scholarly journals An Advanced Systems Pharmacology Strategy Reveals AKR1B1, MMP2, PTGER3 as Key Genes in the Competing Endogenous RNA Network of Compound Kushen Injection Treating Gastric Carcinoma by Integrated Bioinformatics and Experimental Verification

2021 ◽  
Vol 9 ◽  
Author(s):  
Wei Zhou ◽  
Chao Wu ◽  
Chongjun Zhao ◽  
Zhihong Huang ◽  
Shan Lu ◽  
...  
Keyword(s):  
Chinese Medicine ◽  
Gastric Carcinoma ◽  
Signaling Pathways ◽  
Molecular Mechanism ◽  
Functional Enrichment ◽  
High Morbidity ◽  
Systems Pharmacology ◽  
Cerna Network ◽  
Key Genes ◽  
Compound Kushen Injection

Gastric carcinoma (GC) is a severe tumor of the digestive tract with high morbidity and mortality and poor prognosis, for which novel treatment options are urgently needed. Compound Kushen injection (CKI), a classical injection of Chinese medicine, has been widely used to treat various tumors in clinical practice for decades. In recent years, a growing number of studies have confirmed that CKI has a beneficial therapeutic effect on GC, However, there are few reports on the potential molecular mechanism of action. Here, using systems pharmacology combined with proteomics analysis as a core concept, we identified the ceRNA network, key targets and signaling pathways regulated by CKI in the treatment of GC. To further explore the role of these key targets in the development of GC, we performed a meta-analysis to compare the expression differences between GC and normal gastric mucosa tissues. Functional enrichment analysis was further used to understand the biological pathways significantly regulated by the key genes. In addition, we determined the significance of the key genes in the prognosis of GC by survival analysis and immune infiltration analysis. Finally, molecular docking simulation was performed to verify the combination of CKI components and key targets. The anti-gastric cancer effect of CKI and its key targets was verified by in vivo and in vitro experiments. The analysis of ceRNA network of CKI on GC revealed that the potential molecular mechanism of CKI can regulate PI3K/AKT and Toll-like receptor signaling pathways by interfering with hub genes such as AKR1B1, MMP2 and PTGERR3. In conclusion, this study not only partially highlighted the molecular mechanism of CKI in GC therapy but also provided a novel and advanced systems pharmacology strategy to explore the mechanisms of traditional Chinese medicine formulations.

A novel multi-scale bioinformatics strategy for identifying the molecular mechanism by insighting into ceRNA network integrating WGCNA and meta-analysis: compound kushen injection for treating gastric carcinoma as a proof

2020 ◽  
Author(s):  
Wei Zhou ◽  
Jingyuan Zhang ◽  
Siyu Guo ◽  
Xinkui Liu ◽  
Shanshan Jia ◽  
...  
Keyword(s):  
Chinese Medicine ◽  
Molecular Mechanism ◽  
Meta Analysis ◽  
Docking Simulation ◽  
Network Pharmacology ◽  
High Morbidity ◽  
Cerna Network ◽  
Key Genes ◽  
The Impact ◽  
Compound Kushen Injection

Abstract BackgroundGastric carcinoma (GC) is a severe digestive system tumor with high morbidity and mortality and poor prognosis, of which the novel treatments are urgently needed. Compound kushen injection (CKI), a classic Chinese medicine injection, has been widely used to treat a variety of tumors in clinical for decades. In recent years, a growing number of studies have confirmed that CKI has a favorable therapeutic effect on GC, but there are few reports on the potential molecular mechanism of action.MethodsHere, using network pharmacology as the core concept, we identified the ceRNA network and key targets of CKI in the treatment of GC. In order to further explore the impact of key targets, we conducted a meta-analysis of them and compared the expression differences between GC tissues and normal tissues. Functional analysis was utilized to understand the biological regulation pathways involved in key genes. Moreover, we further detected the significance of key genes for the prognosis of GC through survival analysis and immune infiltration analysis. Finally, molecular docking simulation was adopted so as to verify the combination of CKI components and key targets.ResultsAnalysis of the ceRNA network of CKI on GC illustrated that the potential molecular mechanism of CKI was possible to regulate PI3K-AKT and Toll-like receptor signaling pathways by intervening hub genes including AKR1B1, MMP2 and PTGERR3.ConclusionsIn conclusion, this study not only partially highlighted the molecular mechanism of CKI in GC therapy but also provided a novel strategy for exploring the effective mechanisms of traditional Chinese medicine formulations.

