scholarly journals Paralogous synthetic lethality underlies genetic dependencies of the cancer-mutated gene STAG2

2021 ◽  
Vol 4 (11) ◽  
pp. e202101083
Author(s):  
Melanie L Bailey ◽  
David Tieu ◽  
Andrea Habsid ◽  
Amy Hin Yan Tong ◽  
Katherine Chan ◽  
...  
Keyword(s):  
Genetic Interaction ◽  
Synthetic Lethality ◽  
Regulatory Gene ◽  
Chromosome Instability ◽  
Genetic Interactions ◽  
Complex Nature ◽  
Whole Genome ◽  
Cohesin Complex ◽  
Synthetic Lethal ◽  
Cancer Types

STAG2, a component of the mitotically essential cohesin complex, is highly mutated in several different tumour types, including glioblastoma and bladder cancer. Whereas cohesin has roles in many cancer-related pathways, such as chromosome instability, DNA repair and gene expression, the complex nature of cohesin function has made it difficult to determine how STAG2 loss might either promote tumorigenesis or be leveraged therapeutically across divergent cancer types. Here, we have performed whole-genome CRISPR-Cas9 screens for STAG2-dependent genetic interactions in three distinct cellular backgrounds. Surprisingly, STAG1, the paralog of STAG2, was the only negative genetic interaction that was shared across all three backgrounds. We also uncovered a paralogous synthetic lethal mechanism behind a genetic interaction between STAG2 and the iron regulatory gene IREB2. Finally, investigation of an unusually strong context-dependent genetic interaction in HAP1 cells revealed factors that could be important for alleviating cohesin loading stress. Together, our results reveal new facets of STAG2 and cohesin function across a variety of genetic contexts.

scholarly journals Genome-wide mapping of unexplored essential regions in the Saccharomyces cerevisiae genome: evidence for hidden synthetic lethal combinations in a genetic interaction network

2014 ◽  
Vol 42 (15) ◽  
pp. 9838-9853 ◽  
Author(s):  
Saeed Kaboli ◽  
Takuya Yamakawa ◽  
Keisuke Sunada ◽  
Tao Takagaki ◽  
Yu Sasano ◽  
...  
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Genetic Interaction ◽  
Interaction Network ◽  
Essential Genes ◽  
Genetic Interactions ◽  
Lethal Gene ◽  
Synthetic Lethal ◽  
Genome Wide ◽  
A Genome ◽  
Wide Scale

Abstract Despite systematic approaches to mapping networks of genetic interactions in Saccharomyces cerevisiae, exploration of genetic interactions on a genome-wide scale has been limited. The S. cerevisiae haploid genome has 110 regions that are longer than 10 kb but harbor only non-essential genes. Here, we attempted to delete these regions by PCR-mediated chromosomal deletion technology (PCD), which enables chromosomal segments to be deleted by a one-step transformation. Thirty-three of the 110 regions could be deleted, but the remaining 77 regions could not. To determine whether the 77 undeletable regions are essential, we successfully converted 67 of them to mini-chromosomes marked with URA3 using PCR-mediated chromosome splitting technology and conducted a mitotic loss assay of the mini-chromosomes. Fifty-six of the 67 regions were found to be essential for cell growth, and 49 of these carried co-lethal gene pair(s) that were not previously been detected by synthetic genetic array analysis. This result implies that regions harboring only non-essential genes contain unidentified synthetic lethal combinations at an unexpectedly high frequency, revealing a novel landscape of genetic interactions in the S. cerevisiae genome. Furthermore, this study indicates that segmental deletion might be exploited for not only revealing genome function but also breeding stress-tolerant strains.

