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The cancer precision medicine knowledge base for structured clinical-grade mutations and interpretations
Objective: This paper describes the Precision Medicine Knowledge Base (PMKB; https://pmkb.weill.cornell.edu), an interactive online application for collaborative editing, maintenance, and sharing of structured clinical-grade cancer mutation interpretations. Materials and Methods: PMKB was built usin...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5391733/ https://www.ncbi.nlm.nih.gov/pubmed/27789569 http://dx.doi.org/10.1093/jamia/ocw148 |
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author | Huang, Linda Fernandes, Helen Zia, Hamid Tavassoli, Peyman Rennert, Hanna Pisapia, David Imielinski, Marcin Sboner, Andrea Rubin, Mark A Kluk, Michael Elemento, Olivier |
author_facet | Huang, Linda Fernandes, Helen Zia, Hamid Tavassoli, Peyman Rennert, Hanna Pisapia, David Imielinski, Marcin Sboner, Andrea Rubin, Mark A Kluk, Michael Elemento, Olivier |
author_sort | Huang, Linda |
collection | PubMed |
description | Objective: This paper describes the Precision Medicine Knowledge Base (PMKB; https://pmkb.weill.cornell.edu), an interactive online application for collaborative editing, maintenance, and sharing of structured clinical-grade cancer mutation interpretations. Materials and Methods: PMKB was built using the Ruby on Rails Web application framework. Leveraging existing standards such as the Human Genome Variation Society variant description format, we implemented a data model that links variants to tumor-specific and tissue-specific interpretations. Key features of PMKB include support for all major variant types, standardized authentication, distinct user roles including high-level approvers, and detailed activity history. A REpresentational State Transfer (REST) application-programming interface (API) was implemented to query the PMKB programmatically. Results: At the time of writing, PMKB contains 457 variant descriptions with 281 clinical-grade interpretations. The EGFR, BRAF, KRAS, and KIT genes are associated with the largest numbers of interpretable variants. PMKB’s interpretations have been used in over 1500 AmpliSeq tests and 750 whole-exome sequencing tests. The interpretations are accessed either directly via the Web interface or programmatically via the existing API. Discussion: An accurate and up-to-date knowledge base of genomic alterations of clinical significance is critical to the success of precision medicine programs. The open-access, programmatically accessible PMKB represents an important attempt at creating such a resource in the field of oncology. Conclusion: The PMKB was designed to help collect and maintain clinical-grade mutation interpretations and facilitate reporting for clinical cancer genomic testing. The PMKB was also designed to enable the creation of clinical cancer genomics automated reporting pipelines via an API. |
format | Online Article Text |
id | pubmed-5391733 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-53917332017-04-21 The cancer precision medicine knowledge base for structured clinical-grade mutations and interpretations Huang, Linda Fernandes, Helen Zia, Hamid Tavassoli, Peyman Rennert, Hanna Pisapia, David Imielinski, Marcin Sboner, Andrea Rubin, Mark A Kluk, Michael Elemento, Olivier J Am Med Inform Assoc Research and Applications Objective: This paper describes the Precision Medicine Knowledge Base (PMKB; https://pmkb.weill.cornell.edu), an interactive online application for collaborative editing, maintenance, and sharing of structured clinical-grade cancer mutation interpretations. Materials and Methods: PMKB was built using the Ruby on Rails Web application framework. Leveraging existing standards such as the Human Genome Variation Society variant description format, we implemented a data model that links variants to tumor-specific and tissue-specific interpretations. Key features of PMKB include support for all major variant types, standardized authentication, distinct user roles including high-level approvers, and detailed activity history. A REpresentational State Transfer (REST) application-programming interface (API) was implemented to query the PMKB programmatically. Results: At the time of writing, PMKB contains 457 variant descriptions with 281 clinical-grade interpretations. The EGFR, BRAF, KRAS, and KIT genes are associated with the largest numbers of interpretable variants. PMKB’s interpretations have been used in over 1500 AmpliSeq tests and 750 whole-exome sequencing tests. The interpretations are accessed either directly via the Web interface or programmatically via the existing API. Discussion: An accurate and up-to-date knowledge base of genomic alterations of clinical significance is critical to the success of precision medicine programs. The open-access, programmatically accessible PMKB represents an important attempt at creating such a resource in the field of oncology. Conclusion: The PMKB was designed to help collect and maintain clinical-grade mutation interpretations and facilitate reporting for clinical cancer genomic testing. The PMKB was also designed to enable the creation of clinical cancer genomics automated reporting pipelines via an API. Oxford University Press 2017-05 2016-10-27 /pmc/articles/PMC5391733/ /pubmed/27789569 http://dx.doi.org/10.1093/jamia/ocw148 Text en © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Research and Applications Huang, Linda Fernandes, Helen Zia, Hamid Tavassoli, Peyman Rennert, Hanna Pisapia, David Imielinski, Marcin Sboner, Andrea Rubin, Mark A Kluk, Michael Elemento, Olivier The cancer precision medicine knowledge base for structured clinical-grade mutations and interpretations |
title | The cancer precision medicine knowledge base for structured clinical-grade mutations and interpretations |
title_full | The cancer precision medicine knowledge base for structured clinical-grade mutations and interpretations |
title_fullStr | The cancer precision medicine knowledge base for structured clinical-grade mutations and interpretations |
title_full_unstemmed | The cancer precision medicine knowledge base for structured clinical-grade mutations and interpretations |
title_short | The cancer precision medicine knowledge base for structured clinical-grade mutations and interpretations |
title_sort | cancer precision medicine knowledge base for structured clinical-grade mutations and interpretations |
topic | Research and Applications |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5391733/ https://www.ncbi.nlm.nih.gov/pubmed/27789569 http://dx.doi.org/10.1093/jamia/ocw148 |
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