Improving prime editing with an endogenous small RNA-binding protein.

Prime editing enables the precise modification of genomes through reverse transcription of template sequences appended to the 3' ends of CRISPR-Cas guide RNAs1. To identify cellular determinants of prime editing, we developed scalable prime editing reporters and performed genome-scale CRISPR-interference screens. From these screens, a single factor emerged as the strongest mediator of prime editing: the small RNA-binding exonuclease protection factor La. Further investigation revealed that La promotes prime editing across approaches (PE2, PE3, PE4 and PE5), edit types (substitutions, insertions and deletions), endogenous loci and cell types but has no consistent effect on genome-editing approaches that rely on standard, unextended guide RNAs. Previous work has shown that La binds polyuridine tracts at the 3' ends of RNA polymerase III transcripts2. We found that La functionally interacts with the 3' ends of polyuridylated prime editing guide RNAs (pegRNAs). Guided by these results, we developed a prime editor protein (PE7) fused to the RNA-binding, N-terminal domain of La. This editor improved prime editing with expressed pegRNAs and engineered pegRNAs (epegRNAs), as well as with synthetic pegRNAs optimized for La binding. Together, our results provide key insights into how prime editing components interact with the cellular environment and suggest general strategies for stabilizing exogenous small RNAs therein.

Base-editing mutagenesis maps alleles to tune human T cell functions.

CRISPR-enabled screening is a powerful tool for the discovery of genes that control T cell function and has nominated candidate targets for immunotherapies1-6. However, new approaches are required to probe specific nucleotide sequences within key genes. Systematic mutagenesis in primary human T cells could reveal alleles that tune specific phenotypes. DNA base editors are powerful tools for introducing targeted mutations with high efficiency7,8. Here we develop a large-scale base-editing mutagenesis platform with the goal of pinpointing nucleotides that encode amino acid residues that tune primary human T cell activation responses. We generated a library of around 117,000 single guide RNA molecules targeting base editors to protein-coding sites across 385 genes implicated in T cell function and systematically identified protein domains and specific amino acid residues that regulate T cell activation and cytokine production. We found a broad spectrum of alleles with variants encoding critical residues in proteins including PIK3CD, VAV1, LCP2, PLCG1 and DGKZ, including both gain-of-function and loss-of-function mutations. We validated the functional effects of many alleles and further demonstrated that base-editing hits could positively and negatively tune T cell cytotoxic function. Finally, higher-resolution screening using a base editor with relaxed protospacer-adjacent motif requirements9 (NG versus NGG) revealed specific structural domains and protein-protein interaction sites that can be targeted to tune T cell functions. Base-editing screens in primary immune cells thus provide biochemical insights with the potential to accelerate immunotherapy design.

ENPP1 is an innate immune checkpoint of the anticancer cGAMP-STING pathway in breast cancer.

Ectonucleotide pyrophosphatase/phosphodiesterase 1 (ENPP1) expression correlates with poor prognosis in many cancers, and we previously discovered that ENPP1 is the dominant hydrolase of extracellular cGAMP: a cancer-cell-produced immunotransmitter that activates the anticancer stimulator of interferon genes (STING) pathway. However, ENPP1 has other catalytic activities and the molecular and cellular mechanisms contributing to its tumorigenic effects remain unclear. Here, using single-cell RNA-seq, we show that ENPP1 in both cancer and normal tissues drives primary breast tumor growth and metastasis by dampening extracellular 2'3'-cyclic-GMP-AMP (cGAMP)-STING-mediated antitumoral immunity. ENPP1 loss-of-function in both cancer cells and normal tissues slowed primary tumor growth and abolished metastasis. Selectively abolishing the cGAMP hydrolysis activity of ENPP1 phenocopied ENPP1 knockout in a STING-dependent manner, demonstrating that restoration of paracrine cGAMP-STING signaling is the dominant anti-cancer mechanism of ENPP1 inhibition. Finally, ENPP1 expression in breast tumors deterministically predicated whether patients would remain free of distant metastasis after pembrolizumab (anti-PD-1) treatment followed by surgery. Altogether, ENPP1 blockade represents a strategy to exploit cancer-produced extracellular cGAMP for controlled local activation of STING and is therefore a promising therapeutic approach against breast cancer.

Environmental challenge rewires functional connections among human genes.

