PICKLES v3: the updated database of pooled in vitro CRISPR knockout library essentiality screens.

PICKLES (https://pickles.hart-lab.org) is an updated web interface to a freely available database of genome-scale CRISPR knockout fitness screens in human cell lines. Using a completely rewritten interface, researchers can explore gene knockout fitness phenotypes across cell lines and tissue types and compare fitness profiles with fitness, expression, or mutation profiles of other genes. The database has been updated to include data from three CRISPR libraries (Avana, Score, and TKOv3), and includes information from 1162 whole-genome screens probing the knockout fitness phenotype of 18 959 genes. Source code for the interface and the integrated database are available for download.

AR-negative prostate cancer is vulnerable to loss of JMJD1C demethylase.

Prostate cancer is a leading cause of cancer-related mortality in men. The widespread use of androgen receptor (AR) inhibitors has generated an increased incidence of AR-negative prostate cancer, triggering the need for effective therapies for such patients. Here, analysis of public genome-wide CRISPR screens in human prostate cancer cell lines identified histone demethylase JMJD1C (KDM3C) as an AR-negative context-specific vulnerability. Secondary validation studies in multiple cell lines and organoids, including isogenic models, confirmed that small hairpin RNA (shRNA)-mediated depletion of JMJD1C potently inhibited growth specifically in AR-negative prostate cancer cells. To explore the cooperative interactions of AR and JMJD1C, we performed comparative transcriptomics of 1) isogenic AR-positive versus AR-negative prostate cancer cells, 2) AR-positive versus AR-negative prostate cancer tumors, and 3) isogenic JMJD1C-expressing versus JMJD1C-depleted AR-negative prostate cancer cells. Loss of AR or JMJD1C generates a modest tumor necrosis factor alpha (TNFα) signature, whereas combined loss of AR and JMJD1C strongly up-regulates the TNFα signature in human prostate cancer, suggesting TNFα signaling as a point of convergence for the combined actions of AR and JMJD1C. Correspondingly, AR-negative prostate cancer cells showed exquisite sensitivity to TNFα treatment and, conversely, TNFα pathway inhibition via inhibition of its downstream effector MAP4K4 partially reversed the growth defect of JMJD1C-depleted AR-negative prostate cancer cells. Given the deleterious systemic side effects of TNFα therapy in humans and the viability of JMJD1C-knockout mice, the identification of JMJD1C inhibition as a specific vulnerability in AR-negative prostate cancer may provide an alternative drug target for prostate cancer patients progressing on AR inhibitor therapy.

Efficient gene knockout and genetic interaction screening using the in4mer CRISPR/Cas12a multiplex knockout platform.

Genetic interactions mediate the emergence of phenotype from genotype, but technologies for combinatorial genetic perturbation in mammalian cells are challenging to scale. Here, we identify background-independent paralog synthetic lethals from previous CRISPR genetic interaction screens, and find that the Cas12a platform provides superior sensitivity and assay replicability. We develop the in4mer Cas12a platform that uses arrays of four independent guide RNAs targeting the same or different genes. We construct a genome-scale library, Inzolia, that is ~30% smaller than a typical CRISPR/Cas9 library while also targeting ~4000 paralog pairs. Screens in cancer cells demonstrate discrimination of core and context-dependent essential genes similar to that of CRISPR/Cas9 libraries, as well as detection of synthetic lethal and masking/buffering genetic interactions between paralogs of various family sizes. Importantly, the in4mer platform offers a fivefold reduction in library size compared to other genetic interaction methods, substantially reducing the cost and effort required for these assays.

CRISPR screening identifies BET and mTOR inhibitor synergy in cholangiocarcinoma through serine glycine one carbon.

Patients with cholangiocarcinoma have poor clinical outcomes due to late diagnoses, poor prognoses, and limited treatment strategies. To identify drug combinations for this disease, we have conducted a genome-wide CRISPR screen anchored on the bromodomain and extraterminal domain (BET) PROTAC degrader ARV825, from which we identified anticancer synergy when combined with genetic ablation of members of the mTOR pathway. This combination effect was validated using multiple pharmacological BET and mTOR inhibitors, accompanied by increased levels of apoptosis and cell cycle arrest. In a xenograft model, combined BET degradation and mTOR inhibition induced tumor regression. Mechanistically, the 2 inhibitor classes converged on H3K27ac-marked epigenetic suppression of the serine glycine one carbon (SGOC) metabolism pathway, including the key enzymes PHGDH and PSAT1. Knockdown of PSAT1 was sufficient to replicate synergy with single-agent inhibition of either BET or mTOR. Our results tie together epigenetic regulation, metabolism, and apoptosis induction as key therapeutic targets for further exploration in this underserved disease.

Efficient gene knockout and genetic interactions: the IN4MER CRISPR/Cas12a multiplex knockout platform.

