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The cancer precision medicine knowledge base for structured clinical-grade mutations and interpretations

View Article: PubMed Central - PubMed

ABSTRACT

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.

No MeSH data available.


Illustration of information returned by the PMKB API when querying a variant.
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ocw148-F2: Illustration of information returned by the PMKB API when querying a variant.

Mentions: Separating variant descriptions into discrete fields facilitates the process of matching them against existing annotations. PMKB’s REpresentational State Transfer (REST) API is set up to take a variant’s HGVS protein notation as input and match that variant against multiple levels of variant descriptions, then return all relevant interpretations. For example, in the case of a mutation, PMKB’s REST API would take KRAS p.G12A as input (Figure 2) and match it against all KRAS mutations in its database. This API query could return interpretations for KRAS p.G12A, KRAS codon 12 missense, KRAS exon 2 missense, KRAS exon 2 any mutation, and KRAS any mutation (Figure 2). These matches are ranked in order of specificity, based on the width of the sequence they fall in and whether the variant type is a match or “any.” Extra fields in the search query can make PMKB return only those interpretations that are linked to a specific tumor type and tissue type, if desired.Figure 2.


The cancer precision medicine knowledge base for structured clinical-grade mutations and interpretations
Illustration of information returned by the PMKB API when querying a variant.
© Copyright Policy - cc-by-nc
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5391733&req=5

ocw148-F2: Illustration of information returned by the PMKB API when querying a variant.
Mentions: Separating variant descriptions into discrete fields facilitates the process of matching them against existing annotations. PMKB’s REpresentational State Transfer (REST) API is set up to take a variant’s HGVS protein notation as input and match that variant against multiple levels of variant descriptions, then return all relevant interpretations. For example, in the case of a mutation, PMKB’s REST API would take KRAS p.G12A as input (Figure 2) and match it against all KRAS mutations in its database. This API query could return interpretations for KRAS p.G12A, KRAS codon 12 missense, KRAS exon 2 missense, KRAS exon 2 any mutation, and KRAS any mutation (Figure 2). These matches are ranked in order of specificity, based on the width of the sequence they fall in and whether the variant type is a match or “any.” Extra fields in the search query can make PMKB return only those interpretations that are linked to a specific tumor type and tissue type, if desired.Figure 2.

View Article: PubMed Central - PubMed

ABSTRACT

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.

No MeSH data available.