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Issue 1, 2019
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Integrative data fusion for comprehensive assessment of a novel CHEK2 variant using combined genomics, imaging, and functional–structural assessments via protein informatics

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Abstract

The CHEK2 gene and its encoded protein Chk2 have a well-known role in cancers, especially those related to breast cancer mediated through the BRCA1 gene. Additionally Chk2 has a crucial role in DNA repair, apoptosis and the cell cycle, which is why classification of variants of uncertain significance (VUS) is an area highly sought for a better elucidation of the “genomic effect” that results. Because it can often take years before enough clinical data is accumulated, and the costly and expensive functional analysis for individual variants presents a significant hurdle, it is important to identify other tools to help aid in clarifying the impact of specific variants on a protein's function and eventually the patient's health outcome. Here we describe a newly identified CHEK2 variant and analyze with an integrated approach combining genomics (whole exome analysis), clinical study, radiographic imaging, and protein informatics to identify and predict the functional impact of the VUS on the protein's behavior and predicted impact on the related pathways. The observed and analyzed defects in the protein were consistent with the expected clinical effect. Here, we support the use of personalized protein modeling and informatics and further our goal of developing a large-scale protein deposition archive for all protein-level VUS.

Graphical abstract: Integrative data fusion for comprehensive assessment of a novel CHEK2 variant using combined genomics, imaging, and functional–structural assessments via protein informatics

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Article information


Submitted
17 Jun 2018
Accepted
17 Dec 2018
First published
18 Dec 2018

Mol. Omics, 2019,15, 59-66
Article type
Research Article

Integrative data fusion for comprehensive assessment of a novel CHEK2 variant using combined genomics, imaging, and functional–structural assessments via protein informatics

S. L. Hines, A. N. Mohammad, J. Jackson, S. Macklin and T. R. Caulfield, Mol. Omics, 2019, 15, 59
DOI: 10.1039/C8MO00137E

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