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通过网络方法理解癌症中的基因型-表型效应。

Understanding Genotype-Phenotype Effects in Cancer via Network Approaches.

作者信息

Kim Yoo-Ah, Cho Dong-Yeon, Przytycka Teresa M

机构信息

National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, United States of America.

出版信息

PLoS Comput Biol. 2016 Mar 10;12(3):e1004747. doi: 10.1371/journal.pcbi.1004747. eCollection 2016 Mar.

Abstract

Cancer is now increasingly studied from the perspective of dysregulated pathways, rather than as a disease resulting from mutations of individual genes. A pathway-centric view acknowledges the heterogeneity between genomic profiles from different cancer patients while assuming that the mutated genes are likely to belong to the same pathway and cause similar disease phenotypes. Indeed, network-centric approaches have proven to be helpful for finding genotypic causes of diseases, classifying disease subtypes, and identifying drug targets. In this review, we discuss how networks can be used to help understand patient-to-patient variations and how one can leverage this variability to elucidate interactions between cancer drivers.

摘要

如今,癌症越来越多地从失调通路的角度进行研究,而非被视为由单个基因突变导致的疾病。以通路为中心的观点承认不同癌症患者基因组图谱之间的异质性,同时假定突变基因可能属于同一通路并导致相似的疾病表型。事实上,以网络为中心的方法已被证明有助于发现疾病的基因型病因、对疾病亚型进行分类以及识别药物靶点。在本综述中,我们讨论了如何利用网络来帮助理解患者之间的差异,以及如何利用这种变异性来阐明癌症驱动因素之间的相互作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c383/4786343/e3d63af5b46c/pcbi.1004747.g001.jpg

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