scholarly journals In silico identification of natural products from Traditional Chinese Medicine for cancer immunotherapy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Chuipu Cai ◽  
Qihui Wu ◽  
Honghai Hong ◽  
Liying He ◽  
Zhihong Liu ◽  
...  
Keyword(s):  
Natural Products ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Cancer Immunotherapy ◽  
Functional Enrichment ◽  
Literature Mining ◽  
Systems Pharmacology ◽  
Scutellaria Baicalensis Georgi

AbstractAdvances in immunotherapy have revolutionized treatments in many types of cancer. Traditional Chinese Medicine (TCM), which has a long history of clinical adjuvant application against cancer, is emerging as an important medical resource for developing innovative cancer treatments, including immunotherapy. In this study, we developed a quantitative and systems pharmacology-based framework to identify TCM-derived natural products for cancer immunotherapy. Specifically, we integrated 381 cancer immune response-related genes and a compound-target interaction network connecting 3273 proteins and 766 natural products from 66 cancer-related herbs based on literature-mining. Via systems pharmacology-based prediction, we uncovered 182 TCM-derived natural products having potential anti-tumor immune responses effect. Importantly, 32 of the 49 most promising natural products (success rate = 65.31%) are validated by multiple evidence, including published experimental data from clinical studies, in vitro and in vivo assays. We further identified the mechanism-of-action of TCM in cancer immunotherapy using network-based functional enrichment analysis. We showcased that three typical natural products (baicalin, wogonin, and oroxylin A) in Huangqin (Scutellaria baicalensis Georgi) potentially overcome resistance of known oncology agents by regulating tumor immunosuppressive microenvironments. In summary, this study offers a novel and effective systems pharmacology infrastructure for potential cancer immunotherapeutic development by exploiting the medical wealth of natural products in TCM.

scholarly journals The Genetic and Epigenetic Mechanisms Involved in Irreversible Pulp Neural Inflammation

2021 ◽  
Vol 2021 ◽  
pp. 1-26
Author(s):  
Xiaoxi Xi ◽  
Yihong Ma ◽  
Yuzhen Xu ◽  
Anthony Chukwunonso Ogbuehi ◽  
Xiangqiong Liu ◽  
...  
Keyword(s):  
Signaling Pathways ◽  
Noncoding Rna ◽  
Differential Expression Analysis ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Receptor Interaction ◽  
Epigenetic Mechanisms ◽  
Cerna Network ◽  
Epigenetic Biomarkers ◽  
Irreversible Pulpitis

Aim. To identify the critical genetic and epigenetic biomarkers by constructing the long noncoding RNA- (lncRNA-) related competing endogenous RNA (ceRNA) network involved in irreversible pulp neural inflammation (pulpitis). Materials and Methods. The public datasets regarding irreversible pulpitis were downloaded from the gene expression omnibus (GEO) database. The differential expression analysis was performed to identify the differentially expressed genes (DEGs) and DElncRNAs. Functional enrichment analysis was performed to explore the biological processes and signaling pathways enriched by DEGs. By performing a weighted gene coexpression network analysis (WGCNA), the significant gene modules in each dataset were identified. Most importantly, DElncRNA-DEmRNA regulatory network and DElncRNA-associated ceRNA network were constructed. A transcription factor- (TF-) DEmRNA network was built to identify the critical TFs involved in pulpitis. Result. Two datasets (GSE92681 and GSE77459) were selected for analysis. DEGs involved in pulpitis were significantly enriched in seven signaling pathways (i.e., NOD-like receptor (NLR), Toll-like receptor (TLR), NF-kappa B, tumor necrosis factor (TNF), cell adhesion molecules (CAMs), chemokine, and cytokine-cytokine receptor interaction pathways). The ceRNA regulatory relationships were established consisting of three genes (i.e., LCP1, EZH2, and NR4A1), five miRNAs (i.e., miR-340-5p, miR-4731-5p, miR-27a-3p, miR-34a-5p, and miR-766-5p), and three lncRNAs (i.e., XIST, MIR155HG, and LINC00630). Six transcription factors (i.e., GATA2, ETS1, FOXP3, STAT1, FOS, and JUN) were identified to play pivotal roles in pulpitis. Conclusion. This paper demonstrates the genetic and epigenetic mechanisms of irreversible pulpitis by revealing the ceRNA network. The biomarkers identified could provide research direction for the application of genetically modified stem cells in endodontic regeneration.

