Melanoma cells carry hundreds of DNA mutations at once, making it nearly impossible to tell which ones actually drive the cancer. This project uses healthy human melanocytes—the pigment-producing skin cells that give rise to melanoma—and edits them step by step to carry the same mutations found in patients, creating a clean model that mimics how the cancer evolves. The problem is that in real tumours, genetic changes and epigenetic changes (alterations in how DNA is packaged and accessed) are tangled together, and their combined effects on gene activity, cell behaviour, and drug resistance are poorly understood. This research will apply advanced molecular profiling and genome-editing tools to these models to untangle those connections. If successful, it could reveal which specific mutations and chromatin alterations make melanoma cells resistant to therapy, pointing toward new drug targets. This is fundamental science: it will generate new datasets and cell models that clarify the causal links between genetics, epigenetics, and disease progression, laying groundwork for more rational treatment design rather than delivering an immediate clinical tool.
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Alterations in a cell’s DNA, in its sequence and accessibility, drive its transformation into a tumour. Identifying causal connections between the alterations found in cancer patients and disease-relevant phenotypes is key to improving our understanding of cancer development and supporting the design of tailored therapies. However, in tumour types with a high mutational load such as melanoma, drawing these connections is challenging: many mutations co-exist and it is hard to isolate their effects. Melanomas are also characterized by profound rearrangements in the chromatin landscape, which can influence gene expression regulation ultimately impacting disease development. Despite their potential to reveal novel drug targets, the relationships between genetic and epigenetic alterations remain poorly understood. Previously, we sequentially edited primary healthy human melanocytes to bear mutations in pathways commonly altered in melanoma patients, generating isogenic models that mimic cancer evolution. These models allow causal studies of (epi)genotype-to-phenotype relationships, minimizing additional sources of variations. In this proposal, I will leverage and expand upon these models by applying advanced molecular profiling techniques, genome-editing methods, and drug challenges, to: 1.gain insights into how cancer-driver mutations impact chromatin accessibility, shaping gene expression, cell states, and plasticity; 2.study alterations in genes encoding for regulators of chromatin structure: these occur often in patients, but their consequences are unknown; 3.understand how genetic alterations influence how cells respond to therapy and develop drug resistance. This research will generate new models and datasets to inform an improved understanding of the links between genetics, epigenetics and molecular phenotypes in melanoma.
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