Multidimensional transcriptomic alas of recurrent uterine leiomyosarcomas uncovers stem-like hormonal cells with high drug sensitivity and improved patient outcomes

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 fresh 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, three prevalent subtypes emerged: 1) interferon-signaling cells that were distributed throughout sections, 2) mesenchyme-like cells arranged in nest-like configurations and around blood vessels, 3) ischemic cells with a high ribosomal signature organized around necrotic penumbras. Additionally, dedifferentiated stem-like cells with high expression of ESR1 , PGR , and AR , along with Wnt signaling pathway markers, were scattered throughout tumor sections. These hormonal cells clustered into two subtypes on scRNA-seq: 1) those with high ESR1 and low AR/PGR and 2) those with low ESR1 and higher AR/PGR expression. These cells were the most sensitive to all interrogated drugs, including current first-line therapies gemcitabine, docetaxel, and doxorubicin. All other tumor subtypes were highly resistant to most drugs, though several alternative drug candidates uniquely targeting each tumor subtype were identified. Furthermore, by correlating with bulk RNA sequencing, each tumor subtype was shown to be associated with unique patient outcomes. AR and PGR hormone receptor-expressing cells correlated with improved patient survival, whereas ischemic cells correlated with the worst survival outcomes. CONCLUSIONS: We present a comprehensive atlas of ULMS, identifying several transcriptomic subtypes of tumor cells, including dedifferentiated stem-like hormonal cells that correlate with better drug sensitivity and improved patient outcomes. Findings from this study may further facilitate patient prognostication and guide targeted therapeutic management.