Genomic Copy Number Dictates a Gene-Independent Cell Response to CRISPR/Cas9 Targeting

A dynamic subpopulation of CRISPR-Cas overexpressers allows Streptococcus pyogenes to rapidly respond to phage

Many CRISPR-Cas (clustered regularly interspaced short palindromic repeats and CRISPR-associated protein) systems, which provide bacteria with adaptive immunity against phages, are transcriptionally repressed in their native hosts. How CRISPR-Cas expression is induced as needed, for example, during a bacteriophage infection, remains poorly understood. In Streptococcus pyogenes, a non-canonical guide RNA tracr-L directs Cas9 to autorepress its own promoter. Here we describe a dynamic subpopulation of cells harbouring single mutations that disrupt Cas9 binding and cause CRISPR-Cas overexpression. Cas9 actively expands this population by elevating mutation rates at the tracr-L target site. Overexpressers show higher rates of memory formation, stronger potency of old memories and a larger memory storage capacity relative to wild-type cells, which are surprisingly vulnerable to phage infection. However, in the absence of phage, CRISPR-Cas overexpression reduces fitness. We propose that CRISPR-Cas overexpressers are critical players in phage defence, enabling bacterial populations to mount rapid transcriptional responses to phage without requiring transient changes in any one cell.

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.

Scalable genetic screening for regulatory circuits using compressed Perturb-seq

Pooled CRISPR screens with single-cell RNA sequencing readout (Perturb-seq) have emerged as a key technique in functional genomics, but they are limited in scale by cost and combinatorial complexity. In this study, we modified the design of Perturb-seq by incorporating algorithms applied to random, low-dimensional observations. Compressed Perturb-seq measures multiple random perturbations per cell or multiple cells per droplet and computationally decompresses these measurements by leveraging the sparse structure of regulatory circuits. Applied to 598 genes in the immune response to bacterial lipopolysaccharide, compressed Perturb-seq achieves the same accuracy as conventional Perturb-seq with an order of magnitude cost reduction and greater power to learn genetic interactions. We identified known and novel regulators of immune responses and uncovered evolutionarily constrained genes with downstream targets enriched for immune disease heritability, including many missed by existing genome-wide association studies. Our framework enables new scales of interrogation for a foundational method in functional genomics.

A genome-scale deep learning model to predict gene expression changes of genetic perturbations from multiplex biological networks

Systematic characterization of biological effects to genetic perturbation is essential to the application of molecular biology and biomedicine. However, the experimental exhaustion of genetic perturbations on the genome-wide scale is challenging. Here, we show TranscriptionNet, a deep learning model that integrates multiple biological networks to systematically predict transcriptional profiles to three types of genetic perturbations based on transcriptional profiles induced by genetic perturbations in the L1000 project: RNA interference, clustered regularly interspaced short palindromic repeat, and overexpression. TranscriptionNet performs better than existing approaches in predicting inducible gene expression changes for all three types of genetic perturbations. TranscriptionNet can predict transcriptional profiles for all genes in existing biological networks and increases perturbational gene expression changes for each type of genetic perturbation from a few thousand to 26 945 genes. TranscriptionNet demonstrates strong generalization ability when comparing predicted and true gene expression changes on different external tasks. Overall, TranscriptionNet can systemically predict transcriptional consequences induced by perturbing genes on a genome-wide scale and thus holds promise to systemically detect gene function and enhance drug development and target discovery.

Uncovering Porphyrin Accumulation in the Tumor Microenvironment

Heme, an iron-containing tetrapyrrole, is essential in almost all organisms. Heme biosynthesis needs to be precisely regulated particularly given the potential cytotoxicity of protoporphyrin IX, the intermediate preceding heme formation. Here, we report on the porphyrin intermediate accumulation within the tumor microenvironment (TME), which we propose to result from dysregulation of heme biosynthesis concomitant with an enhanced cancer survival dependence on mid-step genes, a process we recently termed "Porphyrin Overdrive". Specifically, porphyrins build up in both lung cancer cells and stromal cells in the TME. Within the TME's stromal cells, evidence supports cancer-associated fibroblasts (CAFs) actively producing porphyrins through an imbalanced pathway. Conversely, normal tissues exhibit no porphyrin accumulation, and CAFs deprived of tumor cease porphyrin overproduction, indicating that both cancer and tumor-stromal porphyrin overproduction is confined to the cancer-specific tissue niche. The clinical relevance of our findings is implied by establishing a correlation between imbalanced porphyrin production and overall poorer survival in more aggressive cancers. These findings illuminate the anomalous porphyrin dynamics specifically within the tumor microenvironment, suggesting a potential target for therapeutic intervention.

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.

