Skip to main content

COVID-19 is an emerging, rapidly evolving situation.

What people with cancer should know: https://www.cancer.gov/coronavirus

Guidance for cancer researchers: https://www.cancer.gov/coronavirus-researchers

Get the latest public health information from CDC: https://www.coronavirus.gov

Get the latest research information from NIH: https://www.nih.gov/coronavirus

Grant Details

Grant Number: 5U24CA237719-02 Interpret this number
Primary Investigator: Griffith, Obi
Organization: Washington University
Project Title: Standardized and Genome-Wide Clinical Interpretation of Complex Genotypes for Cancer Precision Medicine
Fiscal Year: 2020


Abstract

Project Summary/Abstract High-throughput molecular profiling technologies have allowed the systematic identification of molecular drivers of cancer for most major tumor types. Clinical and functional studies have correlated these drivers with patient outcomes and helped develop targeted therapies. However, maintaining current and comprehensive interpretations of the clinical significance of variants represents a major bottleneck. To address this challenge, the Clinical Interpretations of Variants in Cancer knowledgebase (CIViC; ​civicdb.org​) was created to provide a knowledge repository and sophisticated curation interface for expert-crowdsourcing the curation of actionable cancer variants. Importantly, all data are made freely available with a public domain license, daily and monthly data freezes, and public API. This has allowed widespread adoption of CIViC variant interpretations into many research tools for variant annotation as well as commercial and non-commercial report generation workflows. To date, these have focused predominantly on small mutations, detected through targeted sequencing panels, and assumed a single-target-to-single-therapy paradigm. As sequencing costs decrease, whole genome, transcriptome, and epigenome approaches will replace these targeted methods. This will allow increasingly unbiased assay of molecular alterations of most types (large and small) and will simultaneously replace many traditional cytogenetic assays. It will also dramatically increase the number of variants of potential and unknown clinical significance. Furthermore, our understanding has evolved to recognize that spatial and temporal tumor heterogeneity result in complex tumor genotypes of collaborating mutations that will require a more sophisticated decision support framework. To address these challenges, the CIViC data model will be extended to support: new frameworks for representing complex tumor genotypes; ACMG and AMP guidelines for both germline and somatic variant curation; and new evidence codes for assessing somatic variant oncogenicity. New user interfaces will be developed to support curation, browsing and searching of these features. Clinical collaborations will be extended to: (a) develop a distributable clinical-grade (CLIA-certified) analysis platform for comprehensive genomic profiling of patient samples using whole-genome sequencing; (b) support standardized somatic variant curation through the ClinGen Somatic Working group; and (c) integrate CIViC reports into the Personalized Oncogenomics (POG) trial. The proposal will address several key challenges including: 1) understanding the importance of integrating germline annotations with somatic cancer variant interpretations; 2) determining if a whole genome approach can replace existing targeted sequencing panels and cytogenetic assays; and 3) assessing the impact of a public variant interpretation knowledgebase on clinical decisions at molecular tumor board meetings. Finally, community outreach and training will be performed to develop online workshops, improve internship opportunities, and increase interaction with medical genetics fellows to train the next-generation of researchers in precision medicine informatics.



Publications

Neoadjuvant and Adjuvant Pembrolizumab in Resectable Locally Advanced, Human Papillomavirus-Unrelated Head and Neck Cancer: A Multicenter, Phase II Trial.
Authors: Uppaluri R. , Campbell K.M. , Egloff A.M. , Zolkind P. , Skidmore Z.L. , Nussenbaum B. , Paniello R.C. , Rich J.T. , Jackson R. , Pipkorn P. , et al. .
Source: Clinical cancer research : an official journal of the American Association for Cancer Research, 2020-10-01; 26(19), p. 5140-5152.
EPub date: 2020-07-14.
PMID: 32665297
Related Citations

Collaborative, Multidisciplinary Evaluation of Cancer Variants Through Virtual Molecular Tumor Boards Informs Local Clinical Practices.
Authors: Rao S. , Pitel B. , Wagner A.H. , Boca S.M. , McCoy M. , King I. , Gupta S. , Park B.H. , Warner J.L. , Chen J. , et al. .
Source: JCO clinical cancer informatics, 2020 Jul; 4, p. 602-613.
PMID: 32644817
Related Citations

