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.

Details

Title
A comprehensive single-cell map of T cell exhaustion-associated immune environments in human breast cancer
Author
Tietscher, Sandra 1 ; Wagner, Johanna 2   VIAFID ORCID Logo  ; Anzeneder, Tobias 3 ; Langwieder, Claus 4 ; Rees, Martin 4 ; Sobottka, Bettina 5 ; de Souza, Natalie 6 ; Bodenmiller, Bernd 7   VIAFID ORCID Logo 

 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) 
 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) 
 Patients’ Tumor Bank of Hope (PATH), Munich, Germany (GRID:grid.7497.d) 
 Pathology at Josefshaus, Dortmund, Germany (GRID:grid.7497.d) 
 University Hospital Zurich and University of Zurich, Department of Pathology and Molecular Pathology, Zurich, Switzerland (GRID:grid.412004.3) (ISNI:0000 0004 0478 9977) 
 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) 
 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) 
Pages
98
Publication year
2023
Publication date
2023
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2761456494
Copyright
© The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.