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Cell Model Passports—a hub for clinical, genetic and functional datasets of preclinical cancer models
In vitro cancer cell cultures are facile experimental models used widely for research and drug development. Many cancer cell lines are available and efforts are ongoing to derive new models representing the histopathological and molecular diversity of tumours. Cell models have been generated by mult...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6324059/ https://www.ncbi.nlm.nih.gov/pubmed/30260411 http://dx.doi.org/10.1093/nar/gky872 |
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author | van der Meer, Dieudonne Barthorpe, Syd Yang, Wanjuan Lightfoot, Howard Hall, Caitlin Gilbert, James Francies, Hayley E Garnett, Mathew J |
author_facet | van der Meer, Dieudonne Barthorpe, Syd Yang, Wanjuan Lightfoot, Howard Hall, Caitlin Gilbert, James Francies, Hayley E Garnett, Mathew J |
author_sort | van der Meer, Dieudonne |
collection | PubMed |
description | In vitro cancer cell cultures are facile experimental models used widely for research and drug development. Many cancer cell lines are available and efforts are ongoing to derive new models representing the histopathological and molecular diversity of tumours. Cell models have been generated by multiple laboratories over decades and consequently their annotation is incomplete and inconsistent. Furthermore, the relationships between many patient-matched and derivative cell lines have been lost, and accessing information and datasets is time-consuming and difficult. Here, we describe the Cell Model Passports database; cellmodelpassports.sanger.ac.uk, which provides details of cell model relationships, patient and clinical information, as well as access to associated genetic and functional datasets. The Passports database currently contains curated details and standardized annotation for >1200 cell models, including cancer organoid cultures. The Passports will be updated with newly derived cell models and datasets as they are generated. Users can navigate the database via tissue, cancer-type, genetic feature and data availability to select a model most suitable for specific applications. A flexible REST-API provides programmatic data access and exploration. The Cell Model Passports are a valuable tool enabling access to high-dimensional genomic and phenotypic cancer cell model datasets empowering diverse research applications. |
format | Online Article Text |
id | pubmed-6324059 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-63240592019-01-10 Cell Model Passports—a hub for clinical, genetic and functional datasets of preclinical cancer models van der Meer, Dieudonne Barthorpe, Syd Yang, Wanjuan Lightfoot, Howard Hall, Caitlin Gilbert, James Francies, Hayley E Garnett, Mathew J Nucleic Acids Res Database Issue In vitro cancer cell cultures are facile experimental models used widely for research and drug development. Many cancer cell lines are available and efforts are ongoing to derive new models representing the histopathological and molecular diversity of tumours. Cell models have been generated by multiple laboratories over decades and consequently their annotation is incomplete and inconsistent. Furthermore, the relationships between many patient-matched and derivative cell lines have been lost, and accessing information and datasets is time-consuming and difficult. Here, we describe the Cell Model Passports database; cellmodelpassports.sanger.ac.uk, which provides details of cell model relationships, patient and clinical information, as well as access to associated genetic and functional datasets. The Passports database currently contains curated details and standardized annotation for >1200 cell models, including cancer organoid cultures. The Passports will be updated with newly derived cell models and datasets as they are generated. Users can navigate the database via tissue, cancer-type, genetic feature and data availability to select a model most suitable for specific applications. A flexible REST-API provides programmatic data access and exploration. The Cell Model Passports are a valuable tool enabling access to high-dimensional genomic and phenotypic cancer cell model datasets empowering diverse research applications. Oxford University Press 2019-01-08 2018-09-27 /pmc/articles/PMC6324059/ /pubmed/30260411 http://dx.doi.org/10.1093/nar/gky872 Text en © The Author(s) 2018. 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 van der Meer, Dieudonne Barthorpe, Syd Yang, Wanjuan Lightfoot, Howard Hall, Caitlin Gilbert, James Francies, Hayley E Garnett, Mathew J Cell Model Passports—a hub for clinical, genetic and functional datasets of preclinical cancer models |
title | Cell Model Passports—a hub for clinical, genetic and functional datasets of preclinical cancer models |
title_full | Cell Model Passports—a hub for clinical, genetic and functional datasets of preclinical cancer models |
title_fullStr | Cell Model Passports—a hub for clinical, genetic and functional datasets of preclinical cancer models |
title_full_unstemmed | Cell Model Passports—a hub for clinical, genetic and functional datasets of preclinical cancer models |
title_short | Cell Model Passports—a hub for clinical, genetic and functional datasets of preclinical cancer models |
title_sort | cell model passports—a hub for clinical, genetic and functional datasets of preclinical cancer models |
topic | Database Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6324059/ https://www.ncbi.nlm.nih.gov/pubmed/30260411 http://dx.doi.org/10.1093/nar/gky872 |
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