A fundamental question in biology is how a limited number of genes combinatorially govern cellular responses to environmental changes. While the prevailing hypothesis is that relationships between genes, processes, and ontologies could be plastic to achieve this adaptability, quantitatively comparing human gene functional connections between specific environmental conditions at scale is very challenging. Therefore, it remains unclear whether and how human genetic interaction networks are rewired in response to changing environmental conditions. Here, we developed a framework for mapping context-specific genetic interactions, enabling us to measure the plasticity of human genetic architecture upon environmental challenge for ~250,000 interactions, using cell cycle interruption, genotoxic perturbation, and nutrient deprivation as archetypes. We discover large-scale rewiring of human gene relationships across conditions, highlighted by dramatic shifts in the functional connections of epigenetic regulators (TIP60), cell cycle regulators (PP2A), and glycolysis metabolism. Our study demonstrates that upon environmental perturbation, intra-complex genetic rewiring is rare while inter-complex rewiring is common, suggesting a modular and flexible evolutionary genetic strategy that allows a limited number of human genes to enable adaptation to a large number of environmental conditions.

Integrative identification of non-coding regulatory regions driving metastatic prostate cancer.

Large-scale sequencing efforts of thousands of tumor samples have been undertaken to understand the mutational landscape of the coding genome. However, the vast majority of germline and somatic variants occur within non-coding portions of the genome. These genomic regions do not directly encode for specific proteins, but can play key roles in cancer progression, for example by driving aberrant gene expression control. Here, we designed an integrative computational and experimental framework to identify recurrently mutated non-coding regulatory regions that drive tumor progression. Application of this approach to whole-genome sequencing (WGS) data from a large cohort of metastatic castration-resistant prostate cancer (mCRPC) revealed a large set of recurrently mutated regions. We used (i) in silico prioritization of functional non-coding mutations, (ii) massively parallel reporter assays, and (iii) in vivo CRISPR-interference (CRISPRi) screens in xenografted mice to systematically identify and validate driver regulatory regions that drive mCRPC. We discovered that one of these enhancer regions, GH22I030351, acts on a bidirectional promoter to simultaneously modulate expression of U2-associated splicing factor SF3A1 and chromosomal protein CCDC157. We found that both SF3A1 and CCDC157 are promoters of tumor growth in xenograft models of prostate cancer. We nominated a number of transcription factors, including SOX6, to be responsible for higher expression of SF3A1 and CCDC157. Collectively, we have established and confirmed an integrative computational and experimental approach that enables the systematic detection of non-coding regulatory regions that drive the progression of human cancers.

ENPP1 is an innate immune checkpoint of the anticancer cGAMP-STING pathway.

ENPP1 expression correlates with poor prognosis in many cancers, and we previously discovered that ENPP1 is the dominant hydrolase of extracellular cGAMP: a cancer-cell-produced immunotransmitter that activates the anticancer STING pathway. However, ENPP1 has other catalytic activities and the molecular and cellular mechanisms contributing to its tumorigenic effects remain unclear. Here, using single cell RNA-seq (scRNA-seq), we show that ENPP1 overexpression drives primary breast tumor growth and metastasis by synergistically dampening extracellular cGAMP-STING mediated antitumoral immunity and activating immunosuppressive extracellular adenosine (eADO) signaling. In addition to cancer cells, stromal and immune cells in the tumor microenvironment (TME) also express ENPP1 that restrains their response to tumor-derived cGAMP. Enpp1 loss-of-function in both cancer cells and normal tissues slowed primary tumor initiation and growth and prevented metastasis in an extracellular cGAMP- and STING-dependent manner. Selectively abolishing the cGAMP hydrolysis activity of ENPP1 phenocopied total ENPP1 knockout, demonstrating that restoration of paracrine cGAMP-STING signaling is the dominant anti-cancer mechanism of ENPP1 inhibition. Strikingly, we find that breast cancer patients with low ENPP1 expression have significantly higher immune infiltration and improved response to therapeutics impacting cancer immunity upstream or downstream of the cGAMP-STING pathway, like PARP inhibitors and anti-PD1. Altogether, selective inhibition of ENPP1's cGAMP hydrolase activity alleviates an innate immune checkpoint to boost cancer immunity and is therefore a promising therapeutic approach against breast cancer that may synergize with other cancer immunotherapies.

IFITM proteins assist cellular uptake of diverse linked chemotypes.

The search for cell-permeable drugs has conventionally focused on low-molecular weight (MW), nonpolar, rigid chemical structures. However, emerging therapeutic strategies break traditional drug design rules by employing flexibly linked chemical entities composed of more than one ligand. Using complementary genome-scale chemical-genetic approaches we identified an endogenous chemical uptake pathway involving interferon-induced transmembrane proteins (IFITMs) that modulates the cell permeability of a prototypical biopic inhibitor of MTOR (RapaLink-1, MW: 1784 g/mol). We devised additional linked inhibitors targeting BCR-ABL1 (DasatiLink-1, MW: 1518 g/mol) and EIF4A1 (BisRoc-1, MW: 1466 g/mol), uptake of which was facilitated by IFITMs. We also found that IFITMs moderately assisted some proteolysis-targeting chimeras and examined the physicochemical requirements for involvement of this uptake pathway.

