FACS-based genome-wide CRISPR screens define key regulators of DNA damage signaling pathways.

DNA damage-activated signaling pathways are critical for coordinating multiple cellular processes, which must be tightly regulated to maintain genome stability. To provide a comprehensive and unbiased perspective of DNA damage response (DDR) signaling pathways, we performed 30 fluorescence-activated cell sorting (FACS)-based genome-wide CRISPR screens in human cell lines with antibodies recognizing distinct endogenous DNA damage signaling proteins to identify critical regulators involved in DDR. We discovered that proteasome-mediated processing is an early and prerequisite event for cells to trigger camptothecin- and etoposide-induced DDR signaling. Furthermore, we identified PRMT1 and PRMT5 as modulators that regulate ATM protein level. Moreover, we discovered that GNB1L is a key regulator of DDR signaling via its role as a co-chaperone specifically regulating PIKK proteins. Collectively, these screens offer a rich resource for further investigation of DDR, which may provide insight into strategies of targeting these DDR pathways to improve therapeutic outcomes.

High-Resolution CRISPR Screens Reveal Fitness Genes and Genotype-Specific Cancer Liabilities.

The ability to perturb genes in human cells is crucial for elucidating gene function and holds great potential for finding therapeutic targets for diseases such as cancer. To extend the catalog of human core and context-dependent fitness genes, we have developed a high-complexity second-generation genome-scale CRISPR-Cas9 gRNA library and applied it to fitness screens in five human cell lines. Using an improved Bayesian analytical approach, we consistently discover 5-fold more fitness genes than were previously observed. We present a list of 1,580 human core fitness genes and describe their general properties. Moreover, we demonstrate that context-dependent fitness genes accurately recapitulate pathway-specific genetic vulnerabilities induced by known oncogenes and reveal cell-type-specific dependencies for specific receptor tyrosine kinases, even in oncogenic KRAS backgrounds. Thus, rigorous identification of human cell line fitness genes using a high-complexity CRISPR-Cas9 library affords a high-resolution view of the genetic vulnerabilities of a cell.

Functional genomic landscape of cancer-intrinsic evasion of killing by T cells.

The genetic circuits that allow cancer cells to evade destruction by the host immune system remain poorly understood1-3. Here, to identify a phenotypically robust core set of genes and pathways that enable cancer cells to evade killing mediated by cytotoxic T lymphocytes (CTLs), we performed genome-wide CRISPR screens across a panel of genetically diverse mouse cancer cell lines that were cultured in the presence of CTLs. We identify a core set of 182 genes across these mouse cancer models, the individual perturbation of which increases either the sensitivity or the resistance of cancer cells to CTL-mediated toxicity. Systematic exploration of our dataset using genetic co-similarity reveals the hierarchical and coordinated manner in which genes and pathways act in cancer cells to orchestrate their evasion of CTLs, and shows that discrete functional modules that control the interferon response and tumour necrosis factor (TNF)-induced cytotoxicity are dominant sub-phenotypes. Our data establish a central role for genes that were previously identified as negative regulators of the type-II interferon response (for example, Ptpn2, Socs1 and Adar1) in mediating CTL evasion, and show that the lipid-droplet-related gene Fitm2 is required for maintaining cell fitness after exposure to interferon-γ (IFNγ). In addition, we identify the autophagy pathway as a conserved mediator of the evasion of CTLs by cancer cells, and show that this pathway is required to resist cytotoxicity induced by the cytokines IFNγ and TNF. Through the mapping of cytokine- and CTL-based genetic interactions, together with in vivo CRISPR screens, we show how the pleiotropic effects of autophagy control cancer-cell-intrinsic evasion of killing by CTLs and we highlight the importance of these effects within the tumour microenvironment. Collectively, these data expand our knowledge of the genetic circuits that are involved in the evasion of the immune system by cancer cells, and highlight genetic interactions that contribute to phenotypes associated with escape from killing by CTLs.

Recovering false negatives in CRISPR fitness screens with JLOE.

