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利用蛋白质信息学,通过基因组学、影像学和功能结构评估的综合分析,对新型 CHEK2 变异体进行综合评估的综合数据融合。

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

机构信息

Department of Clinical Genomics, Mayo Clinic, Jacksonville, FL 32224, USA.

出版信息

Mol Omics. 2019 Feb 11;15(1):59-66. doi: 10.1039/c8mo00137e.

DOI:10.1039/c8mo00137e
PMID:30633282
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.

摘要

CHEK2 基因及其编码蛋白 Chk2 在癌症中具有众所周知的作用,特别是与 BRCA1 基因介导的乳腺癌有关。此外,Chk2 在 DNA 修复、细胞凋亡和细胞周期中起着至关重要的作用,这就是为什么对意义不确定的变异体(VUS)进行分类是一个高度寻求更好阐明“基因组效应”的领域。因为通常需要数年时间才能积累足够的临床数据,而且对个别变体进行昂贵且昂贵的功能分析是一个重大障碍,因此,确定其他工具来帮助阐明特定变体对蛋白质功能的影响,最终对患者的健康结果非常重要。在这里,我们描述了一个新鉴定的 CHEK2 变体,并通过结合基因组学(全外显子分析)、临床研究、影像学和蛋白质信息学的综合方法进行分析,以确定和预测 VUS 对蛋白质行为的功能影响以及对相关途径的预测影响。观察到的和分析的蛋白质缺陷与预期的临床效果一致。在这里,我们支持使用个性化蛋白质建模和信息学,并进一步实现为所有蛋白质水平 VUS 建立大规模蛋白质沉积档案的目标。

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