Maximizing CRISPRi efficacy and accessibility with dual-sgRNA libraries and optimal effectors.

CRISPR interference (CRISPRi) enables programmable, reversible, and titratable repression of gene expression (knockdown) in mammalian cells. Initial CRISPRi-mediated genetic screens have showcased the potential to address basic questions in cell biology, genetics, and biotechnology, but wider deployment of CRISPRi screening has been constrained by the large size of single guide RNA (sgRNA) libraries and challenges in generating cell models with consistent CRISPRi-mediated knockdown. Here, we present next-generation CRISPRi sgRNA libraries and effector expression constructs that enable strong and consistent knockdown across mammalian cell models. First, we combine empirical sgRNA selection with a dual-sgRNA library design to generate an ultra-compact (1-3 elements per gene), highly active CRISPRi sgRNA library. Next, we compare CRISPRi effectors to show that the recently published Zim3-dCas9 provides an excellent balance between strong on-target knockdown and minimal non-specific effects on cell growth or the transcriptome. Finally, we engineer a suite of cell lines with stable expression of Zim3-dCas9 and robust on-target knockdown. Our results and publicly available reagents establish best practices for CRISPRi genetic screening.

Highly efficient generation of isogenic pluripotent stem cell models using prime editing.

The recent development of prime editing (PE) genome engineering technologies has the potential to significantly simplify the generation of human pluripotent stem cell (hPSC)-based disease models. PE is a multicomponent editing system that uses a Cas9-nickase fused to a reverse transcriptase (nCas9-RT) and an extended PE guide RNA (pegRNA). Once reverse transcribed, the pegRNA extension functions as a repair template to introduce precise designer mutations at the target site. Here, we systematically compared the editing efficiencies of PE to conventional gene editing methods in hPSCs. This analysis revealed that PE is overall more efficient and precise than homology-directed repair of site-specific nuclease-induced double-strand breaks. Specifically, PE is more effective in generating heterozygous editing events to create autosomal dominant disease-associated mutations. By stably integrating the nCas9-RT into hPSCs we achieved editing efficiencies equal to those reported for cancer cells, suggesting that the expression of the PE components, rather than cell-intrinsic features, limit PE in hPSCs. To improve the efficiency of PE in hPSCs, we optimized the delivery modalities for the PE components. Delivery of the nCas9-RT as mRNA combined with synthetically generated, chemically-modified pegRNAs and nicking guide RNAs improved editing efficiencies up to 13-fold compared with transfecting the PE components as plasmids or ribonucleoprotein particles. Finally, we demonstrated that this mRNA-based delivery approach can be used repeatedly to yield editing efficiencies exceeding 60% and to correct or introduce familial mutations causing Parkinson's disease in hPSCs.

From muscles to nerves, our body is formed of many kinds of cells which can each respond slightly differently to the same harmful genetic changes. Understanding the exact relationship between mutations and cell-type specific function is essential to better grasp how conditions such as Parkinson's disease or amyotrophic lateral sclerosis progress and can be treated. Stem cells could be an important tool in that effort, as they can be directed to mature into many cell types in the laboratory. Yet it remains difficult to precisely introduce disease-relevant mutations in these cells. To remove this obstacle, Li et al. focused on prime editing, a cutting-edge 'search and replace' approach which can introduce new genetic information into a specific DNA sequence. However, it was unclear whether this technique could be used to efficiently create stem cell models of human diseases. A first set of experiments showed that prime editing is superior to conventional approaches when generating mutated genes in stem cells. Li et al. then further improved the efficiency and precision of the method by tweaking how prime editing components are delivered into the cells. The refined approach could be harnessed to quickly generate large numbers of stem cells carrying mutations associated with Parkinson's disease; crucially, prime editing could then also be used to revert a mutated gene back to its healthy form. The improved prime editing approach developed by Li et al. removes a major hurdle for scientists hoping to use stem cells to study genetic diseases. This could potentially help to unlock progress in how we understand and ultimately treat these conditions.

A new era in functional genomics screens.

