CRISPR Screens Provide a Comprehensive Assessment of Cancer Vulnerabilities but Generate False-Positive Hits for Highly Amplified Genomic Regions

Selective Degradation of MLK3 by a Novel CEP1347-VHL-02 PROTAC Compound Limits the Oncogenic Potential of TNBC

Triple-negative breast cancer (TNBC) is associated with poor prognosis because of the lack of effective therapies. Mixed-lineage protein kinase 3 (MLK3) is a protein that is often upregulated in TNBC and involved in driving the tumorigenic potential of cancer cells. Here, we present a selective MLK3 degrader, CEP1347-VHL-02, based on the pan-MLK inhibitor CEP1347 and a ligand for E3 ligase von Hippel-Lindau (VHL) by employing proteolysis-targeting chimera (PROTAC) technology. Our compound effectively targeted MLK3 for degradation via the ubiquitin-proteasome system in several cell line models but did not degrade other MLK family members. Furthermore, we showed that CEP1347-VHL-02 robustly degraded MLK3 and inhibited its oncogenic activity in TNBC, measured as a reduction of clonogenic and migratory potential, cell cycle arrest, and the induction of apoptosis in MDA-MB-468 cells. In conclusion, we present CEP1347-VHL-02 as a novel MLK3 degrader that may be a promising new strategy to target MLK3 in TNBC.

RUVBL1/2 Blockade Targets YTHDF1 Activity to Suppress m6A-Dependent Oncogenic Translation and Colorectal Tumorigenesis

The N6-methyladenosine (m6A) RNA-binding protein YTHDF1 is frequently overexpressed in colorectal cancer and drives chemotherapeutic resistance. To systematically identify druggable targets in colorectal cancer with high expression of YTHDF1, this study used a CRISPR/Cas9 screening strategy that revealed RUVBL1 and RUVBL2 as putative targets. RUVBL1/2 were overexpressed in primary colorectal cancer samples and represented independent predictors of poor patient prognosis. Functionally, loss of RUVBL1/2 preferentially impaired the growth of YTHDF1-high colorectal cancer cells, patient-derived primary colorectal cancer organoids, and subcutaneous xenografts. Mechanistically, YTHFD1 and RUVBL1/2 formed a positive feedforward circuit to accelerate oncogenic translation. YTHDF1 bound to m6A-modified RUVBL1/2 mRNA to promote translation initiation and protein expression. Coimmunoprecipitation and mass spectrometry identified that RUVBL1/2 reciprocally interacted with YTHDF1 at 40S translation initiation complexes. Consequently, RUVBL1/2 depletion stalled YTHDF1-driven oncogenic translation and nascent protein biosynthesis, leading to proliferative arrest and apoptosis. Ribosome sequencing revealed that RUVBL1/2 loss impaired the activation of MAPK, RAS, and PI3K-AKT signaling induced by YTHDF1. Finally, the blockade of RUVBL1/2 by the pharmacological inhibitor CB6644 or vesicle-like nanoparticle-encapsulated siRNAs preferentially arrested the growth of YTHDF1-expressing colorectal cancer in vitro and in vivo. Our findings show that RUVBL1/2 are potential prognostic markers and druggable targets that regulate protein translation in YTHDF1-high colorectal cancer. Significance: RUVBL1/2 inhibition is a therapeutic strategy to abrogate YTHDF1-driven oncogenic translation and overcome m6A dysregulation in colorectal cancer.

Genome-Wide Screening Approaches for Biochemical Reactions Independent of Cell Growth

Genome-wide screening is a potent approach for comprehensively understanding the molecular mechanisms of biological phenomena. However, despite its widespread use in the past decades across various biological targets, its application to biochemical reactions with temporal and reversible biological outputs remains a formidable challenge. To uncover the molecular machinery underlying various biochemical reactions, we have recently developed the revival screening method, which combines flow cytometry-based cell sorting with library reconstruction from collected cells. Our refinements to the traditional genome-wide screening technique have proven successful in revealing the molecular machinery of biochemical reactions of interest. In this article, we elucidate the technical basis of revival screening, focusing on its application to CRISPR-Cas9 single guide RNA (sgRNA) library screening. Finally, we also discuss the future of genome-wide screening while describing recent achievements from in vitro and in vivo screening.

Recent advances in CRISPR-Cas systems for colorectal cancer research and therapeutics

INTRODUCTION

Colon cancer, ranked as the fourth leading global cause of cancer death, exhibits a complex progression marked by genetic variations. Over the past decade, the utilization of diverse CRISPR systems has propelled accelerated research into colorectal cancer (CRC) treatment.

AREAS COVERED

CRISPR/Cas9, a key player in this research, identifies new oncogenes, tumor suppressor genes (TSGs), and drug-resistance genes. Additionally, it facilitates the construction of experimental models, conducts genome-wide library screening, and develops new therapeutic targets, especially for targeted knockout in vivo or molecular targeted drug delivery, contributing to personalized treatments and significantly enhancing the care of colon cancer patients. In this review, we provide insights into the mechanism of the CRISPR/Cas9 system, offering a comprehensive exploration of its applications in CRC, spanning screening, modeling, gene functions, diagnosis, and gene therapy. While acknowledging its transformative potential, the article  highlights the challenges and limitations of CRISPR systems.

EXPERT OPINION

The application of CRISPR/Cas9 in CRC research provides a promising avenue for personalized treatments. Its potential for identifying key genes and enabling experimental models and genome-wide screening enhances patient care. This review underscores the significance of CRISPR-Cas9 gene editing technology across basic research, diagnosis, and the treatment landscape of colon cancer.

Exploring factors influencing choice of DNA double-strand break repair pathways

DNA double-strand breaks (DSBs) represent one of the most severe threats to genomic integrity, demanding intricate repair mechanisms within eukaryotic cells. A diverse array of factors orchestrates the complex choreography of DSB signaling and repair, encompassing repair pathways, such as non-homologous end-joining, homologous recombination, and polymerase-θ-mediated end-joining. This review looks into the intricate decision-making processes guiding eukaryotic cells towards a particular repair pathway, particularly emphasizing the processing of two-ended DSBs. Furthermore, we elucidate the transformative role of Cas9, a site-specific endonuclease, in revolutionizing our comprehension of DNA DSB repair dynamics. Additionally, we explore the burgeoning potential of Cas9's remarkable ability to induce sequence-specific DSBs, offering a promising avenue for precise targeting of tumor cells. Through this comprehensive exploration, we unravel the intricate molecular mechanisms of cellular responses to DSBs, shedding light on both fundamental repair processes and cutting-edge therapeutic strategies.

A benchmark of computational methods for correcting biases of established and unknown origin in CRISPR-Cas9 screening data

BACKGROUND

CRISPR-Cas9 dropout screens are formidable tools for investigating biology with unprecedented precision and scale. However, biases in data lead to potential confounding effects on interpretation and compromise overall quality. The activity of Cas9 is influenced by structural features of the target site, including copy number amplifications (CN bias). More worryingly, proximal targeted loci tend to generate similar gene-independent responses to CRISPR-Cas9 targeting (proximity bias), possibly due to Cas9-induced whole chromosome-arm truncations or other genomic structural features and different chromatin accessibility levels.

