用差异模块和突变结构分析鉴定癌症淋巴结转移相关因素。

IF 3.9 2区 生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Xingyi Liu, Bin Yang, Xinpeng Huang, Wenying Yan, Yujuan Zhang, Guang Hu
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引用次数: 1

摘要

复杂疾病通常是由生物网络紊乱和/或多个基因突变引起的。不同疾病状态之间网络拓扑结构的比较可以突出其动态过程中的关键因素。在这里,我们提出了一种差异模块化分析方法,该方法将蛋白质-蛋白质相互作用与基因表达谱相结合,用于模块化分析,并引入模块间边缘和数据中心来识别量化显著表型变异的“核心网络模块”。然后,基于该核心网络模块,通过拓扑功能连接评分和结构建模预测关键因素,包括功能蛋白-蛋白质相互作用、途径和驱动突变。我们应用这种方法来分析癌症的淋巴结转移(LNM)过程。功能富集分析表明,模间边缘和日期中枢在癌症转移和侵袭以及转移特征中都起着重要作用。结构突变分析表明,癌症的LNM可能是转染过程中重排(RET)原相关相互作用和通过RET变构突变的非匿名钙信号通路功能障碍的结果。我们相信,所提出的方法可以为癌症转移等疾病进展提供新的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Identifying Lymph Node Metastasis-Related Factors in Breast Cancer Using Differential Modular and Mutational Structural Analysis.

Identifying Lymph Node Metastasis-Related Factors in Breast Cancer Using Differential Modular and Mutational Structural Analysis.

Complex diseases are generally caused by disorders of biological networks and/or mutations in multiple genes. Comparisons of network topologies between different disease states can highlight key factors in their dynamic processes. Here, we propose a differential modular analysis approach that integrates protein-protein interactions with gene expression profiles for modular analysis, and introduces inter-modular edges and date hubs to identify the "core network module" that quantifies the significant phenotypic variation. Then, based on this core network module, key factors, including functional protein-protein interactions, pathways, and driver mutations, are predicted by the topological-functional connection score and structural modeling. We applied this approach to analyze the lymph node metastasis (LNM) process in breast cancer. The functional enrichment analysis showed that both inter-modular edges and date hubs play important roles in cancer metastasis and invasion, and in metastasis hallmarks. The structural mutation analysis suggested that the LNM of breast cancer may be the outcome of the dysfunction of rearranged during transfection (RET) proto-oncogene-related interactions and the non-canonical calcium signaling pathway via an allosteric mutation of RET. We believe that the proposed method can provide new insights into disease progression such as cancer metastasis.

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来源期刊
Interdisciplinary Sciences: Computational Life Sciences
Interdisciplinary Sciences: Computational Life Sciences MATHEMATICAL & COMPUTATIONAL BIOLOGY-
CiteScore
8.60
自引率
4.20%
发文量
55
期刊介绍: Interdisciplinary Sciences--Computational Life Sciences aims to cover the most recent and outstanding developments in interdisciplinary areas of sciences, especially focusing on computational life sciences, an area that is enjoying rapid development at the forefront of scientific research and technology. The journal publishes original papers of significant general interest covering recent research and developments. Articles will be published rapidly by taking full advantage of internet technology for online submission and peer-reviewing of manuscripts, and then by publishing OnlineFirstTM through SpringerLink even before the issue is built or sent to the printer. The editorial board consists of many leading scientists with international reputation, among others, Luc Montagnier (UNESCO, France), Dennis Salahub (University of Calgary, Canada), Weitao Yang (Duke University, USA). Prof. Dongqing Wei at the Shanghai Jiatong University is appointed as the editor-in-chief; he made important contributions in bioinformatics and computational physics and is best known for his ground-breaking works on the theory of ferroelectric liquids. With the help from a team of associate editors and the editorial board, an international journal with sound reputation shall be created.
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