scholarly journals Decoding directional genetic dependencies through orthogonal CRISPR/Cas screens

2017 ◽  
Author(s):  
Michael Boettcher ◽  
Ruilin Tian ◽  
James Blau ◽  
Evan Markegard ◽  
David Wu ◽  
...  
Keyword(s):  
Genetic Information ◽  
Genetic Interaction ◽  
Human Cancer ◽  
Genetic Interactions ◽  
Combinatorial Screening ◽  
Human Cancer Cells ◽  
Functional Interactions ◽  
Powerful Approach ◽  
Screening Platform ◽  
Interaction Approach

SummaryGenetic interaction studies are a powerful approach to identify functional interactions between genes. This approach can reveal networks of regulatory hubs and connect uncharacterised genes to well-studied pathways. However, this approach has previously been limited to simple gene inactivation studies. Here, we present an orthogonal CRISPR/Cas-mediated genetic interaction approach that allows the systematic activation of one gene while simultaneously knocking out a second gene in the same cell. We have developed this concept into a quantitative and scalable combinatorial screening platform that allows the parallel interrogation of hundreds of thousands of genetic interactions. We demonstrate that the established platform works robustly to uncover genetic interactions in human cancer cells and to interpret the direction of the flow of genetic information.

scholarly journals A map of directional genetic interactions in a metazoan cell

eLife ◽  
2015 ◽  
Vol 4 ◽  
Author(s):  
Bernd Fischer ◽  
Thomas Sandmann ◽  
Thomas Horn ◽  
Maximilian Billmann ◽  
Varun Chaudhary ◽  
...  
Keyword(s):  
Regulatory Networks ◽  
Large Scale ◽  
Genetic Interaction ◽  
Human Cancer ◽  
Genetic Alterations ◽  
Genetic Interactions ◽  
Gene Interactions ◽  
Human Cancer Cells ◽  
Multiple Phenotypes ◽  
Interaction Map

Gene–gene interactions shape complex phenotypes and modify the effects of mutations during development and disease. The effects of statistical gene–gene interactions on phenotypes have been used to assign genes to functional modules. However, directional, epistatic interactions, which reflect regulatory relationships between genes, have been challenging to map at large-scale. Here, we used combinatorial RNA interference and automated single-cell phenotyping to generate a large genetic interaction map for 21 phenotypic features of Drosophila cells. We devised a method that combines genetic interactions on multiple phenotypes to reveal directional relationships. This network reconstructed the sequence of protein activities in mitosis. Moreover, it revealed that the Ras pathway interacts with the SWI/SNF chromatin-remodelling complex, an interaction that we show is conserved in human cancer cells. Our study presents a powerful approach for reconstructing directional regulatory networks and provides a resource for the interpretation of functional consequences of genetic alterations.

scholarly journals Leveraging genetic interaction for adverse drug-drug interaction prediction

2019 ◽  
Author(s):  
Sheng Qian ◽  
Siqi Liang ◽  
Haiyuan Yu
Keyword(s):  
Genetic Interaction ◽  
Genetic Interactions ◽  
Gradient Boosting ◽  
Interaction Prediction ◽  
Training Scheme ◽  
Feature Spaces ◽  
Multiple Drugs ◽  
Interaction Approach ◽  
First Time

ABSTRACTIn light of increased co-prescription of multiple drugs, the ability to discern and predict drug-drug interactions (DDI) has become crucial to guarantee the safety of patients undergoing treatment with multiple drugs. However, information on DDI profiles is incomplete and the experimental determination of DDIs is labor-intensive and time-consuming. Although previous studies have explored various feature spaces for in silico screening of interacting drug pairs, no method currently provides reliable predictions outside of their training sets. Here we demonstrate for the first time targets of adversely interacting drug pairs are significantly more likely to have synergistic genetic interactions than non-interacting drug pairs. Leveraging genetic interaction features and a novel training scheme, we construct a gradient boosting-based classifier that achieves robust DDI prediction even for drugs whose interaction profiles are completely unseen during training. We demonstrate that in addition to classification power—including the prediction of 432 novel DDIs—our genetic interaction approach offers interpretability by providing plausible mechanistic insights into the mode of action of DDIs.

