Identification of oncogenic driver mutations by genome-wide CRISPR-Cas9 dropout screening (original) (raw)
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A systematic genome-wide mapping of oncogenic mutation selection during CRISPR-Cas9 genome editing
Nature Communications
Recent studies have reported that genome editing by CRISPR–Cas9 induces a DNA damage response mediated by p53 in primary cells hampering their growth. This could lead to a selection of cells with pre-existing p53 mutations. In this study, employing an integrated computational and experimental framework, we systematically investigated the possibility of selection of additional cancer driver mutations during CRISPR-Cas9 gene editing. We first confirm the previous findings of the selection for pre-existing p53 mutations by CRISPR-Cas9. We next demonstrate that similar to p53, wildtype KRAS may also hamper the growth of Cas9-edited cells, potentially conferring a selective advantage to pre-existing KRAS-mutant cells. These selective effects are widespread, extending across cell-types and methods of CRISPR-Cas9 delivery and the strength of selection depends on the sgRNA sequence and the gene being edited. The selection for pre-existing p53 or KRAS mutations may confound CRISPR-Cas9 scree...
Genome-wide CRISPR screening reveals genetic modifiers of mutant EGFR dependence in human NSCLC
eLife, 2019
EGFR-mutant NSCLCs frequently respond to EGFR tyrosine kinase inhibitors (TKIs). However, the responses are not durable, and the magnitude of tumor regression is variable, suggesting the existence of genetic modifiers of EGFR dependency. Here, we applied a genome-wide CRISPR-Cas9 screening to identify genetic determinants of EGFR TKI sensitivity and uncovered putative candidates. We show that knockout of RIC8A, essential for G-alpha protein activation, enhanced EGFR TKI-induced cell death. Mechanistically, we demonstrate that RIC8A is a positive regulator of YAP signaling, activation of which rescued the EGFR TKI sensitizing phenotype resulting from RIC8A knockout. We also show that knockout of ARIH2, or other components in the Cullin-5 E3 complex, conferred resistance to EGFR inhibition, in part by promoting nascent protein synthesis through METAP2. Together, these data uncover a spectrum of previously unidentified regulators of EGFR TKI sensitivity in EGFR-mutant human NSCLC, prov...
Cancer discovery, 2016
CRISPR/Cas9 has emerged as a powerful new tool to systematically probe gene function. In this study, we compare the performance of CRISPR to RNAi-based loss-of-function screens for the identification of cancer dependencies by performing parallel deep-coverage shRNA and CRISPR screens targeting 2722 genes across several cancer cell lines. CRISPR-based dropout screens identified more lethal genes compared to RNAi in all five cancer models, indicating that the identification of many cellular dependencies may require full gene inactivation, as induced by CRISPR but not RNAi. However, in two aneuploid cancer models we found that all genes within highly amplified regions, including non-expressed genes, scored as lethal by CRISPR, revealing an unanticipated class of false-positive hits in CRISPR-based screens. Using a CRISPR tiling array that encompassed all possible sgRNAs against the coding regions of 139 genes, we found that sgRNAs targeting essential domains provide the most robust dro...
Prioritisation of oncology therapeutic targets using CRISPR-Cas9 screening
2018
SummaryFunctional genomics approaches can overcome current limitations that hamper oncology drug development such as lack of robust target identification and clinical efficacy. Here we performed genome-scale CRISPR-Cas9 screens in 204 human cancer cell lines from 12 cancer-types and developed a data-driven framework to prioritise cancer therapeutic candidates. We integrated gene cell fitness effects with genomic biomarkers and target tractability for drug development to systematically prioritise new oncology targets in defined tissues and genotypes. Furthermore, we took one of our most promising dependencies, Werner syndrome RecQ helicase, and verified it as a candidate target for tumours with microsatellite instability. Our analysis provides a comprehensive resource of cancer dependencies, a framework to prioritise oncology targets, and nominates specific new candidates. The principles described in this study can transform the initial stages of the drug development process contribu...
