Bessell et al. identified an epitope expressed on commensal bacteria (SVY) with homology to a model tumor antigen (SIY) capable of eliciting cross-reactive T cell responses. Despite different TCR-pMHC affinities between the two epitopes, T cells expanded against SVY or SIY cross-reacted with the other and shared T cell clones. Mice exposed to commensal bacteria expressing SVY, which varied by commercial source (or in some experiments, by co-housing), had slower B16-SIY tumor growth and could generate stronger SVY-specific T cell responses with altered clonal composition. Adoptively transferred SVY-specific T cells slowed B16-SIY growth.
Contributed by Alex Najibi
ABSTRACT: Recent studies show gut microbiota modulate antitumor immune responses; one proposed mechanism is cross-reactivity between antigens expressed in commensal bacteria and neoepitopes. We found that T cells targeting an epitope called SVYRYYGL (SVY), expressed in the commensal bacterium Bifidobacterium breve (B. breve), cross-react with a model neoantigen, SIYRYYGL (SIY). Mice lacking B. breve had decreased SVY-reactive T cells compared with B. breve-colonized mice, and the T cell response was transferable by SVY immunization or by cohousing mice without Bifidobacterium with ones colonized with Bifidobacterium. Tumors expressing the model SIY neoantigen also grew faster in mice lacking B. breve compared with Bifidobacterium-colonized animals. B. breve colonization also shaped the SVY-reactive TCR repertoire. Finally, SVY-specific T cells recognized SIY-expressing melanomas in vivo and led to decreased tumor growth and extended survival. Our work demonstrates that commensal bacteria can stimulate antitumor immune responses via cross-reactivity and how bacterial antigens affect the T cell landscape.
Author Info: (1) Graduate Program in Immunology and. (2) Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA. (3) Human Oncology and Pathogenesis Program, M
Author Info: (1) Graduate Program in Immunology and. (2) Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA. (3) Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, New York, USA. (4) Computational Biology Center, IBM Thomas J. Watson Research Center, Yorktown Heights, New York, USA. (5) Computational Biology Center, IBM Thomas J. Watson Research Center, Yorktown Heights, New York, USA. (6) Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA. (7) Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. (8) Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. (9) Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, New York, USA. (10) Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, New York, USA. (11) Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, New York, USA. (12) Computational Biology Center, IBM Thomas J. Watson Research Center, Yorktown Heights, New York, USA. Department of Chemistry, Columbia University, New York, New York, USA. (13) Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, New York, USA. Immunogenomics and Precision Oncology Platform, Memorial Sloan Kettering Cancer Center, New York, New York, USA. Center for Immunotherapy and Precision Immuno-Oncology, Cleveland Clinic, Cleveland, Ohio, USA. (14) Graduate Program in Immunology and. Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. Institute of Cellular Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