Mapping genetic interactions in human cancer cells with RNAi and multiparametric phenotyping

2013 ◽  
Vol 10 (5) ◽  
pp. 427-431 ◽  
Author(s):  
Christina Laufer ◽  
Bernd Fischer ◽  
Maximilian Billmann ◽  
Wolfgang Huber ◽  
Michael Boutros
Keyword(s):  
Cancer Cells ◽  
Human Cancer ◽  
Genetic Interactions ◽  
Human Cancer Cells

scholarly journals Towards an Integrated Map of Genetic Interactions in Cancer Cells

2017 ◽  
Author(s):  
Benedikt Rauscher ◽  
Florian Heigwer ◽  
Luisa Henkel ◽  
Thomas Hielscher ◽  
Oksana Voloshanenko ◽  
...  
Keyword(s):  
Cancer Cells ◽  
Genetic Variants ◽  
Genetic Interaction ◽  
Human Cancer ◽  
Genetic Network ◽  
Genetic Interactions ◽  
Model Organisms ◽  
Genetic Screens ◽  
New Genotype ◽  
Analytical Approaches

ABSTRACTCancer genomes often harbor hundreds of molecular aberrations. Such genetic variants can be drivers or passengers of tumorigenesis and, as a side effect, create new vulnerabilities for potential therapeutic exploitation. To systematically identify genotype-dependent vulnerabilities and synthetic lethal interactions, forward genetic screens in different genetic backgrounds have been conducted. We devised MINGLE, a computational framework that integrates CRISPR/Cas9 screens originating from many different libraries and laboratories to build genetic interaction maps. It builds on analytical approaches that were established for genetic network discovery in model organisms. We applied this method to integrate and analyze data from 85 CRISPR/Cas9 screens in human cancer cell lines combining functional data with information on genetic variants to explore the relationships of more than 2.1 million gene-background relationships. In addition to known dependencies, our analysis identified new genotype-specific vulnerabilities of cancer cells. Experimental validation of predicted vulnerabilities associated with aberrant Wnt/β-catenin signaling identifiedGANABandPRKCSHas new positive regulators of Wnt/β-catenin signaling. By clustering genes with similar genetic interaction profiles, we drew the largest genetic network in cancer cells to date. Our scalable approach highlights how diverse genetic screens can be integrated to systematically build informative maps of genetic interactions in cancer, which can grow dynamically as more data is included.

scholarly journals A Synthetic Dosage Lethal Genetic Interaction Between CKS1B and PLK1 Is Conserved in Yeast and Human Cancer Cells

Genetics ◽  
2016 ◽  
Vol 204 (2) ◽  
pp. 807-819 ◽  
Author(s):  
R. J. D. Reid ◽  
X. Du ◽  
I. Sunjevaric ◽  
V. Rayannavar ◽  
J. Dittmar ◽  
...  
Keyword(s):  
Cancer Cells ◽  
Genetic Interaction ◽  
Human Cancer ◽  
Human Cancer Cells

Indirubin derivatives inhibit SFKs/Stat signaling associated with apoptosis in human cancer cells

Planta Medica ◽  
2008 ◽  
Vol 74 (09) ◽  
Author(s):  
S Nam ◽  
R Buettner ◽  
X Liu ◽  
J Turkson ◽  
D Kim ◽  
...  
Keyword(s):  
Cancer Cells ◽  
Human Cancer ◽  
Human Cancer Cells ◽  
Stat Signaling

Structure-Reactivity Relationships on Substrates and Inhibitors of the Lysine Deacylase Sirtuin 2 from Schistosoma Mansoni (SmSirt2)

2019 ◽  
Author(s):  
Daria Monaldi ◽  
Dante Rotili ◽  
Julien Lancelot ◽  
Martin Marek ◽  
Nathalie Wössner ◽  
...  
Keyword(s):  
Schistosoma Mansoni ◽  
Human Cancer ◽  
Egg Laying ◽  
Human Cancer Cells ◽  
Parasite Survival ◽  
Survival And Reproduction ◽  
Emergence Of Resistance ◽  
First Time ◽  
Parasitic Life Cycle

The only drug for treatment of Schistosomiasis is Praziquantel, and the possible emergence of resistance makes research on novel therapeutic agents necessary. Targeting of Schistosoma mansoni epigenetic enzymes, which regulate the parasitic life cycle, emerged as promising approach. Due to the strong effects of human Sirtuin inhibitors on parasite survival and reproduction, Schistosoma sirtuins were postulated as therapeutic targets. In vitro testing of synthetic substrates of S. mansoni Sirtuin 2 (SmSirt2) and kinetic experiments on a myristoylated peptide demonstrated lysine long chain deacylation as an intrinsic SmSirt2 activity for the first time. Focused in vitro screening of the GSK Kinetobox library and structure-activity relationships (SAR) of identified hits, led to the first SmSirt2 inhibitors with activity in the low micromolar range. Several SmSirt2 inhibitors showed potency against both larval schistosomes (viability) and adult worms (pairing, egg laying) in culture without general toxicity to human cancer cells.<br>

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