Single-cell Screens Research Articles

Charting and probing the activity of ADARs in human development and cell-fate specification.

Adenosine deaminases acting on RNA (ADARs) impact diverse cellular processes and pathological conditions, but their functions in early cell-fate specification remain less understood. To gain insights here, we began by charting time-course RNA editing profiles in human organs from fetal to adult stages. Next, we utilized hPSC differentiation to experimentally probe ADARs, harnessing brain organoids as neural specific, and teratomas as pan-tissue developmental models. We show that time-series teratomas faithfully recapitulate fetal developmental trends, and motivated by this, conducted pan-tissue, single-cell CRISPR-KO screens of ADARs in teratomas. Knocking out ADAR leads to a global decrease in RNA editing across all germ-layers. Intriguingly, knocking out ADAR leads to an enrichment of adipogenic cells, revealing a role for ADAR in human adipogenesis. Collectively, we present a multi-pronged framework charting time-resolved RNA editing profiles and coupled ADAR perturbations in developmental models, thereby shedding light on the role of ADARs in cell-fate specification.

Linking candidate causal autoimmune variants to T cell networks using genetic and epigenetic screens in primary human T cells.

Genetic variants associated with autoimmune diseases are highly enriched within putative cis -regulatory regions of CD4 + T cells, suggesting that they alter disease risk via changes in gene regulation. However, very few genetic variants have been shown to affect T cell gene expression or function. We tested >18,000 autoimmune disease-associated variants for allele-specific expression using massively parallel reporter assays in primary human CD4 + T cells. The 545 expression-modulating variants (emVars) identified greatly enrich for likely causal variants. We provide evidence that many emVars are mediated by common upstream regulatory conduits, and that putative target genes of primary T cell emVars are highly enriched within a lymphocyte activation network. Using bulk and single-cell CRISPR-interference screens, we confirm that emVar-containing T cell cis -regulatory elements modulate both known and novel target genes that regulate T cell proliferation, providing plausible mechanisms by which these variants alter autoimmune disease risk.

In vivo perturb-seq of cancer and microenvironment cells dissects oncologic drivers and radiotherapy responses in glioblastoma.

Genetic perturbation screens with single-cell readouts have enabled rich phenotyping of gene function and regulatory networks. These approaches have been challenging in vivo, especially in adult disease models such as cancer, which include mixtures of malignant and microenvironment cells. Glioblastoma (GBM) is a fatal cancer, and methods of systematically interrogating gene function and therapeutic targets in vivo, especially in combination with standard of care treatment such as radiotherapy, are lacking. Here, we iteratively develop a multiplex in vivo perturb-seq CRISPRi platform for single-cell genetic screens in cancer and tumor microenvironment cells that leverages intracranial convection enhanced delivery of sgRNA libraries into mouse models of GBM. Our platform enables potent silencing of drivers of in vivo growth and tumor maintenance as well as genes that sensitize GBM to radiotherapy. We find radiotherapy rewires transcriptional responses to genetic perturbations in an in vivo-dependent manner, revealing heterogenous patterns of treatment sensitization or resistance in GBM. Furthermore, we demonstrate targeting of genes that function in the tumor microenvironment, enabling alterations of ligand-receptor interactions between immune and stromal cells following in vivo CRISPRi perturbations that can affect tumor cell phagocytosis. In sum, we demonstrate the utility of multiplexed perturb-seq for in vivo single-cell dissection of adult cancer and normal tissue biology across multiple cell types in the context of therapeutic intervention, a platform with potential for broad application.

Single-cell CRISPR screening characterizes transcriptional deregulation in T-cell acute lymphoblastic leukemia.

T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive type of leukemia caused by accumulation of multiple genetic alterations in T-cell progenitors. However, for many genes it remains unknown how their mutations contribute to disease development. We therefore performed two single-cell CRISPR screens in primary pro-T cells ex vivo to study the transcriptional impact of loss-of-function alterations in T-ALL and correlate this with effects on cell fitness. The various perturbations were clustered based on their effects on E2F/MYC or STAT/NOTCH signatures, which play a defining role in driving T-cell proliferation. Many of the perturbations resulted in positive effects on the STAT and NOTCH signatures and were predicted to behave as haploinsufficient tumor suppressors in T-ALL. Additionally, Spi1 was identified as an essential gene for pro-T-cell survival, associated with deregulation of the MYC signature and epigenetic consequences. In contrast, Bcl11b was identified as a strong tumor suppressor gene in immature T lymphocytes, associated with deregulation of NF-kB and JAK/STAT signaling. We found a correlation between BCL11B expression level and JAK/STAT pathway mutations in T-ALL patients and demonstrated oncogenic cooperation between Bcl11b inactivation and JAK3 hyperactivation in pro-T cells. Altogether, these single-cell CRISPR screens in pro-T cells provide fundamental insights into the mechanisms of transcriptional deregulation caused by genetic alterations in T-ALL.