It is widely accepted that pooled library CRISPR knockout screens offer greater sensitivity and specificity than prior technologies in detecting genes whose disruption leads to fitness defects, a critical step in identifying candidate cancer targets. However, the assumption that CRISPR screens are saturating has been largely untested. Through integrated analysis of screen data in cancer cell lines generated by the Cancer Dependency Map, we show that a typical CRISPR screen has a ∼20% false negative rate, in addition to library-specific false negatives. Replicability falls sharply as gene expression decreases, while cancer subtype-specific genes within a tissue show distinct profiles compared to false negatives. Cumulative analyses across tissues improves our understanding of core essential genes and suggest only a small number of lineage-specific essential genes, enriched for transcription factors that define pathways of tissue differentiation. To recover false negatives, we introduce a method, Joint Log Odds of Essentiality (JLOE), which builds on our prior work with BAGEL to selectively rescue the false negatives without an increased false discovery rate.

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.

Integrated screens uncover a cell surface tumor suppressor gene KIRREL involved in Hippo pathway.

Cell surface proteins play essential roles in various biological processes and are highly related to cancer development. They also serve as important markers for cell identity and targets for pharmacological intervention. Despite their great potentials in biomedical research, comprehensive functional analysis of cell surface proteins remains scarce. Here, with a de novo designed library targeting cell surface proteins, we performed in vivo CRISPR screens to evaluate the effects of cell surface proteins on tumor survival and proliferation. We found that Kirrel1 loss markedly promoted tumor growth in vivo. Moreover, KIRREL was significantly enriched in a separate CRISPR screen based on a specific Hippo pathway reporter. Further studies revealed that KIRREL binds directly to SAV1 to activate the Hippo tumor suppressor pathway. Together, our integrated screens reveal a cell surface tumor suppressor involved in the Hippo pathway and highlight the potential of these approaches in biomedical research.

CRISPR screens identify genomic ribonucleotides as a source of PARP-trapping lesions.

The observation that BRCA1- and BRCA2-deficient cells are sensitive to inhibitors of poly(ADP-ribose) polymerase (PARP) has spurred the development of cancer therapies that use these inhibitors to target deficiencies in homologous recombination1. The cytotoxicity of PARP inhibitors depends on PARP trapping, the formation of non-covalent protein-DNA adducts composed of inhibited PARP1 bound to DNA lesions of unclear origins1-4. To address the nature of such lesions and the cellular consequences of PARP trapping, we undertook three CRISPR (clustered regularly interspersed palindromic repeats) screens to identify genes and pathways that mediate cellular resistance to olaparib, a clinically approved PARP inhibitor1. Here we present a high-confidence set of 73 genes, which when mutated cause increased sensitivity to PARP inhibitors. In addition to an expected enrichment for genes related to homologous recombination, we discovered that mutations in all three genes encoding ribonuclease H2 sensitized cells to PARP inhibition. We establish that the underlying cause of the PARP-inhibitor hypersensitivity of cells deficient in ribonuclease H2 is impaired ribonucleotide excision repair5. Embedded ribonucleotides, which are abundant in the genome of cells deficient in ribonucleotide excision repair, are substrates for cleavage by topoisomerase 1, resulting in PARP-trapping lesions that impede DNA replication and endanger genome integrity. We conclude that genomic ribonucleotides are a hitherto unappreciated source of PARP-trapping DNA lesions, and that the frequent deletion of RNASEH2B in metastatic prostate cancer and chronic lymphocytic leukaemia could provide an opportunity to exploit these findings therapeutically.

The shieldin complex mediates 53BP1-dependent DNA repair.

53BP1 is a chromatin-binding protein that regulates the repair of DNA double-strand breaks by suppressing the nucleolytic resection of DNA termini1,2. This function of 53BP1 requires interactions with PTIP3 and RIF14-9, the latter of which recruits REV7 (also known as MAD2L2) to break sites10,11. How 53BP1-pathway proteins shield DNA ends is currently unknown, but there are two models that provide the best potential explanation of their action. In one model the 53BP1 complex strengthens the nucleosomal barrier to end-resection nucleases12,13, and in the other 53BP1 recruits effector proteins with end-protection activity. Here we identify a 53BP1 effector complex, shieldin, that includes C20orf196 (also known as SHLD1), FAM35A (SHLD2), CTC-534A2.2 (SHLD3) and REV7. Shieldin localizes to double-strand-break sites in a 53BP1- and RIF1-dependent manner, and its SHLD2 subunit binds to single-stranded DNA via OB-fold domains that are analogous to those of RPA1 and POT1. Loss of shieldin impairs non-homologous end-joining, leads to defective immunoglobulin class switching and causes hyper-resection. Mutations in genes that encode shieldin subunits also cause resistance to poly(ADP-ribose) polymerase inhibition in BRCA1-deficient cells and tumours, owing to restoration of homologous recombination. Finally, we show that binding of single-stranded DNA by SHLD2 is critical for shieldin function, consistent with a model in which shieldin protects DNA ends to mediate 53BP1-dependent DNA repair.

