Huse, Jason T.

ABSTRACT Background Most genomic studies of adult-type diffuse gliomas have focused on predominantly European ancestry populations, limiting the generalizability of molecular classifications and precision medicine approaches. We assembled a multi-institutional glioma cohort of diverse patients to investigate how germline ancestry, molecular subtypes, and mutational processes shape tumor biology and clinical outcomes. Methods We analyzed 1,102 adults with WHO 2021–classified diffuse gliomas (IDH-mutant, 1p/19q-codeleted oligodendroglioma; IDH-mutant astrocytoma; IDH-wildtype glioma) from seven U.S. institutions. Whole-exome sequencing (WES) of FFPE tumors identified somatic alterations and COSMIC SBS v3.2 mutational signatures. Genetic ancestry was estimated from WES using 1000 Genomes reference populations. Overall survival was assessed using Kaplan–Meier and multivariable models. Results The cohort included 66.9% European (EUR), 21.1% Admixed American/Hispanic (AMR), 10.3% Admixed African (AFR), and 1.6% Asian (AS) ancestry. Survival followed expected molecular hierarchy (median overall survival: oligodendroglioma 15.7 years, astrocytoma 10.6 years, IDH-wildtype glioma 1.9 years). Within oligodendroglioma, AMR patients showed improved survival versus EUR (HR 0.67, 95% CI 0.48–0.94; p=0.011), with similar trends across subtypes. Somatic profiling confirmed canonical subtype-defining alterations and revealed higher ATRX alterations in AFR and AMR IDH-wildtype tumors compared with EUR. ATRX alterations were associated with improved survival only in AFR (p=0.003). Mutational signature analysis identified subtype-specific signatures, including therapy-associated signatures. Chemotherapy-related signatures were more frequent in EUR and AMR than in AFR. Conclusions This ancestrally diverse glioma cohort confirms established molecular classifications and identifies ancestry-associated differences in survival, somatic alterations, and mutational processes, indicating the critical need for broad representation to inform precision neuro-oncology. Key Points A multi-institutional glioma cohort validates subtype and survival patterns across ancestries. Therapy-associated mutational signatures differ by ancestry, suggesting distinct treatment-related mutational processes. Admixed American patients show improved survival, particularly in oligodendroglioma. Importance of the Study Most genomic studies of adult-type diffuse glioma have focused on populations of predominantly European ancestry which limits the ability to examine variation in tumor biology and clinical outcomes across populations. In this study, we assembled one of the largest ancestrally diverse cohorts of molecularly characterized adult diffuse gliomas, integrating germline ancestry inference with tumor whole-exome sequencing and mutational signature analysis. We confirm that established molecular classifications and survival hierarchies remain robust across ancestry groups. However, we also identified ancestry-associated differences in survival within specific tumor subtypes, higher ATRX alteration frequencies in African American and admixed American patients with IDH-wildtype tumors, and variation in therapy-associated mutational signatures across ancestry groups. These findings highlight the importance of incorporating population differences into genomic studies of glioma and provide a resource for future multi-ancestry investigations of glioma risk, tumor evolution, and treatment response, ultimately supporting more inclusive precision neuro-oncology.

