scholarly journals Genome scale CRISPR Cas9a knockout screen reveals genes that controls glioblastoma susceptibility to the alkylating agent temozolomide

2021 ◽  
Author(s):  
Chidiebere U Awah ◽  
Jan Winter ◽  
Olorunseun Ogunwobi

Glioblastoma is the most fatal of all primary human brain tumors with 14 months survival, at best. The mainstay therapy for this tumor involves temozolomide, surgery, radiotherapy and tumor treating electric field. Cancer resistance to commonly available chemotherapeutics remains a major challenge in glioblastoma patients receiving treatment and unfavorably impact their overall survival and outcome. However, the lack of progress in this area could be attributed to lack of tools to probe unbiasedly at the genome wide level the coding and non-coding elements contribution on a large scale for factors that control resistance to chemotherapeutics. Understanding the mechanisms of resistance to chemotherapeutics will enable precision medicine in the treatment of cancer patients. CRISPR Cas9a has emerged as a functional genomics tool to study at genome level the factors that control cancer resistance to drugs. Recently, we used genome wide CRISPR-Cas9a screen to identify genes responsible for glioblastoma susceptibility to etoposide. We extended our inquiry to understand genes that control glioblastoma response to temozolomide by using genome scale CRISPR. This study shows that the unbiased genome-wide loss of function approach can be applied to discover genes that influence tumor resistance to chemotherapeutics and contribute to chemoresistance in glioblastoma.

2021 ◽  
Author(s):  
Brian C Zhang ◽  
Arjun Biddanda ◽  
Pier Francesco Palamara

Accurate inference of gene genealogies from genetic data has the potential to facilitate a wide range of analyses. We introduce a method for accurately inferring biobank-scale genome-wide genealogies from sequencing or genotyping array data, as well as strategies to utilize genealogies within linear mixed models to perform association and other complex trait analyses. We use these new methods to build genome-wide genealogies using genotyping data for 337,464 UK Biobank individuals and to detect associations in 7 complex traits. Genealogy-based association detects more rare and ultra-rare signals (N = 133, frequency range 0.0004% - 0.1%) than genotype imputation from ~65,000 sequenced haplotypes (N = 65). In a subset of 138,039 exome sequencing samples, these associations strongly tag (average r = 0.72) underlying sequencing variants, which are enriched for missense (2.3×) and loss-of-function (4.5×) variation. Inferred genealogies also capture additional association signals in higher frequency variants. These results demonstrate that large-scale inference of gene genealogies may be leveraged in the analysis of complex traits, complementing approaches that require the availability of large, population-specific sequencing panels.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Valerie Sapp ◽  
Aitor Aguirre ◽  
Gayatri Mainkar ◽  
Jeffrey Ding ◽  
Eric Adler ◽  
...  

AbstractHuman induced pluripotent stem (iPS) cell technologies coupled with genetic engineering now facilitate the study of the molecular underpinnings of disease in relevant human cell types. Application of CRISPR/Cas9-based approaches for genome-scale functional screening in iPS-derived cells, however, has been limited by technical constraints, including inefficient transduction in pooled format, loss of library representation, and poor cellular differentiation. Herein, we present optimized approaches for whole-genome CRISPR/Cas9 based screening in human iPS derived cardiomyocytes with near genome-wide representation at both the iPS and differentiated cell stages. As proof-of-concept, we perform a screen to investigate mechanisms underlying doxorubicin mediated cell death in iPS derived cardiomyocytes. We identified two poorly characterized, human-specific transporters (SLCO1A2, SLCO1B3) whose loss of function protects against doxorubicin-cardiotoxicity, but does not affect cell death in cancer cells. This study provides a technical framework for genome-wide functional screening in iPS derived cells and identifies new targets to mitigate doxorubicin-cardiotoxicity in humans.


2012 ◽  
Vol 48 ◽  
pp. 31-32
Author(s):  
L.Y. Dimberg ◽  
H. Cabrera ◽  
C. Menke ◽  
K. Behbakht ◽  
C.C. Porter ◽  
...  

2021 ◽  
Author(s):  
Fernando Carazo ◽  
Edurne San Jose Eneriz ◽  
Marian Gimeno ◽  
Leire Garate ◽  
Estibaliz Miranda ◽  
...  