HumanNet v3: an improved database of human gene networks for disease research.

Network medicine has proven useful for dissecting genetic organization of complex human diseases. We have previously published HumanNet, an integrated network of human genes for disease studies. Since the release of the last version of HumanNet, many large-scale protein-protein interaction datasets have accumulated in public depositories. Additionally, the numbers of research papers and functional annotations for gene-phenotype associations have increased significantly. Therefore, updating HumanNet is a timely task for further improvement of network-based research into diseases. Here, we present HumanNet v3 (https://www.inetbio.org/humannet/, covering 99.8% of human protein coding genes) constructed by means of the expanded data with improved network inference algorithms. HumanNet v3 supports a three-tier model: HumanNet-PI (a protein-protein physical interaction network), HumanNet-FN (a functional gene network), and HumanNet-XC (a functional network extended by co-citation). Users can select a suitable tier of HumanNet for their study purpose. We showed that on disease gene predictions, HumanNet v3 outperforms both the previous HumanNet version and other integrated human gene networks. Furthermore, we demonstrated that HumanNet provides a feasible approach for selecting host genes likely to be associated with COVID-19.

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.

Genetic vulnerabilities upon inhibition of DNA damage response.

Because of essential roles of DNA damage response (DDR) in the maintenance of genomic integrity, cellular homeostasis, and tumor suppression, targeting DDR has become a promising therapeutic strategy for cancer treatment. However, the benefits of cancer therapy targeting DDR are limited mainly due to the lack of predictive biomarkers. To address this challenge, we performed CRISPR screens to search for genetic vulnerabilities that affect cells' response to DDR inhibition. By undertaking CRISPR screens with inhibitors targeting key DDR mediators, i.e. ATR, ATM, DNAPK and CHK1, we obtained a global and unbiased view of genetic interactions with DDR inhibition. Specifically, we identified YWHAE loss as a key determinant of sensitivity to CHK1 inhibition. We showed that KLHL15 loss protects cells from DNA damage induced by ATM inhibition. Moreover, we validated that APEX1 loss sensitizes cells to DNAPK inhibition. Additionally, we compared the synergistic effects of combining different DDR inhibitors and found that an ATM inhibitor plus a PARP inhibitor induced dramatic levels of cell death, probably through promoting apoptosis. Our results enhance the understanding of DDR pathways and will facilitate the use of DDR-targeting agents in cancer therapy.

DNA polymerase ι compensates for Fanconi anemia pathway deficiency by countering DNA replication stress.

Fanconi anemia (FA) is caused by defects in cellular responses to DNA crosslinking damage and replication stress. Given the constant occurrence of endogenous DNA damage and replication fork stress, it is unclear why complete deletion of FA genes does not have a major impact on cell proliferation and germ-line FA patients are able to progress through development well into their adulthood. To identify potential cellular mechanisms that compensate for the FA deficiency, we performed dropout screens in FA mutant cells with a whole genome guide RNA library. This uncovered a comprehensive genome-wide profile of FA pathway synthetic lethality, including POLI and CDK4 As little is known of the cellular function of DNA polymerase iota (Pol ι), we focused on its role in the loss-of-function FA knockout mutants. Loss of both FA pathway function and Pol ι leads to synthetic defects in cell proliferation and cell survival, and an increase in DNA damage accumulation. Furthermore, FA-deficient cells depend on the function of Pol ι to resume replication upon replication fork stalling. Our results reveal a critical role for Pol ι in DNA repair and replication fork restart and suggest Pol ι as a target for therapeutic intervention in malignancies carrying an FA gene mutation.

Genome-Wide CRISPR Screens Reveal ZATT as a Synthetic Lethal Target of TOP2-Poison Etoposide That Can Act in a TDP2-Independent Pathway.

