Expressed Barcoding Enables High-Resolution Tracking of the Evolution of Drug Tolerance.

For a majority of patients with non-small cell lung cancer with EGFR mutations, treatment with EGFR inhibitors (EGFRi) induces a clinical response. Despite this initial reduction in tumor size, residual disease persists that leads to disease relapse. Elucidating the preexisting biological differences between sensitive cells and surviving drug-tolerant persister cells and deciphering how drug-tolerant cells evolve in response to treatment could help identify strategies to improve the efficacy of EGFRi. In this study, we tracked the origins and clonal evolution of drug-tolerant cells at a high resolution by using an expressed barcoding system coupled with single-cell RNA sequencing. This platform enabled longitudinal profiling of gene expression and drug sensitivity in response to EGFRi across a large number of clones. Drug-tolerant cells had higher expression of key survival pathways such as YAP and EMT at baseline and could also differentially adapt their gene expression following EGFRi treatment compared with sensitive cells. In addition, drug combinations targeting common downstream components (MAPK) or orthogonal factors (chemotherapy) showed greater efficacy than EGFRi alone, which is attributable to broader targeting of the heterogeneous EGFRi-tolerance mechanisms present in tumors. Overall, this approach facilitates thorough examination of clonal evolution in response to therapy that could inform the development of improved diagnostic approaches and treatment strategies for targeting drug-tolerant cells. SIGNIFICANCE: The evolution and heterogeneity of EGFR inhibitor tolerance are identified in a large number of clones at enhanced cellular and temporal resolution using an expressed barcode technology coupled with single-cell RNA sequencing.

SHP2 blockade enhances anti-tumor immunity via tumor cell intrinsic and extrinsic mechanisms.

SHP2 is a ubiquitous tyrosine phosphatase involved in regulating both tumor and immune cell signaling. In this study, we discovered a novel immune modulatory function of SHP2. Targeting this protein with allosteric SHP2 inhibitors promoted anti-tumor immunity, including enhancing T cell cytotoxic function and immune-mediated tumor regression. Knockout of SHP2 using CRISPR/Cas9 gene editing showed that targeting SHP2 in cancer cells contributes to this immune response. Inhibition of SHP2 activity augmented tumor intrinsic IFNγ signaling resulting in enhanced chemoattractant cytokine release and cytotoxic T cell recruitment, as well as increased expression of MHC Class I and PD-L1 on the cancer cell surface. Furthermore, SHP2 inhibition diminished the differentiation and inhibitory function of immune suppressive myeloid cells in the tumor microenvironment. SHP2 inhibition enhanced responses to anti-PD-1 blockade in syngeneic mouse models. Overall, our study reveals novel functions of SHP2 in tumor immunity and proposes that targeting SHP2 is a promising strategy for cancer immunotherapy.

Systematic comparison of single-cell and single-nucleus RNA-sequencing methods.

The scale and capabilities of single-cell RNA-sequencing methods have expanded rapidly in recent years, enabling major discoveries and large-scale cell mapping efforts. However, these methods have not been systematically and comprehensively benchmarked. Here, we directly compare seven methods for single-cell and/or single-nucleus profiling-selecting representative methods based on their usage and our expertise and resources to prepare libraries-including two low-throughput and five high-throughput methods. We tested the methods on three types of samples: cell lines, peripheral blood mononuclear cells and brain tissue, generating 36 libraries in six separate experiments in a single center. To directly compare the methods and avoid processing differences introduced by the existing pipelines, we developed scumi, a flexible computational pipeline that can be used with any single-cell RNA-sequencing method. We evaluated the methods for both basic performance, such as the structure and alignment of reads, sensitivity and extent of multiplets, and for their ability to recover known biological information in the samples.

Author Correction: Systematic comparison of single-cell and single-nucleus RNA-sequencing methods.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Massively parallel single-nucleus RNA-seq with DroNc-seq.

Single-nucleus RNA sequencing (sNuc-seq) profiles RNA from tissues that are preserved or cannot be dissociated, but it does not provide high throughput. Here, we develop DroNc-seq: massively parallel sNuc-seq with droplet technology. We profile 39,111 nuclei from mouse and human archived brain samples to demonstrate sensitive, efficient, and unbiased classification of cell types, paving the way for systematic charting of cell atlases.

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.