Literature DB >> 26320871

Cancer Driver Log (CanDL): Catalog of Potentially Actionable Cancer Mutations.

Senthilkumar Damodaran1, Jharna Miya2, Esko Kautto2, Eliot Zhu2, Eric Samorodnitsky2, Jharna Datta2, Julie W Reeser2, Sameek Roychowdhury3.   

Abstract

Massively parallel sequencing technologies have enabled characterization of genomic alterations across multiple tumor types. Efforts have focused on identifying driver mutations because they represent potential targets for therapy. However, because of the presence of driver and passenger mutations, it is often challenging to assign the clinical relevance of specific mutations observed in patients. Currently, there are multiple databases and tools that provide in silico assessment for potential drivers; however, there is no comprehensive resource for mutations with functional characterization. Therefore, we created an expert-curated database of potentially actionable driver mutations for molecular pathologists to facilitate annotation of cancer genomic testing. We reviewed scientific literature to identify variants that have been functionally characterized in vitro or in vivo as driver mutations. We obtained the chromosome location and all possible nucleotide positions for each amino acid change and uploaded them to the Cancer Driver Log (CanDL) database with associated literature reference indicating functional driver evidence. In addition to a simple interface, the database allows users to download all or selected genes as a comma-separated values file for incorporation into their own analysis pipeline. Furthermore, the database includes a mechanism for third-party contributions to support updates for novel driver mutations. Overall, this freely available database will facilitate rapid annotation of cancer genomic testing in molecular pathology laboratories for mutations.
Copyright © 2015 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.

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Year:  2015        PMID: 26320871      PMCID: PMC4597274          DOI: 10.1016/j.jmoldx.2015.05.002

Source DB:  PubMed          Journal:  J Mol Diagn        ISSN: 1525-1578            Impact factor:   5.568


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