Intra-Tumoral heterogeneity in nras-driven metastatic melanoma
Metastasis is largely refractory to therapy and, thereby, responsible for 90% of cancer-related deaths. An incomplete view of the mechanisms that drive metastasis has been a major barrier to rational development of effective therapeutics and prognostic diagnostics for metastatic patients. There is increasing evidence that this multi-step process involves reversible non-genetic reprogramming events allowing cancer cells to acquire diverse phenotypic features needed to migrate, invade, intra/extra-vasate and actively adapt to the varying environment (stress) they encounter. Understanding metastasis therefore requires methodologies that capture the magnitude and dynamics of non-genetic reprogramming in 4D (space and time) at the single-cell resolution. The advent of reliable single-cell multi-Omics analytical tools allows the simultaneous profiling of single cell’s genome, epigenome and transcriptome. Integrating single-cell profiling with lineage tracing provides a robust framework for defining cell fate transitions, intermediate states and trajectory inference. The host lab has recently used such a powerful combination of approaches to study the cellular origin of melanoma, the early molecular events associated with initiation of the disease and to portray cell state dynamics during therapy response. I propose to exploit this know-how to perform a longitudinal and exhaustive analysis of the diversity and trajectories of melanoma cell states during metastatic dissemination using a clinically-relevant mouse model of melanoma, a disease with a very high metastatic propensity. The gene regulatory networks underlying the identified metastatic cell states will be deciphered and the data exploited to develop therapeutic modalities targeting (amenable) drivers of state switching that contribute to early key steps of the metastatic process. The project is expected to lead to new avenues for early detection and interception of metastatic melanoma.