RESULTS

We benchmarked eight computational methods, rigorously evaluating their ability to reduce both CN and proximity bias in the two largest publicly available cell-line-based CRISPR-Cas9 screens to date. We also evaluated the capability of each method to preserve data quality and heterogeneity by assessing the extent to which the processed data allows accurate detection of true positive essential genes, established oncogenetic addictions, and known/novel biomarkers of cancer dependency. Our analysis sheds light on the ability of each method to correct biases under different scenarios. AC-Chronos outperforms other methods in correcting both CN and proximity biases when jointly processing multiple screens of models with available CN information, whereas CRISPRcleanR is the top performing method for individual screens or when CN information is not available. In addition, Chronos and AC-Chronos yield a final dataset better able to recapitulate known sets of essential and non-essential genes.

CONCLUSIONS

Overall, our investigation provides guidance for the selection of the most appropriate bias-correction method, based on its strengths, weaknesses and experimental settings.

High-resolution genome-wide mapping of chromosome-arm-scale truncations induced by CRISPR-Cas9 editing

Clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR-associated protein 9 (Cas9) is a powerful tool for introducing targeted mutations in DNA, but recent studies have shown that it can have unintended effects such as structural changes. However, these studies have not yet looked genome wide or across data types. Here we performed a phenotypic CRISPR-Cas9 scan targeting 17,065 genes in primary human cells, revealing a 'proximity bias' in which CRISPR knockouts show unexpected similarities to unrelated genes on the same chromosome arm. This bias was found to be consistent across cell types, laboratories, Cas9 delivery methods and assay modalities, and the data suggest that it is caused by telomeric truncations of chromosome arms, with cell cycle and apoptotic pathways playing a mediating role. Additionally, a simple correction is demonstrated to mitigate this pervasive bias while preserving biological relationships. This previously uncharacterized effect has implications for functional genomic studies using CRISPR-Cas9, with applications in discovery biology, drug-target identification, cell therapies and genetic therapeutics.

Germline variation contributes to false negatives in CRISPR-based experiments with varying burden across ancestries

Reducing disparities is vital for equitable access to precision treatments in cancer. Socioenvironmental factors are a major driver of disparities, but differences in genetic variation likely also contribute. The impact of genetic ancestry on prioritization of cancer targets in drug discovery pipelines has not been systematically explored due to the absence of pre-clinical data at the appropriate scale. Here, we analyze data from 611 genome-scale CRISPR/Cas9 viability experiments in human cell line models to identify ancestry-associated genetic dependencies essential for cell survival. Surprisingly, we find that most putative associations between ancestry and dependency arise from artifacts related to germline variants. Our analysis suggests that for 1.2-2.5% of guides, germline variants in sgRNA targeting sequences reduce cutting by the CRISPR/Cas9 nuclease, disproportionately affecting cell models derived from individuals of recent African descent. We propose three approaches to mitigate this experimental bias, enabling the scientific community to address these disparities.

CRISPR-Cas9 for selective targeting of somatic mutations in pancreatic cancers

Somatic mutations are desirable targets for selective elimination of cancer, yet most are found within noncoding regions. We have adapted the CRISPR-Cas9 gene editing tool as a novel, cancer-specific killing strategy by targeting the subset of somatic mutations that create protospacer adjacent motifs (PAMs), which have evolutionally allowed bacterial cells to distinguish between self and non-self DNA for Cas9-induced double strand breaks. Whole genome sequencing (WGS) of paired tumor minus normal (T-N) samples from three pancreatic cancer patients (Panc480, Panc504, and Panc1002) showed an average of 417 somatic PAMs per tumor produced from single base substitutions. Further analyses of 591 paired T-N samples from The International Cancer Genome Consortium found medians of ∼455 somatic PAMs per tumor in pancreatic, ∼2800 in lung, and ∼3200 in esophageal cancer cohorts. Finally, we demonstrated 69-99% selective cell death of three targeted pancreatic cancer cell lines using 4-9 sgRNAs designed using the somatic PAM discovery approach. We also showed no off-target activity from these tumor-specific sgRNAs in either the patient's normal cells or an irrelevant cancer using WGS. This study demonstrates the potential of CRISPR-Cas9 as a novel and selective anti-cancer strategy, and supports the genetic targeting of adult cancers.

Genome-wide CRISPR screens identify PKMYT1 as a therapeutic target in pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is a devastating disease with an overall 5-year survival rate of <12% due to the lack of effective treatments. Novel treatment strategies are urgently needed. Here, PKMYT1 is identified through genome-wide CRISPR screens as a non-mutant, genetic vulnerability of PDAC. Higher PKMYT1 expression levels indicate poor prognosis in PDAC patients. PKMYT1 ablation inhibits tumor growth and proliferation in vitro and in vivo by regulating cell cycle progression and inducing apoptosis. Moreover, pharmacological inhibition of PKMYT1 shows efficacy in multiple PDAC cell models and effectively induces tumor regression without overt toxicity in PDAC cell line-derived xenograft and in more clinically relevant patient-derived xenograft models. Mechanistically, in addition to its canonical function of phosphorylating CDK1, PKMYT1 functions as an oncogene to promote PDAC tumorigenesis by regulating PLK1 expression and phosphorylation. Finally, TP53 function and PRKDC activation are shown to modulate the sensitivity to PKMYT1 inhibition. These results define PKMYT1 dependency in PDAC and identify potential therapeutic strategies for clinical translation.

Positive selection CRISPR screens reveal a druggable pocket in an oligosaccharyltransferase required for inflammatory signaling to NF-κB

Nuclear factor κB (NF-κB) plays roles in various diseases. Many inflammatory signals, such as circulating lipopolysaccharides (LPSs), activate NF-κB via specific receptors. Using whole-genome CRISPR-Cas9 screens of LPS-treated cells that express an NF-κB-driven suicide gene, we discovered that the LPS receptor Toll-like receptor 4 (TLR4) is specifically dependent on the oligosaccharyltransferase complex OST-A for N-glycosylation and cell-surface localization. The tool compound NGI-1 inhibits OST complexes in vivo, but the underlying molecular mechanism remained unknown. We did a CRISPR base-editor screen for NGI-1-resistant variants of STT3A, the catalytic subunit of OST-A. These variants, in conjunction with cryoelectron microscopy studies, revealed that NGI-1 binds the catalytic site of STT3A, where it traps a molecule of the donor substrate dolichyl-PP-GlcNAc2-Man9-Glc3, suggesting an uncompetitive inhibition mechanism. Our results provide a rationale for and an initial step toward the development of STT3A-specific inhibitors and illustrate the power of contemporaneous base-editor and structural studies to define drug mechanism of action.

CRISPRi: a way to integrate iPSC-derived neuronal models

The genetic landscape of neurodegenerative diseases encompasses genes affecting multiple cellular pathways which exert effects in an array of neuronal and glial cell-types. Deconvolution of the roles of genes implicated in disease and the effects of disease-associated variants remains a vital step in the understanding of neurodegeneration and the development of therapeutics. Disease modelling using patient induced pluripotent stem cells (iPSCs) has enabled the generation of key cell-types associated with disease whilst maintaining the genomic variants that predispose to neurodegeneration. The use of CRISPR interference (CRISPRi), alongside other CRISPR-perturbations, allows the modelling of the effects of these disease-associated variants or identifying genes which modify disease phenotypes. This review summarises the current applications of CRISPRi in iPSC-derived neuronal models, such as fluorescence-activated cell sorting (FACS)-based screens, and discusses the future opportunities for disease modelling, identification of disease risk modifiers and target/drug discovery in neurodegeneration.