A harmonized meta-knowledgebase of clinical interpretations of somatic genomic variants in cancer.
Authors: Wagner A.H. , Walsh B. , Mayfield G. , Tamborero D. , Sonkin D. , Krysiak K. , Deu-Pons J. , Duren R.P. , Gao J. , McMurry J. , et al. .
Source: Nature genetics, 2020 04; 52(4), p. 448-457.
EPub date: 2020-04-03.
PMID: 32246132
Related Citations

Wikidata as a knowledge graph for the life sciences.
Authors: Waagmeester A. , Stupp G. , Burgstaller-Muehlbacher S. , Good B.M. , Griffith M. , Griffith O.L. , Hanspers K. , Hermjakob H. , Hudson T.S. , Hybiske K. , et al. .
Source: eLife, 2020-03-17; 9, .
EPub date: 2020-03-17.
PMID: 32180547
Related Citations

CIViCpy: A Python Software Development and Analysis Toolkit for the CIViC Knowledgebase.
Authors: Wagner A.H. , Kiwala S. , Coffman A.C. , McMichael J.F. , Cotto K.C. , Mooney T.B. , Barnell E.K. , Krysiak K. , Danos A.M. , Walker J. , et al. .
Source: JCO clinical cancer informatics, 2020 03; 4, p. 245-253.
PMID: 32191543
Related Citations

pVACtools: A Computational Toolkit to Identify and Visualize Cancer Neoantigens.
Authors: Hundal J. , Kiwala S. , McMichael J. , Miller C.A. , Xia H. , Wollam A.T. , Liu C.J. , Zhao S. , Feng Y.Y. , Graubert A.P. , et al. .
Source: Cancer immunology research, 2020 03; 8(3), p. 409-420.
EPub date: 2020-01-06.
PMID: 31907209
Related Citations

Evidence-Based Network Approach to Recommending Targeted Cancer Therapies.
Authors: Kancherla J. , Rao S. , Bhuvaneshwar K. , Riggins R.B. , Beckman R.A. , Madhavan S. , Corrada Bravo H. , Boca S.M. .
Source: JCO clinical cancer informatics, 2020 01; 4, p. 71-88.
PMID: 31990579
Related Citations

Text-mining clinically relevant cancer biomarkers for curation into the CIViC database.
Authors: Lever J. , Jones M.R. , Danos A.M. , Krysiak K. , Bonakdar M. , Grewal J.K. , Culibrk L. , Griffith O.L. , Griffith M. , Jones S.J.M. .
Source: Genome medicine, 2019-12-03; 11(1), p. 78.
EPub date: 2019-12-03.
PMID: 31796060
Related Citations

Standard operating procedure for curation and clinical interpretation of variants in cancer.
Authors: Danos A.M. , Krysiak K. , Barnell E.K. , Coffman A.C. , McMichael J.F. , Kiwala S. , Spies N.C. , Sheta L.M. , Pema S.P. , Kujan L. , et al. .
Source: Genome medicine, 2019-11-29; 11(1), p. 76.
EPub date: 2019-11-29.
PMID: 31779674
Related Citations

A case for expert curation: an overview of cancer curation in the Clinical Genome Resource (ClinGen).
Authors: Ritter D.I. , Rao S. , Kulkarni S. , Madhavan S. , Offit K. , Plon S.E. .
Source: Cold Spring Harbor molecular case studies, 2019 10; 5(5), .
EPub date: 2019-10-23.
PMID: 31645350
Related Citations

Open-Sourced CIViC Annotation Pipeline to Identify and Annotate Clinically Relevant Variants Using Single-Molecule Molecular Inversion Probes.
Authors: Barnell E.K. , Waalkes A. , Mosior M.C. , Penewit K. , Cotto K.C. , Danos A.M. , Sheta L.M. , Campbell K.M. , Krysiak K. , Rieke D. , et al. .
Source: JCO clinical cancer informatics, 2019 10; 3, p. 1-12.
PMID: 31618044
Related Citations

Best practices for bioinformatic characterization of neoantigens for clinical utility.
Authors: Richters M.M. , Xia H. , Campbell K.M. , Gillanders W.E. , Griffith O.L. , Griffith M. .
Source: Genome medicine, 2019-08-28; 11(1), p. 56.
EPub date: 2019-08-28.
PMID: 31462330
Related Citations




Back to Top