scholarly journals Study on the Mechanism of Prunella Vulgaris L on Diabetes Mellitus Complicated with Hypertension Based on Network Pharmacology and Molecular Docking Analyses

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Xinyi Jiao ◽  
Haiying Liu ◽  
Qinan Lu ◽  
Yu Wang ◽  
Yue Zhao ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Signaling Pathways ◽  
Signaling Pathway ◽  
Molecular Mechanism ◽  
Enrichment Analysis ◽  
Prunella Vulgaris ◽  
Active Components ◽  
Analysis Platform

The role of traditional Chinese medicine Prunella vulagaris L in the treatment of tumors and inflammation has been widely confirmed. We found that some signaling pathways of Prunella vulgaris L action can also regulate diabetes and hypertension, so we decided to study the active ingredients, potential targets and signaling pathway of Prunrlla vulgaris L, and explore the “multi-target, multi-pathway” molecular mechanism of Prunella vulgaris L on diabetes mellitus complicated with hypertension(DH). Methods. Based on TCMSP(Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform) and CNKI(China National Knowledge Infrastructure), the components and action targets related to Prunella vulgaris L were screened. The OMIM(Online Mendelian Inheritance in Man) and GeneCards (The human gene database) were used to search for targets related to DH. The “gene - drug - disease” relationship map was drawn by Cytoscape_v3.7.2 plug-in. The target was amplified by the STRING platform, and the “protein - protein” interaction relationship (PPI) network of the interacting target was obtained by the STRING online analysis platform and the Cytoscape_v3.7.2 plug-in. Finally, GO enrichment analysis and KEGG pathway enrichment analysis were conducted on David and Metascape platform to study the co-acting targets. Results. 11 active components, 41 key targets and 16 significant signaling pathways were identified from Prunella vulgaris L. The main active components of Prunella vulgaris L against DH were quercetin and kaumferol, etc, and potential action targets were IL-6 and INS, etc and signaling pathways were AGE-RAGE signaling pathway, TNF signaling pathway, MAPK signaling pathway, PI3K-AKT signaling pathway, etc. It involves in biological processes such as cell proliferation, apoptosis and inflammatory response. Conclusions. The main molecular mechanism of Prunella vulgaris L against DH is that sterols and flavonoids play an active role by affecting TNF signaling pathway, AGE-RAGE signaling pathway, MAPK pathway, PI3K-Akt pathway related targets such as IL-6 and INS.

scholarly journals A Novel Ferroptosis-Related Gene Risk Signature for Predicting Prognosis and Immunotherapy Response in Gastric Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Shi-jin Liu ◽  
Ya-bing Yang ◽  
Jia-xin Zhou ◽  
Yu-jian Lin ◽  
Yun-long Pan ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Gastric Carcinoma ◽  
Differentially Expressed Genes ◽  
Prognostic Model ◽  
Survival Outcome ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Related Gene ◽  
Value Analysis ◽  
Cerna Network

Background. Gastric cancer (GC) is the third leading cause of cancer death worldwide with complicated molecular and cellular heterogeneity. Iron metabolism and ferroptosis play crucial roles in the pathogenesis of GC. However, the prognostic role and immunotherapy biomarker potential of ferroptosis-related genes (FRGs) in GC still remains to be clarified. Methods. We comprehensively analyzed the prognosis of different expression FRGs, based on gastric carcinoma patients in the TCGA cohort. The functional enrichment and immune microenvironment associated with these genes in gastric cancer were investigated. The prognostic model was constructed to clarify the relation between FRGs and the prognosis of GC. Meanwhile, the ceRNA network of FRGs in the prognostic model was performed to explore the regulatory mechanisms. Results. Gastric carcinoma patients were classified into the A, B, and C FRGClusters with different features based on 19 prognostic ferroptosis-related differentially expressed genes in the TCGA database. To quantify the FRG characteristics of individual patients, FRGScore was constructed. And the research shows the GC patients with higher FRGScore had worse survival outcome. Moreover, thirteen prognostic ferroptosis-related differentially expressed genes (DEGs) were selected to construct a prognostic model for GC survival outcome with a superior accuracy in this research. And we also found that FRG RiskScore can be an independent biomarker for the prognosis of GC patients. Interestingly, GC patients with lower RiskScore had less immune dysfunction and were more likely to respond to immunotherapy according to TIDE value analysis. Finally, a ceRNA network based on FRGs in the prognostic model was analyzed to show the concrete regulation mechanisms. Conclusions. The ferroptosis-related gene risk signature has a superior potent in predicting GC prognosis and acts as the biomarkers for immunotherapy, which may provide a reference in clinic.