Etoposide (ETO) is an anticancer drug that targets topoisomerase II (TOP2). It stabilizes a normally transient TOP2-DNA covalent complex (TOP2cc), thus leading to DNA double-strand breaks (DSBs). Tyrosyl-DNA phosphodiesterases two (TDP2) is directly involved in the repair of TOP2cc by removing phosphotyrosyl peptides from 5'-termini of DSBs. Recent studies suggest that additional factors are required for TOP2cc repair, which include the proteasome and the zinc finger protein associated with TDP2 and TOP2, named ZATT. ZATT may alter the conformation of TOP2cc in a way that renders the accessibility of TDP2 for TOP2cc removal. In this study, our genome-wide clustered regularly interspaced short palindromic repeats (CRISPR) screens revealed that ZATT also has a TDP2-independent role in promoting cell survival following ETO treatment. ZATT KO cells showed relatively higher ETO sensitivity than TDP2-KO cells, and ZATT/TDP2 DKO cells displayed additive hypersensitivity to ETO treatment. The study using a series of deletion mutants of ZATT determined that the N-terminal 1-168 residues of ZATT are required for interaction with TOP2 and this interaction is critical to ETO sensitivity. Moreover, depletion of ZATT resulted in accelerated TOP2 degradation after ETO or cycloheximide (CHX) treatment, suggesting that ZATT may increase TOP2 stability and likely participate in TOP2 turnover. Taken together, this study suggests that ZATT is a critical determinant that dictates responses to ETO treatment and targeting. ZATT is a promising strategy to increase ETO efficacy for cancer therapy.

Optimal construction of a functional interaction network from pooled library CRISPR fitness screens.

BACKGROUND: Functional interaction networks, where edges connect genes likely to operate in the same biological process or pathway, can be inferred from CRISPR knockout screens in cancer cell lines. Genes with similar knockout fitness profiles across a sufficiently diverse set of cell line screens are likely to be co-functional, and these "coessentiality" networks are increasingly powerful predictors of gene function and biological modularity. While several such networks have been published, most use different algorithms for each step of the network construction process. RESULTS: In this study, we identify an optimal measure of functional interaction and test all combinations of options at each step-essentiality scoring, sample variance and covariance normalization, and similarity measurement-to identify best practices for generating a functional interaction network from CRISPR knockout data. We show that Bayes Factor and Ceres scores give the best results, that Ceres outperforms the newer Chronos scoring scheme, and that covariance normalization is a critical step in network construction. We further show that Pearson correlation, mathematically identical to ordinary least squares after covariance normalization, can be extended by using partial correlation to detect and amplify signals from "moonlighting" proteins which show context-dependent interaction with different partners. CONCLUSIONS: We describe a systematic survey of methods for generating coessentiality networks from the Cancer Dependency Map data and provide a partial correlation-based approach for exploring context-dependent interactions.

HumanNet v2: human gene networks for disease research.

Human gene networks have proven useful in many aspects of disease research, with numerous network-based strategies developed for generating hypotheses about gene-disease-drug associations. The ability to predict and organize genes most relevant to a specific disease has proven especially important. We previously developed a human functional gene network, HumanNet, by integrating diverse types of omics data using Bayesian statistics framework and demonstrated its ability to retrieve disease genes. Here, we present HumanNet v2 (http://www.inetbio.org/humannet), a database of human gene networks, which was updated by incorporating new data types, extending data sources and improving network inference algorithms. HumanNet now comprises a hierarchy of human gene networks, allowing for more flexible incorporation of network information into studies. HumanNet performs well in ranking disease-linked gene sets with minimal literature-dependent biases. We observe that incorporating model organisms' protein-protein interactions does not markedly improve disease gene predictions, suggesting that many of the disease gene associations are now captured directly in human-derived datasets. With an improved interactive user interface for disease network analysis, we expect HumanNet will be a useful resource for network medicine.

