement on T1-weighted images. Predictive analyses used Cox proportional hazards models to evaluate baseline factors influencing time to PDAI remission, including BMI, CRP, albumin, PDAI, pCD disease duration, Montreal location and prior biologic exposure (&lt;2 vs 2+). Results A total of 81 patients were treated with UPA for pCD (median age 35 years and 54.3% male). Most had ileocolonic disease (65.4%), with 54% presenting with complex fistulas. Of these, 92.6% had prior anti-TNF exposure, and 91 (88.9%) had prior exposure to 2+ biologics (Table 1). During a median follow-up of 4 months, clinical response (PDAI) was achieved in 17.3%. Improvement was observed in pain and restriction of activities (27.2%), restriction of sexual activity (13.6%), reduction in number of fistulas (11.1%), degree of induration (11.1%), and discharge (35.8%). Median CRP reduction was 21.05% [IQR: 0.00–74.53], and 21.0% achieved a ≥50% reduction in CRP. MRI healing was limited to 17.7% (6/34). Proctitis decreased from 23.5% at baseline to 7.4% at follow-up. During follow-up, hospitalizations occurred in 9.9%, 14.8% required antibiotics, 8.6% underwent examination under anesthesia in 8.6%, seton placement in 6.2%, and abscess drainage in 6.2%. Patients with ileocolonic disease showed the highest remission (54%) and response (15%) rates, while MRI healing was limited across all Montreal locations (7.4%). Lower baseline CRP (p &lt; 0.05) and PDAI scores (p &lt; 0.01) predicted shorter time to remission. Number of prior biologic exposures (p =0.2) and Montreal location (p = 0.7) were not predictive of time to PDAI remission (Figure 1). Conclusion UPA in a real-world cohort is effective in the management of treatment-refractory pCD. Randomized trials are needed to confirm these observations.

The Neurohospitalist Core Competencies comprise a set of competency-based learning objectives that encapsulate the knowledge, skills, and attitudes of neurohospitalitists who specialize in the care of hospitalized patients with neurologic conditions. These competencies serve to characterize the rapidly expanding field of neurohospitalist medicine. The 27 chapters are divided into 3 sections entitled: neurological conditions, clinical interventions and interpretation of ancillary studies, and neurohospitalist role in the healthcare system. Each individual learning objective in the chapters describes a specific concept with an action verb to illustrate the behavior that the neurohospitalist exhibits. The individual neurohospitalist may not exhibit mastery in each of the topics included as individual practices vary in scope and practice pattern. A few examples of how the complete set of competencies may be used include in the creation of curricula for neurohospitalist fellowships, to assist in defining the scope of practice of neurohospitalists for administrative leaders of hospitals and departments, and in influencing the direction of further research and quality improvement in the field.

Abstract Neuronal dysfunction in specific brain regions or across distributed brain networks is a known feature of Alzheimer’s disease. An often reported finding in the early stage of the disease is the presence of increased functional MRI (fMRI) blood oxygenation level-dependent signal under task conditions relative to cognitively normal controls, a phenomenon known as ‘hyperactivation’. However, research in the past decades yielded complex, sometimes conflicting results. The magnitude and topology of fMRI hyperactivation patterns have been found to vary across the preclinical and clinical spectrum of Alzheimer’s disease, including concomitant ‘hypoactivation’ in some cases. These incongruences are likely due to a range of factors, including the disease stage at which the cohort is examined, the brain areas or networks studied and the fMRI paradigm utilized to evoke these functional abnormalities. Additionally, a perennial question pertains to the nature of hyperactivation in the context of Alzheimer’s disease. Some propose it reflects compensatory mechanisms to sustain cognitive performance, while others suggest it is linked to the pathological disruption of a highly regulated homeostatic cycle that contributes to, or even drives, disease progression. Providing a coherent narrative for these empirical and conceptual discrepancies is paramount to develop disease models, understand the synergy between hyperactivation and the Alzheimer’s disease pathological cascade and tailor effective interventions. We first provide a comprehensive overview of functional brain changes spanning the course from normal ageing to the clinical spectrum of Alzheimer’s disease. We then highlight evidence supporting a close relationship between fMRI hyperactivation and in vivo markers of Alzheimer’s pathology. We primarily focus on task-based fMRI studies in humans, but also consider studies using different functional imaging techniques and animal models. We then discuss the potential mechanisms underlying hyperactivation in the context of Alzheimer’s disease and provide a testable framework bridging hyperactivation, ageing, cognition and the Alzheimer’s disease pathological cascade. We conclude with a discussion of future challenges and opportunities to advance our understanding of the fundamental disease mechanisms of Alzheimer’s disease, and the promising development of therapeutic interventions incorporating or aimed at hyperactivation and large-scale functional systems.

ObjectiveDe novo variants in cullin‐3 ubiquitin ligase (CUL3) have been strongly associated with neurodevelopmental disorders (NDDs), but no large case series have been reported so far. Here, we aimed to collect sporadic cases carrying rare variants in CUL3, describe the genotype–phenotype correlation, and investigate the underlying pathogenic mechanism.MethodsGenetic data and detailed clinical records were collected via multicenter collaboration. Dysmorphic facial features were analyzed using GestaltMatcher. Variant effects on CUL3 protein stability were assessed using patient‐derived T‐cells.ResultsWe assembled a cohort of 37 individuals with heterozygous CUL3 variants presenting a syndromic NDD characterized by intellectual disability with or without autistic features. Of these, 35 have loss‐of‐function (LoF) and 2 have missense variants. CUL3 LoF variants in patients may affect protein stability leading to perturbations in protein homeostasis, as evidenced by decreased ubiquitin‐protein conjugates in vitro. Notably, we show that 4E‐BP1 (EIF4EBP1), a prominent substrate of CUL3, fails to be targeted for proteasomal degradation in patient‐derived cells.InterpretationOur study further refines the clinical and mutational spectrum of CUL3‐associated NDDs, expands the spectrum of cullin RING E3 ligase‐associated neuropsychiatric disorders, and suggests haploinsufficiency via LoF variants is the predominant pathogenic mechanism. ANN NEUROL 2025;97:76–89