Biomolecular Modelling Laboratory, Cancer Research UK London Research Institute, London, United Kingdom.
Semin Cancer Biol. 2013 Aug;23(4):219-26. doi: 10.1016/j.semcancer.2013.05.002. Epub 2013 May 13.
Over recent years, with the advances in next-generation sequencing, a large number of cancer mutations have been identified and accumulated in public repositories. Coupled to this is our increased ability to generate detailed interactome maps that help to enrich our knowledge of the biological implications of cancer mutations. As a result, network analysis approaches have become an invaluable tool to predict and interpret mutations that are associated with tumour survival and progression. Our understanding of cancer mechanisms is further enhanced by mapping protein structure information to such networks. Here we review the current methodologies for annotating the functional impacts of cancer mutations, which range from analysis of protein structures to protein-protein interaction network studies.
近年来,随着下一代测序技术的进步,大量的癌症突变已经在公共数据库中被识别和积累。与此同时,我们生成详细互作图谱的能力也在不断增强,这有助于丰富我们对癌症突变生物学意义的认识。因此,网络分析方法已成为预测和解释与肿瘤生存和进展相关的突变的宝贵工具。通过将蛋白质结构信息映射到这些网络中,我们进一步加深了对癌症机制的理解。在这里,我们综述了当前用于注释癌症突变功能影响的方法学,这些方法学的范围从蛋白质结构分析到蛋白质-蛋白质相互作用网络研究。