Abstract INTRODUCTION Glioblastoma is the most common malignant adult brain tumor with poor prognosis, largely due to its heterogeneous landscape. The AI-RANO and RANO-RGP groups organized the BraTS-Pathology 2024 challenge, providing a publicly-available dataset and a benchmarking environment for AI models to automatically identify six clinically-relevant histopathologic sub-regions in H&E-stained whole slide images (WSIs). METHODS We reclassified the TCGA-GBM and TCGA-LGG data according to the WHO 2021 criteria and identified diagnostic WSIs of 188 glioblastoma (IDH-wt, CNS WHO Gr.4) patients. A well-defined annotation protocol was communicated to eight neuropathologists, across eight institutions, who created “ground truth” annotations for Cellular Tumor (CT), Geographic Necrosis, Cortical Infiltration, Pseudopalisading Necrosis (PN), Microvascular Proliferation, and Penetration into White Matter (PWM). Comprehensive WSI curation for elimination of artifactual content and follow up partitioning resulted in approximately 300,000 data samples/patches. FINDINGS Inter-observer variability assessment highlighted difficulties in establishing a “gold standard”. The least annotated sub-regions (PWM and PN) were the most challenging to the participating methods, whereas all methods achieved their highest accuracy in the most annotated sub-region (CT). The highest average performance across sub-regions was obtained by a foundation model-based method. However, this top-ranked solution achieved an F1 score of 0.51 (Accuracy=0.65, Sensitivity=0.56, Specificity=0.93). CONCLUSIONS Our findings suggest that achieving state-of-the-art performance, in automatically identifying clinically-relevant glioblastoma sub-regions, remains an unsolved research problem. Analysis of the ground-truth annotations underscores the critical need for more precisely defined and neuropathologically standardized annotation protocol. Current AI algorithms are facing difficulties in addressing glioblastoma’s heterogeneous histologic landscape in the absence of large, comprehensively, and consistently annotated data. Building upon these findings, and towards developing more accurate AI algorithms, the 2025 iteration of the BraTS-Path challenge is currently on-going by leveraging two million data samples, aiming to enhance our disease understanding and improve diagnostic accuracy, ultimately contributing to improved patient outcomes.

AbstractAbstract Background Central nervous system (CNS) tumors are a significant cause of morbidity and mortality in Sub-Saharan Africa (SSA). This project aimed to assess and map out the current neuro-oncology capacity in SSA, brain tumor registries, and biobanks. Methods This cross-sectional study utilized an online survey to gather data from healthcare professionals involved in CNS tumor care across SSA through the Society for Neuro-Oncology SSA (SNOSSA). The survey captured information on the availability of neuro-oncology practitioners, neuropathology, molecular diagnostics, cancer registries, and biobanking. Results A total of 145 respondents representing 70 healthcare institutions across 22 countries participated. Of the 70 institutions, specialties included neurosurgery (89%, 62/70), anatomic pathology (74%, 52/70), and medical oncology (71%, 50/70). For radiologic evaluation, 64% (45/70) of responding institutions reported having both CT and MRI. Access to molecular testing through immunohistochemistry or next-generation sequencing was available in 46% (32/70) of responding institutions. Multidisciplinary tumor boards were available for CNS cases in 86% (60/70) of responding institutions. Brain tumor-specific registries were available in 29% (20/70) of responding institutions, and 10% (7/70) maintained brain tumor biorepositories. Conclusion This study demonstrates that SSA has substantial potential in neuro-oncology care practice capacity and facilities. The most significant gaps were in neuropathology and molecular testing, which makes widespread implementation of the WHO 2021 diagnosis challenging. Understanding the prevalence of CNS tumor subtypes in SSA is difficult due to the low number of brain tumor registries and biobanks.

Abstract This review explores the pivotal role of preanalytical variables in bringing liquid biopsy approaches into the clinic for brain tumors. Preanalytical variables encompass a range of critical issues, from blood sample collection and handling to the impact of tumor heterogeneity and patient-specific factors. These variables introduce challenges such as false positives, false negatives, and variability in the analysis of tumor signals, which can hinder the diagnostic and prognostic utility of liquid biopsies. Understanding the nuances of preanalytical variables is essential for the successful implementation of liquid biopsy in clinical settings. This paper delves into strategies aimed at mitigating the influence of preanalytical variables by emphasizing the importance of standardized sample collection protocols, optimized sample processing and storage, quality control measures, and the integration of multiple liquid biopsy modalities.