Genome-scale exon perturbation screens uncover exons critical for cell fitness

CRISPR-Cas technology has transformed functional genomics, yet understanding of how individual exons differentially shape cellular phenotypes remains limited. Here, we optimized and conducted massively parallel exon deletion and splice-site mutation screens in human cell lines to identify exons that regulate cellular fitness. Fitness-promoting exons are prevalent in essential and highly expressed genes and commonly overlap with protein domains and interaction interfaces. Conversely, fitness-suppressing exons are enriched in nonessential genes, exhibiting lower inclusion levels, and overlap with intrinsically disordered regions and disease-associated mutations. In-depth mechanistic investigation of the screen-hit TAF5 alternative exon-8 revealed that its inclusion is required for assembly of the TFIID general transcription initiation complex, thereby regulating global gene expression output. Collectively, our orthogonal exon perturbation screens established a comprehensive repository of phenotypically important exons and uncovered regulatory mechanisms governing cellular fitness and gene expression.

Porphyrin overdrive rewires cancer cell metabolism

All cancer cells reprogram metabolism to support aberrant growth. Here, we report that cancer cells employ and depend on imbalanced and dynamic heme metabolic pathways, to accumulate heme intermediates, that is, porphyrins. We coined this essential metabolic rewiring "porphyrin overdrive" and determined that it is cancer-essential and cancer-specific. Among the major drivers are genes encoding mid-step enzymes governing the production of heme intermediates. CRISPR/Cas9 editing to engineer leukemia cell lines with impaired heme biosynthetic steps confirmed our whole-genome data analyses that porphyrin overdrive is linked to oncogenic states and cellular differentiation. Although porphyrin overdrive is absent in differentiated cells or somatic stem cells, it is present in patient-derived tumor progenitor cells, demonstrated by single-cell RNAseq, and in early embryogenesis. In conclusion, we identified a dependence of cancer cells on non-homeostatic heme metabolism, and we targeted this cancer metabolic vulnerability with a novel "bait-and-kill" strategy to eradicate malignant cells.

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.

Structure-guided discovery of highly efficient cytidine deaminases with sequence-context independence

The applicability of cytosine base editors is hindered by their dependence on sequence context and by off-target effects. Here, by using AlphaFold2 to predict the three-dimensional structure of 1,483 cytidine deaminases and by experimentally characterizing representative deaminases (selected from each structural cluster after categorizing them via partitional clustering), we report the discovery of a few deaminases with high editing efficiencies, diverse editing windows and increased ratios of on-target to off-target effects. Specifically, several deaminases induced C-to-T conversions with comparable efficiency at AC/TC/CC/GC sites, the deaminases could introduce stop codons in single-copy and multi-copy genes in mammalian cells without double-strand breaks, and some residue conversions at predicted DNA-interacting sites reduced off-target effects. Structure-based generative machine learning could be further leveraged to expand the applicability of base editors in gene therapies.

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.

Bidirectional epigenetic editing reveals hierarchies in gene regulation

CRISPR perturbation methods are limited in their ability to study non-coding elements and genetic interactions. In this study, we developed a system for bidirectional epigenetic editing, called CRISPRai, in which we apply activating (CRISPRa) and repressive (CRISPRi) perturbations to two loci simultaneously in the same cell. We developed CRISPRai Perturb-seq by coupling dual perturbation gRNA detection with single-cell RNA sequencing, enabling study of pooled perturbations in a mixed single-cell population. We applied this platform to study the genetic interaction between two hematopoietic lineage transcription factors, SPI1 and GATA1, and discovered novel characteristics of their co-regulation on downstream target genes, including differences in SPI1 and GATA1 occupancy at genes that are regulated through different modes. We also studied the regulatory landscape of IL2 (interleukin-2) in Jurkat T cells, primary T cells and chimeric antigen receptor (CAR) T cells and elucidated mechanisms of enhancer-mediated IL2 gene regulation. CRISPRai facilitates investigation of context-specific genetic interactions, provides new insights into gene regulation and will enable exploration of non-coding disease-associated variants.

Engineered CRISPR-Cas12a for higher-order combinatorial chromatin perturbations

Multiplexed genetic perturbations are critical for testing functional interactions among coding or non-coding genetic elements. Compared to double-stranded DNA cutting, repressive chromatin formation using CRISPR interference (CRISPRi) avoids genotoxicity and is more effective for perturbing non-coding regulatory elements in pooled assays. However, current CRISPRi pooled screening approaches are limited to targeting one to three genomic sites per cell. We engineer an Acidaminococcus Cas12a (AsCas12a) variant, multiplexed transcriptional interference AsCas12a (multiAsCas12a), that incorporates R1226A, a mutation that stabilizes the ribonucleoprotein-DNA complex via DNA nicking. The multiAsCas12a-KRAB fusion improves CRISPRi activity over DNase-dead AsCas12a-KRAB fusions, often rescuing the activities of lentivirally delivered CRISPR RNAs (crRNA) that are inactive when used with the latter. multiAsCas12a-KRAB supports CRISPRi using 6-plex crRNA arrays in high-throughput pooled screens. Using multiAsCas12a-KRAB, we discover enhancer elements and dissect the combinatorial function of cis-regulatory elements in human cells. These results instantiate a group testing framework for efficiently surveying numerous combinations of chromatin perturbations for biological discovery and engineering.