Recent functional genomic screens -such as CRISPR-Cas9 or RNAi screening- have fostered a new wave of targeted treatments based on the concept of synthetic lethality. These approaches identified LEthal Dependencies (LEDs) by estimating the effect of genetic events on cell viability. The multiple-hypothesis problem related to a large number of gene knockouts limits the statistical power of these studies. Here, we show that predictions of LEDs from functional screens can be dramatically improved by incorporating the <HUb effect in Genetic Essentiality> (HUGE) of gene alterations. We analyze three recent genome-wide loss-of-function screens -Project Score, CERES score, and DEMETER score- identifying LEDs with 75 times larger statistical power than using state-of-the-art methods. HUGE shows an increased enrichment in a recent harmonized knowledgebase of clinical interpretations of somatic genomic variants in cancer (with an AUROC up to 0.87). Our approach is effective even in tumors with large genetic heterogeneity such as acute myeloid leukemia, where we identified LEDs not recalled by previous pipelines, including FLT3-mutant genotypes sensitive to FLT3 inhibitors. Interestingly, in-vitro validations confirm lethal dependencies of either NRAS or PTPN11 depending on the NRAS mutational status. HUGE will hopefully help discover novel genetic dependencies amenable for precision-targeted therapies in cancer.


Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 273-273 ◽  
Author(s):  
Michal Sheffer ◽  
Yiguo Hu ◽  
Ophir Shalem ◽  
Neville Sanjana ◽  
Eugen Dhimolea ◽  
...  

Abstract Acquired or de novo resistance to established and investigational therapies represents a major clinical challenge for multiple myeloma (MM) and other neoplasias. Despite extensive efforts, clinically-validated molecular markers that predict for proteasome inhibitor (PSI) resistance in most MM patients remain elusive. This challenge is partly due to limited availability so far of molecular data on MM patients before the start of PSI treatment vs. immediately after resistance to it develops; this challenge may also reflect the heterogeneity of the complex molecular mechanisms regulating MM cell response to PSIs. We hypothesized that resistance to PSIs can be mediated by disruption of several functionally overlapping genes, and that the prevalence of any of these lesions may be too low to detect in datasets available thus far. To examine this latter hypothesis, we performed a genome-wide screen for genes whose loss confers to MM cells resistance against bortezomib, through the use of the CRISPR (clustered regularly interspaced short palindromic repeats)–associated nuclease Cas9 system. Specifically RPMI-8226 MM cells were transduced with lentiviral construct for Cas9 nuclease, followed by lentiviral delivery of a genome-scale pooled library of 123,411 single-guide RNAs (sgRNAs), which selectively align to target sequences at the 5′ constitutive exons of 18,080 genes and direct the Cas9 nuclease to cause double-stranded cleavage and loss of function of the respective gene. From the pool of MM cells transduced with the sgRNA library and treated with bortezomib, treatment-resistant cells were processed for deep sequencing, to identify enriched sgRNAs and their corresponding genes. We identified that loss-of-function of 33 candidate genes is associated with bortezomib resistance. We observed a high level of consistency between independent sgRNAs targeting the same gene, as well as a high rate of hit confirmation across different biological replicates. Notably, this set of candidate bortezomib-resistance genes was distinct from the "hits" we identified through a parallel CRISPR screen on the same cell line for resistance to a different targeted therapy (namely the bromodomain inhibitor JQ1), supporting the ability of this approach to identify treatment-specific resistance genes. These candidate bortezomib-resistance genes have documented or presumed roles in the regulation of extrinsic and intrinsic apoptotic cascades, autophagy, Toll-like receptor and NF-kappaB signaling, aggresome function, heat shock protein expression, chromatin remodeling, nutrient sensing, and tumor suppressor gene networks. Importantly, information from several publically available molecular profiling datasets converge to support the putative clinical relevance of these genes. For instance, gene expression data from tumor cells of bortezomib-naive patients with advanced MM revealed several transcriptional signatures of these candidate genes (defined by low transcript levels for any of the genes in the signature) which correlated with shorter time to disease progression after treatment with bortezomib (p<0.01, log-rank test), but not dexamethasone (p>0.426). Congruent with these findings, the highly bortezomib-responsive clinical setting of newly-diagnosed MM is associated with low cumulative frequency of mutations of these bortezomib-resistance genes (e.g. cumulative mutation rate of 3.9%, 95% confidence interval [CI] 1.25-6.55%). Notably, in other malignancies that are typically PSI-resistant, a higher cumulative frequency of such lesions is observed (average of ~28%, range 0-76%, 95% CI 22.46-32.70%; 57 datasets from 20+ neoplasias examined). In summary, this first application of the CRISPR/Cas9-based technology in MM illustrates its power to interrogate gene function on a genome-wide scale. This approach identifies bortezomib-resistance genes that are associated with pathways linked with the regulation of proteasome inhibitor response. Results from molecularly-annotated clinical samples converge to support a possible role for these genes in bortezomib resistance. This experience supports the value of CRISPR/Cas9-based studies to dissect the molecular mechanisms of treatment resistance in MM and other hematologic neoplasias (* equal contribution of M.S. and Y.H.). Disclosures Shalem: Broad Institute: Patent application for CRISPR technology Patents & Royalties. Sanjana:Broad Institute: Patent application for CRISPR technology Patents & Royalties. Zhang:Broad Institute: Patent application for CRISPR technology Patents & Royalties. Mitsiades:Johnson & Johnson: Research Funding; Amgen: Research Funding; Celgene: Consultancy, Honoraria; Millennium Pharmaceuticals: Consultancy, Honoraria.


