Biology subjects

Argenziano, M. G.

Publications and source records attributed to Argenziano, M. G..

6 recordsLinked to original sources

bioRxiv2026

THE MICROANATOMY OF INTRACRANIAL HUMAN THROMBI BY SINGLE NUCLEI TRANSCRIPTOMICS

Rationale: Thrombi are fragile, heterogeneous, and difficult to study with available methods, yet understanding their molecular composition and local microenvironment in stroke is critical to elucidating stroke pathophysiology and improving patient outcomes. Objective: We used a novel platform for harvesting and analyzing intracranial thrombi from endovascular thrombectomy for large vessel occlusion to define the cellular and transcriptomic landscape of thrombi. Methods and results: We performed single-nuclei RNA sequencing (snRNA-seq) on three human intracranial thrombi to define their molecular composition and microenvironment. Across 5,143 nuclei, we identified 8 distinct cellular populations, including monocytes and T cells. Monocytes displayed transcriptional changes on gene and regulon levels suggestive of transdifferentiation. We integrated our snRNA-seq data with publicly available single cell RNA-sequencing (scRNA-seq) data from asymptomatic and symptomatic atherosclerotic carotid plaques, and scRNA-seq data from healthy brain vasculature. We identified shared transcriptional programs between carotid and thrombi monocytes along dimensions including inflammation and endothelial activation, supporting the notion that thrombi monocytes undergo transdifferentiation in stroke. We also inferred potential ligand-receptor interactions that may occur at the site and time of occlusion. Conclusion: Our novel application of snRNA-seq to thrombectomy specimens has allowed us to uncover the full diversity of cell types present in thrombi, including low-abundance and novel cell populations, and to provide evidence of cellular plasticity and intercellular communication at the site of occlusion. This detailed definition of the cellular populations involved in stroke will facilitate mapping of novel interventional targets with direct functional relevance and facilitate greater personalization of post-reperfusion therapy.

molecular biology↗

bioRxiv2026

Paired Tumor Biopsies Reveal Spatiotemporal Myeloid Remodeling After Local Chemotherapy in Glioblastoma

BackgroundStandard-of-care chemotherapy for glioblastoma induces inflammation that may contribute to disease recurrence. Although recurrent tumors are enriched with myeloid cells, the early cellular response to chemotherapy and the mechanisms that initiate this inflammatory remodeling remain poorly understood. In particular, it is unknown how neoplastic and tumor-associated myeloid populations respond during the immediate post-treatment period, and whether tumor-associated myeloid cells directly experience chemotherapy-induced genotoxic stress that contributes to inflammatory state transitions. MethodsWe performed sequencing-based analysis of neoplastic and immune populations following topotecan exposure using multiple complementary model systems and time points. We first analyzed MRI-localized, paired pre- and post-treatment biopsies from a first-in-human trial of 28-day convection enhanced delivery (CED) of topotecan (n=5) using cell-type-deconvolved bulk-RNA-sequencing and immunofluorescence. We then treated syngeneic murine gliomas using an in vivo model of CED-topotecan and measured acute 3-day and 7-day treatment responses by single cell RNA-sequencing. We additionally conducted sequencing analysis of patient-derived slice cultures and in vitro human microglial and glioma cell lines following 24-hour topotecan treatment. ResultsIn paired human biopsies, CED-topotecan induced spatially restricted transcriptional remodeling within the infusion zone, characterized by suppression of proliferative tumor programs and enrichment of inflammatory, interferon, hypoxia, and mesenchymal signatures. Cell-type deconvolution and immunofluorescence linked this response to myeloid remodeling, including enrichment of monocyte-derived tumor-associated macrophage states, increased MARCO-positive myeloid populations, and pH2AX-positive genotoxic stress within Iba1-positive myeloid cells. In the murine CED model, topotecan prolonged survival and reduced tumor cellularity, while also inducing inflammatory and DNA-damage programs in tumor-associated macrophages that evolved by 7-days toward hypoxia, angiogenesis, TGF-{beta} signaling, and mesenchymal/tissue-remodeling programs. Human slice culture and in vitro microglial systems confirmed stress-coupled inflammatory and DNA-damage responses in human myeloid cells. ConclusionsChemotherapy exposure induces a spatially structured inflammatory myeloid response characterized by early genotoxic stress and inflammatory activation, with later emergence of mesenchymal and tissue-remodeling macrophage programs. Across model systems, our analysis supports a model in which chemotherapy-associated damage in both tumor and myeloid cells contributes to an evolving inflammatory microenvironment after treatment.

neuroscience↗

bioRxiv2025

Convection-enhanced delivery of dexamethasone in glioma suppresses myeloid inflammation while avoiding systemic toxicities

