To explore the distinct genotypic and phenotypic states of melanoma tumors we applied single-cell RNA-seq to 4,645 single cells isolated from 19 patients, profiling malignant, immune, stromal and endothelial cells. Malignant cells within the same tumor displayed transcriptional heterogeneity associated with the cell cycle, spatial context, and a drug resistance program. In particular, all tumors harbored malignant cells from two distinct transcriptional cell states, such that “MITF-high” tumors also contained “AXL-high” tumor cells. Single-cell analyses suggested distinct tumor micro-environmental patterns, including cell-to-cell interactions. Analysis of tumor-infiltrating T cells revealed exhaustion programs, their connection to T cell activation and to clonal expansion, and their variability across patients. Overall, we begin to unravel the cellular ecosystem of tumors and how single cell genomics offers insights with implications for both targeted and immune therapies.

SUMMARY Tumor-specific genomic information has the potential to guide therapeutic strategies and revolutionize patient treatment. Currently, this approach is limited by an abundance of disease-associated mutants whose biological functions and impacts on therapeutic response are uncharacterized. To begin to address this limitation, we functionally characterized nearly all (99.84%) missense mutants of MAPK1/ERK2, an essential effector of oncogenic RAS and RAF. Using this approach, we discovered rare gain- and loss-of-function ERK2 mutants found in human tumors, revealing that, in the context of this assay, mutational frequency alone cannot identify all functionally impactful mutants. Gain-of-function ERK2 mutants induced variable responses to RAF-, MEK- and ERK-directed therapies, providing a reference for future treatment decisions. Tumor-associated mutations spatially clustered in two ERK2 effector-recruitment domains, yet produced mutants with opposite phenotypes. This approach articulates an allele-characterization framework that can be scaled to meet the goals of genome-guided oncology.

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