Xu-Yan Yang1, Xu-Zhao Li2, Shuai-Nan Zhang3. 1. First Affiliated Hospital, Heilongjiang University of Chinese Medicine, Harbin 150040, PR China. 2. Pharmacy School, Guiyang University of Chinese Medicine, Guiyang 550025, PR China. Electronic address: xuzhaoli86@yeah.net. 3. Pharmacy School, Guiyang University of Chinese Medicine, Guiyang 550025, PR China. Electronic address: laurahoney@163.com.
Abstract
BACKGROUND: Oral lichen planus (OLP) is a chronic inflammatory mucosal disorder and potentially oral premalignant lesion affecting the stratified squamous epithelia. In OLP, reticular type is the most common clinical form of the disease. However, little is known about it. Metabolomics analysis may help to investigate the disease pathogenesis and to improve clinical treatment. METHODS: Liquid chromatography (LC)-mass spectrometry (MS) system, XCMS software, SIMCA software, and OSI / SMMS software were integrated to identify differentially expressed metabolites for the pathways and pathology analysis. RESULTS: Totally, 21 modulated metabolites were identified, whose dysregulations affected 30 metabolic pathways. Through an impact-value screen (impact-value>0.1), 8 pathways were selected as the significantly dysregulated pathways. Pathological network showed that these metabolites participated in 5 pathological processes, that is, inflammatory lesion, DNA damage and repair disorder, apoptosis process, oxidative stress injury, and abnormal energy expenditure. CONCLUSION: The study revealed the metabolic perturbation of oral mucosa in reticular OLP, which may provide an important reference for the understanding of the pathogenesis of the disease and the discovery of therapeutic targets.
BACKGROUND: Oral lichen planus (OLP) is a chronic inflammatory mucosal disorder and potentially oral premalignant lesion affecting the stratified squamous epithelia. In OLP, reticular type is the most common clinical form of the disease. However, little is known about it. Metabolomics analysis may help to investigate the disease pathogenesis and to improve clinical treatment. METHODS: Liquid chromatography (LC)-mass spectrometry (MS) system, XCMS software, SIMCA software, and OSI / SMMS software were integrated to identify differentially expressed metabolites for the pathways and pathology analysis. RESULTS: Totally, 21 modulated metabolites were identified, whose dysregulations affected 30 metabolic pathways. Through an impact-value screen (impact-value>0.1), 8 pathways were selected as the significantly dysregulated pathways. Pathological network showed that these metabolites participated in 5 pathological processes, that is, inflammatory lesion, DNA damage and repair disorder, apoptosis process, oxidative stress injury, and abnormal energy expenditure. CONCLUSION: The study revealed the metabolic perturbation of oral mucosa in reticular OLP, which may provide an important reference for the understanding of the pathogenesis of the disease and the discovery of therapeutic targets.