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BP10. Single cell and Spatial Transcriptomic Profiling of Uterine Leiomyosarcomas Reveals Molecular Programs with Distinct Therapeutic Vulnerabilities

Friday, March 6, 2026
9:05 AM - 9:12 AM MST
Location: 301A
Introduction

Uterine leiomyosarcomas (ULMS) are rare, aggressive tumors with profound genomic heterogeneity, which has precluded the identification of effective targeted therapies. The overall purpose of this study was to investigate the transcriptomic and spatial landscape of ULMS to identify new therapeutic avenues.

Methods

We performed single-cell RNA sequencing (scRNA-seq) on freshly collected ULMS tumors using the 10X Genomics platform and spatial transcriptomics on FFPE sections using the Singular G4X platform. Resulting cells were integrated with scVI or resolVI and annotated using canonical markers. Tumor signatures were correlated with patient outcomes using bulk RNA sequencing data and novel drugs predictions for each tumor cell subtype were computed using the scIDUC algorithm.

Results

ScRNA-seq was performed on 15 recurrent, metastatic ULMS tumors from 13 patients at the time of debulking surgery, which yielded 204,250 high quality cells. Spatial transcriptomics was performed on 29 sections from 10 patients, which yielded 2.3 million spatially resolved cells. Both assays revealed heterogenous tumor microenvironments comprised of several types of cells, including myeloid cells, lymphoid cells, endothelial cells, and tumor cells. Among the tumor cells, eight subtypes with distinct signatures were identified, including 1) hormone receptor-positive stem-like cells scattered throughout the tumor, 2) metabolically adaptive Glycolytic cells with an inflammatory phenotype, 3) invasive Mesenchyme-like cells growing in fingerlike projections and surrounding blood vessels, and 4) MYC signaling cells that correlated with an ischemic tumor subtype surrounding areas of necrosis. Each tumor subset demonstrated unique associations with patient outcomes, with enrichment of MYC signaling cells correlating with the poorest survival. Current first-line therapies were predicted to be ineffective across most tumor subtypes; however, several alternative drug candidates uniquely targeting each tumor subtype were identified, including the broadly sensitive HDAC inhibitor tacedinaline.

Conclusions

We present a comprehensive transcriptomic and spatial atlas of ULMS, identifying several transcriptomic subtypes that correlate with patient outcomes and unique therapeutic sensitivities. Findings from this study will facilitate patient prognostication and the derivation of novel targeted therapeutic avenues.

Learning Objectives:

  • Identify the functionally distinct subtypes of tumor cells that contribute to aggressive uterine leiomyosarcoma biology.
  • Describe the distinct clinical outcomes that correlate with each ULMS tumor subtype.
  • Discuss the therapeutic avenues that target specific ULMS tumor subtypes and enhance current first-line therapies.