The past 25 years of genomics research first revealed which genes are encoded by the human genome and then a detailed catalogue of human genome variation associated with many diseases. Despite this, the function of many genes and gene regulatory elements remains poorly characterized, which limits our ability to apply these insights to human disease. The advent of new CRISPR functional genomics tools allows for scalable and multiplexable characterization of genes and gene regulatory elements encoded by the human genome. These approaches promise to reveal mechanisms of gene function and regulation, and to enable exploration of how genes work together to modulate complex phenotypes.

A global cancer data integrator reveals principles of synthetic lethality, sex disparity and immunotherapy.

BACKGROUND: Advances in cancer biology are increasingly dependent on integration of heterogeneous datasets. Large-scale efforts have systematically mapped many aspects of cancer cell biology; however, it remains challenging for individual scientists to effectively integrate and understand this data. RESULTS: We have developed a new data retrieval and indexing framework that allows us to integrate publicly available data from different sources and to combine publicly available data with new or bespoke datasets. Our approach, which we have named the cancer data integrator (CanDI), is straightforward to implement, is well documented, and is continuously updated which should enable individual users to take full advantage of efforts to map cancer cell biology. We show that CanDI empowered testable hypotheses of new synthetic lethal gene pairs, genes associated with sex disparity, and immunotherapy targets in cancer. CONCLUSIONS: CanDI provides a flexible approach for large-scale data integration in cancer research enabling rapid generation of hypotheses. The CanDI data integrator is available at https://github.com/GilbertLabUCSF/CanDI .

An integrated functional and clinical genomics approach reveals genes driving aggressive metastatic prostate cancer.

Genomic sequencing of thousands of tumors has revealed many genes associated with specific types of cancer. Similarly, large scale CRISPR functional genomics efforts have mapped genes required for cancer cell proliferation or survival in hundreds of cell lines. Despite this, for specific disease subtypes, such as metastatic prostate cancer, there are likely a number of undiscovered tumor specific driver genes that may represent potential drug targets. To identify such genetic dependencies, we performed genome-scale CRISPRi screens in metastatic prostate cancer models. We then created a pipeline in which we integrated pan-cancer functional genomics data with our metastatic prostate cancer functional and clinical genomics data to identify genes that can drive aggressive prostate cancer phenotypes. Our integrative analysis of these data reveals known prostate cancer specific driver genes, such as AR and HOXB13, as well as a number of top hits that are poorly characterized. In this study we highlight the strength of an integrated clinical and functional genomics pipeline and focus on two top hit genes, KIF4A and WDR62. We demonstrate that both KIF4A and WDR62 drive aggressive prostate cancer phenotypes in vitro and in vivo in multiple models, irrespective of AR-status, and are also associated with poor patient outcome.

Revealing molecular pathways for cancer cell fitness through a genetic screen of the cancer translatome.

The major cap-binding protein eukaryotic translation initiation factor 4E (eIF4E), an ancient protein required for translation of all eukaryotic genomes, is a surprising yet potent oncogenic driver. The genetic interactions that maintain the oncogenic activity of this key translation factor remain unknown. In this study, we carry out a genome-wide CRISPRi screen wherein we identify more than 600 genetic interactions that sustain eIF4E oncogenic activity. Our data show that eIF4E controls the translation of Tfeb, a key executer of the autophagy response. This autophagy survival response is triggered by mitochondrial proteotoxic stress, which allows cancer cell survival. Our screen also reveals a functional interaction between eIF4E and a single anti-apoptotic factor, Bcl-xL, in tumor growth. Furthermore, we show that eIF4E and the exon-junction complex (EJC), which is involved in many steps of RNA metabolism, interact to control the migratory properties of cancer cells. Overall, we uncover several cancer-specific vulnerabilities that provide further resolution of the cancer translatome.

Genome-wide programmable transcriptional memory by CRISPR-based epigenome editing.

A general approach for heritably altering gene expression has the potential to enable many discovery and therapeutic efforts. Here, we present CRISPRoff-a programmable epigenetic memory writer consisting of a single dead Cas9 fusion protein that establishes DNA methylation and repressive histone modifications. Transient CRISPRoff expression initiates highly specific DNA methylation and gene repression that is maintained through cell division and differentiation of stem cells to neurons. Pairing CRISPRoff with genome-wide screens and analysis of chromatin marks establishes rules for heritable gene silencing. We identify single guide RNAs (sgRNAs) capable of silencing the large majority of genes including those lacking canonical CpG islands (CGIs) and reveal a wide targeting window extending beyond annotated CGIs. The broad ability of CRISPRoff to initiate heritable gene silencing even outside of CGIs expands the canonical model of methylation-based silencing and enables diverse applications including genome-wide screens, multiplexed cell engineering, enhancer silencing, and mechanistic exploration of epigenetic inheritance.

