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An Introduction to Resources Facilitating Cancer Variant Interpretation

C.E. Credits: P.A.C.E. CE Florida CE
Speaker
  • Assistant Professor and Senior Developer, Genomics Laboratory Mayo Clinic
    Biography

      Beth Pitel is an Assistant Professor and Senior Developer in the Genomics Laboratory at Mayo Clinic and has helped develop clinical genetic testing using several different testing modalities including NGS oncology panels, RNAseq, Mate Pair sequencing, chromosomal microarray, and qPCR. Beth is the lead on the Genomics of Oncology Annotation Team (GOAT) at Mayo Clinic, which creates interpretive resources for the laboratory based on current knowledgebase and database content, commercial oncology NGS assays, and prevalent literature. Beth has worked at Mayo Clinic since 2007 and completed her Master's degree in Biochemistry and Molecular biology in 2015 with foci on cancer biology and bioinformatics at the Mayo Graduate School. Her interpretation work has led to platform presentations at the Cancer Genomics Consortium annual meeting. Additionally, Beth has developed publicly available knowledgebase tutorials (available on cancervariants.org), and has given a number of workshops and webinars on this topic. Beth is an active member of the Cancer Genomics Consortium (CGC), the ClinGen Somatic Working Group, and co-leads the virtual molecular tumor board for the Variant Interpretation for Cancer Consortium (VICC). Beth has co-authored over 30 peer-reviewed manuscripts, and is frequently involved in clinical and translational research in the Mayo Clinic Genomics Laboratory within the Division of Laboratory Genetics and Genomics. These publications focus mainly on cytogenetics, NGS, bioinformatics, and various other laboratory genetic techniques.


    Abstract

    Many genomic databases and knowledgebases are available and useful in determining the significance of genetic alterations in cancer. Each one of these resources has unique features that allow the user to answer specific questions about the gene, variant, or alteration in question. In this introduction to resources facilitating cancer variant interpretation, we will review different features of several resources (including COSMIC, cBioPortal, OncoKB, CIViC, PeCan Data Portal, JAX-CKB, the Molecular Oncology Almanac, Mitelman Database of Chromosome Aberrations and Gene Fusions in Cancer, Mastermind by Genomenon, and the VICC MetaKB) that make these resources particularly helpful and unique. The goal of this review is to introduce the audience to the landscape of genomic resources available and encourage the use, familiarization, and collaboration with these databases and knowledgebases to ease the burden of interpreting genomic variants in cancer.  In addition to learning about the features incorporated into these resources, the landscape of integration of resources will be reviewed as this field continues to aggregate data and make meaningful connections to benefit the users of this technology.

    Learning Objectives:

    1. Identify different kinds of genomic resources

    2. Learn to apply the features available in genomic resources to cancer variant interpretation

    3. Describe the importance of collaboration and aggregation of genomic variant information


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