Spatial transcriptomics reveals discrete tumour microenvironments and autocrine loops within ovarian cancer subclones.

High-grade serous ovarian carcinoma (HGSOC) is genetically unstable and characterised by the presence of subclones with distinct genotypes. Intratumoural heterogeneity is linked to recurrence, chemotherapy resistance, and poor prognosis. Here, we use spatial transcriptomics to identify HGSOC subclones and study their association with infiltrating cell populations. Visium spatial transcriptomics reveals multiple tumour subclones with different copy number alterations present within individual tumour sections. These subclones differentially express various ligands and receptors and are predicted to differentially associate with different stromal and immune cell populations. In one sample, CosMx single molecule imaging reveals subclones differentially associating with immune cell populations, fibroblasts, and endothelial cells. Cell-to-cell communication analysis identifies subclone-specific signalling to stromal and immune cells and multiple subclone-specific autocrine loops. Our study highlights the high degree of subclonal heterogeneity in HGSOC and suggests that subclone-specific ligand and receptor expression patterns likely modulate how HGSOC cells interact with their local microenvironment.

Sensitization to immune checkpoint blockade through activation of a STAT1/NK axis in the tumor microenvironment.

Cancer immunotherapy using antibodies that target immune checkpoints has delivered outstanding results. However, responses only occur in a subset of patients, and it is not fully understood what biological processes determine an effective outcome. This lack of understanding hinders the development of rational combination treatments. We set out to define the pretreatment microenvironment associated with an effective outcome by using the fact that inbred mouse strains bearing monoclonal cancer cell line-derived tumors respond in a dichotomous manner to immune checkpoint blockade (ICB). We compared the cellular composition and gene expression profiles of responsive and nonresponsive tumors from mice before ICB and validated the findings in cohorts of patients with cancer treated with ICB antibodies. We found that responsive tumors were characterized by an inflammatory gene expression signature consistent with up-regulation of signal transducer and activator of transcription 1 (STAT1) and Toll-like receptor 3 (TLR3) signaling and down-regulation of interleukin-10 (IL-10) signaling. In addition, responsive tumors had more infiltrating-activated natural killer (NK) cells, which were necessary for response. Pretreatment of mice with large established tumors using the STAT1-activating cytokine interferon-γ (IFNγ), the TLR3 ligand poly(I:C), and an anti-IL-10 antibody sensitized tumors to ICB by attracting IFNγ-producing NK cells into the tumor, resulting in increased cure rates. Our results identify a pretreatment tumor microenvironment that predicts response to ICB, which can be therapeutically attained. These data suggest a biomarker-driven approach to patient management to establish whether a patient would benefit from treatment with sensitizing therapeutics before ICB.