How CRISPR Is Revolutionizing the Generation of New Models for Cancer Research

Cancers arise through acquisition of mutations in genes that regulate core biological processes like cell proliferation and cell death. Decades of cancer research have led to the identification of genes and mutations causally involved in disease development and evolution, yet defining their precise function across different cancer types and how they influence therapy responses has been challenging. Mouse models have helped define the in vivo function of cancer-associated alterations, and genome-editing approaches using CRISPR have dramatically accelerated the pace at which these models are developed and studied. Here, we highlight how CRISPR technologies have impacted the development and use of mouse models for cancer research and discuss the many ways in which these rapidly evolving platforms will continue to transform our understanding of this disease.

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

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

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.

Deconstructing cancer with precision genome editing

Recent advances in genome editing technologies are allowing investigators to engineer and study cancer-associated mutations in their endogenous genetic contexts with high precision and efficiency. Of these, base editing and prime editing are quickly becoming gold-standards in the field due to their versatility and scalability. Here, we review the merits and limitations of these precision genome editing technologies, their application to modern cancer research, and speculate how these could be integrated to address future directions in the field.

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.

Higher-order combinatorial chromatin perturbations by engineered CRISPR-Cas12a for functional genomics

Multiplexed genetic perturbations are critical for testing functional interactions among coding or non-coding genetic elements. Compared to double-stranded DNA cutting, repressive chromatin formation using CRISPR interference (CRISPRi) avoids genotoxicity and is more effective for perturbing non-coding regulatory elements in pooled assays. However, current CRISPRi pooled screening approaches are limited to targeting 1-3 genomic sites per cell. To develop a tool for higher-order ( > 3) combinatorial targeting of genomic sites with CRISPRi in functional genomics screens, we engineered an Acidaminococcus Cas12a variant -- referred to as mul tiplexed transcriptional interference AsCas12a (multiAsCas12a). multiAsCas12a incorporates a key mutation, R1226A, motivated by the hypothesis of nicking-induced stabilization of the ribonucleoprotein:DNA complex for improving CRISPRi activity. multiAsCas12a significantly outperforms prior state-of-the-art Cas12a variants in combinatorial CRISPRi targeting using high-order multiplexed arrays of lentivirally transduced CRISPR RNAs (crRNA), including in high-throughput pooled screens using 6-plex crRNA array libraries. Using multiAsCas12a CRISPRi, we discover new enhancer elements and dissect the combinatorial function of cis-regulatory elements. These results instantiate a group testing framework for efficiently surveying potentially numerous combinations of chromatin perturbations for biological discovery and engineering.

A refined Uni-vector prime editing system improves genome editing outcomes in mammalian cells

Prime editing is an advanced technology in CRISPR/Cas research with increasing numbers of improved methodologies. The original multi-vector method hampers the efficiency and precision of prime editing and also has inherent difficulty in generating homozygous mutations in mammalian cells. To overcome these technical issues, we developed a Uni-vector prime editing system, wherein the major components for prime editing were constructed in all-in-one plasmids, pPE3-pPuro and pePEmax-pPuro. The Uni-vector prime editing plasmids enhance the editing efficiency of prime editing and improved the generation of homozygous mutated mammalian cell lines. The editing efficiency is dependent of the transfection efficiency. Remarkably, the Uni-vector ePE5max system achieved an impressive editing rate approximately 79% in average, even in cell lines that are traditionally difficult to transfect, such as FaDu cell line. Furthermore, it resulted in a high frequency of homozygous knocked-in cells, with a rate of 99% in HeLa and 85% in FaDu cells. Together, our Uni-vector approach simplifies the delivery of editing components and improves the editing efficiency, especially in cells with low transfection efficiency. This approach presents an advancement in the field of prime editing.