Mapping cancer genetics at single-cell resolution.

CRISPR genetic interaction mapping reveals networks of genes that drive cancer phenotypes.

Pharmaceutical-Grade Rigosertib Is a Microtubule-Destabilizing Agent.

We recently used CRISPRi/a-based chemical-genetic screens and cell biological, biochemical, and structural assays to determine that rigosertib, an anti-cancer agent in phase III clinical trials, kills cancer cells by destabilizing microtubules. Reddy and co-workers (Baker et al., 2020, this issue of Molecular Cell) suggest that a contaminating degradation product in commercial formulations of rigosertib is responsible for the microtubule-destabilizing activity. Here, we demonstrate that cells treated with pharmaceutical-grade rigosertib (>99.9% purity) or commercially obtained rigosertib have qualitatively indistinguishable phenotypes across multiple assays. The two formulations have indistinguishable chemical-genetic interactions with genes that modulate microtubule stability, both destabilize microtubules in cells and in vitro, and expression of a rationally designed tubulin mutant with a mutation in the rigosertib binding site (L240F TUBB) allows cells to proliferate in the presence of either formulation. Importantly, the specificity of the L240F TUBB mutant for microtubule-destabilizing agents has been confirmed independently. Thus, rigosertib kills cancer cells by destabilizing microtubules, in agreement with our original findings.

Clonal ZEB1-Driven Mesenchymal Transition Promotes Targetable Oncologic Antiangiogenic Therapy Resistance.

Glioblastoma (GBM) responses to bevacizumab are invariably transient with acquired resistance. We profiled paired patient specimens and bevacizumab-resistant xenograft models pre- and post-resistance toward the primary goal of identifying regulators whose targeting could prolong the therapeutic window, and the secondary goal of identifying biomarkers of therapeutic window closure. Bevacizumab-resistant patient specimens and xenografts exhibited decreased vessel density and increased hypoxia versus pre-resistance, suggesting that resistance occurs despite effective therapeutic devascularization. Microarray analysis revealed upregulated mesenchymal genes in resistant tumors correlating with bevacizumab treatment duration and causing three changes enabling resistant tumor growth in hypoxia. First, perivascular invasiveness along remaining blood vessels, which co-opts vessels in a VEGF-independent and neoangiogenesis-independent manner, was upregulated in novel biomimetic 3D bioengineered platforms modeling the bevacizumab-resistant microenvironment. Second, tumor-initiating stem cells housed in the perivascular niche close to remaining blood vessels were enriched. Third, metabolic reprogramming assessed through real-time bioenergetic measurement and metabolomics upregulated glycolysis and suppressed oxidative phosphorylation. Single-cell sequencing of bevacizumab-resistant patient GBMs confirmed upregulated mesenchymal genes, particularly glycoprotein YKL-40 and transcription factor ZEB1, in later clones, implicating these changes as treatment-induced. Serum YKL-40 was elevated in bevacizumab-resistant versus bevacizumab-naïve patients. CRISPR and pharmacologic targeting of ZEB1 with honokiol reversed the mesenchymal gene expression and associated stem cell, invasion, and metabolic changes defining resistance. Honokiol caused greater cell death in bevacizumab-resistant than bevacizumab-responsive tumor cells, with surviving cells losing mesenchymal morphology. Employing YKL-40 as a resistance biomarker and ZEB1 as a target to prevent resistance could fulfill the promise of antiangiogenic therapy. SIGNIFICANCE: Bevacizumab resistance in GBM is associated with mesenchymal/glycolytic shifts involving YKL-40 and ZEB1. Targeting ZEB1 reduces bevacizumab-resistant GBM phenotypes. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/80/7/1498/F1.large.jpg.

Exploring genetic interaction manifolds constructed from rich single-cell phenotypes.

How cellular and organismal complexity emerges from combinatorial expression of genes is a central question in biology. High-content phenotyping approaches such as Perturb-seq (single-cell RNA-sequencing pooled CRISPR screens) present an opportunity for exploring such genetic interactions (GIs) at scale. Here, we present an analytical framework for interpreting high-dimensional landscapes of cell states (manifolds) constructed from transcriptional phenotypes. We applied this approach to Perturb-seq profiling of strong GIs mined from a growth-based, gain-of-function GI map. Exploration of this manifold enabled ordering of regulatory pathways, principled classification of GIs (e.g., identifying suppressors), and mechanistic elucidation of synergistic interactions, including an unexpected synergy between CBL and CNN1 driving erythroid differentiation. Finally, we applied recommender system machine learning to predict interactions, facilitating exploration of vastly larger GI manifolds.