Characterization and bioinformatic filtering of ambient gRNAs in single-cell CRISPR screens using CLEANSER.

Recent technological developments in single-cell RNA-seq CRISPR screens enable high-throughput investigation of the genome. Through transduction of a gRNA library to a cell population followed by transcriptomic profiling by scRNA-seq, it is possible to characterize the effects of thousands of genomic perturbations on global gene expression. A major source of noise in scRNA-seq CRISPR screens are ambient gRNAs, which are contaminating gRNAs that likely originate from other cells. If not properly filtered, ambient gRNAs can result in an excess of false positive gRNA assignments. Here, we utilize CRISPR barnyard assays to characterize ambient gRNA noise in single-cell CRISPR screens. We use these datasets to develop and train CLEANSER, a mixture model that identifies and filters ambient gRNA noise. This model takes advantage of the bimodal distribution between native and ambient gRNAs and includes both gRNA and cell-specific normalization parameters, correcting for confounding technical factors that affect individual gRNAs and cells. The output of CLEANSER is the probability that a gRNA-cell assignment is in the native distribution over the ambient distribution. We find that ambient gRNA filtering methods impact differential gene expression analysis outcomes and that CLEANSER outperforms alternate approaches by increasing gRNA-cell assignment accuracy.

Multiome Perturb-seq unlocks scalable discovery of integrated perturbation effects on the transcriptome and epigenome.

Single-cell CRISPR screens link genetic perturbations to transcriptional states, but high-throughput methods connecting these induced changes to their regulatory foundations are limited. Here we introduce Multiome Perturb-seq, extending single-cell CRISPR screens to simultaneously measure perturbation-induced changes in gene expression and chromatin accessibility. We apply Multiome Perturb-seq in a CRISPRi screen of 13 chromatin remodelers in human RPE-1 cells, achieving efficient assignment of sgRNA identities to single nuclei via an improved method for capturing barcode transcripts from nuclear RNA. We organize expression and accessibility measurements into coherent programs describing the integrated effects of perturbations on cell state, finding that ARID1A and SUZ12 knockdowns induce programs enriched for developmental features. Pseudotime analysis of perturbations connects accessibility changes to changes in gene expression, highlighting the value of multimodal profiling. Overall, our method provides a scalable and simply implemented system to dissect the regulatory logic underpinning cell state.

Robust differential expression testing for single-cell CRISPR screens at low multiplicity of infection.

Single-cell CRISPR screens (perturb-seq) link genetic perturbations to phenotypic changes in individual cells. The most fundamental task in perturb-seq analysis is to test for association between a perturbation and a count outcome, such as gene expression. We conduct the first-ever comprehensive benchmarking study of association testing methods for low multiplicity-of-infection (MOI) perturb-seq data, finding that existing methods produce excess false positives. We conduct an extensive empirical investigation of the data, identifying three core analysis challenges: sparsity, confounding, and model misspecification. Finally, we develop an association testing method - SCEPTRE low-MOI - that resolves these analysis challenges and demonstrates improved calibration and power.

Exponential family measurement error models for single-cell CRISPR screens.

CRISPR genome engineering and single-cell RNA sequencing have accelerated biological discovery. Single-cell CRISPR screens unite these two technologies, linking genetic perturbations in individual cells to changes in gene expression and illuminating regulatory networks underlying diseases. Despite their promise, single-cell CRISPR screens present considerable statistical challenges. We demonstrate through theoretical and real data analyses that a standard method for estimation and inference in single-cell CRISPR screens-"thresholded regression"-exhibits attenuation bias and a bias-variance tradeoff as a function of an intrinsic, challenging-to-select tuning parameter. To overcome these difficulties, we introduce GLM-EIV ("GLM-based errors-in-variables"), a new method for single-cell CRISPR screen analysis. GLM-EIV extends the classical errors-in-variables model to responses and noisy predictors that are exponential family-distributed and potentially impacted by the same set of confounding variables. We develop a computational infrastructure to deploy GLM-EIV across hundreds of processors on clouds (e.g. Microsoft Azure) and high-performance clusters. Leveraging this infrastructure, we apply GLM-EIV to analyze two recent, large-scale, single-cell CRISPR screen datasets, yielding several new insights.

