基于加权基因共表达网络分析的口腔黏膜下纤维性变与其他器官纤维化的比较分子分析。

Comparative molecular analysis of oral submucous fibrosis and other organ fibrosis based on weighted gene co-expression network analysis.

机构信息

Hunan Key Laboratory of Oral Health Research; Hunan 3D Printing Engineering Research Center of Oral Care; Hunan Clinical Research Center of Oral Major Diseases and Oral Health; Xiangya School of Stomatology, Central South University, Changsha 410008.

Department of Periodontics and Oral Medicine, Xiangya Stomatological Hospital, Central South University, Changsha 410008.

出版信息

Zhong Nan Da Xue Xue Bao Yi Xue Ban. 2022 Dec 28;47(12):1663-1672. doi: 10.11817/j.issn.1672-7347.2022.220452.

DOI:10.11817/j.issn.1672-7347.2022.220452

PMID:36748376

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10930262/

Abstract

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.

摘要

目的

目前缺乏能够准确再现口腔黏膜下纤维化（OSF）疾病状态的经济适用的动物模型，这也是 OSF 治疗方法有限的主要原因之一。本研究基于泛癌分析的基本逻辑，从分子、信号通路、生物学过程等方面系统比较 OSF 与其他四种器官纤维化，有助于研究人员发现纤维化疾病的一些普遍规律，也可能为 OSF 研究提供新思路。

方法

从 GEO 下载 GSE64216、GSE76882、GSE171294、GSE92592 和 GSE90051 数据集的微阵列数据，利用 Limma 包鉴定每种纤维化类型的差异表达 mRNAs（DEmRNAs）。采用加权基因共表达网络分析（WGCNA）鉴定各型纤维化相关模块。通过功能和通路富集分析，分析各纤维化相关模块基因的异同。

结果

OSF、肾肠纤维化（KIF）、肝纤维化（LF）、特发性肺纤维化（IPF）和皮肤纤维化（SF）中分别鉴定出 6057、10910、27990、10480 和 4801 个 DEmRNAs。利用 WGCNA 分别鉴定出各型纤维化相关模块，构建各型纤维化的共表达网络。除 KIF 和 LF 有 5 个共同的枢纽基因外，其他纤维化疾病之间没有共同的枢纽基因。OSF、KIF、LF、IPF 和 SF 的共同通路主要集中在免疫相关通路。