A Screen for Dynein Synthetic Lethals in Aspergillus nidulans Identifies Spindle Assembly Checkpoint Genes and Other Genes Involved in Mitosis

Genetics ◽  
1998 ◽  
Vol 149 (1) ◽  
pp. 101-116
Author(s):  
Vladimir P Efimov ◽  
N Ronald Morris
Keyword(s):  
Aspergillus Nidulans ◽  
Spindle Assembly Checkpoint ◽  
Genetic Interaction ◽  
Synthetic Lethality ◽  
Spindle Assembly ◽  
Nuclear Migration ◽  
Cytoplasmic Dynein ◽  
Vesicle Transport ◽  
Synthetic Lethal ◽  
Checkpoint Genes

Abstract Cytoplasmic dynein is a ubiquitously expressed microtubule motor involved in vesicle transport, mitosis, nuclear migration, and spindle orientation. In the filamentous fungus Aspergillus nidulans, inactivation of cytoplasmic dynein, although not lethal, severely impairs nuclear migration. The role of dynein in mitosis and vesicle transport in this organism is unclear. To investigate the complete range of dynein function in A. nidulans, we searched for synthetic lethal mutations that significantly reduced growth in the absence of dynein but had little effect on their own. We isolated 19 sld (synthetic lethality without dynein) mutations in nine different genes. Mutations in two genes exacerbate the nuclear migration defect seen in the absence of dynein. Mutations in six other genes, including sldA and sldB, show a strong synthetic lethal interaction with a mutation in the mitotic kinesin bimC and, thus, are likely to play a role in mitosis. Mutations in sldA and sldB also confer hypersensitivity to the microtubule-destabilizing drug benomyl. sldA and sldB were cloned by complementation of their mutant phenotypes using an A. nidulans autonomously replicating vector. Sequencing revealed homology to the spindle assembly checkpoint genes BUB1 and BUB3 from Saccharomyces cerevisiae. Genetic interaction between dynein and spindle assembly checkpoint genes, as well as other mitotic genes, indicates that A. nidulans dynein plays a role in mitosis. We suggest a model for dynein motor action in A. nidulans that can explain dynein involvement in both mitosis and nuclear distribution.

scholarly journals Mapping genetic interactions in cancer: a road to rational combination therapies

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Beril Tutuncuoglu ◽  
Nevan J. Krogan
Keyword(s):  
Anticancer Drugs ◽  
Genetic Interaction ◽  
Synthetic Lethality ◽  
Parp Inhibitors ◽  
Genetic Interactions ◽  
Parp Inhibition ◽  
Functional Dependencies ◽  
Combination Therapies ◽  
Systematic Screening ◽  
Rational Combination

Abstract The discovery of synthetic lethal interactions between poly (ADP-ribose) polymerase (PARP) inhibitors and BRCA genes, which are involved in homologous recombination, led to the approval of PARP inhibition as a monotherapy for patients with BRCA1/2-mutated breast or ovarian cancer. Studies following the initial observation of synthetic lethality demonstrated that the reach of PARP inhibitors is well beyond just BRCA1/2 mutants. Insights into the mechanisms of action of anticancer drugs are fundamental for the development of targeted monotherapies or rational combination treatments that will synergize to promote cancer cell death and overcome mechanisms of resistance. The development of targeted therapeutic agents is premised on mapping the physical and functional dependencies of mutated genes in cancer. An important part of this effort is the systematic screening of genetic interactions in a variety of cancer types. Until recently, genetic-interaction screens have relied either on the pairwise perturbations of two genes or on the perturbation of genes of interest combined with inhibition by commonly used anticancer drugs. Here, we summarize recent advances in mapping genetic interactions using targeted, genome-wide, and high-throughput genetic screens, and we discuss the therapeutic insights obtained through such screens. We further focus on factors that should be considered in order to develop a robust analysis pipeline. Finally, we discuss the integration of functional interaction data with orthogonal methods and suggest that such approaches will increase the reach of genetic-interaction screens for the development of rational combination therapies.

scholarly journals Synthetic lethality between the cohesin subunits STAG1 and STAG2 in diverse cancer contexts

2017 ◽  
Author(s):  
Petra van der Lelij ◽  
Simone Lieb ◽  
Julian Jude ◽  
Gordana Wutz ◽  
Catarina P. Santos ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
Sister Chromatid ◽  
Synthetic Lethality ◽  
Sister Chromatid Cohesion ◽  
Cohesin Complex ◽  
Wild Type ◽  
Synthetic Lethal ◽  
Recurrent Mutations ◽  
Wide Range ◽  
Chromatid Cohesion