Abstract LB289: Single-cell CRISPR screens at scale to understand T cell biology

Abstract CRISPR screens have become the primary discovery engine in modern biology and are widely used to uncover novel targets in immuno-oncology. However, these genetic screens are usually coupled to rather simplistic read-outs such as cell fitness. In contrast, CROP-Seq (or “CRISPR Droplet” Sequencing) screens combine CRISPR perturbation with single-cell transcriptomics, enabling high-content phenotyping at single-cell resolution. Briefly, cells are perturbed with a pooled sgRNA library and transcriptomic profiles of each cell are recorded using conventional single-cell RNA sequencing platforms. Currently, the scale of these screens is limited to the perturbation of a couple of hundred genes, possibly up to 1.000 genes, because of increased costs for single-cell library preparation and next generation sequencing (NGS). At Myllia, we have built a platform allowing high-content CROP-Seq screens in both CRISPR-ready cancer cell lines as well as primary immune cells, e.g., human T cells. Using CRISPR KO, CRISPR interference or CRISPR activation workflows, we can help accelerate the identification of target genes and regulatory networks involved in immuno-oncology. Primary T cells are of great interest in the immunotherapy community as they are key players in autoimmune and inflammatory disease. Engineered T-lymphocytes such as CAR-T cells are currently developed as novel cellular medicines, yet many T cell-intrinsic features involved in CAR-T potency remain elusive. To enable the discovery of novel targets, we have performed multiple customized CROP-Seq CRISPR KO screens in primary human T cells investigating T cell stemness and effector phenotypes as well as CD4+ T helper cell differentiation towards Th1, Th2, or Th17 subsets. Here, we present screens for regulators of functional T cell plasticity and Th2 commitment in which we aimed to identify genes determining critical T cell fate decisions, potentially linking gene (dys)function to either autoimmune/inflammatory disease or functional persistence of cytotoxic T cells for cancer immunotherapy. Overall, the advanced CROP-Seq platform combining large-scale perturbations and targeted sequencing (TA) read-outs will catalyse a paradigm shift for CROP-Seq enabling high-throughput functional genomic screens that support the validation of drug targets in autoimmunity, inflammation and immuno-oncology. Citation Format: Nicole Untermoser, Johanna Irnstorfer, Anatoly Vasilyev, Nikola Vinko, Sumit Pawar, Anke Loregger, Adam Krejci, Henrik Schmidt, Tilmann Bürckstümmer. Single-cell CRISPR screens at scale to understand T cell biology [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB289.

Abstract 2949: A flexible and efficient approach for single-cell CRISPR perturbation screens combined with targeted RNA-seq expression analysis

Abstract This study presents a novel approach for performing 10X platform-based targeted single-cell RNA-seq analysis in combination with CRISPR perturbation screens. For the analysis, we constructed a custom sgRNA library focused on a small subset of genes associated with the TNFα response (i.e., NFκB pathway). We compared analysis of two targeted gene expression panels—the first, targeting all protein-coding genes (genome-wide) and the other, targeting a selected set of genes representing key hubs in signaling pathway modules. Narrowing down the analyzed gene set enhanced the efficiency of single-cell RNA-seq by reducing the associated next-generation sequencing (NGS) depth required for readout, and significantly streamlining data analysis. Comparing the analysis of the expression panels targeting all protein-coding genes with the smaller pathway-targeted set, we were able to assess the general flexibility of the novel approach for single-cell CRISPR perturbation screens. We evaluated the specific tradeoffs with regard to the size of the CRISPR library, the size of the panel of genes targeted for expression analysis, and NGS sequencing depth. This flexible, targeted approach not only refines the precision of RNA-seq but also provides a more cost-effective solution for comprehensive genomic analyses. Citation Format: Donato Tedesco, Tianbing Liu, Mikhail Makhanov, Dongfang Hu, Nadya Isachenko, Paul Diehl, Alex Chenchik. A flexible and efficient approach for single-cell CRISPR perturbation screens combined with targeted RNA-seq expression analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2949.

