Abstract B08: Beyond synthetic lethality: Multiple mechanisms can explain genetic interactions within childhood cancer

2020 ◽  
Author(s):  
Josephine T. Daub ◽  
Saman Amini ◽  
Frank C.P. Holstege ◽  
Patrick Kemmeren
Keyword(s):  
Childhood Cancer ◽  
Synthetic Lethality ◽  
Genetic Interactions

scholarly journals A comprehensive map of genetic interactions in childhood cancer reveals multiple underlying biological mechanisms

2020 ◽  
Author(s):  
Josephine T. Daub ◽  
Saman Amini ◽  
Denise J.E. Kersjes ◽  
Xiaotu Ma ◽  
Natalie Jäger ◽  
...  
Keyword(s):  
Childhood Cancer ◽  
Genetic Interaction ◽  
Synthetic Lethality ◽  
Child Death ◽  
Developed Countries ◽  
Genetic Interactions ◽  
Cancer Development ◽  
Biological Mechanisms ◽  
Treatment Research ◽  
Interaction Map

AbstractChildhood cancer is a major cause of child death in developed countries. Genetic interactions between mutated genes play an important role in cancer development. They can be detected by searching for pairs of mutated genes that co-occur more (or less) often than expected. Co-occurrence suggests a cooperative role in cancer development, while mutual exclusivity points to synthetic lethality, a phenomenon of interest in cancer treatment research. Little is known about genetic interactions in childhood cancer. We apply a statistical pipeline to detect genetic interactions in a combined dataset comprising over 2,500 tumors from 23 cancer types. The resulting genetic interaction map of childhood cancers comprises 15 co-occurring and 27 mutually exclusive candidates. The biological mechanisms underlying most candidates are either tumor subtype, pathway epistasis or cooperation while synthetic lethality plays a much smaller role. Thus, other explanations beyond synthetic lethality should be considered when interpreting results of genetic interaction tests.

scholarly journals A systematic analysis of genetic interactions and their underlying biology in childhood cancer

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Josephine T. Daub ◽  
Saman Amini ◽  
Denise J. E. Kersjes ◽  
Xiaotu Ma ◽  
Natalie Jäger ◽  
...  
Keyword(s):  
Childhood Cancer ◽  
Genetic Interaction ◽  
Synthetic Lethality ◽  
Child Death ◽  
Developed Countries ◽  
Genetic Interactions ◽  
Cancer Development ◽  
Systematic Analysis ◽  
Treatment Research ◽  
Interaction Map

AbstractChildhood cancer is a major cause of child death in developed countries. Genetic interactions between mutated genes play an important role in cancer development. They can be detected by searching for pairs of mutated genes that co-occur more (or less) often than expected. Co-occurrence suggests a cooperative role in cancer development, while mutual exclusivity points to synthetic lethality, a phenomenon of interest in cancer treatment research. Little is known about genetic interactions in childhood cancer. We apply a statistical pipeline to detect genetic interactions in a combined dataset comprising over 2,500 tumors from 23 cancer types. The resulting genetic interaction map of childhood cancers comprises 15 co-occurring and 27 mutually exclusive candidates. The biological explanation of most candidates points to either tumor subtype, pathway epistasis or cooperation while synthetic lethality plays a much smaller role. Thus, other explanations beyond synthetic lethality should be considered when interpreting genetic interaction test results.

scholarly journals Synthetic Lethality with the dut Defect in Escherichia coli Reveals Layers of DNA Damage of Increasing Complexity Due to Uracil Incorporation

2008 ◽  
Vol 190 (17) ◽  
pp. 5841-5854 ◽  
Author(s):  
Helen Ting ◽  
Elena A. Kouzminova ◽  
Andrei Kuzminov
Keyword(s):  
Escherichia Coli ◽  
Dna Repair ◽  
Metabolic Pathways ◽  
Synthetic Lethality ◽  
Nucleotide Metabolism ◽  
Genetic Interactions ◽  
Single Defect ◽  
Damage Repair ◽  
Mutant Combination ◽  
Dna Incorporation

