Global Genetic Networks and the Genotype-to-Phenotype Relationship

Costanzo, Michael; Kuzmin, Elena; Leeuwen, Jolanda van; Mair, Barbara; Moffat, Jason; Boone, Charles; Andrews, Brenda

doi:10.1016/j.cell.2019.01.033

Cited by 208 publications

(170 citation statements)

References 113 publications

(256 reference statements)

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“…Indeed, recent work has illustrated the power of such screens in identifying new vulnerabilities to PARP and ATR inhibitors as well as to agents like temozolomide, a DNA alkylator (Hustedt et al, 2019a;MacLeod et al, 2019;Wang et al, 2018;Zimmermann et al, 2018). However, as these screens were carried out in isolation, they do not provide a global view of the human DNA damage response nor are they amenable to gene function inference by methods such as genetic interaction similarity profiling (Costanzo et al, 2019). We therefore aimed to map a genetic network of the response to DNA lesions and genotoxic agents, by undertaking 28 genome-scale CRISPR screens in an immortalized human diploid cell line (RPE-1 hTERT) that assessed the response to a wide variety of genotoxic agents that include multiple cancer therapeutics such as ionizing radiation, camptothecin, cisplatin and doxorubicin.…”

Section: Introductionmentioning

confidence: 99%

A genetic map of the response to DNA damage in human cells

Olivieri

Álvarez-Quilón

et al. 2019

Preprint

118

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The response to DNA damage is critical for cellular homeostasis, tumor suppression, immunity and gametogenesis. In order to provide an unbiased and global view of the DNA damage response in human cells, we undertook 28 CRISPR/Cas9 screens against 25 genotoxic agents in the retinal pigment epithelium-1 (RPE1) cell line. These screens identified 840 genes whose loss causes either sensitivity or resistance to DNA damaging agents. Mining this dataset, we uncovered that ERCC6L2, which is mutated in a bone-marrow failure syndrome, codes for a canonical non-homologous end-joining pathway factor; that the RNA polymerase II component ELOF1 modulates the response to transcription-blocking agents and that the cytotoxicity of the G-quadruplex ligand pyridostatin involves trapping topoisomerase II on DNA. This map of the DNA damage response provides a rich resource to study this fundamental cellular system and has implications for the development and use of genotoxic agents in cancer therapy.

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Section: Introductionmentioning

confidence: 99%

A genetic map of the response to DNA damage in human cells

Olivieri

Álvarez-Quilón

et al. 2019

Preprint

118

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“…The systematic mapping of GIs in model organisms like yeast has provided a detailed view into the functional organisation of eukaryotic cells (Costanzo et al , 2019). Recent advances in CRISPR-based genome engineering technologies provide a path for similar systematic GI studies in human cells (Horlbeck et al , 2018; Najm et al , 2018; Han et al , 2017; Norman et al , 2019; Shen et al , 2017).…”

Section: Discussionmentioning

confidence: 99%

Systematic mapping of genetic interactions for de novo fatty acid synthesis

Aregger

Billmann

et al. 2019

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28The de novo synthesis of fatty acids has emerged as a therapeutic target for various 29 diseases including cancer. While several translational efforts have focused on direct 30 perturbation of de novo fatty acid synthesis, only modest responses have been associated 31 with mono-therapies. Since cancer cells are intrinsically buffered to combat metabolic 32 stress, cells may adapt to loss of de novo fatty acid biosynthesis. To explore cellular 33 response to defects in fatty acid synthesis, we used pooled genome-wide CRISPR 34 screens to systematically map genetic interactions (GIs) in human HAP1 cells carrying a 35 loss-of-function mutation in FASN, which catalyzes the formation of long-chain fatty acids. 36FASN mutant cells showed a strong dependence on lipid uptake that was reflected by 37 negative GIs with genes involved in the LDL receptor pathway, vesicle trafficking, and 38 protein glycosylation. Further support for these functional relationships was derived from 39 additional GI screens in query cell lines deficient for other genes involved in lipid 40 metabolism, including LDLR, SREBF1, SREBF2, ACACA. Our GI profiles identified a 41 potential role for a previously uncharacterized gene LUR1 (C12orf49) in exogenous lipid 42 uptake regulation. Overall, our data highlights the genetic determinants underlying the 43 cellular adaptation associated with loss of de novo fatty acid synthesis and demonstrate 44 the power of systematic GI mapping for uncovering metabolic buffering mechanisms in 45 human cells. 65cells adapt to perturbation of de novo fatty acid synthesis could help identify new 66 targetable vulnerabilities that may inform novel therapeutic strategies or biomarker 67 approaches. 69Mapping genetic interaction (GI) networks provides a powerful approach for identifying the 70 functional relationships between genes and their corresponding pathways. The systematic 71 exploration of pairwise GIs in model organisms revealed that GIs often occur among 72 4 functionally related genes and that GI profiles organize a hierarchy of functional modules 73 (Costanzo et al, 2016; Fischer et al, 2015). Thus, GI mapping has become an effective 74 strategy for identifying functional modules and annotating the roles of previously 75 uncharacterized genes. Model organism GI mapping has also provided insight into the 76 mechanistic basis of cellular plasticity or phenotypic switching that occurs as cells evolve 77 within their environments (Harrison et al, 2007; Szappanos et al, 2011). Accordingly, the 78 insights gained through systematic interrogation of GIs have fuelled significant interest to 79 leverage these approaches towards functionally annotating the human genome. 81Recent technological advances using CRISPR-Cas enable the systematic mapping of GIs 82 in human cells (Wright et al, 2016; Doench, 2018). Here, we explore genome-wide GI 83 screens within the context of human query mutant cells defective for de novo fatty acid 84 synthesis. We systematically mapped genome-wide GI profiles for six genes involved in ...

