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Identifying functional evolution processes according to the pathological stages of colorectal cancer

机译:根据大肠癌的病理阶段识别功能进化过程

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Colorectal cancer (CRC) is one of the malignant tumors with high morbidity and mortality. A prevalent method for studying colorectal cancer is to identify differentially expressed genes (DEGs) between control and patient samples, followed by the pathway enrichment analyses. However, many of those studies ignore the fact that different pathological stages of the cancer are often highly different from each other. The mixture of those heterogeneous samples may lack the efficiency of identifying the real DEGs, and loss the opportunity to analyze the dynamic evolution process of cancer. In this study, we develop a feasible framework to identify function evolution processes of cancers according to their pathological stages. Firstly, the limma package was used to identify DEG sets between control and CRC stage I, II, III, and IV samples, separately. Secondly, a pathway interaction network was constructed by taking a comprehensive analysis of pathways at individual stages, and a functional module interaction network was also generated independently by clustering genes into modules in a PPI network. The relationship between pathways and modules in adjacent stages was analyzed for all stages of CRC. A total of 479, 313, 349, and 383 DEGs were identified and they were enriched in 17, 16, 20, and 24 pathways, respectively. A functional evolution network was constructed by using those modules, and two significant evolution processes a2-b1-c2-d1 (Mod1) and a1-b2-c1-d2 (Mod2) were identified which may play critical roles in the development of CRC. The framework proposed in this study can be used to explore molecular mechanisms and evolution processes of CRC.
机译:大肠癌(CRC)是高发病率和高死亡率的恶性肿瘤之一。研究结直肠癌的一种普遍方法是鉴定对照和患者样品之间的差异表达基因(DEG),然后进行途径富集分析。但是,这些研究中有许多忽略了癌症的不同病理阶段常常彼此之间存在很大差异的事实。这些异质样本的混合物可能缺乏识别真实DEG的效率,并失去了分析癌症动态演变过程的机会。在这项研究中,我们建立了一个可行的框架,以根据癌症的病理阶段识别其功能进化过程。首先,limma软件包用于分别识别对照和CRC阶段I,II,III和IV样本之间的DEG集。其次,通过对各个阶段的路径进行全面分析,构建了路径相互作用网络,并且通过将基因聚类到PPI网络中的模块来独立生成功能模块相互作用网络。对于CRC的所有阶段,分析了相邻阶段中途径和模块之间的关系。总共鉴定出479、313、349和383个DEG,它们分别在17、16、20和24个途径中富集。使用这些模块构建了功能进化网络,并确定了两个重要的进化过程a2-b1-c2-d1(Mod1)和a1-b2-c1-d2(Mod2),它们可能在CRC的发展中起关键作用。本研究提出的框架可用于探索CRC的分子机制和进化过程。

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