ABSTRACT Synthetic lethality is inviability of a double-mutant combination of two fully viable single mutants, commonly interpreted as redundancy at an essential metabolic step. The dut-1 defect in Escherichia coli inactivates dUTPase, causing increased uracil incorporation in DNA and known synthetic lethalities [SL(dut) mutations]. According to the redundancy logic, most of these SL(dut) mutations should affect nucleotide metabolism. After a systematic search for SL(dut) mutants, we did identify a single defect in the DNA precursor metabolism, inactivating thymidine kinase (tdk), that confirmed the redundancy explanation of synthetic lethality. However, we found that the bulk of mutations interacting genetically with dut are in DNA repair, revealing layers of damage of increasing complexity that uracil-DNA incorporation sends through the chromosomal metabolism. Thus, we isolated mutants in functions involved in (i) uracil-DNA excision (ung, polA, and xthA); (ii) double-strand DNA break repair (recA, recBC, and ruvABC); and (iii) chromosomal-dimer resolution (xerC, xerD, and ftsK). These mutants in various DNA repair transactions cannot be redundant with dUTPase and instead reveal “defect-damage-repair” cycles linking unrelated metabolic pathways. In addition, two SL(dut) inserts (phoU and degP) identify functions that could act to support the weakened activity of the Dut-1 mutant enzyme, suggesting the “compensation” explanation for this synthetic lethality. We conclude that genetic interactions with dut can be explained by redundancy, by defect-damage-repair cycles, or as compensation.

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.

Beyond Synthetic Lethality: Charting the Landscape of Clinically Relevant Genetic Interactions in Cancer

2019 ◽  
Author(s):  
Assaf Magen ◽  
Avinash Das ◽  
Joo Sang Lee ◽  
Mahfuza Sharmin ◽  
Alexander Lugo ◽  
...  
Keyword(s):  
Synthetic Lethality ◽  
Genetic Interactions

Abstract 2235: A comprehensive map of genetic interactions in childhood cancer reveals multiple underlying biological mechanisms

2021 ◽  
Author(s):  
Josephine Daub ◽  
Saman Amini ◽  
Xiaotu Ma ◽  
Natalie Jager ◽  
Jinghui Zhang ◽  
...  
Keyword(s):  
Childhood Cancer ◽  
Genetic Interactions ◽  
Biological Mechanisms

scholarly journals Genetic evidence for functional interactions between actin noncomplementing (Anc) gene products and actin cytoskeletal proteins in Saccharomyces cerevisiae.

Genetics ◽  
1993 ◽  
Vol 135 (2) ◽  
pp. 275-286
Author(s):  
D B Vinh ◽  
M D Welch ◽  
A K Corsi ◽  
K F Wertman ◽  
D G Drubin
Keyword(s):  
Synthetic Lethality ◽  
Binding Protein ◽  
Cytoskeletal Proteins ◽  
Genetic Interactions ◽  
Null Alleles ◽  
Actin Binding ◽  
Gene Products ◽  
Actin Binding Protein ◽  
Functional Interactions ◽  
Allele Specific

Abstract We describe here genetic interactions between mutant alleles of Actin-NonComplementing (ANC) genes and actin (ACT1) or actin-binding protein (SAC6, ABP1, TPM1) genes. The anc mutations were found to exhibit allele-specific noncomplementing interactions with different act1 mutations. In addition, mutant alleles of four ANC genes (ANC1, ANC2, ANC3 and ANC4) were tested for interactions with null alleles of actin-binding protein genes. An anc1 mutant allele failed to complement null alleles of the SAC6 and TPM1 genes that encode yeast fimbrin and tropomyosin, respectively. Also, synthetic lethality between anc3 and sac6 mutations, and between anc4 and tpm1 mutations was observed. Taken together, the above results strongly suggest that the ANC gene products contribute to diverse aspects of actin function. Finally, we report the results of tests of two models previously proposed to explain extragenic noncomplementation.

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 Common computational tools for analyzing CRISPR screens

2021 ◽  
Author(s):  
Medina Colic ◽  
Traver Hart
Keyword(s):  
Drug Resistance ◽  
Genome Editing ◽  
Analytical Methods ◽  
Computational Analysis ◽  
Synthetic Lethality ◽  
Genetic Interactions ◽  
Computational Tools ◽  
Genome Regulation ◽  
Rna Targeting ◽  
State Of Art

CRISPR–Cas technology offers a versatile toolbox for genome editing, with applications in various cancer-related fields such as functional genomics, immunotherapy, synthetic lethality and drug resistance, metastasis, genome regulation, chromatic accessibility and RNA-targeting. The variety of screening platforms and questions in which they are used have caused the development of a wide array of analytical methods for CRISPR analysis. In this review, we focus on the algorithms and frameworks used in the computational analysis of pooled CRISPR knockout (KO) screens and highlight some of the most significant target discoveries made using these methods. Lastly, we offer perspectives on the design and analysis of state-of-art multiplex screening for genetic interactions.

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