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“…Complementation of gene functions by human homologs, and vice versa , has demonstrated evolutionary conservation of gene functions [285-287]. Like their basic functions, gene interactions are conserved [288,289] and yeast is unique in its capability to address complex genetic interactions experimentally [290]. Here, we model how yeast phenomic assessment of gene-drug interaction could be employed as part of a precision oncology paradigm to predict efficacy of cytotoxic chemotherapy based on the unique cancer genetic profiles of individual patients.…”

Section: Discussionmentioning

confidence: 99%

A humanized yeast phenomic model of deoxycytidine kinase to predict genetic buffering of nucleoside analog cytotoxicity

Santos

Icyuz

Pound

et al. 2019

Preprint

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10Knowledge about synthetic lethality can be applied to enhance the efficacy of 11 anti-cancer therapies in individual patients harboring genetic alterations in their cancer 12 that specifically render it vulnerable. We investigated the potential for high-resolution 13 phenomic analysis in yeast to predict such genetic vulnerabilities by systematic, 14 comprehensive, and quantitative assessment of drug-gene interaction for gemcitabine 15 and cytarabine, substrates of deoxycytidine kinase that have similar molecular structures 16 yet distinct anti-tumor efficacy. Human deoxycytidine kinase (dCK) was conditionally 17 expressed in the S. cerevisiae genomic library of knockout and knockdown (YKO/KD) 18 strains, to globally and quantitatively characterize differential drug-gene interaction for 19 gemcitabine and cytarabine. Pathway enrichment analysis revealed that autophagy, 20 histone modification, chromatin remodeling, and apoptosis-related processes influence 21 gemcitabine specifically, while drug-gene interaction specific to cytarabine was less 22 enriched in Gene Ontology. Processes having influence over both drugs were DNA 23 repair and integrity checkpoints and vesicle transport and fusion. Non-GO-enriched 24 genes were also informative. Yeast phenomic and cancer cell line pharmacogenomics 25 data were integrated to identify yeast-human homologs with correlated differential gene 26 2 expression and drug-efficacy, thus providing a unique resource to predict whether 27 differential gene expression observed in cancer genetic profiles are causal in tumor-28 specific responses to cytotoxic agents. 29 30 Keywords: 31 yeast phenomics, gene-drug interaction, genetic buffering, quantitative high 32 throughput cell array phenotyping (Q-HTCP), cell proliferation parameters (CPPs), 33 gemcitabine, cytarabine, recursive expectation-maximization clustering (REMc), 34 pharmacogenomics 35 36 Introduction: 37Genomics has enabled targeted therapy aimed at cancer driver genes and 38 oncogenic addiction [1], yet traditional cytotoxic chemotherapeutic agents remain among 39 the most widely used and efficacious anti-cancer therapies [2]. Changes in the genetic 40 network underlying cancer can produce vulnerabilities to cytotoxic chemotherapy that 41 further influence the therapeutic window and provide additional insight into their 42 mechanisms of action [3,4]. A potential advantage of so-called synthetic lethality-based 43 treatment strategies is that they could have efficacy against passenger gene mutation or 44 compensatory gene expression, while classic targeted therapies are directed primarily at 45 driver genes ( Fig. 1A). Quantitative high throughput cell array phenotyping of the yeast 46 knockout and knockdown libraries provides a phenomic means for systems level, high- 47resolution modeling of gene interaction [5][6][7][8][9], which is applied here to predict cancer-48 relevant drug-gene interaction through integration with cancer pharmacogenomics 49 resources ( Fig. 1B). 50Nucleoside analogs include a diverse group of co...

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Global Genetic Networks and the Genotype-to-Phenotype Relationship

Cited by 208 publications

References 113 publications

A genetic map of the response to DNA damage in human cells

A genetic map of the response to DNA damage in human cells

Systematic mapping of genetic interactions for de novo fatty acid synthesis

A humanized yeast phenomic model of deoxycytidine kinase to predict genetic buffering of nucleoside analog cytotoxicity

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