Genetic interactions mediate the emergence of phenotype from genotype, but initial technologies for combinatorial genetic perturbation in mammalian cells suffer from inefficiency and are challenging to scale. Recent focus on paralog synthetic lethality in cancer cells offers an opportunity to evaluate different approaches and improve on the state of the art. Here we report a meta-analysis of CRISPR genetic interactions screens, identifying a candidate set of background-independent paralog synthetic lethals, and find that the Cas12a platform provides superior sensitivity and assay replicability. We demonstrate that Cas12a can independently target up to four genes from a single guide array, and we build on this knowledge by constructing a genome-scale library that expresses arrays of four guides per clone, a platform we call 'in4mer'. Our genome-scale human library, with only 49k clones, is substantially smaller than a typical CRISPR/Cas9 monogenic library while also targeting more than four thousand paralog pairs, triples, and quads. Proof of concept screens in four cell lines demonstrate discrimination of core and context-dependent essential genes similar to that of state-of-the-art CRISPR/Cas9 libraries, as well as detection of synthetic lethal and masking/buffering genetic interactions between paralogs of various family sizes, a capability not offered by any extant library. Importantly, the in4mer platform offers a fivefold reduction in the number of clones required to assay genetic interactions, dramatically improving the cost and effort required for these studies.

Actin cytoskeleton vulnerability to disulfide stress mediates disulfidptosis.

SLC7A11-mediated cystine uptake suppresses ferroptosis yet promotes cell death under glucose starvation; the nature of the latter cell death remains unknown. Here we show that aberrant accumulation of intracellular disulfides in SLC7A11high cells under glucose starvation induces a previously uncharacterized form of cell death distinct from apoptosis and ferroptosis. We term this cell death disulfidptosis. Chemical proteomics and cell biological analyses showed that glucose starvation in SLC7A11high cells induces aberrant disulfide bonds in actin cytoskeleton proteins and F-actin collapse in a SLC7A11-dependent manner. CRISPR screens and functional studies revealed that inactivation of the WAVE regulatory complex (which promotes actin polymerization and lamellipodia formation) suppresses disulfidptosis, whereas constitutive activation of Rac promotes disulfidptosis. We further show that glucose transporter inhibitors induce disulfidptosis in SLC7A11high cancer cells and suppress SLC7A11high tumour growth. Our results reveal that the susceptibility of the actin cytoskeleton to disulfide stress mediates disulfidptosis and suggest a therapeutic strategy to target disulfidptosis in cancer treatment.

Dynamic rewiring of biological activity across genotype and lineage revealed by context-dependent functional interactions.

BACKGROUND: Coessentiality networks derived from CRISPR screens in cell lines provide a powerful framework for identifying functional modules in the cell and for inferring the roles of uncharacterized genes. However, these networks integrate signal across all underlying data and can mask strong interactions that occur in only a subset of the cell lines analyzed. RESULTS: Here, we decipher dynamic functional interactions by identifying significant cellular contexts, primarily by oncogenic mutation, lineage, and tumor type, and discovering coessentiality relationships that depend on these contexts. We recapitulate well-known gene-context interactions such as oncogene-mutation, paralog buffering, and tissue-specific essential genes, show how mutation rewires known signal transduction pathways, including RAS/RAF and IGF1R-PIK3CA, and illustrate the implications for drug targeting. We further demonstrate how context-dependent functional interactions can elucidate lineage-specific gene function, as illustrated by the maturation of proreceptors IGF1R and MET by proteases FURIN and CPD. CONCLUSIONS: This approach advances our understanding of context-dependent interactions and how they can be gleaned from these data. We provide an online resource to explore these context-dependent interactions at diffnet.hart-lab.org.

Common computational tools for analyzing CRISPR screens.

CRISPR-Cas technology offers a versatile toolbox for genome editing, with applications in various cancer-related fields such as functional genomics, immunotherapy, synthetic lethality and drug resistance, metastasis, genome regulation, chromatic accessibility and RNA-targeting. The variety of screening platforms and questions in which they are used have caused the development of a wide array of analytical methods for CRISPR analysis. In this review, we focus on the algorithms and frameworks used in the computational analysis of pooled CRISPR knockout (KO) screens and highlight some of the most significant target discoveries made using these methods. Lastly, we offer perspectives on the design and analysis of state-of-art multiplex screening for genetic interactions.

Discovery of putative tumor suppressors from CRISPR screens reveals rewired lipid metabolism in acute myeloid leukemia cells.

CRISPR knockout fitness screens in cancer cell lines reveal many genes whose loss of function causes cell death or loss of fitness or, more rarely, the opposite phenotype of faster proliferation. Here we demonstrate a systematic approach to identify these proliferation suppressors, which are highly enriched for tumor suppressor genes, and define a network of 145 such genes in 22 modules. One module contains several elements of the glycerolipid biosynthesis pathway and operates exclusively in a subset of acute myeloid leukemia cell lines. The proliferation suppressor activity of genes involved in the synthesis of saturated fatty acids, coupled with a more severe loss of fitness phenotype for genes in the desaturation pathway, suggests that these cells operate at the limit of their carrying capacity for saturated fatty acids, which we confirm biochemically. Overexpression of this module is associated with a survival advantage in juvenile leukemias, suggesting a clinically relevant subtype.