AbstractRecent genome analyses have identified recurrent mutations in the cohesin complex in a wide range of human cancers. Here we demonstrate that the most frequently mutated subunit of the cohesin complex, STAG2, displays a strong synthetic lethal interaction with its paralog STAG1. Mechanistically, STAG1 loss abrogates sister chromatid cohesion in STAG2 mutated but not in wild-type cells leading to mitotic catastrophe, defective cell division and apoptosis. STAG1 inactivation inhibits the proliferation of STAG2 mutated but not wild-type bladder cancer and Ewing sarcoma cell lines. Restoration of STAG2 expression in a mutated bladder cancer model alleviates the dependency on STAG1. Thus, STAG1 and STAG2 support sister chromatid cohesion to redundantly ensure cell survival. STAG1 represents a vulnerability of cancer cells carrying mutations in the major emerging tumor suppressor STAG2 across different cancer contexts. Exploiting synthetic lethal interactions to target recurrent cohesin mutations in cancer, e.g. by inhibiting STAG1, holds the promise for the development of selective therapeutics.

scholarly journals Uncovering cancer vulnerabilities by machine learning prediction of synthetic lethality

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Salvatore Benfatto ◽  
Özdemirhan Serçin ◽  
Francesca R. Dejure ◽  
Amir Abdollahi ◽  
Frank T. Zenke ◽  
...  
Keyword(s):  
Machine Learning ◽  
Cancer Genomics ◽  
Genetic Interaction ◽  
Synthetic Lethality ◽  
Interacting Protein ◽  
Synthetic Lethal ◽  
Damage Repair ◽  
Genome Wide ◽  
Machine Learning Approach ◽  
Transcriptomics Data

Abstract Background Synthetic lethality describes a genetic interaction between two perturbations, leading to cell death, whereas neither event alone has a significant effect on cell viability. This concept can be exploited to specifically target tumor cells. CRISPR viability screens have been widely employed to identify cancer vulnerabilities. However, an approach to systematically infer genetic interactions from viability screens is missing. Methods Here we describe PAn-canceR Inferred Synthetic lethalities (PARIS), a machine learning approach to identify cancer vulnerabilities. PARIS predicts synthetic lethal (SL) interactions by combining CRISPR viability screens with genomics and transcriptomics data across hundreds of cancer cell lines profiled within the Cancer Dependency Map. Results Using PARIS, we predicted 15 high confidence SL interactions within 549 DNA damage repair (DDR) genes. We show experimental validation of an SL interaction between the tumor suppressor CDKN2A, thymidine phosphorylase (TYMP) and the thymidylate synthase (TYMS), which may allow stratifying patients for treatment with TYMS inhibitors. Using genome-wide mapping of SL interactions for DDR genes, we unraveled a dependency between the aldehyde dehydrogenase ALDH2 and the BRCA-interacting protein BRIP1. Our results suggest BRIP1 as a potential therapeutic target in ~ 30% of all tumors, which express low levels of ALDH2. Conclusions PARIS is an unbiased, scalable and easy to adapt platform to identify SL interactions that should aid in improving cancer therapy with increased availability of cancer genomics data.

scholarly journals Integrative analysis of large-scale loss-of-function screens identifies robust cancer-associated genetic interactions

2019 ◽  
Author(s):  
Christopher J. Lord ◽  
Niall Quinn ◽  
Colm J. Ryan
Keyword(s):  
Protein Interactions ◽  
Large Scale ◽  
Genetic Interaction ◽  
Interaction Network ◽  
Genetic Interactions ◽  
Molecular Heterogeneity ◽  
Loss Of Function ◽  
Driver Genes ◽  
Lethal Effects ◽  
Synthetic Lethal

