Preclinical GEM and GDA Models of Primary and Metastatic Melanoma

Division Of Basic Sciences - Nci

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Linked publications & trials

Abstract

Metastatic melanoma is featured by predominant resistance to the conventional therapies, resulting in poor prognoses and almost uniformly high lethality due to this disease. About 60% of all melanoma clinical cases harbor the BrafV600E mutation, and most are responsive to the recently approved therapies that target the mutant Braf protein. However, disease generally recurs within 12-15 months displaying the acquires resistance to Braf inhibitors, aggressive growth and enhanced metastatic potential. Additional promising results that demonstrate the possibility of durable responses in a subset of patients have recently been achieved with immune checkpoint modulation therapy that targets PD1/PDL1 or CTLA4 or the combination, and further immunomodulation therapies are being developed. However, it is not clear why some patients respond so well, while others don't respond at all. In addition, it will be critical to determine dosing regimens, effective combinations of multiple immunotherapies and their combination with cancer cells or other components of the cancer stroma. The metastatic melanoma GDA models developed in this project has been demonstrated as a highly valuable preclinical resource in determining potential mechanisms of drug resistance and the development of effective combination treatments, dosing regimens and diagnostic strategies for evaluation in patients. The established and validated GDA models include HGF/MET-driven primary and metastatic melanoma, including models in which tumors express luciferase. In addition, primary Braf driven and primary and metastatic HGF/MET/Braf driven models have been established. These models have been actively employed during a broad-scope collaboration study aimed at a comparative assessment of the effects of checkpoint inhibitors in BRAF or HGF-driven mouse models of melanoma in collaboration with Dr. Glenn Merlino's CCR laboratory. CAPR scientists in collaboration with Dr. Merlino's melanoma researchers completed recently an impressive continuum of experimental activities aimed at description and molecular characterization of multiple melanoma models featuring metastatic spread post-resection and is currently advancing studies to model the outcomes of checkpoint blockade therapies in adjuvant vs. neo-adjuvant settings for melanoma therapy. These experiments, conducted in HGF/SF- and Cdkn2a-driven melanoma models, allowed to establish conditions and therapeutic schedules for treatment of tumor-bearing animals with PD-1 checkpoint inhibitor, in both adjuvant and neoadjuvant settings following tumor resection this preparing the foundation for a large scale comparative efficacy experiment. As one of the additional key goals of this study, the melanoma disease response to such therapeutic intervention will be compared across at least three different melanoma models driven by a combination of distinct oncogenic molecular aberrations. A high-profile collaborative paper in Nature Medicine journal has been recently published to report on comparative assessment of genomic and transcriptional signatures and profiles of immune infiltrating cell landscapes to examine correlations between the properties of melanoma-associated adaptive immune cells and tumor resistance to therapeutic challenges. In addition, these experiments suggested an intriguing connection of intra-tumoral heterogeneity and differentiation status of melanoma malignancies and sensitivity to therapeutic inhibition of immune checkpoint signaling. Taken together, these findings are broadly anticipated to have a significant translational impact for future melanoma therapeutic development. A follow up study published by CAPR scientists in Mol Cancer Research further expanded the translational impact of ongoing research conducted in melanoma models by identifying a spectrum of biomarkers and evaluating the complexity of T-cell receptor repertoires as a yet another informative molecular facet of melanoma malignancy predictive of tumor response to immunomodulatory therapeutics.