CRISPR/CAS9-based DNA damage response screens reveal gene-drug interactions.

DNA damage response (DDR) is critically important for cell survival, genome maintenance, and its defect has been exploited therapeutically in cancer treatment. Many DDR-targeting agents have been generated and have entered the clinic and/or clinical trials. In order to provide a global and unbiased view of DDR network, we designed a focused CRISPR library targeting 365 DDR genes and performed CRISPR screens on the responses to several DDR inhibitors and DNA-damaging agents in 293A cells. With these screens, we determined responsive pathways enriched under treatment with different types of small-molecule agents. Additionally, we showed that POLE3/4-deficient cells displayed enhanced sensitivity to an ATR inhibitor, a PARP inhibitor, and camptothecin. Moreover, by performing DDR screens in isogenic TP53 wild-type and TP53 knock-out cell lines, our results suggest that the performance of our CRISPR DDR dropout screens is independent of TP53 status. Collectively, our findings indicate that CRISPR DDR screens can be used to identify potential targets of small-molecule drugs and reveal that TP53 status does not affect the outcome of these screens.

Genome-wide In Vivo CNS Screening Identifies Genes that Modify CNS Neuronal Survival and mHTT Toxicity.

Unbiased in vivo genome-wide genetic screening is a powerful approach to elucidate new molecular mechanisms, but such screening has not been possible to perform in the mammalian central nervous system (CNS). Here, we report the results of the first genome-wide genetic screens in the CNS using both short hairpin RNA (shRNA) and CRISPR libraries. Our screens identify many classes of CNS neuronal essential genes and demonstrate that CNS neurons are particularly sensitive not only to perturbations to synaptic processes but also autophagy, proteostasis, mRNA processing, and mitochondrial function. These results reveal a molecular logic for the common implication of these pathways across multiple neurodegenerative diseases. To further identify disease-relevant genetic modifiers, we applied our screening approach to two mouse models of Huntington's disease (HD). Top mutant huntingtin toxicity modifier genes included several Nme genes and several genes involved in methylation-dependent chromatin silencing and dopamine signaling, results that reveal new HD therapeutic target pathways.

Chemogenetic interactions in human cancer cells.

Chemogenetic profiling enables the identification of genes that enhance or suppress the phenotypic effect of chemical compounds. Using this approach in cancer therapies could improve our ability to predict the response of specific tumor genotypes to chemotherapeutic agents, thus accelerating the development of personalized drug therapy. In the not so distant past, this strategy was only applied in model organisms because there was no feasible technology to thoroughly exploit desired genetic mutations and their impact on drug efficacy in human cells. Today, with the advent of CRISPR gene-editing technology and its application to pooled library screens in mammalian cells, chemogenetic screens are performed directly in human cell lines with high sensitivity and specificity. Chemogenetic profiling provides insights into drug mechanism-of-action, genetic vulnerabilities, and resistance mechanisms, all of which will help to accurately deliver the right drug to the right target in the right patient while minimizing side effects.

A network of human functional gene interactions from knockout fitness screens in cancer cells.

Genetic interactions mediate the emergence of phenotype from genotype. The systematic survey of genetic interactions in yeast showed that genes operating in the same biological process have highly correlated genetic interaction profiles, and this observation has been exploited to infer gene function in model organisms. Such assays of digenic perturbations in human cells are also highly informative, but are not scalable, even with CRISPR-mediated methods. As an alternative, we developed an indirect method of deriving functional interactions. We show that genes having correlated knockout fitness profiles across diverse, non-isogenic cell lines are analogous to genes having correlated genetic interaction profiles across isogenic query strains and similarly imply shared biological function. We constructed a network of genes with correlated fitness profiles across 276 high-quality CRISPR knockout screens in cancer cell lines into a "coessentiality network," with up to 500-fold enrichment for co-functional gene pairs, enabling strong inference of gene function and highlighting the modular organization of the cell.

Identifying chemogenetic interactions from CRISPR screens with drugZ.

BACKGROUND: Chemogenetic profiling enables the identification of gene mutations that enhance or suppress the activity of chemical compounds. This knowledge provides insights into drug mechanism of action, genetic vulnerabilities, and resistance mechanisms, all of which may help stratify patient populations and improve drug efficacy. CRISPR-based screening enables sensitive detection of drug-gene interactions directly in human cells, but until recently has primarily been used to screen only for resistance mechanisms. RESULTS: We present drugZ, an algorithm for identifying both synergistic and suppressor chemogenetic interactions from CRISPR screens. DrugZ identifies synthetic lethal interactions between PARP inhibitors and both known and novel members of the DNA damage repair pathway, confirms KEAP1 loss as a resistance factor for ERK inhibitors in oncogenic KRAS backgrounds, and defines the genetic context for temozolomide activity. CONCLUSIONS: DrugZ is an open-source Python software for the analysis of genome-scale drug modifier screens. The software accurately identifies genetic perturbations that enhance or suppress drug activity. Interestingly, analysis of new and previously published data reveals tumor suppressor genes are drug-agnostic resistance genes in drug modifier screens. The software is available at github.com/hart-lab/drugz .