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Abstract
Immune checkpoint therapy in breast cancer remains restricted to triple negative patients, and long-term clinical benefit is rare. The primary aim of immune checkpoint blockade is to prevent or reverse exhausted T cell states, but T cell exhaustion in breast tumors is not well understood. Here, we use single-cell transcriptomics combined with imaging mass cytometry to systematically study immune environments of human breast tumors that either do or do not contain exhausted T cells, with a focus on luminal subtypes. We find that the presence of a PD-1high exhaustion-like T cell phenotype is associated with an inflammatory immune environment with a characteristic cytotoxic profile, increased myeloid cell activation, evidence for elevated immunomodulatory, chemotactic, and cytokine signaling, and accumulation of natural killer T cells. Tumors harboring exhausted-like T cells show increased expression of MHC-I on tumor cells and of CXCL13 on T cells, as well as altered spatial organization with more immature rather than mature tertiary lymphoid structures. Our data reveal fundamental differences between immune environments with and without exhausted T cells within luminal breast cancer, and show that expression of PD-1 and CXCL13 on T cells, and MHC-I – but not PD-L1 – on tumor cells are strong distinguishing features between these environments.
T cell exhaustion in breast tumours remains to be fully characterised. Here, single cell transcriptomics and imaging mass cytometry analysis of luminal breast tumours with or without exhausted T cells suggests distinct patterns of PD-1 and CXCL13 expression in T cells, and of MHC-I, but not PD-L1, expression in tumour cells.
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1 University of Zurich, Department of Quantitative Biomedicine, Zurich, Switzerland (GRID:grid.7400.3) (ISNI:0000 0004 1937 0650); ETH Zurich, Institute for Molecular Health Sciences, Zurich, Switzerland (GRID:grid.5801.c) (ISNI:0000 0001 2156 2780); ETH Zurich and University of Zurich, Life Science Zurich Graduate School, Zurich, Switzerland (GRID:grid.7400.3) (ISNI:0000 0004 1937 0650)
2 University of Zurich, Department of Quantitative Biomedicine, Zurich, Switzerland (GRID:grid.7400.3) (ISNI:0000 0004 1937 0650); German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT) Heidelberg, Division of Translational Medical Oncology, Heidelberg, Germany (GRID:grid.7497.d) (ISNI:0000 0004 0492 0584)
3 Patients’ Tumor Bank of Hope (PATH), Munich, Germany (GRID:grid.7497.d)
4 Pathology at Josefshaus, Dortmund, Germany (GRID:grid.7497.d)
5 University Hospital Zurich and University of Zurich, Department of Pathology and Molecular Pathology, Zurich, Switzerland (GRID:grid.412004.3) (ISNI:0000 0004 0478 9977)
6 University of Zurich, Department of Quantitative Biomedicine, Zurich, Switzerland (GRID:grid.7400.3) (ISNI:0000 0004 1937 0650); ETH Zurich, Institute of Molecular Systems Biology, Zurich, Switzerland (GRID:grid.5801.c) (ISNI:0000 0001 2156 2780)
7 University of Zurich, Department of Quantitative Biomedicine, Zurich, Switzerland (GRID:grid.7400.3) (ISNI:0000 0004 1937 0650); ETH Zurich, Institute for Molecular Health Sciences, Zurich, Switzerland (GRID:grid.5801.c) (ISNI:0000 0001 2156 2780)