Specific targeting of point mutations in EGFR L858R-positive lung cancer by CRISPR/Cas9
Laboratory investigation; a journal of technical methods and pathology, 2018
Cancer cells are defined genetically by the mutations they harbor, commonly single nucleotide substitutions. Therapeutic approaches which specifically target cancer cells by recognizing these defining genetic aberrations are expected to exhibit minimal side-effects. However, current protein-based targeted therapy is greatly limited by the range of genes that can be targeted, as well as by acquired resistance. We hypothesized that a therapeutic oligonucleotide-based strategy may address this need of specific cancer targeting. We used CRISPR/Cas9 system to target a commonly occurring EGFR point mutation, L858R, with an oligonucleotide guide that recognizes L858R as the suitable protospacer-adjacent motif (PAM) sequence for DNA cleavage. We found that this strategy, which utilized PAM to differentiate cancer mutation from normal, afforded high specificity to the extent of a single nucleotide substitution. The anti-L858R vehicle resulted in selective genome cleavage only in L858R mutant...
Unsupervised correction of gene-independent cell responses to CRISPR-Cas9 targeting
BMC Genomics, 2018
Background: Genome editing by CRISPR-Cas9 technology allows large-scale screening of gene essentiality in cancer. A confounding factor when interpreting CRISPR-Cas9 screens is the high false-positive rate in detecting essential genes within copy number amplified regions of the genome. We have developed the computational tool CRISPRcleanR which is capable of identifying and correcting gene-independent responses to CRISPR-Cas9 targeting. CRISPRcleanR uses an unsupervised approach based on the segmentation of single-guide RNA fold change values across the genome, without making any assumption about the copy number status of the targeted genes. Results: Applying our method to existing and newly generated genome-wide essentiality profiles from 15 cancer cell lines, we demonstrate that CRISPRcleanR reduces false positives when calling essential genes, correcting biases within and outside of amplified regions, while maintaining true positive rates. Established cancer dependencies and essentiality signals of amplified cancer driver genes are detectable post-correction. CRISPRcleanR reports sgRNA fold changes and normalised read counts, is therefore compatible with downstream analysis tools, and works with multiple sgRNA libraries. Conclusions: CRISPRcleanR is a versatile open-source tool for the analysis of CRISPR-Cas9 knockout screens to identify essential genes.
Evaluation and Design of Genome-wide CRISPR/Cas9 Knockout Screens
2017
The adaptation of CRISPR/Cas9 technology to mammalian cell lines is transforming the study of human functional genomics. Pooled libraries of CRISPR guide RNAs (gRNAs), targeting human protein-coding genes and encoded in viral vectors, have been used to systematically create gene knockouts in a variety of human cancer and immortalized cell lines, in an effort to identify whether these knockouts cause cellular fitness defects. Previous work has shown that CRISPR screens are more sensitive and specific than pooled library shRNA screens in similar assays, but currently there exists significant variability across CRISPR library designs and experimental protocols. In this study, we re-analyze 17 genome-scale knockout screens in human cell lines from three research groups using three different genome-scale gRNA libraries, using the Bayesian Analysis of Gene Essentiality (BAGEL) algorithm to identify essential genes, to refine and expand our previously defined set of human core essential ge...
CSC software corrects off-target mediated gRNA depletion in CRISPR-Cas9 essentiality screens
Nature Communications, 2021
Off-target effects are well established confounders of CRISPR negative selection screens that impair the identification of essential genomic loci. In particular, non-coding regulatory elements and repetitive regions are often difficult to target with specific gRNAs, effectively precluding the unbiased screening of a large portion of the genome. To address this, we developed CRISPR Specificity Correction (CSC), a computational method that corrects for the effect of off-targeting on gRNA depletion. We benchmark CSC with data from the Cancer Dependency Map and show that it significantly improves the overall sensitivity and specificity of viability screens while preserving known essentialities, particularly for genes targeted by highly promiscuous gRNAs. We believe this tool will further enable the functional annotation of the genome as it represents a robust alternative to the traditional filtering strategy of discarding unspecific guides from the analysis. CSC is an open-source softwa...
A CRISPR/Cas9 Functional Screen Identifies Rare Tumor Suppressors
Scientific Reports, 2016
An enormous amount of tumor sequencing data has been generated through large scale sequencing efforts. The functional consequences of the majority of mutations identified by such projects remain an open, unexplored question. This problem is particularly complicated in the case of rare mutations where frequency of occurrence alone or prediction of functional consequences are insufficient to distinguish driver from passenger or bystander mutations. We combine genome editing technology with a powerful mouse cancer model to uncover previously unsuspected rare oncogenic mutations in Burkitt’s lymphoma. We identify two candidate tumor suppressors whose loss cooperate with MYC over-expression to accelerate lymphomagenesis. Our results highlight the utility of in vivo CRISPR/Cas9 screens combined with powerful mouse models to identify and validate rare oncogenic modifier events from tumor mutational data.