Citations

Background: Pulsed field ablation (PFA) is an innovative modality for treating arrhythmias that is mostly non-thermal and renders myocardial tissue non-viable by creating pores in cardiac cell membranes. The impact of contact force (CF) on PFA efficacy is not well characterized. Hypothesis: We hypothesize that, while contact is necessary for PFA, increasing CF will not have a significant effect on in vivo ablation lesion size. Aim: We seek to investigate the effects of CF on acute PFA lesions in a beating porcine heart model. Methods: The ventricles of 7 porcine animals were ablated in vivo with PFA (500V, at 20μs for 50 pulses separated by 200ms) using a focal bipolar irrigated ablation catheter and BTX 830 electroporation generator (Harvard Apparatus). CF was measured before and after each PFA application using CARTO 3. Lesions were divided into standard CF (5-15g), high CF (16-30g), and very high CF (>31g). Results: A total of 46 lesions were analyzed. Gross pathology showed no significant difference in maximum width, lesion depth, and lesion volume between the three groups ( Figure 1A-B ). Linear regression showed a decrease of 0.003 mm in depth (depth = -0.003 × CF + 1.8, R = 0.05), an increase of 0.01 mm in width (width = 0.01 × CF + 5.7, R = 0.09), and a decrease of 0.05 mm 3 in volume (volume = -0.05 × CF + 26.8, R = 0.03) for each additional gram of CF ( Figure 1C ). Conclusion: While contact is necessary, increasing CF did not have a significant effect on in-vivo PFA lesion dimensions in a beating porcine heart model.

Background: Pulsed field ablation (PFA) has emerged as an innovative technology for treating cardiac arrhythmias. PFA increases cell permeability, which can lead to apoptosis. Greater PFA energy may be necessary to ablate ventricular myocardium for ventricular tachycardia circuits, but this carries risks of side effects such as gaseous formation (microbubbles) and hemolysis. Ethanol (EtOH) infusion has been used to ablate pathologic myocardial tissues in hypertrophic cardiomyopathy and for refractory arrhythmias. Hypothesis: We hypothesize that PFA in the ventricle can increase EtOH uptake through PFA-generated pores, thereby enhancing ablation efficacy, even at low powers, by utilizing the cell permeability effects of PFA. Aim: The aim of this study is to investigate the effect of local EtOH infusion after PFA on lesion size in porcine ventricles. Methods: The ventricles of five porcine subjects were ablated in vivo with a PFA low power setting (750 V, at 20 μs for 50 pulses separated by 200 ms) using a focal bipolar irrigated ablation catheter and BTX 830 electroporation generator (Harvard Apparatus). After PFA was performed, 2 ml of 90 % EtOH vs. saline (control) was infused through the catheter tip to the site of ablation. We compared the electrograms voltage amplitude reduction before and after PFA, and the ablation lesion characteristics. Results: A total of 10 lesions in the control group and 9 lesions in the EtOH group were analyzed. For the controls, the voltage after PFA was not reduced. In contrast, for the EtOH group, the voltage after PFA was significantly reduced ( Figure 1A ). On gross pathology, there were significant differences in ablation lesion depths and volumes between the 2 lesion sets ( Figure 1A-B ). Conclusion: Local EtOH infusion after ventricular PFA enhanced acute efficacy of electroporation. Concurrent PFA with local EtOH infusion has the potential to improve efficacy without requiring higher energy parameters, thereby reducing PFA risks. Future studies on chronic efficacy are warranted.

The NCCN Guidelines for the Management of Immunotherapy-Related Toxicities are intended to provide oncology practitioners with guidance on how to manage the wide-ranging and potentially fatal toxicities that may occur with cancer immunotherapy. The guidelines address immune-related adverse events related to immune checkpoint inhibitors, CAR T-cell therapies, and lymphocyte engagers (which include T-cell–engaging bispecific antibodies). These NCCN Guidelines Insights highlight recent guideline updates pertaining to the management of emerging toxicities related to cancer immunotherapy.

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.

