CRISPR screens decode cancer cell pathways that trigger γδ T cell detection
(1) Mamedov MR (2) Vedova S (3) Freimer JW (4) Sahu AD (5) Ramesh A (6) Arce MM (7) Meringa AD (8) Ota M (9) Chen PA (10) Hanspers K (11) Nguyen VQ (12) Takeshima KA (13) Rios AC (14) Pritchard JK (15) Kuball J (16) Sebestyen Z (17) Adams EJ (18) Marson A
(1) Mamedov MR (2) Vedova S (3) Freimer JW (4) Sahu AD (5) Ramesh A (6) Arce MM (7) Meringa AD (8) Ota M (9) Chen PA (10) Hanspers K (11) Nguyen VQ (12) Takeshima KA (13) Rios AC (14) Pritchard JK (15) Kuball J (16) Sebestyen Z (17) Adams EJ (18) Marson A
ABSTRACT: γδ T cells are potent anticancer effectors with the potential to target tumours broadly, independent of patient-specific neoantigens or human leukocyte antigen background1-5. γδ T cells can sense conserved cell stress signals prevalent in transformed cells2,3, although the mechanisms behind the targeting of stressed target cells remain poorly characterized. Vγ9Vδ2 T cells-the most abundant subset of human γδ T cells4-recognize a protein complex containing butyrophilin 2A1 (BTN2A1) and BTN3A1 (refs. 6-8), a widely expressed cell surface protein that is activated by phosphoantigens abundantly produced by tumour cells. Here we combined genome-wide CRISPR screens in target cancer cells to identify pathways that regulate γδ T cell killing and BTN3A cell surface expression. The screens showed previously unappreciated multilayered regulation of BTN3A abundance on the cell surface and triggering of γδ T cells through transcription, post-translational modifications and membrane trafficking. In addition, diverse genetic perturbations and inhibitors disrupting metabolic pathways in the cancer cells, particularly ATP-producing processes, were found to alter BTN3A levels. This induction of both BTN3A and BTN2A1 during metabolic crises is dependent on AMP-activated protein kinase (AMPK). Finally, small-molecule activation of AMPK in a cell line model and in patient-derived tumour organoids led to increased expression of the BTN2A1-BTN3A complex and increased Vγ9Vδ2 T cell receptor-mediated killing. This AMPK-dependent mechanism of metabolic stress-induced ligand upregulation deepens our understanding of γδ T cell stress surveillance and suggests new avenues available to enhance γδ T cell anticancer activity.
Author Info:
(1) Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA. murad.mamedov@ucsf.edu. Department of Medicine, University of California, San Francisco, San Francisco,
CA, USA. murad.mamedov@ucsf.edu. (2) Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA. Department of Medicine, University of California, San Francisco, San Francisco, CA, USA. (3) Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA. Department of Medicine, University of California, San Francisco, San Francisco, CA, USA. Department of Genetics, Stanford University, Stanford, CA, USA. (4) Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA. Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA. UNM Comprehensive Cancer Center, University of New Mexico, Albuquerque, NM, USA. (5) Department of Biochemistry and Molecular Biology, University of Chicago, Chicago, IL, USA. (6) Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA. Department of Medicine, University of California, San Francisco, San Francisco, CA, USA. (7) Center for Translational Immunology, University Medical Center Utrecht, Utrecht, the Netherlands. (8) Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA. Department of Medicine, University of California, San Francisco, San Francisco, CA, USA. Department of Genetics, Stanford University, Stanford, CA, USA. (9) Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA. Department of Medicine, University of California, San Francisco, San Francisco, CA, USA. (10) Institute of Data Science and Biotechnology, Gladstone Institutes, San Francisco, CA, USA. (11) Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA. Department of Surgery, University of California, San Francisco, San Francisco, CA, USA. Diabetes Center, University of California, San Francisco, San Francisco, CA, USA. UCSF CoLabs, University of California, San Francisco, San Francisco, CA, USA. (12) Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA. (13) Princess Mxima Center for Pediatric Oncology, Utrecht, the Netherlands. Oncode Institute, Utrecht, the Netherlands. (14) Department of Genetics, Stanford University, Stanford, CA, USA. Department of Biology, Stanford University, Stanford, CA, USA. (15) Center for Translational Immunology, University Medical Center Utrecht, Utrecht, the Netherlands. Department of Hematology, University Medical Center Utrecht, Utrecht, the Netherlands. (16) Center for Translational Immunology, University Medical Center Utrecht, Utrecht, the Netherlands. (17) Department of Biochemistry and Molecular Biology, University of Chicago, Chicago, IL, USA. Committee on Immunology, University of Chicago, Chicago, IL, USA. (18) Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA. alexander.marson@ucsf.edu. Department of Medicine, University of California, San Francisco, San Francisco, CA, USA. alexander.marson@ucsf.edu. Diabetes Center, University of California, San Francisco, San Francisco, CA, USA. alexander.marson@ucsf.edu. Department of Microbiology and Immunology, University of California, San Francisco, San Francisco, CA, USA. alexander.marson@ucsf.edu. Innovative Genomics Institute, University of California-Berkeley, Berkeley, CA, USA. alexander.marson@ucsf.edu. UCSF Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA. alexander.marson@ucsf.edu. Parker Institute for Cancer Immunotherapy, University of California, San Francisco, San Francisco, CA, USA. alexander.marson@ucsf.edu. Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA. alexander.marson@ucsf.edu.
