← BioTransfer GEO Dataset Finder
GEO series

Spatially-Resolved Multiomic Atlas of Leiomyosarcoma Identifies Two Clinically Relevant Epigenetically-Driven Cell States [scMultiomic]

GSE324206 Homo sapiens Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing 32 samples 2026/04/01 GPL24676
Summary
Leiomyosarcoma (LMS) is a malignant smooth muscle tumor characterized by substantial clinical and molecular heterogeneity. To investigate the cellular and regulatory landscape of LMS at single-cell resolution, we performed single-nucleus multiome sequencing to jointly profile gene expression (snRNA-seq) and chromatin accessibility (snATAC-seq) in 16 untreated primary leiomyosarcoma tumors arising from retroperitoneal, extremity, and uterine sites. After quality control, 94,439 nuclei were analyzed, revealing diverse tumor and microenvironmental cell populations including macrophages, T cells, and endothelial cells. Malignant cells segregated predominantly into two major transcriptional and epigenetic states: a dedifferentiated mesenchymal-like subtype (MES) and a differentiated smooth muscle cell–like subtype (SMC). Integration of transcriptomic and chromatin accessibility profiles identified distinct regulatory programs underlying these states, including enrichment of NFI transcription factor motifs in MES cells and AP-1 family motifs in SMC cells. These data provide a comprehensive multiomic resource for understanding tumor heterogeneity and regulatory mechanisms in leiomyosarcoma.
Download
NCBI GEO page ↗ {# Names what the click gives you. "Open in finder" meant nothing to a visitor who arrived from a search engine and has never seen the tool. #} Find more human RNA-seq datasets →
Similar datasets

Search all human RNA-seq datasets in GEO →

Share this dataset

Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.