Mapping the functional impact of non-coding regulatory elements in primary T cells through single-cell CRISPR screens

BackgroundDrug targets with genetic evidence are expected to increase clinical success by at least twofold. Yet, translating disease-associated genetic variants into functional knowledge remains a fundamental challenge of drug discovery. A key issue is that the vast majority of complex disease associations cannot be cleanly mapped to a gene. Immune disease-associated variants are enriched within regulatory elements found in T-cell-specific open chromatin regions.ResultsTo identify genes and molecular programs modulated by these regulatory elements, we develop a CRISPRi-based single-cell functional screening approach in primary human T cells. Our pipeline enables the interrogation of transcriptomic changes induced by the perturbation of regulatory elements at scale. We first optimize an efficient CRISPRi protocol in primary CD4+ T cells via CROPseq vectors. Subsequently, we perform a screen targeting 45 non-coding regulatory elements and 35 transcription start sites and profile approximately 250,000 T -cell single-cell transcriptomes. We develop a bespoke analytical pipeline for element-to-gene (E2G) mapping and demonstrate that our method can identify both previously annotated and novel E2G links. Lastly, we integrate genetic association data for immune-related traits and demonstrate how our platform can aid in the identification of effector genes for GWAS loci.ConclusionsWe describe “primary T cell crisprQTL” — a scalable, single-cell functional genomics approach for mapping regulatory elements to genes in primary human T cells. We show how this framework can facilitate the interrogation of immune disease GWAS hits and propose that the combination of experimental and QTL-based techniques is likely to address the variant-to-function problem.

Detecting subtle transcriptomic perturbations induced by lncRNAs knock-down in single-cell CRISPRi screening using a new sparse supervised autoencoder neural network.

Single-cell CRISPR-based transcriptome screens are potent genetic tools for concomitantly assessing the expression profiles of cells targeted by a set of guides RNA (gRNA), and inferring target gene functions from the observed perturbations. However, due to various limitations, this approach lacks sensitivity in detecting weak perturbations and is essentially reliable when studying master regulators such as transcription factors. To overcome the challenge of detecting subtle gRNA induced transcriptomic perturbations and classifying the most responsive cells, we developed a new supervised autoencoder neural network method. Our Sparse supervised autoencoder (SSAE) neural network provides selection of both relevant features (genes) and actual perturbed cells. We applied this method on an in-house single-cell CRISPR-interference-based (CRISPRi) transcriptome screening (CROP-Seq) focusing on a subset of long non-coding RNAs (lncRNAs) regulated by hypoxia, a condition that promote tumor aggressiveness and drug resistance, in the context of lung adenocarcinoma (LUAD). The CROP-seq library of validated gRNA against a subset of lncRNAs and, as positive controls, HIF1A and HIF2A, the 2 main transcription factors of the hypoxic response, was transduced in A549 LUAD cells cultured in normoxia or exposed to hypoxic conditions during 3, 6 or 24h. We first validated the SSAE approach on HIF1A and HIF2 by confirming the specific effect of their knock-down during the temporal switch of the hypoxic response. Next, the SSAE method was able to detect stable short hypoxia-dependent transcriptomic signatures induced by the knock-down of some lncRNAs candidates, outperforming previously published machine learning approaches. This proof of concept demonstrates the relevance of the SSAE approach for deciphering weak perturbations in single-cell transcriptomic data readout as part of CRISPR-based screening.

