Mívalt, Filip

Abstract Introduction: Neuroblastoma is the most common solid tumor in infants and arises from progenitor cells during sympathoadrenal development. While the majority of primary tumor cells resembles adrenergic neurons, more undifferentiated mesenchymal or neural-crest cell-like phenotypes have been found, especially in pretreated and high-risk cases. In most high-risk neuroblastoma patients, tumor cells have disseminated to the bone marrow. Problem Statement and Aim: However, the bone marrow, as a key regulator of hematopoietic and mesenchymal stem cell quiescence, is a frequent site of dissemination not only of neuroblastoma but also of other solid cancers such as breast and prostate cancer. Still, comprehensive single-cell analyses of bone marrow metastases, i.e. disseminated tumor cells (DTCs) and cells of their microenvironment, have not yet been undertaken. Herein, we aimed to capture tumor heterogeneity and investigate microenvironmental changes in a solid cancer with bone marrow involvement. Methods: To that end, we applied a multi-omics data mining approach to define a multiplex imaging panel and designed DeepFLEX, a computational pipeline for subsequent multiplex image analysis. Thereby, we obtained a single-cell map of over 35,000 DTCs and cells of their microenvironment in the metastatic bone marrow niche. In addition, we independently profiled the transcriptome of 38 patients with and without bone marrow metastasis. Results: We revealed vast diversity among DTCs and suggest that FAIM2 can act as a complementary marker to capture DTC heterogeneity. However, DTCs in this study mainly expressed markers of the adrenergic lineage, such as GD2, but did not show a mesenchymal phenotype. Interestingly, we demonstrate that malignant bone marrow infiltration is associated with an inflammatory response and at the same time the presence of immuno-suppressive cell types, most significantly an immature neutrophil/granulocyte-myeloid derived suppressor-like cell type. Conclusion: Our findings demonstrate a high level of heterogeneity among DTCs and suggest that the latter shape the bone marrow microenvironment, warranting deeper investigations of spatio-temporal dynamics at the single-cell level and their clinical relevance. Citation Format: Daria Lazic, Florian Kromp, Fikret Rifatbegovic, Peter Repiscak, Filip Mivalt, Florian Halbritter, Marie Bernkopf, Andrea Bileck, Marek Ussowicz, Inge M. Ambros, Peter F. Ambros, Christopher Gerner, Ruth Ladenstein, Christian Ostalecki, Sabine Taschner-Mandl. Mapping bone marrow metastasis in neuroblastoma by deep multiplex imaging and transcriptomics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 977.

Abstract Early implantable epilepsy therapy devices provided open-loop electrical stimulation without brain sensing, computing, or an interface for synchronized behavioural inputs from patients. Recent epilepsy stimulation devices provide brain sensing but have not yet developed analytics for accurately tracking and quantifying behaviour and seizures. Here we describe a distributed brain co-processor providing an intuitive bi-directional interface between patient, implanted neural stimulation and sensing device, and local and distributed computing resources. Automated analysis of continuous streaming electrophysiology is synchronized with patient reports using a handheld device and integrated with distributed cloud computing resources for quantifying seizures, interictal epileptiform spikes and patient symptoms during therapeutic electrical brain stimulation. The classification algorithms for interictal epileptiform spikes and seizures were developed and parameterized using long-term ambulatory data from nine humans and eight canines with epilepsy, and then implemented prospectively in out-of-sample testing in two pet canines and four humans with drug-resistant epilepsy living in their natural environments. Accurate seizure diaries are needed as the primary clinical outcome measure of epilepsy therapy and to guide brain-stimulation optimization. The brain co-processor system described here enables tracking interictal epileptiform spikes, seizures and correlation with patient behavioural reports. In the future, correlation of spikes and seizures with behaviour will allow more detailed investigation of the clinical impact of spikes and seizures on patients.