Objectives: There is currently a lack of economic and suitable animal models that can accurately recapitulate the oral submucous fibrosis (OSF) disease state for indepth study. This is one of the primary reasons for the limited therapeutic methods available for OSF. Based on the underlying logic of pan-cancer analysis, this study systematically compares OSF and the other four types of organ fibrosis from the aspects of molecules, signaling pathways, biological processes, etc. A comprehensive analysis of the similarities and differences between OSF and other organ fibrosis is helpful for researchers to discover some general rules of fibrosis disease and may provide new ideas for studying OSF.
Methods: Microarray data of the GSE64216, GSE76882, GSE171294, GSE92592, and GSE90051 datasets were downloaded from GEO. Differentially expressed mRNAs (DEmRNAs) of each type of fibrosis were identified by Limma package. Weighted gene co-expression network analysis (WGCNA) was used to identify each type of fibrosis-related module. The similarities and differences of each fibrosis-related-module genes were analyzed by function and pathway enrichment analysis.
Results: A total of 6 057, 10 910, 27 990, 10 480, and 4 801 DEmRNAs were identified in OSF, kidney intestinal fibrosis (KIF), liver fibrosis (LF), idiopathic pulmonary fibrosis (IPF), and skin fibrosis (SF), respectively. By using WGCNA, each type of fibrosis-related module was identified. The co-expression networks for each type of fibrosis were constructed respectively. Except that KIF and LF have 5 common hub genes, other fibrotic diseases have no common hub genes with each other. The common pathways of OSF, KIF, LF, IPF, and SF mainly focus on immune-related pathways.
Conclusions: OSF and the other 4 types of fibrotic diseases are tissue- and organ-specific at the molecular level, but they share many common signaling pathways and biological processes, mainly in inflammation and immunity.
目的: 目前尚无成熟且经济的动物模型模拟口腔黏膜下纤维化(oral submucous fibrosis，OSF)，这是制约OSF的机制和药物研究的主要障碍之一。本研究参考泛癌分析的底层逻辑，从分子、信号通路、生物学过程等方面对OSF及其他4种器官纤维化进行系统比较，这有利于学者们发现不同器官纤维化基因组之间的异同，寻找到某些普遍规律，也为OSF的研究提供新思路。方法: 从基因表达综合数据库(Gene Expression Omnibus，GEO)网站下载GSE64216、GSE76882、GSE171294、GSE92592和GSE90051数据集的芯片数据。用“Limma”软件包检测各类型纤维化的差异表达mRNAs(differentially expressed mRNAs，DEmRNAs)。采用加权基因共表达网络分析(weighted gene co-expression network analysis，WGCNA)鉴定各类型纤维化相关模块。通过功能富集和通路富集分析各纤维化相关模块基因的异同。结果: OSF、肾间质纤维化(kidney intestinal fibrosis，KIF)、肝纤维化(liver fibrosis，LF)、特发性肺纤维化(idiopathic pulmonary fibrosis，IPF)、皮肤纤维化(skin fibrosis，SF)中分别检测到6 057、10 910、27 990、10 480和4 801个DEmRNAs。通过WGCNA对各器官纤维化相关模块进行识别，分别构建各类型纤维化的共表达网络。除了KIF和LF有5个共同的hub基因外，其他纤维化疾病之间没有共同的hub基因。OSF、KIF、LF、IPF和SF的共同通路主要集中于免疫相关通路。结论: OSF和其他4种器官纤维化在分子水平上具有组织和器官特异性，但它们有许多共同的信号通路和生物学过程，主要是在炎症和免疫方面。.
目的: 目前尚无成熟且经济的动物模型模拟口腔黏膜下纤维化(oral submucous fibrosis，OSF)，这是制约OSF的机制和药物研究的主要障碍之一。本研究参考泛癌分析的底层逻辑，从分子、信号通路、生物学过程等方面对OSF及其他4种器官纤维化进行系统比较，这有利于学者们发现不同器官纤维化基因组之间的异同，寻找到某些普遍规律，也为OSF的研究提供新思路。
方法: 从基因表达综合数据库(Gene Expression Omnibus，GEO)网站下载GSE64216、GSE76882、GSE171294、GSE92592和GSE90051数据集的芯片数据。用“Limma”软件包检测各类型纤维化的差异表达mRNAs(differentially expressed mRNAs，DEmRNAs)。采用加权基因共表达网络分析(weighted gene co-expression network analysis，WGCNA)鉴定各类型纤维化相关模块。通过功能富集和通路富集分析各纤维化相关模块基因的异同。
结果: OSF、肾间质纤维化(kidney intestinal fibrosis，KIF)、肝纤维化(liver fibrosis，LF)、特发性肺纤维化(idiopathic pulmonary fibrosis，IPF)、皮肤纤维化(skin fibrosis，SF)中分别检测到6 057、10 910、27 990、10 480和4 801个DEmRNAs。通过WGCNA对各器官纤维化相关模块进行识别，分别构建各类型纤维化的共表达网络。除了KIF和LF有5个共同的hub基因外，其他纤维化疾病之间没有共同的hub基因。OSF、KIF、LF、IPF和SF的共同通路主要集中于免疫相关通路。
结论: OSF和其他4种器官纤维化在分子水平上具有组织和器官特异性，但它们有许多共同的信号通路和生物学过程，主要是在炎症和免疫方面。
Keywords: fibrotic diseases; immunity; inflammation; oral submucous fibrosis; weighted gene co-expression network analysis.