Single-cell CRISPR screens in vivo map T cell fate regulomes in cancer

CD8+ cytotoxic T cells (CTLs) orchestrate antitumour immunity and exhibit inherent heterogeneity1,2, with precursor exhausted T (Tpex) cells but not terminally exhausted T (Tex) cells capable of responding to existing immunotherapies3–7. The gene regulatory network that underlies CTL differentiation and whether Tex cell responses can be functionally reinvigorated are incompletely understood. Here we systematically mapped causal gene regulatory networks using single-cell CRISPR screens in vivo and discovered checkpoints for CTL differentiation. First, the exit from quiescence of Tpex cells initiated successive differentiation into intermediate Tex cells. This process is differentially regulated by IKAROS and ETS1, the deficiencies of which dampened and increased mTORC1-associated metabolic activities, respectively. IKAROS-deficient cells accumulated as a metabolically quiescent Tpex cell population with limited differentiation potential following immune checkpoint blockade (ICB). Conversely, targeting ETS1 improved antitumour immunity and ICB efficacy by boosting differentiation of Tpex to intermediate Tex cells and metabolic rewiring. Mechanistically, TCF-1 and BATF are the targets for IKAROS and ETS1, respectively. Second, the RBPJ–IRF1 axis promoted differentiation of intermediate Tex to terminal Tex cells. Accordingly, targeting RBPJ enhanced functional and epigenetic reprogramming of Tex cells towards the proliferative state and improved therapeutic effects and ICB efficacy. Collectively, our study reveals that promoting the exit from quiescence of Tpex cells and enriching the proliferative Tex cell state act as key modalities for antitumour effects and provides a systemic framework to integrate cell fate regulomes and reprogrammable functional determinants for cancer immunity.

In-organoid single-cell CRISPR screening reveals determinants of hepatocyte differentiation and maturation

BackgroundHarnessing hepatocytes for basic research and regenerative medicine demands a complete understanding of the genetic determinants underlying hepatocyte differentiation and maturation. Single-cell CRISPR screens in organoids could link genetic perturbations with parallel transcriptomic readout in single cells, providing a powerful method to delineate roles of cell fate regulators. However, a big challenge for identifying key regulators during data analysis is the low expression levels of transcription factors (TFs), which are difficult to accurately estimate due to noise and dropouts in single-cell sequencing. Also, it is often the changes in TF activities in the transcriptional cascade rather than the expression levels of TFs that are relevant to the cell fate transition.ResultsHere, we develop Organoid-based Single-cell CRISPR screening Analyzed with Regulons (OSCAR), a framework using regulon activities as readouts to dissect gene knockout effects in organoids. In adult-stem-cell-derived liver organoids, we map transcriptomes in 80,576 cells upon 246 perturbations associated with transcriptional regulation of hepatocyte formation. Using OSCAR, we identify known and novel positive and negative regulators, among which Fos and Ubr5 are the top-ranked ones. Further single-gene loss-of-function assays demonstrate that Fos depletion in mouse and human liver organoids promote hepatocyte differentiation by specific upregulation of liver metabolic genes and pathways, and conditional knockout of Ubr5 in mouse liver delays hepatocyte maturation.ConclusionsAltogether, we provide a framework to explore lineage specifiers in a rapid and systematic manner, and identify hepatocyte determinators with potential clinical applications.

Antibody dependent cell-mediated cytotoxicity selection pressure induces diverse mechanisms of resistance

ABSTRACT Targeted monoclonal antibody therapy has emerged as a powerful therapeutic strategy for cancer. However, only a minority of patients have durable responses and the development of resistance remains a major clinical obstacle. Antibody-dependent cell-mediated cytotoxicity (ADCC) represents a crucial therapeutic mechanism of action; however, few studies have explored ADCC resistance. Using multiple in vitro models of ADCC selection pressure, we have uncovered both shared and distinct resistance mechanisms. Persistent ADCC selection pressure yielded ADCC-resistant cells that are characterized by a loss of NK cell conjugation and this shared resistance phenotype is associated with cell-line dependent modulation of cell surface proteins that contribute to immune synapse formation and NK cell function. We employed single-cell RNA sequencing and proteomic screens to interrogate molecular mechanisms of resistance. We demonstrate that ADCC resistance involves upregulation of interferon/STAT1 and DNA damage response signaling as well as activation of the immunoproteasome. Here, we identify pathways that modulate ADCC sensitivity and report strategies to enhance ADCC-mediated elimination of cancer cells. ADCC resistance could not be reversed with combinatorial treatment approaches. Hence, our findings indicate that tumor cells utilize multiple strategies to inhibit NK cell mediated-ADCC. Future research and development of NK cell-based immunotherapies must incorporate plans to address or potentially prevent the induction of resistance.