The Tudor-knot Domain of KAT5 Regulates Nucleosomal Substrate Acetylation

The lysine acetyltransferase KAT5 is a pivotal enzyme responsible for catalyzing histone H4 acetylation in cells. In addition to its indispensable HAT domain, KAT5 also encompasses a conserved Tudor-knot domain at its N-terminus. However, the function of this domain remains elusive, with conflicting findings regarding its role as a histone reader. In our study, we have employed a CRISPR tiling array approach and unveiled the Tudor-knot motif as an essential domain for cell survival. The Tudor-knot domain does not bind to histone tails and is not required for KAT5's chromatin occupancy. However, its absence leads to a global reduction in histone acetylation, accompanied with genome-wide alterations in gene expression that consequently result in diminished cell viability. Mechanistically, we find that the Tudor-knot domain regulates KAT5's HAT activity on nucleosomes by fine-tuning substrate accessibility. In summary, our study uncovers the Tudor-knot motif as an essential domain for cell survival and reveals its critical role in modulating KAT5's catalytic efficiency on nucleosome and KAT5-dependent transcriptional programs critical for cell viability.

Genome-scale pan-cancer interrogation of lncRNA dependencies using CasRx

Although long noncoding RNAs (lncRNAs) dominate the transcriptome, their functions are largely unexplored. The extensive overlap of lncRNAs with coding and regulatory sequences restricts their systematic interrogation by DNA-directed perturbation. Here we developed genome-scale lncRNA transcriptome screening using Cas13d/CasRx. We show that RNA targeting overcomes limitations inherent to other screening methods, thereby considerably expanding the explorable space of the lncRNAome. By evolving the screening system toward pan-cancer applicability, it supports molecular and phenotypic data integration to contextualize screening hits or infer lncRNA function. We thereby addressed challenges posed by the enormous transcriptome size and tissue specificity through a size-reduced multiplexed gRNA library termed Albarossa, targeting 24,171 lncRNA genes. Its rational design incorporates target prioritization based on expression, evolutionary conservation and tissue specificity, thereby reconciling high discovery power and pan-cancer representation with scalable experimental throughput. Applied across entities, the screening platform identified numerous context-specific and common essential lncRNAs. Our work sets the stage for systematic exploration of lncRNA biology in health and disease.

A novel class of inhibitors that disrupts the stability of integrin heterodimers identified by CRISPR-tiling-instructed genetic screens

The plasma membrane is enriched for receptors and signaling proteins that are accessible from the extracellular space for pharmacological intervention. Here we conducted a series of CRISPR screens using human cell surface proteome and integrin family libraries in multiple cancer models. Our results identified ITGAV (integrin αV) and its heterodimer partner ITGB5 (integrin β5) as the essential integrin α/β pair for cancer cell expansion. High-density CRISPR gene tiling further pinpointed the integral pocket within the β-propeller domain of ITGAV for integrin αVβ5 dimerization. Combined with in silico compound docking, we developed a CRISPR-Tiling-Instructed Computer-Aided (CRISPR-TICA) pipeline for drug discovery and identified Cpd_AV2 as a lead inhibitor targeting the β-propeller central pocket of ITGAV. Cpd_AV2 treatment led to rapid uncoupling of integrin αVβ5 and cellular apoptosis, providing a unique class of therapeutic action that eliminates the integrin signaling via heterodimer dissociation. We also foresee the CRISPR-TICA approach to be an accessible method for future drug discovery studies.

Preclinical Anticipation of On- and Off-Target Resistance Mechanisms to Anti-Cancer Drugs: A Systematic Review

The advent of targeted therapies has led to tremendous improvements in treatment options and their outcomes in the field of oncology. Yet, many cancers outsmart precision drugs by developing on-target or off-target resistance mechanisms. Gaining the ability to resist treatment is the rule rather than the exception in tumors, and it remains a major healthcare challenge to achieve long-lasting remission in most cancer patients. Here, we discuss emerging strategies that take advantage of innovative high-throughput screening technologies to anticipate on- and off-target resistance mechanisms before they occur in treated cancer patients. We divide the methods into non-systematic approaches, such as random mutagenesis or long-term drug treatment, and systematic approaches, relying on the clustered regularly interspaced short palindromic repeats (CRISPR) system, saturated mutagenesis, or computational methods. All these new developments, especially genome-wide CRISPR-based screening platforms, have significantly accelerated the processes for identification of the mechanisms responsible for cancer drug resistance and opened up new avenues for future treatments.

High-throughput CRISPR technology: a novel horizon for solid organ transplantation

Organ transplantation is the gold standard therapy for end-stage organ failure. However, the shortage of available grafts and long-term graft dysfunction remain the primary barriers to organ transplantation. Exploring approaches to solve these issues is urgent, and CRISPR/Cas9-based transcriptome editing provides one potential solution. Furthermore, combining CRISPR/Cas9-based gene editing with an ex vivo organ perfusion system would enable pre-implantation transcriptome editing of grafts. How to determine effective intervention targets becomes a new problem. Fortunately, the advent of high-throughput CRISPR screening has dramatically accelerated the effective targets. This review summarizes the current advancements, utilization, and workflow of CRISPR screening in various immune and non-immune cells. It also discusses the ongoing applications of CRISPR/Cas-based gene editing in transplantation and the prospective applications of CRISPR screening in solid organ transplantation.

Advancements in CRISPR screens for the development of cancer immunotherapy strategies

CRISPR screen technology enables systematic and scalable interrogation of gene function by using the CRISPR-Cas9 system to perturb gene expression. In the field of cancer immunotherapy, this technology has empowered the discovery of genes, biomarkers, and pathways that regulate tumor development and progression, immune reactivity, and the effectiveness of immunotherapeutic interventions. By conducting large-scale genetic screens, researchers have successfully identified novel targets to impede tumor growth, enhance anti-tumor immune responses, and surmount immunosuppression within the tumor microenvironment (TME). Here, we present an overview of CRISPR screens conducted in tumor cells for the purpose of identifying novel therapeutic targets. We also explore the application of CRISPR screens in immune cells to propel the advancement of cell-based therapies, encompassing T cells, natural killer cells, dendritic cells, and macrophages. Furthermore, we outline the crucial components necessary for the successful implementation of immune-specific CRISPR screens and explore potential directions for future research.

Rational design of a SOCS1-edited tumor-infiltrating lymphocyte therapy using CRISPR/Cas9 screens

Cell therapies such as tumor-infiltrating lymphocyte (TIL) therapy have shown promise in the treatment of patients with refractory solid tumors, with improvement in response rates and durability of responses nevertheless sought. To identify targets capable of enhancing the antitumor activity of T cell therapies, large-scale in vitro and in vivo clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 screens were performed, with the SOCS1 gene identified as a top T cell-enhancing target. In murine CD8+ T cell-therapy models, SOCS1 served as a critical checkpoint in restraining the accumulation of central memory T cells in lymphoid organs as well as intermediate (Texint) and effector (Texeff) exhausted T cell subsets derived from progenitor exhausted T cells (Texprog) in tumors. A comprehensive CRISPR tiling screen of the SOCS1-coding region identified sgRNAs targeting the SH2 domain of SOCS1 as the most potent, with an sgRNA with minimal off-target cut sites used to manufacture KSQ-001, an engineered TIL therapy with SOCS1 inactivated by CRISPR/Cas9. KSQ-001 possessed increased responsiveness to cytokine signals and enhanced in vivo antitumor function in mouse models. These data demonstrate the use of CRISPR/Cas9 screens in the rational design of T cell therapies.

