Context-dependent genetic interactions in cancer

Henkel, Luisa; Rauscher, Benedikt; Boutros, Michael

doi:10.1016/j.gde.2019.03.004

Cited by 19 publications

(19 citation statements)

References 61 publications

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“…It has become clear that many synthetic lethal interactions operate only within specific genetic backgrounds or contexts (Ryan et al , 2018; Henkel et al , 2019; Lord et al , 2020; Ku et al , 2020). Interactions that are observed in multiple cell lines are more likely to be robust in the face of the molecular heterogeneity that exists in tumours, and consequently may be of significantly greater therapeutic importance (Ryan et al , 2018).…”

Section: Resultsmentioning

confidence: 99%

“…robust to cancer type and genetic background. There are likely additional context-specific synthetic lethal relationships (Ryan et al , 2018; Henkel et al , 2019) among our candidate paralog pairs but we cannot detect them here. In contrast, the paralog pairs screened by Thompson et al and Dede et al, who both tested three different cell lines, are initially called SL in a cell-line specific fashion.…”

Section: Discussionmentioning

confidence: 97%

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Comprehensive prediction of robust synthetic lethality between paralog pairs in cancer cell lines

Kegel

Quinn

Thompson

et al. 2020

Preprint

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Pairs of paralogs may share common functionality and hence display synthetic lethal interactions. As the majority of human genes have an identifiable paralog, exploiting synthetic lethality between paralogs may be a broadly applicable approach for targeting gene loss in cancer. However, only a minority of human paralog pairs have been tested for synthetic lethality to date and the factors predictive of synthetic lethality are largely unknown. Here we derive a set of synthetic lethal paralog pairs by integrating molecular profiling data with CRISPR screens in cancer cell lines. Using this resource we identify a number of features that are individually predictive of synthetic lethality between paralogs, including shared protein-protein interactions and evolutionary conservation. We develop a machine-learning classifier to predict, with explanations, which paralog pairs are most likely to be synthetic lethal. We show that our classifier accurately predicts the results of combinatorial CRISPR screens in cancer cell lines and furthermore can distinguish pairs that are synthetic lethal in multiple cell lines from those that are cell-line specific.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 97%

Comprehensive prediction of robust synthetic lethality between paralog pairs in cancer cell lines

Kegel

Quinn

Thompson

et al. 2020

Preprint

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show abstract

“…Molecular assays, however, rely on markers that often exhibit extensive disparities across model systems, and are subject to cellular context-specific modulation [21,22,23]. E-cadherin expression and membrane localization, often gauged in clinical specimens by immuno-histochemical scoring, were exclusively associated with the lack of metastasis [24,25,26]; however, the detection of this adherens junction molecule in collectively metastasizing cells challenges its inverse correlation with dissemination [27,28].…”

Section: Snapshot Assays For Metastasis Assessmentmentioning

confidence: 99%

Uncoupling Traditional Functionalities of Metastasis: The Parting of Ways with Real-Time Assays

Varankar

Bapat

2019

JCM

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The experimental evaluation of metastasis overly focuses on the gain of migratory and invasive properties, while disregarding the contributions of cellular plasticity, extra-cellular matrix heterogeneity, niche interactions, and tissue architecture. Traditional cell-based assays often restrict the inclusion of these processes and warrant the implementation of approaches that provide an enhanced spatiotemporal resolution of the metastatic cascade. Time lapse imaging represents such an underutilized approach in cancer biology, especially in the context of disease progression. The inclusion of time lapse microscopy and microfluidic devices in routine assays has recently discerned several nuances of the metastatic cascade. Our review emphasizes that a complete comprehension of metastasis in view of evolving ideologies necessitates (i) the use of appropriate, context-specific assays and understanding their inherent limitations; (ii) cautious derivation of inferences to avoid erroneous/overestimated clinical extrapolations; (iii) corroboration between multiple assay outputs to gauge metastatic potential; and (iv) the development of protocols with improved in situ implications. We further believe that the adoption of improved quantitative approaches in these assays can generate predictive algorithms that may expedite therapeutic strategies targeting metastasis via the development of disease relevant model systems. Such approaches could potentiate the restructuring of the cancer metastasis paradigm through an emphasis on the development of next-generation real-time assays.

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“…Similarly, various mathematical approaches and modeling have been helpful in deciphering the significant genes and molecular networks associated with the spectrum of epithelial and mesenchymal states, as well as phenotypic plasticity (Jolly et al, 2017;Bocci et al, 2018;Jia et al, 2019;Yang et al, 2019). However, it is crucial to acknowledge that the modalities and analytical approaches utilized in the field of EMP present context-specific studies, such that inferences derived will not provide an overarching conclusion (Henkel et al, 2019). Inherent limitations of the employed assays should always be taken into consideration while extrapolating from the data.…”

Section: Current Modalities To Investigate Plasticitymentioning

confidence: 99%

New Insights Into the Role of Phenotypic Plasticity and EMT in Driving Cancer Progression

Bhatia

Wang

Toh

et al. 2020

Front. Mol. Biosci.

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Tumor cells demonstrate substantial plasticity in their genotypic and phenotypic characteristics. Epithelial-mesenchymal plasticity (EMP) can be characterized into dynamic intermediate states and can be orchestrated by many factors, either intercellularly via epigenetic reprograming, or extracellularly via growth factors, inflammation and/or hypoxia generated by the tumor stromal microenvironment. EMP has the capability to alter phenotype and produce heterogeneity, and thus by changing the whole cancer landscape can attenuate oncogenic signaling networks, invoke antiapoptotic features, defend against chemotherapeutics and reprogram angiogenic and immune recognition functions. We discuss here the role of phenotypic plasticity in tumor initiation, progression and metastasis and provide an update of the modalities utilized for the molecular characterization of the EMT states and attributes of cellular behavior, including cellular metabolism, in the context of EMP. We also summarize recent findings in dynamic EMP studies that provide new insights into the phenotypic plasticity of EMP flux in cancer and propose therapeutic strategies to impede the metastatic outgrowth of phenotypically heterogeneous tumors.

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Context-dependent genetic interactions in cancer

Cited by 19 publications

References 61 publications

Comprehensive prediction of robust synthetic lethality between paralog pairs in cancer cell lines

Comprehensive prediction of robust synthetic lethality between paralog pairs in cancer cell lines

Uncoupling Traditional Functionalities of Metastasis: The Parting of Ways with Real-Time Assays

New Insights Into the Role of Phenotypic Plasticity and EMT in Driving Cancer Progression

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