GiRAFR improves gRNA detection and annotation in single-cell CRISPR screens

Novel methods that combine single cell RNA-seq with CRISPR screens enable high-throughput characterization of transcriptional changes caused by genetic perturbations. Dedicated software is however lacking to annotate CRISPR guide RNA (gRNA) libraries and associate them with single cell transcriptomes. Here, we describe a CRISPR droplet sequencing (CROP-seq) dataset. During analysis, we observed that the most commonly used method fails to detect mutant gRNAs. We therefore developed a python tool to identify and characterize intact and mutant gRNAs, called GiRAFR. We show that mutant gRNAs are dysfunctional, and failure to detect and annotate them leads to an inflated estimate of the number of untransformed cells, attenuated downregulation of target genes, as well as an underestimated multiplet frequency. These findings are mirrored in publicly available datasets, where we find that up to 35% of cells are transduced with a mutant gRNA. Applying GiRAFR hence stands to improve the annotation and quality of single cell CRISPR screens.

Discovery of target genes and pathways at GWAS loci by pooled single-cell CRISPR screens.

Most variants associated with complex traits and diseases identified by genome-wide association studies (GWAS) map to noncoding regions of the genome with unknown effects. Using ancestrally diverse, biobank-scale GWAS data, massively parallel CRISPR screens, and single-cell transcriptomic and proteomic sequencing, we discovered 124 cis-target genes of 91 noncoding blood trait GWAS loci. Using precise variant insertion through base editing, we connected specific variants with gene expression changes. We also identified trans-effect networks of noncoding loci when cis target genes encoded transcription factors or microRNAs. Networks were themselves enriched for GWAS variants and demonstrated polygenic contributions to complex traits. This platform enables massively parallel characterization of the target genes and mechanisms of human noncoding variants in both cis and trans.

Abstract LB341: Single-cell CRISPR screens in primary human T cells identify regulators of Th2 cell skewing

Abstract CRISPR screens have become the primary discovery engine in modern biology. However, many screening workflows are still performed in cancer cell lines and coupled to simplistic read-outs such as cellular fitness. At Myllia Biotechnology, we combine CRISPR screening with single-cell RNA sequencing, leveraging two transformative technologies to enable genetic screening for complex phenotypes. We utilize the CRISPR screening workflow to map the impact of thousands of genetic perturbations on the global transcriptome at single-cell resolution. Our powerful approach has broad applications in identifying novel drug targets or elucidating unknown mechanisms of actions of drugs. Primary human T cells are currently of great interest in the scientific community. They are not only key players in autoimmunity and other inflammatory diseases, but also represent attractive targets for immunotherapy of cancer. To enable the discovery of novel targets, we built a workflow that utilizes CD4+ T cells from peripheral blood and allows functional genomic screens in these cells. Upon activation, naïve CD4+ T cells proliferate and differentiate into specific T helper cell subsets, such as Th1, Th2, or Th17 cells. Here, we present data of an experiment in which we screened for regulators of T helper cell differentiation and skewed cells towards the Th2 subset. We aimed to identify genes whose knockout boosts or attenuates the ability of primary naïve CD4+ T cells to become Th2 cells. Th2 cells support the humoral immune response, and their dysfunction has been linked to inflammatory diseases, including asthma. In our screen, the different T cell subsets could be captured using curated transcriptomic signatures. Importantly, several gene KOs introduced in a pooled fashion using CRISPR/Cas9 accumulated in distinct subpopulations, suggesting that these genes regulate the differentiation of naïve T cells into the various T helper cell subsets. Overall, our pooled screening approach in primary human T cells allows for novel insights in the plasticity of T cells and identifies genes that could serve as drug targets in autoimmunity, inflammation and immuno-oncology. Citation Format: Anke Loregger, Johanna Irnstorfer, Nicole Untermoser, Nikola Vinko, Adam Krejci, Henrik Schmidt, Tilmann Bürckstümmer. Single-cell CRISPR screens in primary human T cells identify regulators of Th2 cell skewing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 2 (Clinical Trials and Late-Breaking Research); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(8_Suppl):Abstract nr LB341.