Intrinsic deletion at 10q23.31, including the PTEN gene locus, is aggravated upon CRISPR-Cas9-mediated genome engineering in HAP1 cells mimicking cancer profiles

The CRISPR-Cas9 system is a powerful tool for studying gene functions and holds potential for disease treatment. However, precise genome editing requires thorough assessments to minimize unintended on- and off-target effects. Here, we report an unexpected 283-kb deletion on Chromosome 10 (10q23.31) in chronic myelogenous leukemia-derived HAP1 cells, which are frequently used in CRISPR screens. The deleted region encodes regulatory genes, including PAPSS2, ATAD1, KLLN, and PTEN We found that this deletion was not a direct consequence of CRISPR-Cas9 off-targeting but rather occurred frequently during the generation of CRISPR-Cas9-modified cells. The deletion was associated with global changes in histone acetylation and gene expression, affecting fundamental cellular processes such as cell cycle and DNA replication. We detected this deletion in cancer patient genomes. As in HAP1 cells, the deletion contributed to similar gene expression patterns among cancer patients despite interindividual differences. Our findings suggest that the unintended deletion of 10q23.31 can confound CRISPR-Cas9 studies and underscore the importance to assess unintended genomic changes in CRISPR-Cas9-modified cells, which could impact cancer research.

A scalable platform for efficient CRISPR-Cas9 chemical-genetic screens of DNA damage-inducing compounds

Current approaches to define chemical-genetic interactions (CGIs) in human cell lines are resource-intensive. We designed a scalable chemical-genetic screening platform by generating a DNA damage response (DDR)-focused custom sgRNA library targeting 1011 genes with 3033 sgRNAs. We performed five proof-of-principle compound screens and found that the compounds' known modes-of-action (MoA) were enriched among the compounds' CGIs. These scalable screens recapitulated expected CGIs at a comparable signal-to-noise ratio (SNR) relative to genome-wide screens. Furthermore, time-resolved CGIs, captured by sequencing screens at various time points, suggested an unexpected, late interstrand-crosslinking (ICL) repair pathway response to camptothecin-induced DNA damage. Our approach can facilitate screening compounds at scale with 20-fold fewer resources than commonly used genome-wide libraries and produce biologically informative CGI profiles.

Chromosome 7 to the rescue: overcoming chromosome 10 loss in gliomas

The co-occurrence of chromosome 10 loss and chromosome 7 gain in gliomas is the most frequent loss-gain co-aneuploidy pair in human cancers, a phenomenon that has been investigated without resolution since the late 1980s. Expanding beyond previous gene-centric studies, we investigate the co-occurrence in a genome-wide manner taking an evolutionary perspective. First, by mining large tumor aneuploidy data, we predict that the more likely order is 10 loss followed by 7 gain. Second, by analyzing extensive genomic and transcriptomic data from both patients and cell lines, we find that this co-occurrence can be explained by functional rescue interactions that are highly enriched on 7, which can possibly compensate for any detrimental consequences arising from the loss of 10. Finally, by analyzing transcriptomic data from normal, non-cancerous, human brain tissues, we provide a plausible reason why this co-occurrence happens preferentially in cancers originating in certain regions of the brain.

A robust and inducible precise genome editing via an all-in-one prime editor in human pluripotent stem cells

Prime editing (PE) allows for precise genome editing in human pluripotent stem cells (hPSCs), such as introducing single nucleotide modifications, small deletions, or insertions at a specific genomic locus, a strategy that shows great promise for creating "Disease in a dish" models. To improve the effectiveness of prime editing in hPSCs, we systematically compared and combined the "inhibition of mismatch repair pathway and p53" on top of the "PEmax" to generate an all-in-one "PE-Plus" prime editor. We show that PE-Plus conducts the most efficient editing among the current PE tools in hPSCs. We further established an inducible prime editing platform in hPSCs by incorporating the all-in-one PE vector into a safe-harbor locus and demonstrated temporal control of precise editing in both hPSCs and differentiated cells. By evaluating disease-associated mutations, we show that this platform allows efficient creation of both monoallelic and biallelic disease-relevant mutations in hPSCs. In addition, this platform enables the efficient introduction of single or multiple edits in one step, demonstrating potential for multiplex editing. Therefore, our method presents an efficient and controllable multiplex prime editing tool in hPSCs and their differentiated progeny.

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.

CRISPR-Cas9 Gene Editing: Curing Genetic Diseases by Inherited Epigenetic Modifications