Targeting the non-coding genome and temozolomide signature enables CRISPR-mediated glioma oncolysis

Glioblastoma (GBM) is the most common lethal primary brain cancer in adults. Despite treatment regimens including surgical resection, radiotherapy, and temozolomide (TMZ) chemotherapy, growth of residual tumor leads to therapy resistance and death. At recurrence, a quarter to a third of all gliomas have hypermutated genomes, with mutational burdens orders of magnitude greater than in normal tissue. Here, we quantified the mutational landscape progression in a patient's primary and recurrent GBM, and we uncovered Cas9-targetable repeat elements. We show that CRISPR-mediated targeting of highly repetitive loci enables rapid elimination of GBM cells, an approach we term "genome shredding." Importantly, in the patient's recurrent GBM, we identified unique repeat sequences with TMZ mutational signature and demonstrated that their CRISPR targeting enables cancer-specific cell ablation. "Cancer shredding" leverages the non-coding genome and therapy-induced mutational signatures for targeted GBM cell depletion and provides an innovative paradigm to develop treatments for hypermutated glioma.

Epigenetic-focused CRISPR/Cas9 screen identifies (absent, small, or homeotic)2-like protein (ASH2L) as a regulator of glioblastoma cell survival

BACKGROUND

Glioblastoma is the most common and aggressive primary brain tumor with extremely poor prognosis, highlighting an urgent need for developing novel treatment options. Identifying epigenetic vulnerabilities of cancer cells can provide excellent therapeutic intervention points for various types of cancers.

METHOD

In this study, we investigated epigenetic regulators of glioblastoma cell survival through CRISPR/Cas9 based genetic ablation screens using a customized sgRNA library EpiDoKOL, which targets critical functional domains of chromatin modifiers.

RESULTS

Screens conducted in multiple cell lines revealed ASH2L, a histone lysine methyltransferase complex subunit, as a major regulator of glioblastoma cell viability. ASH2L depletion led to cell cycle arrest and apoptosis. RNA sequencing and greenCUT&RUN together identified a set of cell cycle regulatory genes, such as TRA2B, BARD1, KIF20B, ARID4A and SMARCC1 that were downregulated upon ASH2L depletion. Mass spectrometry analysis revealed the interaction partners of ASH2L in glioblastoma cell lines as SET1/MLL family members including SETD1A, SETD1B, MLL1 and MLL2. We further showed that glioblastoma cells had a differential dependency on expression of SET1/MLL family members for survival. The growth of ASH2L-depleted glioblastoma cells was markedly slower than controls in orthotopic in vivo models. TCGA analysis showed high ASH2L expression in glioblastoma compared to low grade gliomas and immunohistochemical analysis revealed significant ASH2L expression in glioblastoma tissues, attesting to its clinical relevance. Therefore, high throughput, robust and affordable screens with focused libraries, such as EpiDoKOL, holds great promise to enable rapid discovery of novel epigenetic regulators of cancer cell survival, such as ASH2L.

CONCLUSION

Together, we suggest that targeting ASH2L could serve as a new therapeutic opportunity for glioblastoma. Video Abstract.

Outlook on the Security and Potential Improvements of CRISPR-Cas9

Gene editing technology is regarded as a good news to save patients with genetic diseases because of its significant function of specifically changing genetic information. From zinc-finger proteins to transcription activator-like effector protein nucleases gene editing tools are constantly updated. At the same time, scientists are constantly developing a variety of new gene editing therapy strategies, in order to promote gene editing therapy from various aspects and realize the maturity of the technology as soon as possible. In 2016, CRISPR-Cas9-mediated CAR-T therapy was the first to enter the clinical trial stage, indicating that the use of CRISPR-Cas system as the blade of the genetic lancet to save patients is officially on the schedule. The first challenge to achieve this exciting goal is to improve the security of the technology. This review will introduce the gene security issues faced by the CRISPR system as a clinical treatment tool, the current safer delivery methods and the newly developed CRISPR editing tools with higher precision. Many reviews summarize the means of improving the security of gene editing therapy and the comprehensive delivery method, while few articles focus on the threat of gene editing to the genomic security of the treatment target. Therefore, this review focuses on the risks brought by gene editing therapy to the patient genome, which provides a broader perspective for exploring and improving the security of gene editing therapy from two aspects of delivery system and CRISPR editing tools.

Applications of CRISPR-Cas9 for advancing precision medicine in oncology: from target discovery to disease modeling

The clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated protein 9 (Cas9) (CRISPR/Cas9) system is a powerful tool that enables precise and efficient gene manipulation. In a relatively short time, CRISPR has risen to become the preferred gene-editing system due to its high efficiency, simplicity, and programmability at low costs. Furthermore, in the recent years, the CRISPR toolkit has been rapidly expanding, and the emerging advancements have shown tremendous potential in uncovering molecular mechanisms and new therapeutic strategies for human diseases. In this review, we provide our perspectives on the recent advancements in CRISPR technology and its impact on precision medicine, ranging from target identification, disease modeling, and diagnostics. We also discuss the impact of novel approaches such as epigenome, base, and prime editing on preclinical cancer drug discovery.

Guide-specific loss of efficiency and off-target reduction with Cas9 variants

High-fidelity clustered regularly interspaced palindromic repeats (CRISPR)-associated protein 9 (Cas9) variants have been developed to reduce the off-target effects of CRISPR systems at a cost of efficiency loss. To systematically evaluate the efficiency and off-target tolerance of Cas9 variants in complex with different single guide RNAs (sgRNAs), we applied high-throughput viability screens and a synthetic paired sgRNA-target system to assess thousands of sgRNAs in combination with two high-fidelity Cas9 variants HiFi and LZ3. Comparing these variants against wild-type SpCas9, we found that ∼20% of sgRNAs are associated with a significant loss of efficiency when complexed with either HiFi or LZ3. The loss of efficiency is dependent on the sequence context in the seed region of sgRNAs, as well as at positions 15-18 in the non-seed region that interacts with the REC3 domain of Cas9, suggesting that the variant-specific mutations in the REC3 domain account for the loss of efficiency. We also observed various degrees of sequence-dependent off-target reduction when different sgRNAs are used in combination with the variants. Given these observations, we developed GuideVar, a transfer learning-based computational framework for the prediction of on-target efficiency and off-target effects with high-fidelity variants. GuideVar facilitates the prioritization of sgRNAs in the applications with HiFi and LZ3, as demonstrated by the improvement of signal-to-noise ratios in high-throughput viability screens using these high-fidelity variants.

CRISPR-Cas9 for selective targeting of somatic mutations in pancreatic cancers

Somatic mutations are desirable targets for selective elimination of cancer, yet most are found within the noncoding regions. We propose a novel, cancer-specific killing approach using CRISPR-Cas9 which exploits the requirement of a protospacer adjacent motif (PAM) for Cas9 activity. Through whole genome sequencing (WGS) of paired tumor minus normal (T-N) samples from three pancreatic cancer patients (Panc480, Panc504, and Panc1002), we identified an average of 417 somatic PAMs per tumor produced from single base substitutions. We analyzed 591 paired T-N samples from The International Cancer Genome Consortium and discovered medians of ~455 somatic PAMs per tumor in pancreatic, ~2800 in lung, and ~3200 in esophageal cancer cohorts. Finally, we demonstrated >80% selective cell death of two targeted pancreatic cancer cell lines in co-cultures using 4-9 sgRNAs, targeting noncoding regions, designed from the somatic PAM discovery approach. We also showed no off-target activity from these tumor-specific sgRNAs through WGS.