scholarly journals Synergistic Network Pharmacology for Traditional Chinese Medicine Liangxue Tongyu Formula in Acute Intracerebral Hemorrhagic Stroke

2021 ◽  
Vol 2021 ◽  
pp. 1-21
Author(s):  
Yang Chen ◽  
Ju Dong ◽  
Dongqing Yang ◽  
Qin Qian ◽  
Pengcheng Wang ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Signaling Pathways ◽  
Signaling Pathway ◽  
Kegg Pathway ◽  
Functional Enrichment ◽  
Network Pharmacology ◽  
Rna Seq ◽  
Anti Inflammatory

Background. Nowadays, acute intracerebral hemorrhage stroke (AICH) still causes higher mortality. Liangxue Tongyu Formula (LXTYF), originating from a traditional Chinese medicine (TCM) prescription, is widely used as auxiliary treatment for AICH. Objective. To dig into the multicomponent, multitarget, and multipathway mechanism of LXTYF on treating AICH via network pharmacology and RNA-seq. Methods. Network pharmacology analysis was used by ingredient collection, target exploration and prediction, network construction, and Gene Ontology (GO) and KEGG analysis, with the Cytoscape software and ClusterProfiler package in R. The RNA-seq data of the AICH-rats were analyzed for differential expression and functional enrichments. Herb-Compound-Target-Pathway (H-C-T-P) network was shown to clarify the mechanism of LXTYF for AICH. Results. 76 active ingredients (quercetin, Alanine, kaempferol, etc.) of LXTYF and 376 putative targets to alleviate AICH (PTGS2, PTGS1, ESR1, etc.) were successfully identified. The protein-protein interaction (PPI) network indicated the important role of STAT3. The functional enrichment of GO and KEGG pathway showed that LXTYF is most likely to influence MAPK and PI3K-Akt signaling pathways for AICH treatment. From the RNA-seq of AICH-rats, 583 differential mRNAs were identified and 14 of them were consistent with the putative targets of LXTYF for AICH treatment. The KEGG pathway enrichment also implied that the MAPK signaling pathway was the most correlated one among all the related signaling pathways. Many important targets with expression changes of LXTYF for AICH treatment and their related pathways are great markers of antioxidation, anti-inflammatory, antiapoptosis, and lowering blood pressure, which indicated that LXTYF may play mutiroles in the mechanisms for AICH treatment. Conclusion. The LXTYF attenuates AICH partially by antioxidation, anti-inflammatory, and antiapoptosis and lowers blood pressure roles through regulating the targets involved MAPK, calcium, apoptosis, and TNF signaling pathway, which provide notable clues for further experimental validation.

scholarly journals Identification of Key Genes and Pathways in Ulcerative Colitis Through Bioinformatics Analysis

2021 ◽  
Author(s):  
Mingdi Liu ◽  
Fa Ping Li ◽  
Yong Ping Jian ◽  
Ge Yang ◽  
Dan Zhang ◽  
...  
Keyword(s):  
Ulcerative Colitis ◽  
Colon Cancer ◽  
Signaling Pathways ◽  
Malignant Transformation ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Chronic Inflammatory Disease ◽  
Functional Enrichment ◽  
Self Healing ◽  
Key Genes