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

The adaptation of CRISPR/Cas9 systems for pooled library genetic knockout screens in mammalian cells has substantially advanced the state of the art in human functional genomics. Screening panels of cell lines for genes whose knockout imposes a significant fitness defect has dramatically expanded our catalog of high-confidence essential genes, and has already proven useful in identifying tumor-specific essential genes for the development of targeted therapies. However, nonexperts currently lack an easy to use way to access this data and to identify whether their genes of interest are essential across different genetic backgrounds. The volume of screening data is expected to grow massively, making the problem more intractable. Here we describe PICKLES, the database of Pooled In vitro CRISPR Knockout Library Essentiality Screens, where end users can display and download raw or normalized essentiality profiles for more that 18 000 protein-coding genes across more than 50 cell lines. An additional data set with 15,000 genes targeted by pooled library shRNA in over 100 cell lines is also included. Researchers can see at a glance the relative fitness defect and tissue specificity of their genes of interest, generate and save figures locally, and download all raw data. The database is available at http://pickles.hart-lab.org.

Defining CD4 T cell memory by the epigenetic landscape of CpG DNA methylation.

Memory T cells are primed for rapid responses to Ag; however, the molecular mechanisms responsible for priming remain incompletely defined. CpG methylation in promoters is an epigenetic modification, which regulates gene transcription. Using targeted bisulfite sequencing, we examined methylation of 2100 genes (56,000 CpGs) mapped by deep sequencing of T cell activation in human naive and memory CD4 T cells. Four hundred sixty-six CpGs (132 genes) displayed differential methylation between naive and memory cells. Twenty-one genes exhibited both differential methylation and gene expression before activation, linking promoter DNA methylation states to gene regulation; 6 of 21 genes encode proteins closely studied in T cells, whereas 15 genes represent novel targets for further study. Eighty-four genes demonstrated differential methylation between memory and naive cells that correlated to differential gene expression following activation, of which 39 exhibited reduced methylation in memory cells coupled with increased gene expression upon activation compared with naive cells. These reveal a class of primed genes more rapidly expressed in memory compared with naive cells and putatively regulated by DNA methylation. These findings define a DNA methylation signature unique to memory CD4 T cells that correlates with activation-induced gene expression.

BAGEL: a computational framework for identifying essential genes from pooled library screens.

BACKGROUND: The adaptation of the CRISPR-Cas9 system to pooled library gene knockout screens in mammalian cells represents a major technological leap over RNA interference, the prior state of the art. New methods for analyzing the data and evaluating results are needed. RESULTS: We offer BAGEL (Bayesian Analysis of Gene EssentiaLity), a supervised learning method for analyzing gene knockout screens. Coupled with gold-standard reference sets of essential and nonessential genes, BAGEL offers significantly greater sensitivity than current methods, while computational optimizations reduce runtime by an order of magnitude. CONCLUSIONS: Using BAGEL, we identify ~2000 fitness genes in pooled library knockout screens in human cell lines at 5 % FDR, a major advance over competing platforms. BAGEL shows high sensitivity and specificity even across screens performed by different labs using different libraries and reagents.

Extensive mapping of an innate immune network with CRISPR.

The application of the CRISPR­Cas9 system marks a major breakthrough for genetic screens, particularly in mammalian cells where high­throughput targeted gene editing has been lacking. Parnas et al (2015) apply this screening technology to mouse bone marrow­derived dendritic cells in order to study the regulation of the immune response triggered by PAMPs. Through integrated analysis of gene knockouts in conjunction with changes in protein and mRNA expression, CRISPR screens are facilitating dissection of immune regulatory networks at unprecedented resolution.

Measuring error rates in genomic perturbation screens: gold standards for human functional genomics.

Technological advancement has opened the door to systematic genetics in mammalian cells. Genome-scale loss-of-function screens can assay fitness defects induced by partial gene knockdown, using RNA interference, or complete gene knockout, using new CRISPR techniques. These screens can reveal the basic blueprint required for cellular proliferation. Moreover, comparing healthy to cancerous tissue can uncover genes that are essential only in the tumor; these genes are targets for the development of specific anticancer therapies. Unfortunately, progress in this field has been hampered by off-target effects of perturbation reagents and poorly quantified error rates in large-scale screens. To improve the quality of information derived from these screens, and to provide a framework for understanding the capabilities and limitations of CRISPR technology, we derive gold-standard reference sets of essential and nonessential genes, and provide a Bayesian classifier of gene essentiality that outperforms current methods on both RNAi and CRISPR screens. Our results indicate that CRISPR technology is more sensitive than RNAi and that both techniques have nontrivial false discovery rates that can be mitigated by rigorous analytical methods.