Using the MC38 tumor model, Damei et al. showed that CD103+CD8 TRM cells are involved in responses to anti-PD-1 treatment, but not CTLA-4 blockade. The benefits of anti-PD-1 treatment were compromised in animals challenged with anti-CD8 and anti-CD103 blocking antibodies. CTLA-4 blockade expanded CD49a+CD4+ TRM cells and increased tumor-specific CD4+ TIL-mediated cytotoxicity. CD49a+CD4+ TRM cells with cytotoxic potential were present in human melanoma and lung tumors. Furthermore, a high density of CD49a+CD4 TRM cells in pre-treatment melanoma was predictive of response to CTLA-4 plus PD-1 blockade therapy.
Contributed by Shishir Pant
ABSTRACT: The involvement of tumour-resident memory T (T(RM)) cells in responses to immune checkpoint inhibitors remains unclear. Here, we show that while CD103(+)CD8 T(RM) cells are involved in response to PD-1 blockade, CD49a(+)CD4 T(RM) cells are required for the response to anti-CTLA-4. Using preclinical mouse models, we demonstrate that the benefits of anti-PD-1 treatment are compromised in animals challenged with anti-CD8 and anti-CD103 blocking antibodies. By contrast, the benefits of anti-CTLA-4 are decreased by anti-CD4 and anti-CD49a neutralizing antibodies. Single-cell RNA sequencing on tumour-infiltrating T-lymphocytes (TIL) reveals a CD49a(+)CD4 T(RM) signature, enriched in Ctla-4 transcripts, exacerbated upon anti-CTLA-4. CTLA-4 blockade expands CD49a(+)CD4 T(RM) cells and increases tumour-specific CD4-TIL-mediated cytotoxicity. A CD49a(+)CD4 T(RM) signature enriched in CTLA-4 and cytotoxicity-linked transcripts is also identified in human TILs. Multiplex immunohistochemistry in a cohort of anti-CTLA-4-plus-anti-PD-1-treated melanomas reveals an increase in CD49a(+)CD4 T-cell density in pre-treatment tumours, which correlates with higher rates of patient progression-free survival. Thus, CD49a(+)CD4 T(RM) cells may correspond to a predictive biomarker of response to combined immunotherapy.
Author Info: (1) INSERM UMR 1186, Integrative Tumour Immunology and Immunotherapy, Gustave Roussy, Faculte de Médecine-Universite Paris-Sud, Université Paris-Saclay, Villejuif, France. (2) INSE
Author Info: (1) INSERM UMR 1186, Integrative Tumour Immunology and Immunotherapy, Gustave Roussy, Faculte de Médecine-Universite Paris-Sud, Université Paris-Saclay, Villejuif, France. (2) INSERM UMR 1186, Integrative Tumour Immunology and Immunotherapy, Gustave Roussy, Faculte de Médecine-Universite Paris-Sud, Université Paris-Saclay, Villejuif, France. (3) Department of Medicine, Institut Bergonié, Bordeaux, France. (4) INSERM UMR 1186, Integrative Tumour Immunology and Immunotherapy, Gustave Roussy, Faculte de Médecine-Universite Paris-Sud, Université Paris-Saclay, Villejuif, France. Department of Pathology, Paris Saint Joseph Hospital, Paris, France. (5) Single Cell Biomarkers UTechS, Institut Pasteur, Universit Paris Cité, Paris, France. (6) Single Cell Biomarkers UTechS, Institut Pasteur, Université Paris Cité, Paris, France. (7) INSERM U970, Paris Cardiovascular Research Centre, Université Paris-Descartes, Sorbonne Paris Cité, Equipe Labellisée Ligue Contre le Cancer, Hôpital Européen Georges Pompidou, Service d'Immunologie Biologique, Paris, France. (8) Dermatology Unit, Department of Oncology, Institut Gustave Roussy, Villejuif, France. (9) INSERM UMR 1186, Integrative Tumour Immunology and Immunotherapy, Gustave Roussy, Faculte de Médecine-Universite Paris-Sud, Université Paris-Saclay, Villejuif, France. (10) INSERM UMR 1186, Integrative Tumour Immunology and Immunotherapy, Gustave Roussy, Faculte de Médecine-Universite Paris-Sud, Université Paris-Saclay, Villejuif, France. fathia.mami-chouaib@gustaveroussy.fr.
