Identification of key genes related to immune infiltration in cirrhosis via bioinformatics analysis.

Cirrhosis is the most common subclass of liver disease worldwide and correlated to immune infiltration. However, the immune-related molecular mechanism underlying cirrhosis remains obscure. Two gene expression profiles GSE89377 and GSE139602 were investigated to identify differentially expressed genes (DEGs) related to cirrhosis. Enrichment analysis for DEGs was conducted. Next, the immune infiltration of DEGs was evaluated using CIBERSORT algorithm. The hub DEGs with tight connectivity were identified using the String and Cytoscape databases, and the expression difference of these hub genes between normal liver and cirrhosis samples was determined. Moreover, in order to evaluate the discriminatory ability of hub genes and obtained the area under the receiver operating characteristic curve values in the GSE89377 and GSE139602 datasets. Finally, the association between hub DEGs and immune cell infiltration was explored by Spearman method. Among the 299 DEGs attained, 136 were up-regulated and 163 were down-regulated. Then the enrichment function analysis of DEGs and CIBERSORT algorithm showed significant enrichment in immune and inflammatory responses. And four hub DEGs (ACTB, TAGLN, VIM, SOX9) were identified, which also showed a diagnostic value in the GSE89377 and GSE 139,602 datasets. Finally, the immune infiltration analysis indicated that, these hub DEGs were highly related to immune cells. This study revealed key DEGs involved in inflammatory immune responses of cirrhosis, which could be used as biomarkers for diagnosis or therapeutic targets of cirrhosis.

Identification of key immune-related genes in dilated cardiomyopathy using bioinformatics analysis.

Dilated cardiomyopathy (DCM) is characterized by the left ventricular dilatation and impaired myocardial systolic dysfunction with high mortality and morbidity. However, the underlying mechanisms remain elusive. We first identified the differentially expressed genes (DEGs) between the DCM and control group using two expression profiles from GSE3585 and GSE84796. Enrichment analysis was conducted to explore the potential mechanisms underlying DCM. A total of four algorithms, including key module of MCODE, degree, maximum neighborhood component (MNC), and maximal clique centrality (MCC), were used to identify the hub genes within Cytoscape. The correlation between hub genes and infiltrated immune cells was evaluated to determine potential immune-related genes. The expression analysis and diagnosis value analysis of potential immune-related genes were performed. Finally, the expression analysis with GSE57338 and relationship analysis with the comparative toxicogenomics database (CTD) were performed to identify the key immune-related genes in DCM. A total of 80 DEGs were screened for DCM. Enrichment analysis revealed that DEGs were involved in the immune-related pathological process. Immune infiltration analysis indicated a potentially abnormal immune response in DCM. Four up-regulated genes (COL1A2, COL3A1, CD53, and POSTN) were identified as potential immune-related genes. Finally, three genes (COL1A2, COL3A1, and POSTN) were determined as the key immune-related genes in DCM via expression analysis with a validation set (GSE57338) and relationship analysis with CTD. Our study suggested that the upregulated COL1A2, COL3A1, and POSTN might be the key immune-related genes for DCM. Further studies are needed to validate the underlying mechanisms.