Dexamethasone is widely used to control cerebral edema and inflammation in glioblastoma, but its benefits are limited by systemic toxicities and adverse prognostic associations. We evaluated local administration of dexamethasone via convection-enhanced delivery (CED) to maximize intratumoral anti-inflammatory effects by increasing local corticosteroid exposure while minimizing systemic exposure. In two glioma mouse models, continuous intraparenchymal infusion of dexamethasone was well tolerated with no adverse effects. Pharmacokinetic analyses supported preferential intratumoral distribution and reduced systemic exposure with CED compared with systemic dosing. Single-nucleus RNA sequencing (snRNA-seq) and immunohistochemistry showed attenuation of glioma-associated inflammation with downregulation of reactive microglial/macrophage programs and reduced tumor-infiltrating myeloid cells with a morphology consistent with a less activated state. Experiments in human induced pluripotent stem cell (iPSC)-derived microglia confirmed that dexamethasone directly suppresses inflammatory gene expression, indicating a conserved mechanism across species. This inflammatory suppression was recapitulated in both immortalized microglial (HMC3) and macrophage (THP1) cell lines. These findings suggest that localized dexamethasone delivered by CED reprograms the glioma immune microenvironment and achieves control of inflammation without the systemic adverse effects associated with standard systemic dexamethasone therapy. This clinically translatable strategy may improve symptom management and provide a platform for integrating local immunomodulation with future glioblastoma therapies.

cancer biology↗

bioRxiv2024

A pharmacological toolkit for human microglia identifies Topoisomerase I inhibitors as immunomodulators for Alzheimer's disease

AbstractWhile efforts to identify microglial subtypes have recently accelerated, the relation of transcriptomically defined states to function has been largely limited to in silico annotations. Here, we characterize a set of pharmacological compounds that have been proposed to polarize human microglia towards two distinct states - one enriched for AD and MS genes and another characterized by increased expression of antigen presentation genes. Using different model systems including HMC3 cells, iPSC-derived microglia and cerebral organoids, we characterize the effect of these compounds in mimicking human microglial subtypes in vitro. We show that the Topoisomerase I inhibitor Camptothecin induces a CD74high/MHChigh microglial subtype which is specialized in amyloid beta phagocytosis. Camptothecin suppressed amyloid toxicity and restored microglia back to their homeostatic state in a zebrafish amyloid model. Our work provides avenues to recapitulate human microglial subtypes in vitro, enabling functional characterization and providing a foundation for modulating human microglia in vivo.

neuroscience↗

bioRxiv2023

A cell state specific metabolic vulnerability to GPX4-dependent ferroptosis in glioblastoma

Glioma cells hijack developmental transcriptional programs to control cell state. During neural development, lineage trajectories rely on specialized metabolic pathways. However, the link between tumor cell state and metabolic programs is poorly understood in glioma. Here we uncover a glioma cell state-specific metabolic liability that can be leveraged therapeutically. To model cell state diversity, we generated genetically engineered murine gliomas, induced by deletion of p53 alone (p53) or with constitutively active Notch signaling (N1IC), a pathway critical in controlling cellular fate. N1IC tumors harbored quiescent astrocyte-like transformed cell states while p53 tumors were predominantly comprised of proliferating progenitor-like cell states. N1IC cells exhibit distinct metabolic alterations, with mitochondrial uncoupling and increased ROS production rendering them more sensitive to inhibition of the lipid hydroperoxidase GPX4 and induction of ferroptosis. Importantly, treating patient-derived organotypic slices with a GPX4 inhibitor induced selective depletion of quiescent astrocyte-like glioma cell populations with similar metabolic profiles.

cancer biology↗

bioRxiv2022

Biologically-informed deep neural networks provide quantitative assessment of intratumoral heterogeneity in post-treatment glioblastoma

Intratumoral heterogeneity poses a significant challenge to the diagnosis and treatment of glioblastoma (GBM). This heterogeneity is further exacerbated during GBM recurrence, as treatment-induced reactive changes produce additional intratumoral heterogeneity that is ambiguous to differentiate on clinical imaging. There is an urgent need to develop non-invasive approaches to map the heterogeneous landscape of histopathological alterations throughout the entire lesion for each patient. We propose to predictively fuse Magnetic Resonance Imaging (MRI) with the underlying intratumoral heterogeneity in recurrent GBM using machine learning (ML) by leveraging image-localized biopsies with their associated locoregional MRI features. To this end, we develop BioNet, a biologically-informed neural network model, to predict regional distributions of three tissue-specific gene modules: proliferating tumor, reactive/inflammatory cells, and infiltrated brain tissue. BioNet offers valuable insights into the integration of multiple implicit and qualitative biological domain knowledge, which are challenging to describe in mathematical formulations. BioNet performs significantly better than a range of existing methods on cross-validation and blind test datasets. Voxel-level prediction maps of the gene modules by BioNet help reveal intratumoral heterogeneity, which can improve surgical targeting of confirmatory biopsies and evaluation of neuro-oncological treatment effectiveness. The non-invasive nature of the approach can potentially facilitate regular monitoring of the gene modules over time, and making timely therapeutic adjustment. These results also highlight the emerging role of ML in precision medicine.

cancer biology↗