Journal
CANCERS
Volume 14, Issue 19, Pages -Publisher
MDPI
DOI: 10.3390/cancers14194830
Keywords
immune checkpoint blockade; melanoma; mouse models; antigen presentation; major histocompatibility (MHC) class I; interferon; T lymphocytes; immunological memory
Categories
Funding
- Macquarie University, Melanoma Institute Australia
- New South Wales Department of Health, NSW Health Pathology, National Health and Medical Research Council of Australia (NHMRC) [1128951, 1130423, 1104503, 1093017]
- Cancer Institute NSW
- Sydney Vital Translational Cancer Research Centre
- NHMRC Practitioner Fellowship [1141295]
- NHMRC Fellowship [2007839]
- University of Sydney Medical Foundation
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This study presents a biomarker-driven workflow to generate a mouse melanoma model responsive to anti-PD1 and anti-CTLA4 immunotherapy. The model recapitulates human immunotherapy-responding tumor phenotypes and provides insights into the mechanisms underlying the durability of response to immune checkpoint inhibitors.
Simple Summary Immunotherapy has improved the outcomes of patients with advanced melanoma, although many patients will progress while on treatment. Preclinical animal models provide valuable insights into immunotherapy response or resistance and can be used to test novel treatment combinations. The development of animal cancer models rarely involves the systematic analysis and inclusion of predictive biomarkers of immunotherapy response. This study describes a biomarker-driven workflow to generate a transplantable mouse melanoma model responsive to anti-PD1 and anti-CTLA4 immunotherapy. This model recapitulates human immunotherapy-responding tumor phenotypes and provides unique insights into the discrete mechanisms underlying the durability of response to immune checkpoint inhibitors. Immunotherapy has transformed the management of patients with advanced melanoma, with five-year overall survival rates reaching 52% for combination immunotherapies blocking the cytotoxic T-lymphocyte-associated antigen-4 (CTLA4) and programmed cell death-1 (PD1) immune axes. Yet, our understanding of local and systemic determinants of immunotherapy response and resistance is restrained by the paucity of preclinical models, particularly those for anti-PD1 monotherapy. We have therefore generated a novel murine model of melanoma by integrating key immunotherapy response biomarkers into the model development workflow. The resulting YUMM3.3(UVR)c34 (BrafV600E; Cdkn2a-/-) model demonstrated high mutation burden and response to interferon (IFN)gamma, including induced expression of antigen-presenting molecule MHC-I and the principal PD1 ligand PD-L1, consistent with phenotypes of human melanoma biopsies from patients subsequently responding to anti-PD1 monotherapy. Syngeneic immunosufficient mice bearing YUMM3.3(UVR)c34 tumors demonstrated durable responses to anti-PD1, anti-CTLA4, or combined treatment. Immunotherapy responses were associated with early on-treatment changes in the tumor microenvironment and circulating T-cell subsets, and systemic immunological memory underlying protection from tumor recurrence. Local and systemic immunological landscapes associated with immunotherapy response in the YUMM3.3(UVR)c34 melanoma model recapitulate immunotherapy responses observed in melanoma patients and identify discrete immunological mechanisms underlying the durability of responses to anti-PD1 and anti-CTLA4 treatments.
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