2020 ◽  
Author(s):  
Matthew R. Hass ◽  
Daniel Brisette ◽  
Sreeja Parameswaran ◽  
Mario Pujato ◽  
Omer Donmez ◽  
...  

AbstractRunt-related transcription factor 1 (Runx1) can act as both an activator and a repressor. Here we show that CRISPR-mediated deletion of Runx1 in an embryonic kidney-derived cell (mK4) results in large-scale genome-wide changes to chromatin accessibility and gene expression. Open chromatin regions near down-regulated loci are enriched for Runx sites, remain bound by Runx2, but lose chromatin accessibility and expression in Runx1 knockout cells. Unexpectedly, regions near upregulated genes are depleted of Runx sites and are instead enriched for Zeb transcription factor binding sites. Re-expressing Zeb2 in Runx1 knockout cells restores suppression. These data confirm that Runx1 activity is uniquely needed to maintain open chromatin at many loci, and demonstrate that genome-scale derepression is an indirect consequence of losing Runx1-dependent Zeb expression.


2018 ◽  
Author(s):  
Kendall R Sanson ◽  
Ruth E Hanna ◽  
Mudra Hegde ◽  
Katherine F Donovan ◽  
Christine Strand ◽  
...  

ABSTRACTAdvances in CRISPR-Cas9 technology have enabled the flexible modulation of gene expression at large scale. In particular, the creation of genome-wide libraries for CRISPR knockout (CRISPRko), CRISPR interference (CRISPRi), and CRISPR activation (CRISPRa) has allowed gene function to be systematically interrogated. Here, we evaluate numerous CRISPRko libraries and show that our recently-described CRISPRko library (Brunello) is more effective than previously published libraries at distinguishing essential and non-essential genes, providing approximately the same perturbation-level performance improvement over GeCKO libraries as GeCKO provided over RNAi. Additionally, we developed genome-wide libraries for CRISPRi (Dolcetto) and CRISPRa (Calabrese). Negative selection screens showed that Dolcetto substantially outperforms existing CRISPRi libraries with fewer sgRNAs per gene and achieves comparable performance to CRISPRko in the detection of gold-standard essential genes. We also conducted positive selection CRISPRa screens and show that Calabrese outperforms the SAM library approach at detecting vemurafenib resistance genes. We further compare CRISPRa to genome-scale libraries of open reading frames (ORFs). Together, these libraries represent a suite of genome-wide tools to efficiently interrogate gene function with multiple modalities.tracr


2014 ◽  
Author(s):  
Neville E Sanjana ◽  
Ophir Shalem ◽  
Feng Zhang

Genome-wide, targeted loss-of-function pooled screens using the CRISPR (clustered regularly interspaced short palindrome repeats)?associated nuclease Cas9 in human and mouse cells provide an alternative screening system to RNA interference (RNAi). Initial lentiviral delivery systems for CRISPR screening had low viral titer or required a cell line already expressing Cas9, limiting the range of biological systems amenable to screening. In this work, we present 1- and 2-vector lentiCRISPR systems capable of producing higher viral titers and, in these vectors, new human and mouse libraries for genome-scale CRISPR knock-out (GeCKO) screening.


