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Integrative analysis of large-scale loss-of-function screens identifies robust cancer-associated genetic interactions
Genetic interactions, including 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....
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7289598/ https://www.ncbi.nlm.nih.gov/pubmed/32463358 http://dx.doi.org/10.7554/eLife.58925 |
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author | Lord, Christopher J Quinn, Niall Ryan, Colm J |
author_facet | Lord, Christopher J Quinn, Niall Ryan, Colm J |
author_sort | Lord, Christopher J |
collection | PubMed |
description | Genetic interactions, including 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. Here, by developing a new computational approach, we identified 220 robust driver-gene associated genetic interactions that can be reproduced across independent experiments and across non-overlapping cell line panels. Analysis of these interactions demonstrated that: (i) oncogene addiction effects are more robust than oncogene-related synthetic lethal effects; and (ii) robust genetic interactions are enriched among gene pairs whose protein products physically interact. Exploiting the latter observation, we used a protein–protein interaction network to identify robust synthetic lethal effects associated with passenger gene alterations and validated two new synthetic lethal effects. Our results suggest that protein–protein interaction networks can be used to prioritise therapeutic targets that will be more robust to tumour heterogeneity. |
format | Online Article Text |
id | pubmed-7289598 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-72895982020-06-15 Integrative analysis of large-scale loss-of-function screens identifies robust cancer-associated genetic interactions Lord, Christopher J Quinn, Niall Ryan, Colm J eLife Cancer Biology Genetic interactions, including 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. Here, by developing a new computational approach, we identified 220 robust driver-gene associated genetic interactions that can be reproduced across independent experiments and across non-overlapping cell line panels. Analysis of these interactions demonstrated that: (i) oncogene addiction effects are more robust than oncogene-related synthetic lethal effects; and (ii) robust genetic interactions are enriched among gene pairs whose protein products physically interact. Exploiting the latter observation, we used a protein–protein interaction network to identify robust synthetic lethal effects associated with passenger gene alterations and validated two new synthetic lethal effects. Our results suggest that protein–protein interaction networks can be used to prioritise therapeutic targets that will be more robust to tumour heterogeneity. eLife Sciences Publications, Ltd 2020-05-28 /pmc/articles/PMC7289598/ /pubmed/32463358 http://dx.doi.org/10.7554/eLife.58925 Text en © 2020, Lord et al http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Cancer Biology Lord, Christopher J Quinn, Niall Ryan, Colm J Integrative analysis of large-scale loss-of-function screens identifies robust cancer-associated genetic interactions |
title | Integrative analysis of large-scale loss-of-function screens identifies robust cancer-associated genetic interactions |
title_full | Integrative analysis of large-scale loss-of-function screens identifies robust cancer-associated genetic interactions |
title_fullStr | Integrative analysis of large-scale loss-of-function screens identifies robust cancer-associated genetic interactions |
title_full_unstemmed | Integrative analysis of large-scale loss-of-function screens identifies robust cancer-associated genetic interactions |
title_short | Integrative analysis of large-scale loss-of-function screens identifies robust cancer-associated genetic interactions |
title_sort | integrative analysis of large-scale loss-of-function screens identifies robust cancer-associated genetic interactions |
topic | Cancer Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7289598/ https://www.ncbi.nlm.nih.gov/pubmed/32463358 http://dx.doi.org/10.7554/eLife.58925 |
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