Introduction  CRISPR-Cas9 gene editing, leveraging bacterial defense mechanisms, offers precise DNA modifications, holding promise in curing genetic diseases. This review critically assesses its potential, analyzing evidence on therapeutic applications, challenges, and future prospects. Examining diverse genetic disorders, it evaluates efficacy, safety, and limitations, emphasizing the need for a thorough understanding among medical professionals and researchers. Acknowledging its transformative impact, a systematic review is crucial for informed decision-making, responsible utilization, and guiding future research to unlock CRISPR-Cas9's full potential in realizing the cure for genetic diseases. Methods  A comprehensive literature search across PubMed, Scopus, and the Web of Science identified studies applying CRISPR-Cas9 gene editing for genetic diseases, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Inclusion criteria covered in vitro and in vivo models targeting various genetic diseases with reported outcomes on disease modification or potential cure. Quality assessment revealed a generally moderate to high risk of bias. Heterogeneity prevented quantitative meta-analysis, prompting a narrative synthesis of findings. Discussion  CRISPR-Cas9 enables precise gene editing, correcting disease-causing mutations and offering hope for previously incurable genetic conditions. Leveraging inherited epigenetic modifications, it not only fixes mutations but also restores normal gene function and controls gene expression. The transformative potential of CRISPR-Cas9 holds promise for personalized treatments, improving therapeutic outcomes, but ethical considerations and safety concerns must be rigorously addressed to ensure responsible and safe application, especially in germline editing with potential long-term implications.

Untangling the Context-Specificity of Essential Genes by Means of Machine Learning: A Constructive Experience

Gene essentiality is a genetic concept crucial for a comprehensive understanding of life and evolution. In the last decade, many essential genes (EGs) have been determined using different experimental and computational approaches, and this information has been used to reduce the genomes of model organisms. A growing amount of evidence highlights that essentiality is a property that depends on the context. Because of their importance in vital biological processes, recognising context-specific EGs (csEGs) could help for identifying new potential pharmacological targets and to improve precision therapeutics. Since most of the computational procedures proposed to identify and predict EGs neglect their context-specificity, we focused on this aspect, providing a theoretical and experimental overview of the literature, data and computational methods dedicated to recognising csEGs. To this end, we adapted existing computational methods to exploit a specific context (the kidney tissue) and experimented with four different prediction methods using the labels provided by four different identification approaches. The considerations derived from the analysis of the obtained results, confirmed and validated also by further experiments for a different tissue context, provide the reader with guidance on exploiting existing tools for achieving csEGs identification and prediction.

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.

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.

Landscape of enhancer disruption and functional screen in melanoma cells

BACKGROUND

The high mutation rate throughout the entire melanoma genome presents a major challenge in stratifying true driver events from the background mutations. Numerous recurrent non-coding alterations, such as those in enhancers, can shape tumor evolution, thereby emphasizing the importance in systematically deciphering enhancer disruptions in melanoma.

RESULTS

Here, we leveraged 297 melanoma whole-genome sequencing samples to prioritize highly recurrent regions. By performing a genome-scale CRISPR interference (CRISPRi) screen on highly recurrent region-associated enhancers in melanoma cells, we identified 66 significant hits which could have tumor-suppressive roles. These functional enhancers show unique mutational patterns independent of classical significantly mutated genes in melanoma. Target gene analysis for the essential enhancers reveal many known and hidden mechanisms underlying melanoma growth. Utilizing extensive functional validation experiments, we demonstrate that a super enhancer element could modulate melanoma cell proliferation by targeting MEF2A, and another distal enhancer is able to sustain PTEN tumor-suppressive potential via long-range interactions.

CONCLUSIONS

Our study establishes a catalogue of crucial enhancers and their target genes in melanoma growth and progression, and illuminates the identification of novel mechanisms of dysregulation for melanoma driver genes and new therapeutic targeting strategies.

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.

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.

A Druggable FOXA1-Glucocorticoid Receptor Transcriptional Axis Drives Tumor Growth in a Subset of Non-Small Cell Lung Cancer

The FOXA1 pioneer factor is an essential mediator of steroid receptor function in multiple hormone-dependent cancers, including breast and prostate cancers, enabling nuclear receptors such as estrogen receptor (ER) and androgen receptor (AR) to activate lineage-specific growth programs. FOXA1 is also highly expressed in non-small cell lung cancer (NSCLC), but whether and how it regulates tumor growth in this context is not known. Analyzing data from loss-of-function screens, we identified a subset of NSCLC tumor lines where proliferation is FOXA1 dependent. Using rapid immunoprecipitation and mass spectrometry of endogenous protein, we identified chromatin-localized interactions between FOXA1 and glucocorticoid receptor (GR) in these tumor cells. Knockdown of GR inhibited proliferation of FOXA1-dependent, but not FOXA1-independent NSCLC cells. In these FOXA1-dependent models, FOXA1 and GR cooperate to regulate gene targets involved in EGF signaling and G1-S cell-cycle progression. To investigate the therapeutic potential for targeting this complex, we examined the effects of highly selective inhibitors of the GR ligand-binding pocket and found that GR antagonism with ORIC-101 suppressed FOXA1/GR target expression, activation of EGF signaling, entry into the S-phase, and attendant proliferation in vitro and in vivo. Taken together, our findings point to a subset of NSCLCs harboring a dependence on the FOXA1/GR growth program and provide rationale for its therapeutic targeting.