AbstractGenetic interactions, such as synthetic lethal effects, can now be systematically identified in cancer cell lines using high-throughput genetic perturbation screens. Despite this advance, few genetic interactions have been reproduced across multiple studies and many appear highly context-specific. Understanding which genetic interactions are robust in the face of the molecular heterogeneity observed in tumours and what factors influence this robustness could streamline the identification of therapeutic targets. Here, we develop a computational approach to identify robust genetic interactions that can be reproduced across independent experiments and across non-overlapping cell line panels. We used this approach to evaluate >140,000 potential genetic interactions involving cancer driver genes and identified 1,520 that are significant in at least one study but only 220 that reproduce across multiple studies. Analysis of these interactions demonstrated that: (i) oncogene addiction effects are more robust than oncogene-related synthetic lethal effects; and (ii) robust genetic interactions in cancer are enriched for gene pairs whose protein products physically interact. This suggests that protein-protein interactions can be used not only to understand the mechanistic basis of genetic interaction effects, but also to prioritise robust targets for further development. To explore the utility of this approach, we used a protein-protein interaction network to guide the search for robust synthetic lethal interactions associated with passenger gene alterations and validated two novel robust synthetic lethalities.

scholarly journals Exploring genetic interaction manifolds constructed from rich phenotypes

2019 ◽  
Author(s):  
Thomas M. Norman ◽  
Max A. Horlbeck ◽  
Joseph M. Replogle ◽  
Alex Y. Ge ◽  
Albert Xu ◽  
...  
Keyword(s):  
Single Cell ◽  
Genetic Interaction ◽  
Erythroid Differentiation ◽  
Analytical Framework ◽  
Genetic Interactions ◽  
Synthetic Lethal ◽  
Regulatory Pathways ◽  
Synergistic Interactions ◽  
Dimensional Interaction ◽  
Synthetic Lethal Interactions

AbstractSynergistic interactions between gene functions drive cellular complexity. However, the combinatorial explosion of possible genetic interactions (GIs) has necessitated the use of scalar interaction readouts (e.g. growth) that conflate diverse outcomes. Here we present an analytical framework for interpreting manifolds constructed from high-dimensional interaction phenotypes. We applied this framework to rich phenotypes obtained by Perturb-seq (single-cell RNA-seq pooled CRISPR screens) profiling of strong GIs mined from a growth-based, gain-of-function GI map. Exploration of this manifold enabled ordering of regulatory pathways, principled classification of GIs (e.g. identifying true suppressors), and mechanistic elucidation of synthetic lethal interactions, including an unexpected synergy between CBL and CNN1 driving erythroid differentiation. Finally, we apply recommender system machine learning to predict interactions, facilitating exploration of vastly larger GI manifolds.One Sentence SummaryPrinciples and mechanisms of genetic interactions are revealed by rich phenotyping using single-cell RNA sequencing.

scholarly journals Shuffle-Seq: En masse combinatorial encoding for n-way genetic interaction screens

2019 ◽  
Author(s):  
Atray Dixit ◽  
Olena Kuksenko ◽  
David Feldman ◽  
Aviv Regev
Keyword(s):  
Large Scale ◽  
Genetic Interaction ◽  
Synthetic Lethality ◽  
Genetic Interactions ◽  
Pairwise Interactions ◽  
Affect Cell Viability ◽  
Melanoma Model ◽  
Dividing Cells ◽  
Combinatorial Encoding ◽  
Massive Number

AbstractGenetic interactions, defined as the non-additive phenotypic impact of combinations of genes, are a hallmark of the mapping from genotype to phenotype. However, genetic interactions remain challenging to systematically test given the massive number of possible combinations. In particular, while large-scale screening efforts in yeast have quantified pairwise interactions that affect cell viability, or synthetic lethality, between all pairs of genes as well as for a limited number of three-way interactions, it has previously been intractable to perform the large screens needed to comprehensively assess interactions in a mammalian genome. Here, we develop Shuffle-Seq, a scalable method to assay genetic interactions. Shuffle-Seq leverages the co-inheritance of genetically encoded barcodes in dividing cells and can scale in proportion to sequencing throughput. We demonstrate the technical validity of Shuffle-Seq and apply it to screening for mechanisms underlying drug resistance in a melanoma model. Shuffle-Seq should allow screens of hundreds of millions of combinatorial perturbations and facilitate the understanding of genetic dependencies and drug sensitivities.

scholarly journals Therapeutic targeting of SETD2-deficient cancer cells with the small-molecule compound RITA

