Weighted Gene Co-Expression Network Analysis of Oxymatrine in Psoriasis Treatment

被引:9
作者
Xue, Xiaoxiao [1 ]
Guo, Yatao [2 ]
Zhao, Qianying [3 ]
Li, Yongwen [1 ]
Rao, Mi [1 ]
Qi, Wenjing [1 ]
Shi, Huijuan [1 ]
机构
[1] Gen Hosp Ningxia Med Univ, Dept Dermatovenereol, Yinchuan 750004, Peoples R China
[2] Baoji Cent Hosp, Dermatol Dept, Shaanxi 721008, Peoples R China
[3] Gen Hosp Ningxia Med Univ, Med Expt Ctr, Yinchuan 750004, Peoples R China
关键词
enrichment analysis; epidermal differentiation complex; epithelial tissue; homeostasis; EPIDERMAL DIFFERENTIATION COMPLEX; CORNIFIED ENVELOPE; PATHWAY; CANCER; KERATINOCYTE;
D O I
10.2147/JIR.S402535
中图分类号
R392 [医学免疫学]; Q939.91 [免疫学];
学科分类号
100102 ;
摘要
Purpose: Psoriasis is a common, chronic, inflammatory, recurrent, immune-mediated skin disease. Oxymatrine is effective for treating moderate and severe psoriasis. Here, transcriptional changes in skin lesions before and after oxymatrine treatment of patients with psoriasis were identified using full-length transcriptome analysis and then compared with those of normal skin tissues.Patients and Methods: Co-expression modules were constructed by combining the psoriasis area and severity index (PASI) score with weighted gene co-expression network analysis to explore the action mechanism of oxymatrine in improving clinical PASI. The expression of selected genes was verified using immunohistochemistry, quantitative real-time PCR, and Western blotting.Results: Kyoto Encyclopedia of Gene and Genome pathway analysis revealed that oxymatrine treatment reversed the abnormal pathways, with an improvement in lesions and a reduction in PASI scores. Gene Ontology (GO) analysis revealed that oxymatrine treatment led to altered GO terms being regulated with a decrease in the PASI score in patients. Therefore, oxymatrine treatment may improve the skin barrier, differentiation of keratinocytes, and alleviate abnormality of organelles such as desmosomes. Protein-protein interaction network interaction analysis revealed that the top five hub genes among many interrelated genes were CNFN, S100A8, SPRR2A, SPRR2D, and SPRR2E, associated with the epidermal differentiation complex (EDC). EDC regulates keratinocyte differ-entiation. This result indicates that oxymatrine treatment can restore keratinocyte differentiation by regulating the expression of EDC-related genes.Conclusion: Oxymatrine can improve erythema, scales, and other clinical symptoms of patients with psoriasis by regulating EDC-related genes and multiple pathways, thereby promoting the repair of epithelial tissue and maintaining the dynamic balance of skin keratosis.
引用
收藏
页码:845 / 859
页数:15
相关论文
共 50 条
[41]   Identification of Prognostic Genes in Leiomyosarcoma by Gene Co-Expression Network Analysis [J].
Yang, Jun ;
Li, Cuili ;
Zhou, Jiaying ;
Liu, Xiaoquan ;
Wang, Shaohua .
FRONTIERS IN GENETICS, 2020, 10
[42]   Identification of KIF18B as a Hub Candidate Gene in the Metastasis of Clear Cell Renal Cell Carcinoma by Weighted Gene Co-expression Network Analysis [J].
Yang, Huiying ;
Wang, Yukun ;
Zhang, Ziyi ;
Li, Hua .
FRONTIERS IN GENETICS, 2020, 11
[43]   Screening key lncRNAs for human lung adenocarcinoma based on machine learning and weighted gene co-expression network analysis [J].
Wang, Yu ;
Fu, Junfeng ;
Wang, Ze ;
Lv, Zhenyang ;
Fan, Zhe ;
Lei, Ting .
CANCER BIOMARKERS, 2019, 25 (04) :313-324
[44]   Weighted Gene Co-Expression Network Analysis Identified Cancer Cell Proliferation as a Common Phenomenon During Perineural Invasion [J].
Huang, Ting ;
Wang, Yiwei ;
Wang, Zhihua ;
Cui, Yunxia ;
Sun, Xiao ;
Wang, Yudong .
ONCOTARGETS AND THERAPY, 2019, 12 :10361-10374
[45]   Weighted gene co-expression network analysis in identification of key genes and networks for ischemic-reperfusion remodeling myocardium [J].
Guo, Nan ;
Zhang, Nan ;
Yan, Liqiu ;
Lian, Zheng ;
Wang, Jiawang ;
Lv, Fengfeng ;
Wang, Yunfei ;
Cao, Xufen .
MOLECULAR MEDICINE REPORTS, 2018, 18 (02) :1955-1962
[46]   A Naive Bayes model on lung adenocarcinoma projection based on tumor microenvironment and weighted gene co-expression network analysis [J].
Ye, Zhiqiang ;
Song, Pingping ;
Zheng, Degao ;
Zhang, Xu ;
Wu, Jianhong .
INFECTIOUS DISEASE MODELLING, 2022, 7 (03) :498-509
[47]   Identification of T cell-related biomarkers for breast cancer based on weighted gene co-expression network analysis [J].
Ye, Zhenkai .
JOURNAL OF CHEMOTHERAPY, 2023, 35 (04) :298-306
[48]   Identification of 13 Key Genes Correlated With Progression and Prognosis in Hepatocellular Carcinoma by Weighted Gene Co-expression Network Analysis [J].
Gu, Yang ;
Li, Jun ;
Guo, Deliang ;
Chen, Baiyang ;
Liu, Pengpeng ;
Xiao, Yusha ;
Yang, Kang ;
Liu, Zhisu ;
Liu, Quanyan .
FRONTIERS IN GENETICS, 2020, 11
[49]   Identification of hub genes in papillary thyroid carcinoma: robust rank aggregation and weighted gene co-expression network analysis [J].
Liu, Yang ;
Chen, Ting-Yu ;
Yang, Zhi-Yan ;
Fang, Wei ;
Wu, Qian ;
Zhang, Chao .
JOURNAL OF TRANSLATIONAL MEDICINE, 2020, 18 (01)
[50]   Identifying 13 Hub Genes Associated with Progression and Prognosis of Hepatocellular Carcinoma with Weighted Gene Co-Expression Network Analysis [J].
Liu, Yuanguang ;
Cheng, Ran ;
Chang, Qing ;
Wu, Yijie ;
Liu, Chunmei ;
Liu, Yang ;
Wu, Xiaotang ;
Cheng, Ling ;
Hu, Liang ;
Yin, Jun .
CRITICAL REVIEWS IN EUKARYOTIC GENE EXPRESSION, 2021, 31 (04) :59-69