Significance

NSCLC is the leading cause of cancer deaths worldwide. There is a need to identify novel druggable dependencies. We identify a subset of NSCLCs dependent on FOXA1-GR and sensitive to GR antagonism.

Flourishing tumor organoids: History, emerging technology, and application

Malignant tumors are one of the leading causes of death which impose an increasingly heavy burden on all countries. Therefore, the establishment of research models that closely resemble original tumor characteristics is crucial to further understanding the mechanisms of malignant tumor development, developing safer and more effective drugs, and formulating personalized treatment plans. Recently, organoids have been widely used in tumor research owing to their advantages including preserving the structure, heterogeneity, and cellular functions of the original tumor, together with the ease of manipulation. This review describes the history and characteristics of tumor organoids and the synergistic combination of three-dimensional (3D) culture approaches for tumor organoids with emerging technologies, including tissue-engineered cell scaffolds, microfluidic devices, 3D bioprinting, rotating wall vessels, and clustered regularly interspaced short palindromic repeats-CRISPR-associated protein 9 (CRISPR-Cas9). Additionally, the progress in research and the applications in basic and clinical research of tumor organoid models are summarized. This includes studies of the mechanism of tumor development, drug development and screening, precision medicine, immunotherapy, and simulation of the tumor microenvironment. Finally, the existing shortcomings of tumor organoids and possible future directions are discussed.

Genome-guided discovery of cancer therapeutic targets

The success of precision oncology-which aims to match the right therapies to the right patients based on molecular status-is predicated on a robust pipeline of molecular targets against which therapies can be developed. Recent advances in genomics and functional genetics have enabled the unbiased discovery of novel molecular targets at scale. We summarize the promise and challenges in integrating genomic and functional genetic landscapes of cancer to establish the next generation of cancer targets.

GATA2 co-opts TGFβ1/SMAD4 oncogenic signaling and inherited variants at 6q22 to modulate prostate cancer progression

BACKGROUND

Aberrant somatic genomic alteration including copy number amplification is a hallmark of cancer genomes. We previously profiled genomic landscapes of prostate cancer (PCa), yet the underlying causal genes with prognostic potential has not been defined. It remains unclear how a somatic genomic event cooperates with inherited germline variants contribute to cancer predisposition and progression.

METHODS

We applied integrated genomic and clinical data, experimental models and bioinformatic analysis to identify GATA2 as a highly prevalent metastasis-associated genomic amplification in PCa. Biological roles of GATA2 in PCa metastasis was determined in vitro and in vivo. Global chromatin co-occupancy and co-regulation of GATA2 and SMAD4 was investigated by coimmunoprecipitation, ChIP-seq and RNA-seq assays. Tumor cellular assays, qRT-PCR, western blot, ChIP, luciferase assays and CRISPR-Cas9 editing methods were performed to mechanistically understand the cooperation of GATA2 with SMAD4 in promoting TGFβ1 and AR signaling and mediating inherited PCa risk and progression.

RESULTS

In this study, by integrated genomics and experimental analysis, we identified GATA2 as a prevalent metastasis-associated genomic amplification to transcriptionally augment its own expression in PCa. Functional experiments demonstrated that GATA2 physically interacted and cooperated with SMAD4 for genome-wide chromatin co-occupancy and co-regulation of PCa genes and metastasis pathways like TGFβ signaling. Mechanistically, GATA2 was cooperative with SMAD4 to enhance TGFβ and AR signaling pathways, and activated the expression of TGFβ1 via directly binding to a distal enhancer of TGFβ1. Strinkingly, GATA2 and SMAD4 globally mediated inherited PCa risk and formed a transcriptional complex with HOXB13 at the PCa risk-associated rs339331/6q22 enhancer, leading to increased expression of the PCa susceptibility gene RFX6.

CONCLUSIONS

Our study prioritizes causal genomic amplification genes with prognostic values in PCa and reveals the pivotal roles of GATA2 in transcriptionally activating the expression of its own and TGFβ1, thereby co-opting to TGFβ1/SMAD4 signaling and RFX6 at 6q22 to modulate PCa predisposition and progression.

