Developing organoid models of mucosal melanoma for functional genetics and metastasis

Mucosal melanoma is a rare and highly aggressive and metastatic form of melanoma.  Unlike cutaneous melanoma that can respond to targeted and immune based therapies, there are limited treatment options for mucosal melanomas. New mucosal melanoma models are needed to understand drug resistance, the high propensity for metastasis, and to test new therapeutic strategies. 

The goal of this PhD project is to develop organoid models of metastatic mucosal melanoma, with a focus on metastasis to the brain. In our first model, we will use gene editing of mouse melanocytes to generate melanoma organoids that can be transplanted to mucosal sites in the mouse and studied for metastasis to sites, including the brain. In our second model, we will use patient mucosal melanoma cells that can be transplanted into brain organoids (to form “assembloids”) to study the cellular interactions between the brain tissue and the melanoma using spatial transcriptomics. Ultimately, we aim to screen for new drug targets and genetic mechanisms of metastasis in the organoids that can then be tested in our mouse model in vivo. 

The mouse studies will be performed at the MRC HGU, and in collaboration with the Myant laboratory, where we have access to excellent animal facilities, advanced imaging, genome engineer resources, cell culture and flow cytometry facilities. The assembloid studies will be performed in the Rybak-Wolf laboratory at the MDC, which has extensive experience with brain organoids and high-throughput omics technologies, including assembloids and immunocompetent- vascularized brain organoids. The student will spend three months at the MDC to be trained to develop brain organoids and to learn OPEN-ST spatial transcriptomic method (in collaboration with the Rajewsky lab), which will be then utilized for assembloids characterization. We aim to also have in person visits between Edinburgh and Berlin at least once a year to share expertise and unpublished data. In addition, the student will meet with both supervisory teams at least once a month by video call.

For informal enquiries about this project, please contact Liz Patton (e.patton@ed.ac.uk).