Abstract 4380: Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-sequencing

Abstract

Abstract Tumors are heterogeneous ecosystems composed of genetically and epigenetically distinct cancer cell populations embedded in an intricate tumor microenvironment. The complexity and cell-to-cell interactions within this system pose a tremendous therapeutic challenge and opportunity. Due to technical constraints, current profiling technologies only provide average signals that do not reflect this intrinsic genetic and phenotypic variability. Here, we applied single-cell RNA-sequencing to examine 4,645 single cells isolated from 19 freshly procured melanomas, profiling malignant, immune and stromal cells. Malignant cells within the same tumor displayed transcriptional heterogeneity associated with the cell cycle, stem-like cells, spatial context, and a drug treatment resistance program. All tumors harbored malignant cells from two distinct transcriptional cell states, such that treatment-sensitive “MITF-high” tumors also contained drug-resistant “AXL-high” tumor cells; similar heterogeneity was present in 18 established melanoma cell lines. The frequency of AXL-high cells increased in post-relapse resistant tumors following treatment with BRAF/MEK inhibitors. Using multiplexed, quantitative single-cell immunofluorescence analysis and FACS, we validated these observations in melanoma cell lines treated with BRAF±MEK inhibitors. Signatures of cell types identified from single-cell analysis revealed distinct patterns of the tumor microenvironment. We inferred cell-to-cell interactions between stromal, immune and malignant cells, and identified factors, including known secreted gene products (e.g. CXCL12) and several complement factors. We validated the association between cancer-associated fibroblast (CAF)-expressed complement factor 3 (C3) and TIL infiltration in an independent set of 308 melanomas. Finally, analysis of TILs revealed T-cell activation dependent and independent exhaustion programs that varied among patients dependent on their exposure to treatment with immune checkpoint-inhibitors. In addition to co-expression of several known co-inhibitory receptors, including PD1, CTLA-4, and TIM-3, we identified common markers associated with cytotoxicity-independent T-cell exhaustion across patients. To identify potential T-cell clones, we classified single T-cells by their isoforms of the V and J segments of the alpha and beta TCR chains, allowing us to identify expanded T-cell clones. We found that clonally expanded T-cells expressed a strong exhaustion program, while non-expanded T-cells lacked this phenotype. This study represents the most comprehensive single-cell genomics analysis in humans to date and begins to unravel the cellular ecosystem of tumors. Single-cell genomics offer new insights with implications for both targeted and immune therapies by simultaneously profiling numerous aspects of a tumor with a single assay. Citation Format: Benjamin Izar, Itay Tirsh, Sanjay Prakadan, Marc Wadsworth, Daniel Treacy, John Trombetta, Asaf Rotem, Christine Lian, George Murphy, Mohammad Fallahi-Sichani, Ken Dutton-Regester, Jia-Ren Lin, Judit Jane-Valbuena, Orit Rozenblatt-Rosen, Charles Yoon, Alex Shalek, Aviv Regev, Levi Garraway. Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-sequencing. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 4380.