Comprehensive spatiotemporal mapping of single-cell lineages in developing mouse brain by CRISPR-based barcoding

A fundamental interest in developmental neuroscience lies in the ability to map the complete single-cell lineages within the brain. To this end, we developed a CRISPR editing-based lineage-specific tracing (CREST) method for clonal tracing in Cre mice. We then used two complementary strategies based on CREST to map single-cell lineages in developing mouse ventral midbrain (vMB). By applying snapshotting CREST (snapCREST), we constructed a spatiotemporal lineage landscape of developing vMB and identified six progenitor archetypes that could represent the principal clonal fates of individual vMB progenitors and three distinct clonal lineages in the floor plate that specified glutamatergic, dopaminergic or both neurons. We further created pandaCREST (progenitor and derivative associating CREST) to associate the transcriptomes of progenitor cells in vivo with their differentiation potentials. We identified multiple origins of dopaminergic neurons and demonstrated that a transcriptome-defined progenitor type comprises heterogeneous progenitors, each with distinct clonal fates and molecular signatures. Therefore, the CREST method and strategies allow comprehensive single-cell lineage analysis that could offer new insights into the molecular programs underlying neural specification.

PE-STOP: A versatile tool for installing nonsense substitutions amenable for precise reversion

The rapid advances in genome editing technologies have revolutionized the study of gene functions in cell or animal models. The recent generation of double-stranded DNA cleavage-independent base editors has been suitably adapted for interrogation of protein-coding genes on the basis of introducing premature stop codons or disabling the start codons. However, such versions of stop/start codon-oriented genetic tools still present limitations on their versatility, base-level precision, and target specificity. Here, we exploit a newly developed prime editor (PE) that differs from base editors by its adoption of a reverse transcriptase activity, which enables incorporation of various types of precise edits templated by a specialized prime editing guide RNA. Based on such a versatile platform, we established a prime editing-empowered method (PE-STOP) for installation of nonsense substitutions, providing a complementary approach to the present gene-targeting tools. PE-STOP is bioinformatically predicted to feature substantially expanded coverage in the genome space. In practice, PE-STOP introduces stop codons with good efficiencies in human embryonic kidney 293T and N2a cells (with medians of 29% [ten sites] and 25% [four sites] editing efficiencies, respectively), while exhibiting minimal off-target effects and high on-target precision. Furthermore, given the fact that PE installs prime editing guide RNA-templated mutations, we introduce a unique strategy for precise genetic rescue of PE-STOP-dependent nonsense mutation via the same PE platform. Altogether, the present work demonstrates a versatile and specific tool for gene inactivation and for functional interrogation of nonsense mutations.

Microtubule Dynamics Deregulation Induces Apoptosis in Human Urothelial Bladder Cancer Cells via a p53-Independent Pathway

Bladder cancer (BLCA) is the sixth most common type of cancer and has a dismal prognosis if diagnosed late. To identify treatment options for BLCA, we systematically evaluated data from the Broad Institute DepMap project. We found that urothelial BLCA cell lines are among the most sensitive to microtubule assembly inhibition by paclitaxel treatment. Strikingly, we revealed that the top dependencies in BLCA cell lines include genes encoding proteins involved in microtubule assembly. This highlights the importance of microtubule network dynamics as a major vulnerability in human BLCA. In cancers such as ovarian and breast, where paclitaxel is the gold standard of care, resistance to paclitaxel treatment has been linked to p53-inactivating mutations. To study the response of BLCA to microtubule assembly inhibition and its mechanistic link with the mutational status of the p53 protein, we treated a collection of BLCA cell lines with a dose range of paclitaxel and performed a detailed characterization of the response. We discovered that BLCA cell lines are significantly sensitive to low concentrations of paclitaxel, independently of their p53 status. Paclitaxel induced a G2/M cell cycle arrest and growth inhibition, followed by robust activation of apoptosis. Most importantly, we revealed that paclitaxel triggered a robust DNA-damage response and apoptosis program without activating the p53 pathway. Integration of transcriptomics, epigenetic, and dependency data demonstrated that the response of BLCA to paclitaxel is independent of p53 mutational signatures but strongly depends on the expression of DNA repair genes. Our work highlights urothelial BLCA as an exceptional candidate for paclitaxel treatment. It paves the way for the rational use of a combination of paclitaxel and DNA repair inhibitors as an effective, novel therapeutic strategy.

Tumour mutations in long noncoding RNAs enhance cell fitness

Long noncoding RNAs (lncRNAs) are linked to cancer via pathogenic changes in their expression levels. Yet, it remains unclear whether lncRNAs can also impact tumour cell fitness via function-altering somatic "driver" mutations. To search for such driver-lncRNAs, we here perform a genome-wide analysis of fitness-altering single nucleotide variants (SNVs) across a cohort of 2583 primary and 3527 metastatic tumours. The resulting 54 mutated and positively-selected lncRNAs are significantly enriched for previously-reported cancer genes and a range of clinical and genomic features. A number of these lncRNAs promote tumour cell proliferation when overexpressed in in vitro models. Our results also highlight a dense SNV hotspot in the widely-studied NEAT1 oncogene. To directly evaluate the functional significance of NEAT1 SNVs, we use in cellulo mutagenesis to introduce tumour-like mutations in the gene and observe a significant and reproducible increase in cell fitness, both in vitro and in a mouse model. Mechanistic studies reveal that SNVs remodel the NEAT1 ribonucleoprotein and boost subnuclear paraspeckles. In summary, this work demonstrates the utility of driver analysis for mapping cancer-promoting lncRNAs, and provides experimental evidence that somatic mutations can act through lncRNAs to enhance pathological cancer cell fitness.