Precision Oncology Comes of Age: Designing Best-in-Class Small Molecules by Integrating Two Decades of Advances in Chemistry, Target Biology, and Data Science

Small-molecule drugs have enabled the practice of precision oncology for genetically defined patient populations since the first approval of imatinib in 2001. Scientific and technology advances over this 20-year period have driven the evolution of cancer biology, medicinal chemistry, and data science. Collectively, these advances provide tools to more consistently design best-in-class small-molecule drugs against known, previously undruggable, and novel cancer targets. The integration of these tools and their customization in the hands of skilled drug hunters will be necessary to enable the discovery of transformational therapies for patients across a wider spectrum of cancers.

SIGNIFICANCE

Target-centric small-molecule drug discovery necessitates the consideration of multiple approaches to identify chemical matter that can be optimized into drug candidates. To do this successfully and consistently, drug hunters require a comprehensive toolbox to avoid following the "law of instrument" or Maslow's hammer concept where only one tool is applied regardless of the requirements of the task. Combining our ever-increasing understanding of cancer and cancer targets with the technological advances in drug discovery described below will accelerate the next generation of small-molecule drugs in oncology.

Genome-scale CRISPR-Cas9 screening stratifies pancreatic cancer with distinct outcomes and immunotherapeutic efficacy

Pancreatic cancer (PC) was featured by dramatic heterogeneity and dismal outcomes. An ideal classification strategy capable of achieving risk stratification and individualized treatment is urgently needed to significantly improve prognosis. In this study, using the 105 prognostic cancer essential genes identified by genome-scale CRISPR-Cas9 screening and univariate Cox analysis, we established and verified three heterogeneous subtypes via non-negative matrix factorization (NMF) and nearest template prediction (NTP) algorithms in the TCGA-PAAD cohort (176 samples) and four multi-center cohorts (233 samples), respectively. Among them, C1 with the worst prognosis was enriched in immune-related pathways, possessed superior infiltration abundance of immune cells and immune checkpoint molecules expression, and might be most sensitive to immunotherapy. C3, owing a moderate prognosis, might be featured by proliferative biological function, and despite its highest immunogenicity, the defects in antigen processing and presentation ability coupled with barren immune environment render it ineffective for immunotherapy, while it had potential sensitivity to paclitaxel and methotrexate. Besides, C2 harbored the best prognosis and was characterized by metabolism-related functions. These results could deepen our understanding of PC molecular heterogeneity and provide a trustworthy reference for prognostic stratification management and precision medicine in clinical practice.

CHSY1 promotes CD8+ T cell exhaustion through activation of succinate metabolism pathway leading to colorectal cancer liver metastasis based on CRISPR/Cas9 screening

BACKGROUND

The most common site of metastasis in colorectal cancer (CRC) is the liver and liver metastases occur in more than 50% of patients during diagnosis or treatment. The occurrence of metastasis depends on a series of events known as the invasive-metastasis cascade. Currently, the underlying genes and pathways regulating metastasis initiation in the liver microenvironment are unknown.

METHODS

We performed systematic CRISPR/Cas9 screening using an in vivo mouse model of CRC liver metastasis to identify key regulators of CRC metastasis. We present the full results of this screen,which included a list of genes that promote or repress CRC liver colonization. By silencing these genes individually, we found that chondroitin sulfate synthase 1 (CHSY1) may be involved in CRC metastasis. We verified the function of CHSY1 and its involvement in liver metastasis of CRC through in vivo and in vitro experiments.

RESULT

The results of TCGA and CRISPR/Cas9 showed that CHSY1 was overexpressed in CRC primary and liver metastasis tissues and indicated a worse clinical prognosis. In vitro and in vivo experiments confirmed that CHSY1 facilitated the liver metastasis of CRC and CHSY1 induced CD8+ T cell exhaustion and upregulated PD-L1 expression. The metabolomic analysis indicated that CHSY1 promoted CD8+ T cell exhaustion by activating the succinate metabolism pathway leading to liver metastasis of CRC. Artemisinin as a CHSY1 inhibitor reduced liver metastasis and enhanced the effect of anti-PD1 in CRC. PLGA-loaded Artemisinin and ICG probe reduced liver metastasis and increased the efficiency of anti-PD1 treatment in CRC.

CONCLUSION

CHSY1 could promote CD8+ T cell exhaustion through activation of the succinate metabolic and PI3K/AKT/HIF1A pathway, leading to CRC liver metastasis. The combination of CHSY1 knockdown and anti-PD1 contributes to synergistic resistance to CRC liver metastasis. Artemisinin significantly inhibits CHSY1 activity and in combination with anti-PD1 could synergistically treat CRC liver metastases. This study provides new targets and specific strategies for the treatment of CRC liver metastases, bringing new hope and benefits to patients.

TAZ2 truncation confers overactivation of p300 and cellular vulnerability to HDAC inhibition

The histone acetyltransferase p300/CBP is composed of several conserved domains, among which, the TAZ2 domain is known as a protein-protein interaction domain that binds to E1A and various transcription factors. Here we show that TAZ2 has a HAT autoinhibitory function. Truncating p300/CBP at TAZ2 leads to hyperactive HAT and elevated histone H3K27 and H3K18 acetylation in cells. Mechanistically, TAZ2 cooperates with other HAT neighboring domains to maintain the HAT active site in a 'closed' state. Truncating TAZ2 or binding of transcription factors to TAZ2 induces a conformational change that 'opens' the active site for substrate acetylation. Importantly, genetic mutations that lead to p300/CBP TAZ2 truncations are found in human cancers, and cells with TAZ2 truncations are vulnerable to histone deacetylase inhibitors. Our study reveals a function of the TAZ2 domain in HAT autoinhibitory regulation and provides a potential therapeutic strategy for the treatment of cancers harboring p300/CBP TAZ2 truncations.

CRISPR-Cas9 identifies growth-related subtypes of glioblastoma with therapeutical significance through cell line knockdown

BACKGROUND

Glioblastoma (GBM) is a type of highly malignant brain tumor that is known for its significant intratumoral heterogeneity, meaning that there can be a high degree of variability within the tumor tissue. Despite the identification of several subtypes of GBM in recent years, there remains to explore a classification based on genes related to proliferation and growth.

METHODS

The growth-related genes of GBM were identified by CRISPR-Cas9 and univariate Cox regression analysis. The expression of these genes in the Cancer Genome Atlas cohort (TCGA) was used to construct growth-related genes subtypes (GGSs) via consensus clustering. Validation of this subtyping was performed using the nearest template prediction (NTP) algorithm in two independent Gene Expression Omnibus (GEO) cohorts and the ZZ cohort. Additionally, copy number variations, biological functions, and potential drugs were analyzed for each of the different subtypes separately.

RESULTS

Our research established multicenter-validated GGSs. GGS1 exhibits the poorest prognosis, with the highest frequency of chr 7 gain & chr 10 loss, and the lowest frequency of chr 19 & 20 co-gain. Additionally, GGS1 displays the highest expression of EGFR. Furthermore, it is significantly enriched in metabolic, stemness, proliferation, and signaling pathways. Besides we showed that Foretinib may be a potential therapeutic agent for GGS1, the worst prognostic subtype, through data screening and in vitro experiments. GGS2 has a moderate prognosis, with a slightly higher proportion of chr 7 gain & chr 10 loss, and the highest proportion of chr 19 & 20 co-gain. The prognosis of GGS3 is the best, with the least chr 7 gain & 10 loss and EGFR expression.

CONCLUSIONS

These results enhance our understanding of the heterogeneity of GBM and offer insights for stratified management and precise treatment of GBM patients.