2013 ◽  
Vol 42 (5) ◽  
pp. e32-e32 ◽  
Author(s):  
Jun Li ◽  
Hairong Wei ◽  
Tingsong Liu ◽  
Patrick Xuechun Zhao

Abstract The accurate construction and interpretation of gene association networks (GANs) is challenging, but crucial, to the understanding of gene function, interaction and cellular behavior at the genome level. Most current state-of-the-art computational methods for genome-wide GAN reconstruction require high-performance computational resources. However, even high-performance computing cannot fully address the complexity involved with constructing GANs from very large-scale expression profile datasets, especially for the organisms with medium to large size of genomes, such as those of most plant species. Here, we present a new approach, GPLEXUS (http://plantgrn.noble.org/GPLEXUS/), which integrates a series of novel algorithms in a parallel-computing environment to construct and analyze genome-wide GANs. GPLEXUS adopts an ultra-fast estimation for pairwise mutual information computing that is similar in accuracy and sensitivity to the Algorithm for the Reconstruction of Accurate Cellular Networks (ARACNE) method and runs ∼1000 times faster. GPLEXUS integrates Markov Clustering Algorithm to effectively identify functional subnetworks. Furthermore, GPLEXUS includes a novel ‘condition-removing’ method to identify the major experimental conditions in which each subnetwork operates from very large-scale gene expression datasets across several experimental conditions, which allows users to annotate the various subnetworks with experiment-specific conditions. We demonstrate GPLEXUS’s capabilities by construing global GANs and analyzing subnetworks related to defense against biotic and abiotic stress, cell cycle growth and division in Arabidopsis thaliana.


2019 ◽  
Author(s):  
Muhammad Yasir ◽  
Keith Turner ◽  
Sarah Bastkowski ◽  
Ian Charles ◽  
Mark A. Webber

AbstractFosfomycin is an antibiotic which has seen a revival in use due to its unique mechanism of action and resulting efficacy against isolates resistant to many other antibiotics. Mechanisms of resistance have been elucidated and loss of function mutations within the genes encoding the sugar importers, GlpT and UhpT are commonly selected for by fosfomycin exposure in E. coli. There has however not been a genome wide analysis of the basis for fosfomycin sensitivity reported to date. Here we used ‘TraDIS-Xpress’ a high-density transposon mutagenesis approach to assay the role of all genes in E. coli in fosfomycin sensitivity. The data confirmed known mechanisms of action and resistance as well as identifying a set of novel loci involved in fosfomycin sensitivity. The assay was able to identify sub domains within genes of importance and also revealed essential genes with roles in fosfomycin sensitivity based on expression changes. Novel genes identified included those involved in glucose metabolism, the phosphonate import and breakdown system, phnC-M and the phosphate importer, pstSACB. The impact of these genes in fosfomycin sensitivity was validated by measuring the susceptibility of defined inactivation mutants. This work reveals a wider set of genes contribute to fosfomycin sensitivity including core sugar metabolism genes and two transport systems previously unrecognised as having a role in fosfomycin sensitivity. The work also suggests new routes by which drugs with a phosphonate moiety may be transported across the inner membrane of Gram-negative bacteria.ImportanceThe emergence and spread of antibiotic resistant bacteria had resulted in increased use of alternative drugs which retain efficacy against isolates resistant to other classes of drugs. One example is fosfomycin; an old drug which has found greatly increased use in recent years. We studied the mechanisms of fosfomycin resistance by applying a genome wide screen based on comparing the fitness of a massive library of transposon mutants in the presence of fosfomycin. This approach identified the previously known mechanisms of resistance but also identified a number of new pathways which contribute to fosfomycin sensitivity including two importer systems. This information advances our knowledge about an increasingly important antibiotic and identifies new potential routes to resistance.


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