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.

Overcoming Multidrug Resistance by Base-Editing-Induced Codon Mutation

Multidrug resistance (MDR) is the main obstacle in cancer chemotherapy. ATP binding cassette (ABC) transporters on the MDR cell membrane can transport a wide range of antitumor drugs out of cells, which is one of the main causes of MDR. Therefore, disturbing ABC transporters becomes the key to reversing MDR. In this study, we implement a cytosine base editor (CBE) system to knock out the gene encoding ABC transporters by base editing. When the CBE system works in MDR cells, the MDR cells are manipulated, and the genes encoding ABC transporters can be inactivated by precisely changing single in-frame nucleotides to induce stop (iSTOP) codons. In this way, the expression of ABC efflux transporters is reduced and intracellular drug retention is significantly increased in MDR cells. Ultimately, the drug shows considerable cytotoxicity to the MDR cancer cells. Moreover, the substantial downregulation of P-glycoprotein (P-gp) and breast cancer resistance protein (BCRP) implies the successful application of the CBE system in the knockout of different ABC efflux transporters. The recovery of chemosensitivity of MDR cancer cells to the chemotherapeutic drugs revealed that the system has a satisfactory universality and applicability. We believe that the CBE system will provide valuable clues for the use of CRISPR technology to defeat the MDR of cancer cells.

KLIPP - a precision CRISPR approach to target structural variant junctions in cancer

Current cancer therapies typically give rise to dose-limiting normal tissue toxicity. We have developed KLIPP, a precision cancer approach that specifically kills cancer cells using CRISPR/Cas9 technology. The approach consists of guide RNAs that target cancer-specific structural variant junctions to nucleate two parts of a dCas9-conjugated endonuclease, Fok1, leading to its activation. We show that KLIPP causes induction of DNA double strand breaks (DSBs) at the targeted junctions and cell death. When cancer cells were grown orthotopically in mice, activation of Fok1 at only two junctions led to the disappearance of tumor cells in 7/11 mice. This therapeutic approach has high specificity for tumor cells and is independent of tumor-specific drivers. Individualized translation of KLIPP to patients would be transformative and lead to consistent and simplified cancer treatment decisions.

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.

Mapping the landscape of genetic dependencies in chordoma

Identifying the spectrum of genes required for cancer cell survival can reveal essential cancer circuitry and therapeutic targets, but such a map remains incomplete for many cancer types. We apply genome-scale CRISPR-Cas9 loss-of-function screens to map the landscape of selectively essential genes in chordoma, a bone cancer with few validated targets. This approach confirms a known chordoma dependency, TBXT (T; brachyury), and identifies a range of additional dependencies, including PTPN11, ADAR, PRKRA, LUC7L2, SRRM2, SLC2A1, SLC7A5, FANCM, and THAP1. CDK6, SOX9, and EGFR, genes previously implicated in chordoma biology, are also recovered. We find genomic and transcriptomic features that predict specific dependencies, including interferon-stimulated gene expression, which correlates with ADAR dependence and is elevated in chordoma. Validating the therapeutic relevance of dependencies, small-molecule inhibitors of SHP2, encoded by PTPN11, have potent preclinical efficacy against chordoma. Our results generate an emerging map of chordoma dependencies to enable biological and therapeutic hypotheses.

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.

Optimized whole-genome CRISPR interference screens identify ARID1A-dependent growth regulators in human induced pluripotent stem cells

Perturbing expression is a powerful way to understand the role of individual genes, but can be challenging in important models. CRISPR-Cas screens in human induced pluripotent stem cells (iPSCs) are of limited efficiency due to DNA break-induced stress, while the less stressful silencing with an inactive Cas9 has been considered less effective so far. Here, we developed the dCas9-KRAB-MeCP2 fusion protein for screening in iPSCs from multiple donors. We found silencing in a 200 bp window around the transcription start site in polyclonal pools to be as effective as using wild-type Cas9 for identifying essential genes, but with much reduced cell numbers. Whole-genome screens to identify ARID1A-dependent dosage sensitivity revealed the PSMB2 gene, and enrichment of proteasome genes among the hits. This selective dependency was replicated with a proteasome inhibitor, indicating a targetable drug-gene interaction. Many more plausible targets in challenging cell models can be efficiently identified with our approach.