The APC/C E3 ligase subunit ANAPC11 mediates FOXO3 protein degradation to promote cell proliferation and lymph node metastasis in urothelial bladder cancer

Urothelial bladder cancer (UBC) is one of the most prevalent malignancies worldwide, with striking tumor heterogeneity. Elucidating the molecular mechanisms that can be exploited for the treatment of aggressive UBC is a particularly relevant goal. Protein ubiquitination is a critical post-translational modification (PTM) that mediates the degradation of target protein via the proteasome. However, the roles of aberrant protein ubiquitination in UBC development and the underlying mechanisms by which it drives tumor progression remain unclear. In this study, taking advantage of clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR-associated protein (Cas) 9 technology, we identified the ubiquitin E3 ligase ANAPC11, a critical subunit of the anaphase-promoting complex/cyclosome (APC/C), as a potential oncogenic molecule in UBC cells. Our clinical analysis showed that elevated expression of ANAPC11 was significantly correlated with high T stage, positive lymph node (LN) metastasis, and poor outcomes in UBC patients. By employing a series of in vitro experiments, we demonstrated that ANAPC11 enhanced the proliferation and invasiveness of UBC cells, while knockout of ANAPC11 inhibited the growth and LN metastasis of UBC cells in vivo. By conducting immunoprecipitation coupled with mass spectrometry, we confirmed that ANAPC11 increased the ubiquitination level of the Forkhead transcription factor FOXO3. The resulting decrease in FOXO3 protein stability led to the downregulation of the cell cycle regulator p21 and decreased expression of GULP1, a downstream effector of androgen receptor signaling. Taken together, these findings indicated that ANAPC11 plays an oncogenic role in UBC by modulating FOXO3 protein degradation. The ANAPC11-FOXO3 regulatory axis might serve as a novel therapeutic target for UBC.

Base editor screens for in situ mutational scanning at scale

A fundamental challenge in biology is understanding the molecular details of protein function. How mutations alter protein activity, regulation, and response to drugs is of critical importance to human health. Recent years have seen the emergence of pooled base editor screens for in situ mutational scanning: the interrogation of protein sequence-function relationships by directly perturbing endogenous proteins in live cells. These studies have revealed the effects of disease-associated mutations, discovered novel drug resistance mechanisms, and generated biochemical insights into protein function. Here, we discuss how this "base editor scanning" approach has been applied to diverse biological questions, compare it with alternative techniques, and describe the emerging challenges that must be addressed to maximize its utility. Given its broad applicability toward profiling mutations across the proteome, base editor scanning promises to revolutionize the investigation of proteins in their native contexts.

Amplified therapeutic targets in high-grade serous ovarian carcinoma - a review of the literature with quantitative appraisal

High-grade serous ovarian carcinoma is a unique cancer characterised by universal TP53 mutations and widespread copy number alterations. These copy number alterations include deletion of tumour suppressors and amplification of driver oncogenes. Given their key oncogenic roles, amplified driver genes are often proposed as therapeutic targets. For example, development of anti-HER2 agents has been clinically successful in treatment of ERBB2-amplified tumours. A wide scope of preclinical work has since investigated numerous amplified genes as potential therapeutic targets in high-grade serous ovarian carcinoma. However, variable experimental procedures (e.g., choice of cell lines), ambiguous phenotypes or lack of validation hinders further clinical translation of many targets. In this review, we collate the genes proposed to be amplified therapeutic targets in high-grade serous ovarian carcinoma, and quantitatively appraise the evidence in support of each candidate gene. Forty-four genes are found to have evidence as amplified therapeutic targets; the five highest scoring genes are CCNE1, PAX8, URI1, PRKCI and FAL1. This review generates an up-to-date list of amplified therapeutic target candidates for further development and proposes comprehensive criteria to assist amplified therapeutic target discovery in the future.

Epigenetic Control of Translation Checkpoint and Tumor Progression via RUVBL1-EEF1A1 Axis

Epigenetic dysregulation is reported in multiple cancers including Ewing sarcoma (EwS). However, the epigenetic networks underlying the maintenance of oncogenic signaling and therapeutic response remain unclear. Using a series of epigenetics- and complex-focused CRISPR screens, RUVBL1, the ATPase component of NuA4 histone acetyltransferase complex, is identified to be essential for EwS tumor progression. Suppression of RUVBL1 leads to attenuated tumor growth, loss of histone H4 acetylation, and ablated MYC signaling. Mechanistically, RUVBL1 controls MYC chromatin binding and modulates the MYC-driven EEF1A1 expression and thus protein synthesis. High-density CRISPR gene body scan pinpoints the critical MYC interacting residue in RUVBL1. Finally, this study reveals the synergism between RUVBL1 suppression and pharmacological inhibition of MYC in EwS xenografts and patient-derived samples. These results indicate that the dynamic interplay between chromatin remodelers, oncogenic transcription factors, and protein translation machinery can provide novel opportunities for combination cancer therapy.

Using traditional machine learning and deep learning methods for on- and off-target prediction in CRISPR/Cas9: a review

CRISPR/Cas9 (Clustered Regularly Interspaced Short Palindromic Repeats and CRISPR-associated protein 9) is a popular and effective two-component technology used for targeted genetic manipulation. It is currently the most versatile and accurate method of gene and genome editing, which benefits from a large variety of practical applications. For example, in biomedicine, it has been used in research related to cancer, virus infections, pathogen detection, and genetic diseases. Current CRISPR/Cas9 research is based on data-driven models for on- and off-target prediction as a cleavage may occur at non-target sequence locations. Nowadays, conventional machine learning and deep learning methods are applied on a regular basis to accurately predict on-target knockout efficacy and off-target profile of given single-guide RNAs (sgRNAs). In this paper, we present an overview and a comparative analysis of traditional machine learning and deep learning models used in CRISPR/Cas9. We highlight the key research challenges and directions associated with target activity prediction. We discuss recent advances in the sgRNA-DNA sequence encoding used in state-of-the-art on- and off-target prediction models. Furthermore, we present the most popular deep learning neural network architectures used in CRISPR/Cas9 prediction models. Finally, we summarize the existing challenges and discuss possible future investigations in the field of on- and off-target prediction. Our paper provides valuable support for academic and industrial researchers interested in the application of machine learning methods in the field of CRISPR/Cas9 genome editing.

CRISPR-Cas9 knockout screen identifies novel treatment targets in childhood high-grade glioma

BACKGROUND

Brain tumours are the leading cause of cancer-related death in children, and there is no effective treatment. A growing body of evidence points to deregulated epigenetics as a tumour driver, particularly in paediatric cancers as they have relatively few genomic alterations, and key driver mutations have been identified in histone 3 (H3). Cancer stem cells (CSC) are implicated in tumour development, relapse and therapy resistance and thus particularly important to target. We therefore aimed to identify novel epigenetic treatment targets in CSC derived from H3-mutated high-grade glioma (HGG) through a CRISPR-Cas9 knockout screen.

RESULTS

The knockout screen identified more than 100 novel genes essential for the growth of CSC derived from paediatric HGG with H3K27M mutation. We successfully validated 12 of the 13 selected hits by individual knockout in the same two CSC lines, and for the top six hits we included two additional CSC lines derived from H3 wild-type paediatric HGG. Knockout of these genes led to a significant decrease in CSC growth, and altered stem cell and differentiation markers.

