Perturb-Seq: Dissecting Molecular Circuits with Scalable Single-Cell RNA Profiling of Pooled Genetic Screens

Genetic screens help infer gene function in mammalian cells, but it has remained difficult to assay complex phenotypes—such as transcriptional profiles—at scale. Here, we develop Perturb-seq, combining single-cell RNA sequencing (RNA-seq) and clustered regularly interspaced short palindromic repeats (CRISPR)-based perturbations to perform many such assays in a pool. We demonstrate Perturb-seq by analyzing 200,000 cells in immune cells and cell lines, focusing on transcription factors regulating the response of dendritic cells to lipopolysaccharide (LPS). Perturb-seq accurately identifies individual gene targets, gene signatures, and cell states affected by individual perturbations and their genetic interactions. We posit new functions for regulators of differentiation, the anti-viral response, and mitochondrial function during immune activation. By decomposing many high content measurements into the effects of perturbations, their interactions, and diverse cell metadata, Perturb-seq dramatically increases the scope of pooled genomic assays. Keywords: single-cell RNA-seq; pooled screen; CRISPR; epistasis; genetic interaction

Tankyrase inhibition sensitizes melanoma to PD-1 immune checkpoint blockade in syngeneic mouse models

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Melanoma Models for the Next Generation of Therapies

There is a lack of appropriate melanoma models that can be used to evaluate the efficacy of novel therapeutic modalities. Here, we discuss the current state of the art of melanoma models including genetically engineered mouse, patient-derived xenograft, zebrafish, and ex vivo and in vitro models. We also identify five major challenges that can be addressed using such models, including metastasis and tumor dormancy, drug resistance, the melanoma immune response, and the impact of aging and environmental exposures on melanoma progression and drug resistance. Additionally, we discuss the opportunity for building models for rare subtypes of melanomas, which represent an unmet critical need. Finally, we identify key recommendations for melanoma models that may improve accuracy of preclinical testing and predict efficacy in clinical trials, to help usher in the next generation of melanoma therapies

DIALOGUE maps multicellular programs in tissue from single-cell or spatial transcriptomics data

Deciphering the functional interactions of cells in tissues remains a major challenge. Here we describe DIALOGUE, a method to systematically uncover multicellular programs (MCPs)-combinations of coordinated cellular programs in different cell types that form higher-order functional units at the tissue level-from either spatial data or single-cell data obtained without spatial information. Tested on spatial datasets from the mouse hypothalamus, cerebellum, visual cortex and neocortex, DIALOGUE identified MCPs associated with animal behavior and recovered spatial properties when tested on unseen data while outperforming other methods and metrics. In spatial data from human lung cancer, DIALOGUE identified MCPs marking immune activation and tissue remodeling. Applied to single-cell RNA sequencing data across individuals or regions, DIALOGUE uncovered MCPs marking Alzheimer's disease, ulcerative colitis and resistance to cancer immunotherapy. These programs were predictive of disease outcome and predisposition in independent cohorts and included risk genes from genome-wide association studies. DIALOGUE enables the analysis of multicellular regulation in health and disease

Synovial sarcoma oncogenesis revealed by single-cell profiling

Synovial sarcoma is a soft tissue malignancy driven by the SS18-SSX fusion oncoprotein. In Nature Medicine, Jerby-Arnon et al. present a single-cell dataset for synovial sarcoma that reveals a novel 'core oncogenic program' driven by SS18-SSX, with implications for treatment strategies based on epigenetics, cell-cycle control, and immune augmentation.Medicine, Faculty ofReviewedFacultyGraduat