2021 ◽  
Author(s):  
Kirsten A Lopez ◽  
Sovan Sarkar ◽  
Elena Seraia ◽  
Chiara Toffanin ◽  
Christian Cooper ◽  
...  
Keyword(s):  
Cancer Cells ◽  
Therapeutic Target ◽  
Therapeutic Strategy ◽  
Genetic Interaction ◽  
Synthetic Lethality ◽  
Replication Fork Progression ◽  
Stress Markers ◽  
Small Molecule Compound ◽  
Cancer Types ◽  
Novel Therapeutic

The histone methyltransferase SETD2 and its associated histone mark H3 lysine 36 trimethylation (H3K36me3) are frequently lost in certain cancer types, pinpointing SETD2 as an important therapeutic target. Here we show that SETD2-deficient cancer cells are profoundly sensitive to the compound RITA, resulting in significant p53 induction and apoptosis. This is further associated with defects in DNA replication, leading to delays in S-phase progression, increased recruitment of replication stress markers, and reduced replication fork progression. RITA sensitivity is linked to the phenol sulphotransferase SULT1A1, which we find to be highly upregulated in cells that lack SETD2. Depletion of SULT1A1 or addition of the phenol sulphotransferase inhibitor DCNP abolishes these phenotypes and suppresses the sensitivity of SETD2-deficient cancer cells, identifying SULT1A1 activity to be critical in mediating the potent cytotoxicity of RITA against SETD2-deficient cells. These findings define a novel therapeutic strategy for targeting the loss of SETD2 in cancer. Significance: The histone-modifying enzyme SETD2 has emerged as an important tumour suppressor in a number of different cancer types, identifying it as a promising therapeutic target. The concept of synthetic lethality, a genetic interaction in which the simultaneous loss of two genes or pathways that regulate a common essential process renders the cell nonviable, is a useful tool for killing cancer cells that have known mutations. In this study, we conducted a synthetic lethality screen for compounds that specifically target SETD2-deficient cancer cells. The top hit, a compound called RITA, reduces cell viability and induces cell death only in the context of SETD2 loss, thereby highlighting a potential novel therapeutic strategy for treating SETD2-deficient cancers.

scholarly journals VRK1 is a Paralog Synthetic Lethal Target in VRK2-methylated Glioblastoma

2022 ◽  
Author(s):  
Julie A Shields ◽  
Samuel R Meier ◽  
Madhavi Bandi ◽  
Maria Dam Ferdinez ◽  
Justin L Engel ◽  
...  
Keyword(s):  
Kinase Activity ◽  
Genetic Interaction ◽  
Synthetic Lethality ◽  
Cancer Therapeutics ◽  
Tumor Growth Inhibition ◽  
Synthetic Lethal Interaction ◽  
Synthetic Lethal ◽  
Aggressive Cancer ◽  
Nuclear Envelope Formation ◽  
Redundant Functions

Synthetic lethality - a genetic interaction that results in cell death when two genetic deficiencies co-occur but not when either deficiency occurs alone - can be co-opted for cancer therapeutics. A pair of paralog genes is among the most straightforward synthetic lethal interaction by virtue of their redundant functions. Here we demonstrate a paralog-based synthetic lethality by targeting Vaccinia-Related Kinase 1 (VRK1) in Vaccinia-Related Kinase 2 (VRK2)-methylated glioblastoma (GBM). VRK2 is silenced by promoter methylation in approximately two-thirds of GBM, an aggressive cancer with few available targeted therapies. Genetic knockdown of VRK1 in VRK2-null or VRK2-methylated cells results in decreased activity of the downstream substrate Barrier to Autointegration Factor (BAF), a regulator of post-mitotic nuclear envelope formation. VRK1 knockdown, and thus reduced BAF activity, causes nuclear lobulation, blebbing and micronucleation, which subsequently results in G2/M arrest and DNA damage. The VRK1-VRK2 synthetic lethal interaction is dependent on VRK1 kinase activity and is rescued by ectopic VRK2 expression. Knockdown of VRK1 leads to robust tumor growth inhibition in VRK2-methylated GBM xenografts. These results indicate that inhibiting VRK1 kinase activity could be a viable therapeutic strategy in VRK2-methylated GBM.

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