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Characterizing intra- and intertumor heterogeneity in ovarian high-grade serous carcinoma subtypes using single-cell and spatial transcriptomics

    • 1Computational Bioscience Graduate Program, University of Colorado Anschutz, Aurora, Colorado 80045, USA;
    • 2Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah 84112, USA;
    • 3Department of Population Health Sciences, University of Utah, Salt Lake City, Utah 84112, USA;
    • 4Department of Oncological Sciences, University of Utah, Salt Lake City, Utah 84112, USA;
    • 5Department of Biomedical Informatics, University of Colorado Anschutz, Aurora, Colorado 80045, USA;
    • 6Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland 21205, USA;
    • 7Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 21218, USA;
    • 8Data Science and AI Institute, Johns Hopkins University, Baltimore, Maryland 21209, USA;
    • 9Kavli Neuroscience Discovery Institute, Johns Hopkins University, Baltimore, Maryland 21218, USA;
    • 10Center for Computational Biology, Johns Hopkins University, Baltimore, Maryland 21218, USA;
    • 11Malone Center for Engineering in Healthcare, Johns Hopkins University, Baltimore, Maryland 21218, USA
Published August 17, 2026. https://doi.org/10.1101/gr.281433.125
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cover of Genome Research Vol 36 Issue 9
Current Issue:
September 2026, Vol. 36, No. 9
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Abstract

Ovarian high-grade serous carcinoma (HGSC) is an aggressive ovarian cancer with a heterogeneous tumor microenvironment (TME). Advances in single-cell RNA sequencing (scRNA-seq) and spatially resolved transcriptomics have enabled the study of complex TME. This study explores connections between molecular subtypes described from bulk transcriptomes and spatial domains characterized by distinct gene expression in HGSC and their variability between patients. We quantify both intra- and intertumor heterogeneity across 2D space and identify differing spatial patterns of gene expression pertaining to immune pathways and vasculature development. Functional characterization of tumor spaces reveals potentially shared cell states across molecular subtypes, whereas correlation analysis underscores subtype-specific spatial anticolocalization between spots exhibiting antigen-presenting functions and B cell–mediated immunity. Lastly, we perform spatially aware cell–cell communication analysis on the spatial samples and identify a molecular subtype specific difference in total signaling activity and heterogeneity in midkine signaling between the differentiated subtypes. Our results suggest that generating multiple tissue slices per patient might be necessary to enable comprehensive characterization of HGSC spatial transcriptomes.

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