Abstract Background Ulcerative colitis (UC) is a chronic inflammatory disease whose therapy remains largely uncertain due to the lack of etiological understanding. It is also a higher risk factor for colon cancer. Aims This study was designed to identify key genes correlated with intestinal epithelial repair and their associated signaling pathways in the pathogenesis and malignant transformation of UC.Methods With an online database pubmed2ensemble, correlative genes were identified to be associated with both UC and its self-healing, and then were imported in Cytoscape for enrichment analysis. A protein-protein interaction network containing was established, and the most significant gene modules and top ten hub genes were selected for further enrichment analysis. Then, potential drugs that target the corresponding genes were identified with online tool in DGIdb. A map which reflected the links among genes, drugs, and their associated pathways was constructed. Finally, we searched the TCGA database and CPTAC database for testing the gene expression of identified UC-associated genes in colon cancer.Results We identified FN1, GRB2, EGF, CXCL8, VEGFA, STAT3, IL6, IL4, IL10, TNF, CSF2, IL13, IL1A, CCL2, ICAM1 and IL18 had closest associations with the function of epithelial function in UC patients, based on functional enrichment analysis. Besides, 11 of them were validated in colon cancer. Conclusions The corresponding signaling pathways that are altered in UC, which provide a new clue for understanding the mechanism underlying the UC pathogenesis and malignant transformation. Key signals in the process and their target drugs might serve as new treatment strategy for UC.

scholarly journals Two Similar Signatures for Predicting the Prognosis and Immunotherapy Efficacy of Stomach Adenocarcinoma Patients

2021 ◽  
Vol 9 ◽  
Author(s):  
Taohua Yue ◽  
Shuai Zuo ◽  
Jing Zhu ◽  
Shihao Guo ◽  
Zhihao Huang ◽  
...  
Keyword(s):  
Gene Signature ◽  
Functional Enrichment ◽  
Venn Diagram ◽  
High Morbidity ◽  
Barr Virus ◽  
Genes Expression ◽  
Stomach Adenocarcinoma ◽  
Key Genes ◽  
Epstein Barr ◽  
Cox Analysis

BackgroundGlobally, stomach adenocarcinoma (STAD)’s high morbidity and mortality should arouse our urgent attention. How long can STAD patients survive after surgery and whether novel immunotherapy is effective are questions that our clinicians cannot escape.MethodsVarious R packages, GSEA software, Metascape, STRING, Cytoscape, Venn diagram, TIMER2.0 website, TCGA, and GEO databases were used in our study.ResultsIn the TCGA and GEO, macrophage abundance of STAD tissues was significantly higher than that of adjacent tissues and was an independent prognostic factor, significantly related to the overall survival (OS) of STAD patients. Between the high- and low- macrophage abundance, we conducted differential expression, univariate and multivariate Cox analysis, and obtained 12 candidate genes, and finally constructed a 3-gene signature. Both low macrophage abundance group and group D had higher TMB and PD-L1 expression. Furthermore, top 5 common gene-mutated STAD tissues had lower macrophage abundance. Macrophage abundance and 3 key genes expression were also lower in the Epstein-Barr Virus (EBV) and HM-indel STAD subtypes and significantly correlated with the tumor microenvironment score. The functional enrichment and ssGSEA revealed 2 signatures were similar and closely related to BOQUEST_STEM_CELL_UP, including genes up-regulated in proliferative stromal stem cells. Hsa-miR-335-5p simultaneously regulated 3 key genes and significantly related to the expression of PD-L1, CD8A and PDCD1.Conclusionmacrophage abundance and 3-gene signature could simultaneously predict the OS and immunotherapy efficacy, and both 2 signatures had remarkable similarities. Hsa-miR-335-5p and BOQUEST_STEM_CELL_UP might be novel immunotherapy targets.

scholarly journals WGCNA reveals key gene modules regulated by the combined treatment of colon cancer with PHY906 and CPT11

2020 ◽  
Vol 40 (9) ◽  
Author(s):  
Shuqin Xing ◽  
Yafei Wang ◽  
Kaiwen Hu ◽  
Fen Wang ◽  
Tao Sun ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Side Effects ◽  
Molecular Mechanism ◽  
Combined Treatment ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Pcr Analysis ◽  
Hub Genes ◽  
Key Genes

