Immune response persisting melanoma cells: Mechanisms of immune escape

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Recent advances in therapeutics harnessing the intrinsic power of the immune system to recognize and destroy tumors have revolutionized cancer treatment. Indeed, immune checkpoint inhibitors (ICI) may result in rapid and durable antitumor responses. However, numerous melanoma patients treated with ICI will not experience these benefits, as durable response rates do not exceed 60%. In ICI refractory patients, the complexity of adaptive immune responses is surpassed by at least one or even multiple immune escape mechanisms. These may include dysfunctional T cells, regulatory immune and stromal cells, or tumour cell characteristics. It should be noted, that this list is not exhaustive and none of the factors stands alone, but they are closely intertwined. Moreover, the immune-resistant phenotype is not static; rather, it is constantly adapting to dynamically changing immunological, intrinsic and therapeutic circumstances that exert selection pressure. When addressing PTEN function as a controller of the PI3K/AKT-pathway in the triple transgenic LLA-TG3/PTENflox/Cre melanoma model in FP1, the dynamic interactions between the melanoma and the immune system became obvious, illustrating that some ‘established’ functions of a given individual signalling pathway represent an endpoint resulting from an evolutional integral of diverse cellular effects in the cancer cell together with (immune) editing mechanism of the host. Thus, to remove the blinkers, we plan an integrative approach taking advantage of single cell analyses not only in the projected murine model, but also for longitudinally collected clinical samples obtained before, one week after initiation of ICI and at the time of progression. This is facilitated by being part of the PhenoTImE using the collective understanding of tumor cell genetics and epigenetics including the resulting functional and metabolomic cell states. Vice versa, we contribute our insights into tumor and stromal cell interaction and tumor (immune) evolution as well as our technical expertise in single cell analysis and spatial proteomics plus the respective bioinformatics. Our overall hypothesis is that the dynamic heterogeneity of melanoma cell states and the plasticity in adaptive immune responses represent two steadily interacting facets within one complex evolutionary ecosystem. As part of our long-term efforts across different skin cancers, we want to find out what molecular signals drive the therapeutically unfavourable terminal differentiation/exhaustion of T-cells and how advantageous central memory/stem cell-like T cells are maintained. The expected results together with machine learning models for mouse-to-human inference (and vice versa) will allow us to increase the translational significance of our project, ultimately resulting in innovative strategies to overcome immune resistance in melanoma.