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Single-cell sequencing reveal transcriptional cell lineage heterogeneity in extracranial arteriovenous malformation

ABSTRACT: Extracranial arteriovenous malformations (eAVMs) are rare congenital vascular anomalies consisting of abnormal artery-vein bypass with no intervening capillary network and can lead to disability and death. In this study, an integration of two cutting-edge technologies, single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST), was applied to uncover the underlying pathophysiology of eAVMs. Patient-matched eAVM tissue samples and normal tissue control data were analyzed. We identified different cell states of endothelial cells (ECs), perivascular cells and immune cells in eAVMs and characterized their spatial distributions with multiple immunofluorescence staining (mIF), immunostaining and spatial transcriptomics. Dysregulated cell-to-cell interactions among ECs, perivascular cells and immune cells that are associated with disease progression were cataloged. By performing scRNA-seq on 117,360 individual cells, we identified 14 transcriptomically defined cell lineages from eAVMs. We uncovered the presence of MAFB+ nidus ECs. Moreover, mesenchymal activation was observed in ECs, characterized by high expression of POSTN or FN1 and the upregulation of the NOTCH and TGF-β pathways. mIF and ST verified the location of MAFB+ nidus ECs and mesenchymal activation of eAVM ECs. We identified transcriptional variation within perivascular cells and the presence of smooth muscle–like pericytes in eAVMs. Ligand‒receptor-based cell‒cell interaction analysis indicated that Nd ECs might specifically communicate with perivascular cells through the MDK, VEGF, SEMA3 and ANGPT pathways, and this cellular crosstalk was supported by colocalization analysis of spatial transcriptomics. In addition, we found that hypoxia plays an important role in the development of eAVMs, and hyperbaric oxygen therapy (HBOT) was used to treat one large pelvic eAVM. Thus, correcting the hypoxic microenvironment could be a promising therapeutic strategy.

ORGANISM(S): Homo sapiens

PROVIDER: GSE242274 | GEO | 2026/01/07

REPOSITORIES: GEO

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Project description:Spatial transcriptomics is a rapidly advancing field, yet it lacks standardized metrics for evaluating imaging-based in situ hybridization technologies. In this study, we emphasize the importance of rigorous experimental design and standardized operating procedures (SOPs) in defining performance metrics across multiple modalities—from single-cell to spatial transcriptomics to spatial proteomics. Our Spatial Touchstone (ST) dataset, generated from six tissue types across three global sites (n=76 assays), provides a comprehensive evaluation of reproducibility, sensitivity, dynamic ranges, signal-to-noise ratio, false discovery rates, cell type annotation, and congruence with single-cell profiling. Using single-nucleus RNA sequencing (snRNA-seq) on the same formalin-fixed paraffin-embedded tissues, we created a reference for transcriptional profiles to assess cellular organization and biomarker localization. In the absence of an independent 'gold standard’ in the field, this study provides an objective assessment of technical performance through standardized protocols, Spatial Touchstone Protocols (STSOP). Our open-source software, SpatialQC, allows users to evaluate samples across all technical metrics and directly impute cell annotations from single-cell datasets. This study features the largest imaging-based spatial transcriptomics data repository available, with a total of 203 spatial profiles. It incorporates both public (n=127) and ST datasets (n=76) through the Spatial Touchstone Portal (STP), available at www.spatialtouchstone.org. This resource offers users easy access to analyze and compare their own data against an extensive collection of imaging-based datasets. We show that the ST datasets demonstrate high reproducibility (r=0.93 to 1.0) and set a new benchmark for the field. Finally, we establish metrics to evaluate and integrate imaging based multi omics data from single cell into spatial transcriptomics to spatial proteomics. The ST project provides a comprehensive, reproducible assessment across platforms and sites, establishing essential standards for imaging-based spatial multi omics (transcriptomics and proteomics) and paving the way for future research and technological advancements.

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Single-cell sequencing reveal transcriptional cell lineage heterogeneity in extracranial arteriovenous malformation

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