Abstract Irinotecan (CPT11) is one of the most effective drugs for treating colon cancer, but its severe side effects limit its application. Recently, a traditional Chinese herbal preparation, named PHY906, has been proved to be effective for improving therapeutic effect and reducing side effects of CPT11. The aim of the present study was to provide novel insight to understand the molecular mechanism underlying PHY906-CPT11 intervention of colon cancer. Based on the GSE25192 dataset, for different three treatments (PHY906, CPT11, and PHY906-CPT11), we screened out differentially expressed genes (DEGs) and constructed a co-expression network by weighted gene co-expression network analysis (WGCNA) to identify hub genes. The key genes of the three treatments were obtained by merging the DEGs and hub genes. For the PHY906-CPT11 treatment, a total of 18 key genes including Eif4e, Prr15, Anxa2, Ddx5, Tardbp, Skint5, Prss12 and Hnrnpa3, were identified. The results of functional enrichment analysis indicated that the key genes associated with PHY906-CPT11 treatment were mainly enriched in ‘superoxide anion generation’ and ‘complement and coagulation cascades’. Finally, we validated the key genes by Gene Expression Profiling Interactive Analysis (GEPIA) and RT-PCR analysis, the results indicated that EIF4E, PRR15, ANXA2, HNRNPA3, NCF1, C3AR1, PFDN2, RGS10, GNG11, and TMSB4X might play an important role in the treatment of colon cancer with PHY906-CPT11. In conclusion, a total of 18 key genes were identified in the present study. These genes showed strong correlation with PHY906-CPT11 treatment in colon cancer, which may help elucidate the underlying molecular mechanism of PHY906-CPT11 treatment in colon cancer.

scholarly journals AB0005 IDENTIFICATION OF KEY GENES AND PATHWAYS FOR PSORIASIS BASED ON GEO DATABASES BY BIOINFORMATICS ANALYSIS

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 1037.2-1038
Author(s):  
X. Sun ◽  
S. X. Zhang ◽  
S. Song ◽  
T. Kong ◽  
C. Zheng ◽  
...  
Keyword(s):  
Gene Expression ◽  
Signaling Pathways ◽  
Differentially Expressed Genes ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Shanxi Province ◽  
Receptor Interaction ◽  
Term Therapy ◽  
Pathway Enrichment Analysis ◽  
Key Genes

Background:Psoriasis is an immune-mediated, genetic disease manifesting in the skin or joints or both, and also has a strong genetic predisposition and autoimmune pathogenic traits1. The hallmark of psoriasis is sustained inflammation that leads to uncontrolled keratinocyte proliferation and dysfunctional differentiation. And it’s also a chronic relapsing disease, which often necessitates a long-term therapy2.Objectives:To investigate the molecular mechanisms of psoriasis and find the potential gene targets for diagnosis and treating psoriasis.Methods:Total 334 gene expression data of patients with psoriasis research (GSE13355 GSE14905 and GSE30999) were obtained from the Gene Expression Omnibus database. After data preprocessing and screening of differentially expressed genes (DEGs) by R software. Online toll Metascape3 was used to analyze Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs. Interactions of proteins encoded by DEGs were discovered by Protein-protein interaction network (PPI) using STRING online software. Cytoscape software was utilized to visualize PPI and the degree of each DEGs was obtained by analyzing the topological structure of the PPI network.Results:A total of 611 DEGs were found to be differentially expressed in psoriasis. GO analysis revealed that up-regulated DEGs were mostly associated with defense and response to external stimulus while down-regulated DEGs were mostly associated with metabolism and synthesis of lipids. KEGG enrichment analysis suggested they were mainly enriched in IL-17 signaling, Toll-like receptor signaling and PPAR signaling pathways, Cytokine-cytokine receptor interaction and lipid metabolism. In addition, top 9 key genes (CXCL10, OASL, IFIT1, IFIT3, RSAD2, MX1, OAS1, IFI44 and OAS2) were identified through Cytoscape.Conclusion:DEGs of psoriasis may play an essential role in disease development and may be potential pathogeneses of psoriasis.References:[1]Boehncke WH, Schon MP. Psoriasis. Lancet 2015;386(9997):983-94. doi: 10.1016/S0140-6736(14)61909-7 [published Online First: 2015/05/31].[2]Zhang YJ, Sun YZ, Gao XH, et al. Integrated bioinformatic analysis of differentially expressed genes and signaling pathways in plaque psoriasis. Mol Med Rep 2019;20(1):225-35. doi: 10.3892/mmr.2019.10241 [published Online First: 2019/05/23].[3]Zhou Y, Zhou B, Pache L, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun 2019;10(1):1523. doi: 10.1038/s41467-019-09234-6 [published Online First: 2019/04/05].Acknowledgements:This project was supported by National Science Foundation of China (82001740), Open Fund from the Key Laboratory of Cellular Physiology (Shanxi Medical University) (KLCP2019) and Innovation Plan for Postgraduate Education in Shanxi Province (2020BY078).Disclosure of Interests:None declared

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