Patients with cancer with liver metastasis demonstrate significantly worse outcomes than those without liver metastasis when treated with anti-PD-1 immunotherapy. The mechanism of liver metastases-induced reduction in systemic antitumor immunity is unclear. Using a dual-tumor immunocompetent mouse model, we found that the immune response to tumor antigen presence within the liver led to the systemic suppression of antitumor immunity. The immune suppression was antigen specific and associated with the coordinated activation of regulatory T cells (Tregs) and modulation of intratumoral CD11b+ monocytes. The dysfunctional immune state could not be reversed by anti-PD-1 monotherapy unless Treg cells were depleted (anti-CTLA-4) or destabilized (EZH2 inhibitor). Thus, this study provides a mechanistic understanding and rationale for adding Treg and CD11b+ monocyte targeting agents in combination with anti-PD-1 to treat patients with cancer with liver metastasis.

Single-cell RNA sequencing (scRNA-seq) of tissues has revealed remarkable heterogeneity of cell types and states but does not provide information on the spatial organization of cells. To better understand how individual cells function within an anatomical space, we developed XYZeq, a workflow that encodes spatial metadata into scRNA-seq libraries. We used XYZeq to profile mouse tumor models to capture spatially barcoded transcriptomes from tens of thousands of cells. Analyses of these data revealed the spatial distribution of distinct cell types and a cell migration-associated transcriptomic program in tumor-associated mesenchymal stem cells (MSCs). Furthermore, we identify localized expression of tumor suppressor genes by MSCs that vary with proximity to the tumor core. We demonstrate that XYZeq can be used to map the transcriptome and spatial localization of individual cells in situ to reveal how cell composition and cell states can be affected by location within complex pathological tissue.