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. 2017 May 1;24(3):513-519.
doi: 10.1093/jamia/ocw148.

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

Linda Huang  1   2 , Helen Fernandes  1   3 , Hamid Zia  1   3 , Peyman Tavassoli  1   3 , Hanna Rennert  3 , David Pisapia  1   3 , Marcin Imielinski  1   3 , Andrea Sboner  1   2   3 , Mark A Rubin  1   3 , Michael Kluk  1   3 , Olivier Elemento  1   2
Affiliations

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

Linda Huang et al. J Am Med Inform Assoc. .

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.

Keywords: application-programming interface; cancer genomics; clinical reporting; database; pathology; precision medicine.

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Figures

Figure 1.
Figure 1.
Diagram of the variant description data types.
Figure 2.
Figure 2.
Illustration of information returned by the PMKB API when querying a variant.
Figure 3.
Figure 3.
Screenshots of (a) the interface for entering an interpretation in PMKB, and (b) summary view of an interpretation after entry/edit. This also demonstrates how PubMed IDs in the citations entry were resolved to complete citations in the display.
Figure 4.
Figure 4.
Growth of the knowledge base over time. Entries created prior to December 2015 represent work that IPM pathologists had saved in Excel spreadsheets. Currently, a small team at the IPM makes contributions to PMKB, and expansion in PMKB’s user base could result in a much higher rate of growth.
Figure 5.
Figure 5.
(a) The top 10 genes in PMKB when ranked by number of variant descriptions in the database. (b) The top 10 genes in PMKB when ranked by number of interpretations in the database. The prevalence of certain genes in PMKB naturally corresponds to genes that have well-studied variants with possible diagnostic use. (c) The top 10 solid tumor types in PMKB when ranked by number of interpretations.
See this image and copyright information in PMC

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