Importance Molecular techniques, including next-generation sequencing, genomic copy number profiling, fusion transcript detection, and genomic DNA methylation arrays, are now indispensable tools for the workup of central nervous system (CNS) tumors. Yet there remains a great deal of heterogeneity in using such biomarker testing across institutions and hospital systems. This is in large part because there is a persistent reluctance among third-party payers to cover molecular testing. The objective of this Review is to describe why comprehensive molecular biomarker testing is now required for the accurate diagnosis and grading and prognostication of CNS tumors and, in so doing, to justify more widespread use by clinicians and coverage by third-party payers. Observations The 5th edition of the World Health Organization (WHO) classification system for CNS tumors incorporates specific molecular signatures into the essential diagnostic criteria for most tumor entities. Many CNS tumor types cannot be reliably diagnosed according to current WHO guidelines without molecular testing. The National Comprehensive Cancer Network also incorporates molecular testing into their guidelines for CNS tumors. Both sets of guidelines are maximally effective if they are implemented routinely for all patients with CNS tumors. Moreover, the cost of these tests is less than 5% of the overall average cost of caring for patients with CNS tumors and consistently improves management. This includes more accurate diagnosis and prognostication, clinical trial eligibility, and prediction of response to specific treatments. Each major group of CNS tumors in the WHO classification is evaluated and how molecular diagnostics enhances patient care is described. Conclusions and Relevance Routine advanced multidimensional molecular profiling is now required to provide optimal standard of care for patients with CNS tumors.

Abstract Background Brain tumors represent a significant global health challenge, with rising incidence and mortality impacting individuals worldwide and contributing to cancer-related morbidity and mortality. In Africa, this burden is exacerbated by limited access to advanced diagnostics, treatment options, and multidisciplinary care, compounded by the absence of standardized cancer registration and tumor biobanking. The introduction of molecular diagnostics, as outlined in the 2021 World Health Organization central nervous system (CNS) tumor classification, adds complexity to brain tumor management, particularly in regions with scarce resources. Methods To address these issues, the Brain Tumor Consortium for Africa (BTCA) was established in 2023, bringing together experts to improve CNS tumor diagnosis, patient care, and research. The initial project, conducted via an electronic questionnaire, aimed to assess neuro-oncology capacity across Sub-Saharan Africa. Results The study revealed significant gaps, with a limited number of institutions incorporating molecular subtyping into their diagnostic algorithms. The consortium’s efforts focus on enhancing local data use, informing public policy, and promoting collaboration to advance neuro-oncology practices in Africa. By fostering a network enlisting the expertise of collaborators in the fields of neurosurgery, neurology, neuropathology, anatomic pathology, and medical and radiation oncology, the BTCA seeks to improve brain tumor management through better diagnostics, infrastructure, and policy advocacy. Future directions include expanding molecular diagnostic capabilities, standardizing brain tumor biobanking, enhancing data collection, and advocating for improved brain tumor care in national health agendas. Conclusions The BTCA represents a pioneering model of collaboration and innovation in addressing the unique challenges of brain tumor care in Africa.

Abstract Glioblastoma, the most common malignant primary adult brain tumor, poses significant diagnostic and treatment challenges due to its heterogeneous molecular and micro-environmental profiles. To this end, we organize the BraTS-Path challenge to provide a public benchmarking environment and a comprehensive dataset to develop and validate AI models for identifying distinct histopathologic glioblastoma sub-regions in H&E-stained digitized tissue sections. We identified 188 multi-institutional diagnostic slides of glioblastoma (IDH-wt, Gr.4) cases, from the TCGA-GBM and TCGA-LGG data collections, following their reclassification according to the 2021 WHO classification criteria. Sub-regions were selected according to distinctive morphology of histopathologic features and included aggressive tumor biology and areas consistent with potential treatment effect. Selected sub-region annotations included cellular tumor, geographic necrosis, cortical infiltration, pseudopalisading necrosis, microvascular proliferation, white matter penetration, regions dense with macrophages, leptomeningeal infiltration, and presence of lymphocytes. We obtained 107,340 patches of size 512x512 from the 9 sub-regions. A global network of board-certified expert neuropathologists defined and followed a systematic annotation protocol based on clinical definitions and only delineated sub-regions with high confidence, thus ensuring high-quality standardized data. Each tissue section was assigned to an annotator-approver pair, with the annotator delineating sub-regions and the approver ensuring the consistency of the annotations. By crowdsourcing annotations, the BraTS-Path challenge harnesses the collective expertise of clinical neuropathologists and fosters a collaborative environment to advance the neuro-oncology field. The anticipated developed algorithms are expected to integrate state-of-the-art computational methods, achieving high accuracy in identifying diverse histopathologic features and advancing clinical decision-making processes. The BraTS-Path challenge aims to bridge the gap between research and clinical practice by promoting the development of AI-driven tools for precise tumor characterization. This collaborative effort can significantly enhance our understanding of glioblastoma, improve diagnostic accuracy, and inform treatment strategies, thereby contributing to better patient outcomes.