CONCLUSIONS

The screen robustly identified essential genes known in the literature, but also many novel genes essential for CSC growth in paediatric HGG. Six of the novel genes (UBE2N, CHD4, LSM11, KANSL1, KANSL3 and EED) were validated individually thus demonstrating their importance for CSC growth in H3-mutated and wild-type HGG. These genes should be further studied and evaluated as novel treatment targets in paediatric HGG.

Targeting synthetic lethal paralogs in cancer

Synthetic lethal interactions, where mutation of one gene renders cells sensitive to inhibition of another gene, can be exploited for the development of targeted therapeutics in cancer. Pairs of duplicate genes (paralogs) often share common functionality and hence are a potentially rich source of synthetic lethal interactions. Because the majority of human genes have paralogs, exploiting such interactions could be a widely applicable approach for targeting gene loss in cancer. Moreover, existing small-molecule drugs may exploit synthetic lethal interactions by inhibiting multiple paralogs simultaneously. Consequently, the identification of synthetic lethal interactions between paralogs could be extremely informative for drug development. Here we review approaches to identify such interactions and discuss some of the challenges of exploiting them.

Integrated CRISPR screening and drug profiling identifies combination opportunities for EGFR, ALK, and BRAF/MEK inhibitors

Anti-tumor efficacy of targeted therapies is variable across patients and cancer types. Even in patients with initial deep response, tumors are typically not eradicated and eventually relapse. To address these challenges, we present a systematic screen for targets that limit the anti-tumor efficacy of EGFR and ALK inhibitors in non-small cell lung cancer and BRAF/MEK inhibitors in colorectal cancer. Our approach includes genome-wide CRISPR screens with or without drugs targeting the oncogenic driver ("anchor therapy"), and large-scale pairwise combination screens of anchor therapies with 351 other drugs. Interestingly, targeting of a small number of genes, including MCL1, BCL2L1, and YAP1, sensitizes multiple cell lines to the respective anchor therapy. Data from drug combination screens with EGF816 and ceritinib indicate that dasatinib and agents disrupting microtubules act synergistically across many cell lines. Finally, we show that a higher-order-combination screen with 26 selected drugs in two resistant EGFR-mutant lung cancer cell lines identified active triplet combinations.

Homology-Directed-Repair-Based Genome Editing in HSPCs for the Treatment of Inborn Errors of Immunity and Blood Disorders

Genome engineering via targeted nucleases, specifically CRISPR-Cas9, has revolutionized the field of gene therapy research, providing a potential treatment for diseases of the blood and immune system. While numerous genome editing techniques have been used, CRISPR-Cas9 homology-directed repair (HDR)-mediated editing represents a promising method for the site-specific insertion of large transgenes for gene knock-in or gene correction. Alternative methods, such as lentiviral/gammaretroviral gene addition, gene knock-out via non-homologous end joining (NHEJ)-mediated editing, and base or prime editing, have shown great promise for clinical applications, yet all possess significant drawbacks when applied in the treatment of patients suffering from inborn errors of immunity or blood system disorders. This review aims to highlight the transformational benefits of HDR-mediated gene therapy and possible solutions for the existing problems holding the methodology back. Together, we aim to help bring HDR-based gene therapy in CD34+ hematopoietic stem progenitor cells (HSPCs) from the lab bench to the bedside.

Mechanism of delayed cell death following simultaneous CRISPR-Cas9 targeting in pancreatic cancers

When we transduced pancreatic cancers with sgRNAs that targeted 2-16 target sites in the human genome, we found that increasing the number of CRISPR-Cas9 target sites produced greater cytotoxicity, with >99% growth inhibition observed by targeting only 12 sites. However, cell death was delayed by 2-3 weeks after sgRNA transduction, in contrast to the repair of double strand DNA breaks (DSBs) that happened within 3 days after transduction. To explain this discrepancy, we used both cytogenetics and whole genome sequencing to interrogate the genome. We first detected chromatid and chromosome breaks, followed by radial formations, dicentric, ring chromosomes, and other chromosomal aberrations that peaked at 14 days after transduction. Structural variants (SVs) were detected at sites that were directly targeted by CRISPR-Cas9, including SVs generated from two sites that were targeted, but the vast majority of SVs (89.4%) were detected elsewhere in the genome that arose later than those directly targeted. Cells also underwent polyploidization that peaked at day 10 as detected by XY FISH assay, and ultimately died via apoptosis. Overall, we found that the simultaneous DSBs induced by CRISPR-Cas9 in pancreatic cancers caused chromosomal instability and polyploidization that ultimately led to delayed cell death.

Analysis of Cancer Genomic Amplifications Identifies Druggable Collateral Dependencies within the Amplicon

The identification of novel therapeutic targets for specific cancer molecular subtypes is crucial for the development of precision oncology. In the last few years, CRISPR/Cas9 screens have accelerated the discovery and validation of new targets associated with different tumor types, mutations, and fusions. However, there are still many cancer vulnerabilities associated with specific molecular features that remain to be explored. Here, we used data from CRISPR/Cas9 screens in 954 cancer cell lines to identify gene dependencies associated with 16 common cancer genomic amplifications. We found that high-copy-number genomic amplifications generate multiple collateral dependencies within the amplified region in most cases. Further, to prioritize candidate targets for each chromosomal region amplified, we integrated gene dependency parameters with both druggability data and subcellular location. Finally, analysis of the relationship between gene expression and gene dependency led to the identification of genes, the expression of which may constitute predictive biomarkers of dependency. In conclusion, our study provides a set of druggable targets specific for each amplification, opening the possibility to specifically target amplified tumors on this basis.

Predicting gene knockout effects from expression data

BACKGROUND

The study of gene essentiality, which measures the importance of a gene for cell division and survival, is used for the identification of cancer drug targets and understanding of tissue-specific manifestation of genetic conditions. In this work, we analyze essentiality and gene expression data from over 900 cancer lines from the DepMap project to create predictive models of gene essentiality.

METHODS

We developed machine learning algorithms to identify those genes whose essentiality levels are explained by the expression of a small set of "modifier genes". To identify these gene sets, we developed an ensemble of statistical tests capturing linear and non-linear dependencies. We trained several regression models predicting the essentiality of each target gene, and used an automated model selection procedure to identify the optimal model and hyperparameters. Overall, we examined linear models, gradient boosted trees, Gaussian process regression models, and deep learning networks.

RESULTS

We identified nearly 3000 genes for which we accurately predict essentiality using gene expression data of a small set of modifier genes. We show that both in the number of genes we successfully make predictions for, as well as in the prediction accuracy, our model outperforms current state-of-the-art works.

CONCLUSIONS

Our modeling framework avoids overfitting by identifying the small set of modifier genes, which are of clinical and genetic importance, and ignores the expression of noisy and irrelevant genes. Doing so improves the accuracy of essentiality prediction in various conditions and provides interpretable models. Overall, we present an accurate computational approach, as well as interpretable modeling of essentiality in a wide range of cellular conditions, thus contributing to a better understanding of the molecular mechanisms that govern tissue-specific effects of genetic disease and cancer.

Modeling CRISPR-Cas13d on-target and off-target effects using machine learning approaches

A major challenge in the application of the CRISPR-Cas13d system is to accurately predict its guide-dependent on-target and off-target effect. Here, we perform CRISPR-Cas13d proliferation screens and design a deep learning model, named DeepCas13, to predict the on-target activity from guide sequences and secondary structures. DeepCas13 outperforms existing methods to predict the efficiency of guides targeting both protein-coding and non-coding RNAs. Guides targeting non-essential genes display off-target viability effects, which are closely related to their on-target efficiencies. Choosing proper negative control guides during normalization mitigates the associated false positives in proliferation screens. We apply DeepCas13 to the guides targeting lncRNAs, and identify lncRNAs that affect cell viability and proliferation in multiple cell lines. The higher prediction accuracy of DeepCas13 over existing methods is extensively confirmed via a secondary CRISPR-Cas13d screen and quantitative RT-PCR experiments. DeepCas13 is freely accessible via http://deepcas13.weililab.org .