Abstract Despite exhibiting longer overall survival that IDH-wt counterparts, IDH-mutant gliomas remain uniformly deadly and impact patients in the prime of adult life. The immune microenvironment of IDH-mutant gliomas remains incompletely characterized, particularly with regard to distinctions between IDH-mutant astrocytoma and IDH-mutant, 1p/19q codeleted oligodendroglioma. To address this knowledge gap, we subjected dissociated tumor suspensions derived from 7 astrocytoma and 7 oligodendroglioma clinical samples to flow cytometry-based sorting for the pan-immune marker, CD45, and the microglial marker, P2RY12. This process yielded both microglial and non-microglial immune cell populations, which were then analyzed by scRNA sequencing. This workflow revealed a single large cluster of microglia, characterized by expression of Galectin-1 and lysosomal Lipase A, which was present at a significantly higher level in oligodendroglioma. While the biological significance of this cluster is unclear, gene set enrichment analysis exploring phenotypic differences between microglia in astrocytoma and oligodendroglioma revealed significant increases in expression of gene sets related to antigen presentation in astrocytoma. Parallel analysis of the non-microglial immune fraction showed an increase in the expression of pro-inflammatory gene sets, such as genes related to cytokine secretion, within the CD8 T-cell compartment of astrocytomas. We also observed upregulation of the expression of inflammatory gene sets within the dendritic cells of astrocytomas. Taken together, these changes suggest that the immune compartment of astrocytoma is more active and inflamed, and targeting the immune system in these tumors may represent a potential therapeutic avenue.

Abstract Glioblastoma (GBM) presents as a highly aggressive and malignant brain tumor with limited treatment options. Despite the availability of existing therapies, the invasive characteristics of GBM frequently result in tumor recurrence and poor prognosis. We previously developed a B-cell-based therapy (BVax) that has shown promising results in its ability to induce therapeutic responses in preclinical models of GBM. Our research revealed potency of BVax can be attributed to its robust antigen-presenting capability, cognate antigen specificity with T cells, and ability to generate tumor-reactive antibodies. The present study aims to characterize the unique antigenic reactivity of BVax-derived antibodies by evaluating their immunological effects and therapeutic potential in both murine models and GBM patient-specific samples. Leveraging CD45.1 and CD45.2 congenic mouse models, we first revealed that BVax preferentially migrated to glioma-bearing brains upon intravenous injection, resulting in a CD38+CD20-CD19+ plasmablast phenotype. To further characterize the reactivity of BVax-derived immunoglobulins (Ig), we utilized proteomic analysis and identified preferential targets of Gelsolin, Fibronectin, Versican, Fibrinogen, and collagen type IV alpha, commonly associated with cell motility and the extracellular matrix. Microdialysis data confirmed the increased presence of many of these BVax-derived Igs-recognized antigens in tumor regions compared to normal brain regions in GBM patients. Utilizing purified BVax-derived antibodies from patient specimen, in vitro cell motility assays demonstrated a significant prevention of the invasion and migration of cell lines from patient derived xenograft (PDX). In this study, we concluded that BVax elicits antitumor activity through targeted migration to tumor-bearing regions, differentiation into plasmablasts, and robust secretion of specific Igs that retain the ability to inhibit functionalities associated with cell invasion and migration. Here, we present the first in-depth study that characterizes GBM patients’ antibody reactivity, specifically a subset of inflammatory B cells (BVax) with therapeutic effects that offer an indication for a new direction of immunotherapies.

Abstract BACKGROUND CODEX (CO-Detection by indEXing) imaging has emerged as a pivotal tool in cellular biology, providing unprecedented insights into cellular distributions and interactions within the tissue microenvironment, crucial for advancing computational pathology. Despite its advantages, CODEX is susceptible to stitching errors during the merging of image tiles, which can significantly distort spatial analysis by introducing artifacts that obscure true cellular architecture. METHODS Addressing this challenge, we introduce CISD (CODEX Image Stitch Detection), a novel, user-friendly algorithm optimized for the detection of stitching artifacts in large-scale CODEX datasets. Developed and validated using a comprehensive dataset from 7 matched glioblastoma patients—encompassing over 2800 images across 29 immune protein markers—CISD utilizes a combination of image preprocessing, statistical measures, and thresholding to detect stitching errors. RESULTS CISD demonstrates robust performance, achieving a median Area Under Curve (AUC) value in the gold standard dataset where 73% of markers exceed 70% AUC, and 17% surpass 90%. Further validation shows that in a secondary dataset, 45% of markers maintain AUC values over 70% with 38% exceeding 90%, validating the algorithm’s consistent efficacy across varied datasets. CONCLUSION CISD’s significance lies not only in its computational achievements but also in its accessibility, facilitating high-quality analysis of extensive datasets without complex pattern recognition requirements. This democratizes high-precision computational pathology, enabling more researchers to accurately analyze spatial data. By reducing technical barriers, CISD sets a new benchmark in CODEX imaging, enhancing data reliability and accelerating research discoveries in cellular biology. This innovation stands to substantially refine spatial analysis in digital pathology, ensuring dependable interpretation of complex biological data.