Abstract Effective immune synapses are a prerequisite for desirable immune surveillance and control of tumour growth. Cell-to-cell interactions form the basis of immune synapses, resulting in either immunoprotected or immunosuppressed manifestations in the tumour brain that could explain glioblastoma (GBM) recurrence. Using state-of-the-art multiplex imaging, spatial statistics, and spatially aware deep learning tools in 14 patient-matching tissues from primary and recurrent GBM, we detected spatial immune networks (SINets). SINets across 105 regions of interest comprising 2.3 million cells show stronger spatial engagement between myeloid and lymphoid lineages at recurrence. SINets’ architecture in primary tumours is associated with relapse timing. Patients, where the SINets are more modular, recur sooner than patients with denser SiNets. In addition, this association presents sexual dimorphism in our cohort (N=3 females, and N=4 males). Phenotype-to-phenotype spatial coexistence also contributes to enhancing phenotype prediction. A spatial-aware deep learning model trained with single-cell data from primary tumours reaches an average balanced accuracy of 0.76 in primary tumour cellular communities unseen during training, compared to a spatial-agnostic model that reached an average balanced accuracy of 0.69. In summary, we detected a distinct spatial engagement in glioblastoma undergoing chemo-radiation treatment. The spatial patterns of coexistence represent ecological niches that contribute to defining cell occurrence and may underpin effective immune synapses. Overall, the spatiotemporal elements provide a newer approach for dissecting glioblastoma’s complexity and discovering opportunities for stratifying patients by harnessing spatial information encoded in multicellular niches.

Abstract Brain tumors constitute significant morbidity and mortality in sub-Saharan Africa (SSA). There is no previous large-scale effort focusing on brain tumor genetics in SSA. This project aims to map out the current neuro-oncology capacity in terms of workforce and available services in SSA. This is an ongoing online survey among a cross section of neuro-oncology practitioners spread across SSA countries to capture information on the distribution, number of available neuro-oncology care practitioners, capacity for neuropathology and molecular diagnosis, management of brain tumors, cancer registration, and tumor biobanking. The survey was disseminated by the Society for Neuro-oncology in SSA (SNOSSA). There were 83 respondents representing 15 countries and 52 health institutions: 46 tertiary, 4 secondary, 1 private and 1 other. Here, we present data on the 52 institutions. The prevalence of specialties was 87% neurosurgery, 75% anatomic pathology, 69% medical oncology, 64% neurology, 60% radiation oncology, and 39% neuropathology. For radiologic evaluation, 81% of institutions were reported to have both CT and MRI, 17% CT only, and one institution neither. For molecular testing, 46% have access to IHC or NGS testing, whereas 52% were reported to have neither. A neuro-oncology tumor board was reported at 58% of institutions. A general cancer registry is available in 64% of institutions, 31% have a brain tumor specific registry and 10% have a brain tumor biorepository. This study shows that SSA has substantial potential in neuro-oncology care practice capacity and facilities. Most significant gaps remain in areas such as neuropathology and molecular testing, which makes widespread implementation of the WHO 2021 diagnosis challenging. Understanding the prevalence of CNS tumor subtypes is also difficult due to low number of brain tumor registries and biobanks in SSA. The present findings reveal strategic opportunities, especially in neuropathology, tumor registries, biobanks, and infrastructure for IHC and NGS in SSA.