Abstract 667: Single-cell functional genomics of natural killer cell evasion by tumor cells

Abstract Background: Natural killer (NK) cells are emerging as a promising therapeutic option in cancer. To better understand how cancer cells evade NK cells, we studied interacting NK and blood cancer cells using single-cell and genome-scale functional genomics screens. Methods: We performed multiplexed single-cell RNA-seq (scRNA-seq) on co-cultures of NK cells and 26 cell lines representing diverse blood cancers. Using screens of pooled DNA-barcoded cell lines (PRISM), we quantified the sensitivity of over 60 blood cancer cell lines and integrated the results with CCLE multi-omics to uncover molecular correlates of tumor cell susceptibility to NK cells. We performed 12 genome-scale CRISPR loss-of-function and gain-of-function screens of cancer-cell intrinsic NK cell resistance mechanisms across 7 blood cancer cell lines. Finally, we investigated the mechanisms-of-action of 65 genome-scale screen hits using CRISPR screens with scRNA-seq readout in both tumor and NK cells. Results: At single-cell resolution, interaction of NK and cancer cells induced distinct activation states in both cell types depending on the cancer cell lineage and molecular phenotype. NK cells transitioned either into an activated state characterized by 4-1BB, GITR, TIM-3, and TIGIT or a state marked by type I interferon signature. Tumor cells responded to NK cell attack by activating interferon gamma (IFNy) signaling, inducing MHC class I. The activation states correlated with sensitivity to NK cells, ranging from more sensitive myeloid to more resistant B-lymphoid cancers. Molecular correlates of increased sensitivity included expression of activating receptor ligands NCR3LG1, PVR, and ULBP1, whereas TRAF3 mutations correlated with resistance. CRISPR screens uncovered cancer cell-intrinsic genes driving sensitivity and resistance, including antigen presentation and death receptor signaling mediators and adhesion molecules. The screens identified new ​​blood cancer-specific NK cell inhibitory regulators (SELPLG, SPN, and MYB ) and genes previously underappreciated in NK cell evasion, including protein fucosylation and transcriptional regulators (e.g. GFI1B). CRISPR screens with scRNA-seq readout identified MHC-I, IFNy, and NF-κB regulation as underlying mechanisms. Cancer cell knockout of positive regulators of NK cell response (CD58, NCR3LG1) induced an inactive NK cell state, providing experimental evidence how cancer cell-intrinsic genetic alterations can shape the molecular profile of attacking immune cells to promote immune evasion. Conclusions: By integrating diverse functional genomics screens and patient genomic profiles, we provide a comprehensive landscape of potential biomarkers and functionally validated genetic mechanisms which influence how NK cells recognize and kill malignant cells. The results offer a roadmap to facilitate development of NK-cell based immunotherapy for blood cancers and beyond. Citation Format: Olli Dufva, Sara Gandolfi, Jani Huuhtanen, Olga Dashevsky, Khalid Saeed, Jay Klievink, Petra Nygren, Jonas Bouhlal, Jenni Lahtela, Anna Näätänen, Bishwa Ghimire, Tiina Hannunen, Pekka Ellonen, Hanna Duàn, Jason Theodoropoulos, Essi Laajala, Jouni Härkönen, Petri Pölönen, Merja Heinäniemi, Shizuka Yamano, Ryosuke Shirasaki, David Barbie, Jennifer Roth, Rizwan Romee, Michal Sheffer, Harri Lähdesmäki, Dean A. Lee, Ricardo De Matos Simoes, Matti Kankainen, Constantine S. Mitsiades, Satu Mustjoki. Single-cell functional genomics of natural killer cell evasion by tumor cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 667.

Structural and functional properties of mSWI/SNF chromatin remodeling complexes revealed through single-cell perturbation screens

The mammalian SWI/SNF (mSWI/SNF or BAF) family of chromatin remodeling complexes play critical roles in regulating DNA accessibility and gene expression. The three final-form subcomplexes-cBAF, PBAF, and ncBAF-are distinct in biochemical componentry, chromatin targeting, and roles in disease; however, the contributions of their constituent subunits to gene expression remain incompletely defined. Here, we performed Perturb-seq-based CRISPR-Cas9 knockout screens targeting mSWI/SNF subunits individually and in select combinations, followed by single-cell RNA-seq and SHARE-seq. We uncovered complex-, module-, and subunit-specific contributions to distinct regulatory networks and defined paralog subunit relationships and shifted subcomplex functions upon perturbations. Synergistic, intra-complex genetic interactions between subunits reveal functional redundancy and modularity. Importantly, single-cell subunit perturbation signatures mapped across bulk primary human tumor expression profiles both mirror and predict cBAF loss-of-function status in cancer. Our findings highlight the utility of Perturb-seq to dissect disease-relevant gene regulatory impacts of heterogeneous, multi-component master regulatory complexes.