Integrative Microarray Analysis And Screening And Validation Of Core Genes In CCL4 Induced Liver Fibrosis Model In Mice

Background and objectives:Liver cirrhosis is a pathological change resulting from remodelling of hepatic lobules,pseudolobules and fibrous nodule formation in the liver in response to chronic inflammatory stimuli,which may further progress to liver cancer.Liver cirrhosis is a worldwide health problem,which can be caused by a variety of etiologies,and liver fibrosis is its obligatory stage during the formation of cirrhosis.The current study is generally believed that liver fibrosis is reversible,with the progress of sequencing technology and the continuous increase of sequencing data in gene databases,people through the analysis of the data found that some of the genes and pathways involved in the process of liver fibrosis lesions,and after targeted enhancement or inhibition of the expression of some genes,liver fibrosis was reversed to various degrees,These experiments proved feasible to treat liver fibrosis by regulating gene expression.At present,many relevant studies have revealed some important genes and pathways,such as the TGF-β(transforming growth factor-β)pathway,etc.,but there are currently no specific drugs for the treatment of liver fibrosis,so there are still some gaps and room for further exploration in the study of targeting gene expression changes during the progression of the disease.This study used bioinformatics methods to explore and analyze the key pathogenic genes in the progression of liver fibrosis in mice,and the results of bioinformatics analysis were experimentally validated by PCR to provide a basis for the early diagnosis and individualized treatment of liver fibrosis.Methods:1.In GEO(gene expression omnibus)at NCBI(National Center for Biotechnology Information)database were screened and downloaded the CCl4 induced mouse liver fibrosis gene chip data GSE27640 and GSE55747,the chip data were further explored using R language to find out the differentially expressed genes among them,David database was used to analyze the cell functions and pathways involved in the differentially expressed genes,and Cytoscape software was used to construct the regulatory network to screen out 10 nuclei located at the nodes Heart disease genes,and in the NCBI’s gene database to query the function of core disease causing genes and research progress;2.Using CCL4 induction to construct a mouse model of liver fibrosis,liver cirrhosis tissues from mice in the experimental group and healthy liver tissues from mice in the control group were obtained to observe the gene expression situation through PCR experiments to verify the results of our bioinformatics approach analysis.4.PCR validation results showed that 9 of the 10 core genes screened were expressed at the transcript level largely matched the results of bioinformatics analysis of the gene chip data that we downloaded from the geo database.Results:1.Integration analysis of the two sets of GEO data resulted in 117 common differentially expressed genes(of which 108 genes were up-regulated and 9 genes were down regulated).2.After functional enrichment analysis of the common differentially expressed genes,we found that the differentially expressed gene functions and signaling pathways were significantly enriched in the following aspects: 1)in biological process(BP),the common upregulated genes were significantly enriched in apoptosis process,transformation,protein folding and other processes.2)The co upregulated genes were significantly enriched in functions including protein binding,poly(a)RNA binding,and protein homodimerization activity in molecular function(MF).3)In the cellular component(CC),the co upregulated genes were mainly found in the cytoplasm,exosomes,extracellular space,and so on.Signaling pathway enrichment analysis of the differentially expressed genes revealed that the co upregulated genes were mainly enriched in the following pathways: protein processing in the endoplasmic reticulum(ER),arginine and proline metabolism.3.To draw a protein-protein interaction network diagram for the differentially expressed genes,10 core pathogenic genes were finally screened out using Cytoscape software: Lgals3,Actb,Anxa5,Lyz2,Sec61a1,Anxa2,Isg15,Timp1,P4 hb,Rpl37.Conclusion:1.Integration of the two sets of microarray data using bioinformatics methods analysis we obtained 117 common differentially expressed genes,of which the upregulated 108 genes were involved in apoptosis,protein binding and other processes;2.From the common differentially expressed genes screened,we selected 10 core disease causing genes based on the following findings queried in the NCBI’s gene database: 1)genes that have been clearly documented to be associated with liver fibrosis such as Lgals3,Actb,Timp-1,2)genes that have been reported in the literature to be associated with fibrosis in other organ tissues such as Lyz2,Anxa2,3)genes that were not identified in the current study Genes associated with liver fibrosis such as Anxa5,Isg15,P4 hb,Rpl37,Sec61a1;3.The results of our bioinformatics analysis were validated by constructing a mouse model of liver fibrosis and performing PCR experiments,which demonstrated that the core disease causing genes we screened could be used as targets for the diagnosis and treatment of liver fibrosis.