A competitive precision CRISPR method to identify the fitness effects of transcription factor binding sites

Here we describe a competitive genome editing method that measures the effect of mutations on molecular functions, based on precision CRISPR editing using template libraries with either the original or altered sequence, and a sequence tag, enabling direct comparison between original and mutated cells. Using the example of the MYC oncogene, we identify important transcriptional targets and show that E-box mutations at MYC target gene promoters reduce cellular fitness.

An interactive web application for processing, correcting, and visualizing genome-wide pooled CRISPR-Cas9 screens

A limitation of pooled CRISPR-Cas9 screens is the high false-positive rate in detecting essential genes arising from copy-number-amplified genomics regions. To solve this issue, we previously developed CRISPRcleanR: a computational method implemented as R/python package and in a dockerized version. CRISPRcleanR detects and corrects biased responses to CRISPR-Cas9 targeting in an unsupervised fashion, accurately reducing false-positive signals while maintaining sensitivity in identifying relevant genetic dependencies. Here, we present CRISPRcleanR WebApp , a web application enabling access to CRISPRcleanR through an intuitive interface. CRISPRcleanR WebApp removes the complexity of R/python language user interactions; provides user-friendly access to a complete analytical pipeline, not requiring any data pre-processing and generating gene-level summaries of essentiality with associated statistical scores; and offers a range of interactively explorable plots while supporting a more comprehensive range of CRISPR guide RNAs' libraries than the original package. CRISPRcleanR WebApp is available at https://crisprcleanr-webapp.fht.org/.

Glioblastoma and the search for non-hypothesis driven combination therapeutics in academia

Glioblastoma (GBM) remains a cancer of high unmet clinical need. Current standard of care for GBM, consisting of maximal surgical resection, followed by ionisation radiation (IR) plus concomitant and adjuvant temozolomide (TMZ), provides less than 15-month survival benefit. Efforts by conventional drug discovery to improve overall survival have failed to overcome challenges presented by inherent tumor heterogeneity, therapeutic resistance attributed to GBM stem cells, and tumor niches supporting self-renewal. In this review we describe the steps academic researchers are taking to address these limitations in high throughput screening programs to identify novel GBM combinatorial targets. We detail how they are implementing more physiologically relevant phenotypic assays which better recapitulate key areas of disease biology coupled with more focussed libraries of small compounds, such as drug repurposing, target discovery, pharmacologically active and novel, more comprehensive anti-cancer target-annotated compound libraries. Herein, we discuss the rationale for current GBM combination trials and the need for more systematic and transparent strategies for identification, validation and prioritisation of combinations that lead to clinical trials. Finally, we make specific recommendations to the preclinical, small compound screening paradigm that could increase the likelihood of identifying tractable, combinatorial, small molecule inhibitors and better drug targets specific to GBM.

Evolution of precision oncology-guided treatment paradigms

Cancer treatment is gradually evolving from the classical use of nonspecific cytotoxic drugs targeting generic mechanisms of cell growth and proliferation. Instead, new "patient-specific treatment paradigms" that are based on an individual patient's tumor-specific molecular features are emerging, and these include "druggable" genomic alterations such as oncogenic driver mutations, downstream activities of cancer-signaling pathways, and the expression of specific genes involved in tumorigenesis and cancer progression. This evolving landscape of making evidence-based treatment decisions forms the foundation of precision oncology, which aims to deliver "the right drug, to the right patient and at the right time". The long-term vision for this approach is to maximize the treatment efficacy while minimizing exposure to ineffective therapy and reducing co-morbidity-related side effects. Successful clinical translation and implementation of this vision have the potential to revolutionize treatment paradigms from predominantly reactive, to more evidence-based, proactive and predictive care. In this article, we review the past and current approaches in precision oncology, and describe their remarkable power and limitations. We also speculate on the evolution of newly emerging methodologies of the future that can be used to address some of the key challenges associated with the existing paradigms. This article is categorized under: Cancer > Genetics/Genomics/Epigenetics Cancer > Molecular and Cellular Physiology Cancer > Computational Models.

Genome-Wide CRISPR Screening for the Identification of Therapy Resistance-Associated Genes in Urothelial Carcinoma

The application of CRISPR (clustered regularly interspaced short palindromic repeats)-Cas9 technology with pooled guide RNA libraries enables genome-wide screening, which has some advantages over other screening methods using chemical DNA mutagens for inducing genetic changes, RNA interference, or arrayed screens. Here we describe the use of genome-wide knockout and transcriptional activation screening enabling the CRISPR-Cas9 system to discover resistance mechanisms to CDK4/6 inhibition in bladder cancer along with next-generation sequencing (NGS) analysis. We will describe the approach for transcriptional activation in the bladder cancer cell line T24 and provide guidance on critical points during the experimental workflow.

Biological network topology features predict gene dependencies in cancer cell-lines

Motivation

Protein-protein interaction (PPI) networks have been shown to successfully predict essential proteins. However, such networks are derived generically from experiments on many thousands of different cells. Consequently, conventional PPI networks cannot capture the variation of genetic dependencies that exists across different cell types, let alone those that emerge as a result of the massive cell restructuring that occurs during carcinogenesis. Predicting cell-specific dependencies is of considerable therapeutic benefit, facilitating the use of drugs to inhibit those proteins on which the cancer cells have become specifically dependent. In order to go beyond the limitations of the generic PPI, we have attempted to personalise PPI networks to reflect cell-specific patterns of gene expression and mutation. By using 12 topological features of the resulting PPIs, together with matched gene dependency data from DepMap, we trained random-forest classifiers (DependANT) to predict novel gene dependencies.

Results

We found that DependANT improves the power of the baseline generic PPI models in predicting common gene dependencies, by up to 10.8% and is more sensitive than the baseline generic model when predicting genes on which only a small number of cell types are dependent.

Availability and implementation

Software available at https://bitbucket.org/bioinformatics_lab_sussex/dependant2.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

The methyltransferase domain of DNMT1 is an essential domain in acute myeloid leukemia independent of DNMT3A mutation

Aberrant DNA methylation patterns are a prominent feature of cancer. Methylation of DNA is mediated by the DNA methyltransferase (DNMT) protein family, which regulates de novo (DNMT3A and DNMT3B) and maintenance (DNMT1) methylation. Mutations in DNMT3A are observed in approximately 22% of acute myeloid leukemia (AML). We hypothesized that DNMT1 or DNMT3B could function as a synthetic lethal therapeutic strategy for DNMT3A-mutant AML. CRISPR-Cas9 tiling screens were performed to identify functional domains within DNMT1/DNMT3B that exhibited greater dependencies in DNMT3A mutant versus wild-type cell lines. Although increased sensitivity to DNMT1 mutation was observed in some DNMT3A mutant cellular models tested, the subtlety of these results prevents us from basing any conclusions on a synthetic lethal relationship between DNMT1 and DNMT3A. Our data suggests that a therapeutic window for DNMT1 methyltransferase inhibition in DNMT3A-driven AML may exist, but validation in more biologically relevant models is required.