Objective:To study the common pathogenesis of gout and rheumatoid arthritis(RA)by bioinformatics analysis.Methods:Microarray expression profiles of peripheral blood mononuclear cells in gout and RA were obtained from the GEO public da-tabase.R language and other tools were used to re-annotates the chip,and then the differential genes(DEGs)of the two were screened and the intersection was taken.The protein-protein interaction(PPI)network and topology analysis of common differential genes(CO-DEGs)were constructed by STRING database and Cytoscape software(including CytoNCA plug-in).The HubGene was screened and validated by ROC curve.Finally,the DAVID online analysis tool was used to perform GO and KEGG functional enrichment analysis of HubGene.Results:There were 9 HubGene screened,they were TNF,RGS1,CD69,IL7R,DDX3X,SOCS3,IFIT1,IFIT3,CCL3.GO enrichment showed that HubGene was mainly involves the regulation of virus,STAT receptor signaling pathway and positive regu-lation of neuroinflammatory response.KEGG enrichment showed that HubGene was mainly involved in Toll like receptor signaling pathway,TNF signaling pathway,JAK-STAT signaling pathway,adipocytokine signaling pathway,RIG-Ⅰ-like receptor signaling pathway and osteoclast differentiation.Conclusion:Using bioinformatics analysis,nine HubGene and related signaling pathways in-volved in the pathogenesis of gout and RA have been identified,which may serve as novel biomarkers and potential targets.

Objective To examined gene mutations in thymic carcinoma (TC) patients and to explore prognostic correlates and potential targets for therapy. Methods We retrospectively included TC patients in Sichuan Cancer Hospital between January 2015 and Febuary 2021.Whole-exome sequencing was performed on tumor tissues from TC patients and their control peripheral blood samples, and the raw data were subjected to bioinformatics analysis and statistical analysis. Results We finally included 24 TC patients with 16 males and 8 females at a median age of 55 (42-74) years. The highest frequency of single nucleotide mutations in this cohort were in the TTN gene (42%), HSPG2 (29%), and OBSCN (29%). Higher frequency of copy number variations occurred in ZNF276 gene (54%, loss), BEND3 (50%, loss), DHODH (50%, loss), and VAC14 (50%, loss). Microsatellite instability (MSI) phenotype was found in 25% of the patients, and the mean tumor mutation burden (TMB) was 9.86. Conclusion This study is the first comprehensive analysis of the mutation profile of thymic carcinoma in China to date. The mutation frequencies of TTN, OBSCN, and ZNF276 genes were high. The biomarker analysis suggests that patients may benefit from immunotherapy and have a long effective survival.

Objective:To analyze identification of copper death gene related subtypes,construction of prognosis model and influence of immune infiltration in osteosarcoma(OS)on basis of copper death gene.Methods:Survival and prognosis of OS associated copper death gene were analyzed combining by TARGET and GEO database.OS was divided into different subtypes of copper death by consistent clustering method.SSGSEA was used to analyze difference of immune cells in classification of copper death.Setting P value= 0.05 and q value=0.05,GO and KEGG enrichment analysis were performed on differential genes of copper death typing.Prognosis model was constructed according to results of Lasso regression analysis and cross validation,risk assessment analysis and ROC curve were used to evaluate accuracy of model prediction.Combined with clinical characteristics,nomograms were constructed to predict survival time of patients,and risk differences were analyzed.Immune cell infiltration and tumor microenvironment analysis were performed on OS samples."pRRophetic"package in R software was used to analyze drug sensitivity of OS samples.Results:FDX1,GLS,DLAT and PDHB as high-risk genes for OS prognosis were identified.According to copper death classification of OS samples,OS could be divided into two types:CRGclusterA and CRGclusterB.CRGclusterA was associated with Th2 cells,and CRGclusterB was associated with Th1 cells.Most OS copper death genes were highly expressed in CRGclusterA.Immune cell infiltration analysis results showed that γδ T cells,resting mast cells and resting dendritic cells were positively correlated with risk score,while CD8 T cells were negatively correlated with risk score.Drug sensitivity analysis showed that OS showed higher sensitivity to Elesclomol and GW.441756.Conclusion:Two subtypes of CRGclusterA and CRGclusterB are identified in this study.Four high-risk prognostic genes FDX1,GLS,DLAT and PDHB are identified,providing new insights into prognostic evaluation and immunotherapy target candidates for OS.

Objective:To explore the molecular mechanism of Danggui Niantong Decoction in the treatment of gouty arthritis (GA) based on network pharmacology and molecular docking.Methods:By selecting for the active components and targets of Danggui Niantong Decoction with TCMSP, and retrieving the GeneCards, OMIM, PharmGKB and DrugBank databases to obtain GA related targets. The potential targets of Danggui Niantong Decoction in the treatment of GA were obtained by the intersection of mappings. The regulation network of Chinese medicine compound and protein-protein interaction network of Danggui Niantong Decoction were constructed by Cytoscape software, and the targets of Danggui Niantong Decoction in the treatment of GA were analyzed by GO and KEGG enrichment by David Database. Finally, molecular docking was performed by using Autodock software.Results:There are 198 active components that could treat GA in Danggui Niantong Decoction. The key active components are Quercetin and Kaempferol. There are 46 key targets, the core targets are NFE2L2, HMOX1, PPARA, PTGS2, IL1β, CXCL8. GO enrichment suggests that the key genes are primarily involved in many biological processes such as Inflammatory response regulation, response to oxidative stress, Fatty acid metabolism process, steroid metabolism, lipopolysaccharide response and reactive oxygen species metabolism. KEGG pathway indicates that Danggui Niantong Decoction mainly acted on IL-17 signal pathway, HIF-1 signal pathway, TNF signal pathway and AGE-RAGE signal pathway. Molecular docking shows that the active components of Danggui Niantong Decoction and action target of GA can combine toghether with high efficiency, and the structure is stable.Conclusion:Danggui Niantong Decoction has multi-component, multi pathway and multi-protein characteristics. Danggui Niantong Decoction can treat GA by regulating immune inflammatory reaction and oxidative stress reaction.