Fatima Mechta-Grigoriou, Karin Tarte, Sylvain Baulande, Floriane Pelon, Andrei Zinovyev, Luca Albergante, Gérard Zalcman, Brigitte Bourachot, Sonia Lameiras, Hocine Rachid Hocine, Yann Kieffer, Charles Bernard, Claire Bonneau, Géraldine Gentric, Alice Guyard, Anne Vincent-Salomon, Institut Curie [Paris], Genomics of Excellence (ICGex) Platform, Institut Curie Research Center, Cancer et génome: Bioinformatique, biostatistiques et épidémiologie d'un système complexe, Mines Paris - PSL (École nationale supérieure des mines de Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut Curie [Paris]-Institut National de la Santé et de la Recherche Médicale (INSERM), CIC - CHU Bichat, Institut National de la Santé et de la Recherche Médicale (INSERM), Microenvironment, Cell Differentiation, Immunology and Cancer (MICMAC), Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), INCa-DGOS-4654, Institut National Du Cancer, Scientific council, Fondation pour la Recherche Médicale, Labelisation, Ligue Contre le Cancer, Incentive and Cooperative program, Institut Curie, Grand Prix, Fondation Simone et Cino Del Duca, ANR-10-INBS-09-08, Agence Nationale de la Recherche, PC201317, Institut National de la Sante et de la Recherche Medicale, Grand Prix, Le Cancer du sein, Parlons-en, ANR-19-P3IA-0001,PRAIRIE,PaRis Artificial Intelligence Research InstitutE(2019), MINES ParisTech - École nationale supérieure des mines de Paris, Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), Jonchère, Laurent, and PaRis Artificial Intelligence Research InstitutE - - PRAIRIE2019 - ANR-19-P3IA-0001 - P3IA - VALID
A subset of cancer-associated fibroblasts (FAP+/CAF-S1) mediates immunosuppression in breast cancers, but its heterogeneity and its impact on immunotherapy response remain unknown. Here, we identify 8 CAF-S1 clusters by analyzing more than 19,000 single CAF-S1 fibroblasts from breast cancer. We validate the five most abundant clusters by flow cytometry and in silico analyses in other cancer types, highlighting their relevance. Myofibroblasts from clusters 0 and 3, characterized by extracellular matrix proteins and TGFβ signaling, respectively, are indicative of primary resistance to immunotherapies. Cluster 0/ecm-myCAF upregulates PD-1 and CTLA4 protein levels in regulatory T lymphocytes (Tregs), which, in turn, increases CAF-S1 cluster 3/TGFβ-myCAF cellular content. Thus, our study highlights a positive feedback loop between specific CAF-S1 clusters and Tregs and uncovers their role in immunotherapy resistance. Significance: Our work provides a significant advance in characterizing and understanding FAP+ CAF in cancer. We reached a high resolution at single-cell level, which enabled us to identify specific clusters associated with immunosuppression and immunotherapy resistance. Identification of cluster-specific signatures paves the way for therapeutic options in combination with immunotherapies. This article is highlighted in the In This Issue feature, p. 1241