Aleth Gaillard

To explore the distinct genotypic and phenotypic states of melanoma tumors, we applied single-cell RNA sequencing (RNA-seq) to 4645 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 tumors characterized by high levels of the MITF transcription factor also contained cells with low MITF and elevated levels of the AXL kinase. Single-cell analyses suggested distinct tumor microenvironmental patterns, including cell-to-cell interactions. Analysis of tumor-infiltrating T cells revealed exhaustion programs, their connection to T cell activation and 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.

The orchestrated action of genes controls complex biological phenotypes, yet the systematic discovery of gene and drug combinations that modulate these phenotypes in human cells is labor intensive and challenging to scale. Here, we created a platform for the massively parallel screening of barcoded combinatorial gene perturbations in human cells and translated these hits into effective drug combinations. This technology leverages the simplicity of the CRISPR-Cas9 system for multiplexed targeting of specific genomic loci and the versatility of combinatorial genetics en masse (CombiGEM) to rapidly assemble barcoded combinatorial genetic libraries that can be tracked with high-throughput sequencing. We applied CombiGEM-CRISPR to create a library of 23,409 barcoded dual guide-RNA (gRNA) combinations and then perform a high-throughput pooled screen to identify gene pairs that inhibited ovarian cancer cell growth when they were targeted. We validated the growth-inhibiting effects of specific gene sets, including epigenetic regulators KDM4C/BRD4 and KDM6B/BRD4, via individual assays with CRISPR-Cas-based knockouts and RNA-interference-based knockdowns. We also tested small-molecule drug pairs directed against our pairwise hits and showed that they exerted synergistic antiproliferative effects against ovarian cancer cells. We envision that the CombiGEM-CRISPR platform will be applicable to a broad range of biological settings and will accelerate the systematic identification of genetic combinations and their translation into novel drug combinations that modulate complex human disease phenotypes.

Abstract A single tumor is composed of malignant cells in diverse genetic and epigenetic states, and this diversity presents a significant barrier for targeted therapies. Furthermore, diverse non-malignant cells, such as immune, fibroblasts and endothelial cells shape the tumor microenvironment and are emerging as important drug targets. However, the diversity of cellular states among malignant and non-malignant cells within any tumor remains poorly understood. To begin to address these challenges we applied single-cell RNA-seq to profile >3,000 single cells isolated from 16 fresh human melanomas, and characterized distinct cell types and cell states. We found that malignant cells within the same tumor display transcriptional heterogeneity associated with multiple biological processes. In particular, subpopulations of cells in treatment-naïve tumors expressed a transcriptional program associated with resistance to RAF/MEK inhibition, and these were enriched in post-relapsed samples. Among several non-malignant cell types that were identified we focused on tumor-infiltrating T-cells and identified multiple profiles of exhaustion which differed among patients and could be linked to prior immunotherapies. Finally, we used our single cell–derived profiles of cell types within melanoma to deconvolve publicly available bulk tumor profiles and infer interactions between cells in the tumor microenvironment. This work demonstrates the capacity of single cell transcriptomics to offer new insights with implications for both targeted and immune therapies and will be broadly applicable to other tumor types. Citation Format: Itay Tirosh, Benjamin Izar, Sanjay M. Prakadan, Marc H. Wadsworth II, Daniel Treacy, John J. Trombetta, Diana Lu, Asaf Rotem, Christine Lian, George Murphy, Ofir Cohen, Eli van Allen, Monica Bertagnolli, Alex Genshaft, Travis K. Hughes, Carly G. K. Ziegler, Samuel W. Kazer, Aleth Gaillard, Kellie E. Kolb, Judit Valbuena1, Charles Yoon, Orit Rozenblatt-Rosen, Alex K. Shalek, Aviv Regev and Levi Garraway. Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2015 Nov 5-9; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2015;14(12 Suppl 2):Abstract nr CN07-04.