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Metastatic plasticity in melanoma

Metastasis is 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. 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 (epi)-genome and transcriptome. Integrating single-cell profiling with lineage tracing provides a robust framework for defining cell fate transitions, intermediate states and trajectory inference. Using such tools, we propose to monitor the diversity and dynamics of melanoma cell states during metastatic dissemination using a clinically-relevant mouse model of (NRAS-driven) melanoma, a disease with high metastatic propensity. The overarching objective being the identification of key (druggable) drivers of cellular reprogramming into metastatic initiating cell state(s).

Date:1 Jan 2020  →  Today
Keywords:Metastasis, cancer-related deaths, non-genetic reprogramming in 4D, single-cell profiling, lineage tracing
Disciplines:Cancer biology