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Project Score database: a resource for investigating cancer cell dependencies and prioritizing therapeutic targets
CRISPR genetic screens in cancer cell models are a powerful tool to elucidate oncogenic mechanisms and to identify promising therapeutic targets. The Project Score database (https://score.depmap.sanger.ac.uk/) uses genome-wide CRISPR–Cas9 dropout screening data in hundreds of highly annotated cancer...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7778984/ https://www.ncbi.nlm.nih.gov/pubmed/33068406 http://dx.doi.org/10.1093/nar/gkaa882 |
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author | Dwane, Lisa Behan, Fiona M Gonçalves, Emanuel Lightfoot, Howard Yang, Wanjuan van der Meer, Dieudonne Shepherd, Rebecca Pignatelli, Miguel Iorio, Francesco Garnett, Mathew J |
author_facet | Dwane, Lisa Behan, Fiona M Gonçalves, Emanuel Lightfoot, Howard Yang, Wanjuan van der Meer, Dieudonne Shepherd, Rebecca Pignatelli, Miguel Iorio, Francesco Garnett, Mathew J |
author_sort | Dwane, Lisa |
collection | PubMed |
description | CRISPR genetic screens in cancer cell models are a powerful tool to elucidate oncogenic mechanisms and to identify promising therapeutic targets. The Project Score database (https://score.depmap.sanger.ac.uk/) uses genome-wide CRISPR–Cas9 dropout screening data in hundreds of highly annotated cancer cell models to identify genes required for cell fitness and prioritize novel oncology targets. The Project Score database currently allows users to investigate the fitness effect of 18 009 genes tested across 323 cancer cell models. Through interactive interfaces, users can investigate data by selecting a specific gene, cancer cell model or tissue type, as well as browsing all gene fitness scores. Additionally, users can identify and rank candidate drug targets based on an established oncology target prioritization pipeline, incorporating genetic biomarkers and clinical datasets for each target, and including suitability for drug development based on pharmaceutical tractability. Data are freely available and downloadable. To enhance analyses, links to other key resources including Open Targets, COSMIC, the Cell Model Passports, UniProt and the Genomics of Drug Sensitivity in Cancer are provided. The Project Score database is a valuable new tool for investigating genetic dependencies in cancer cells and the identification of candidate oncology targets. |
format | Online Article Text |
id | pubmed-7778984 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-77789842021-01-06 Project Score database: a resource for investigating cancer cell dependencies and prioritizing therapeutic targets Dwane, Lisa Behan, Fiona M Gonçalves, Emanuel Lightfoot, Howard Yang, Wanjuan van der Meer, Dieudonne Shepherd, Rebecca Pignatelli, Miguel Iorio, Francesco Garnett, Mathew J Nucleic Acids Res Database Issue CRISPR genetic screens in cancer cell models are a powerful tool to elucidate oncogenic mechanisms and to identify promising therapeutic targets. The Project Score database (https://score.depmap.sanger.ac.uk/) uses genome-wide CRISPR–Cas9 dropout screening data in hundreds of highly annotated cancer cell models to identify genes required for cell fitness and prioritize novel oncology targets. The Project Score database currently allows users to investigate the fitness effect of 18 009 genes tested across 323 cancer cell models. Through interactive interfaces, users can investigate data by selecting a specific gene, cancer cell model or tissue type, as well as browsing all gene fitness scores. Additionally, users can identify and rank candidate drug targets based on an established oncology target prioritization pipeline, incorporating genetic biomarkers and clinical datasets for each target, and including suitability for drug development based on pharmaceutical tractability. Data are freely available and downloadable. To enhance analyses, links to other key resources including Open Targets, COSMIC, the Cell Model Passports, UniProt and the Genomics of Drug Sensitivity in Cancer are provided. The Project Score database is a valuable new tool for investigating genetic dependencies in cancer cells and the identification of candidate oncology targets. Oxford University Press 2020-10-17 /pmc/articles/PMC7778984/ /pubmed/33068406 http://dx.doi.org/10.1093/nar/gkaa882 Text en © The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Database Issue Dwane, Lisa Behan, Fiona M Gonçalves, Emanuel Lightfoot, Howard Yang, Wanjuan van der Meer, Dieudonne Shepherd, Rebecca Pignatelli, Miguel Iorio, Francesco Garnett, Mathew J Project Score database: a resource for investigating cancer cell dependencies and prioritizing therapeutic targets |
title | Project Score database: a resource for investigating cancer cell dependencies and prioritizing therapeutic targets |
title_full | Project Score database: a resource for investigating cancer cell dependencies and prioritizing therapeutic targets |
title_fullStr | Project Score database: a resource for investigating cancer cell dependencies and prioritizing therapeutic targets |
title_full_unstemmed | Project Score database: a resource for investigating cancer cell dependencies and prioritizing therapeutic targets |
title_short | Project Score database: a resource for investigating cancer cell dependencies and prioritizing therapeutic targets |
title_sort | project score database: a resource for investigating cancer cell dependencies and prioritizing therapeutic targets |
topic | Database Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7778984/ https://www.ncbi.nlm.nih.gov/pubmed/33068406 http://dx.doi.org/10.1093/nar/gkaa882 |
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