小桶
基因
基因共表达网络
计算生物学
基因表达
生物信息学
医学
癌基因
生物
癌症研究
遗传学
细胞周期
基因本体论
作者
Weibin Wu,Ai Chen,Siming Lin,Qiuran Wang,Guili Lian,Li Luo,Liangdi Xie
标识
DOI:10.1186/s12890-022-02275-6
摘要
Abstract Background Pulmonary arterial hypertension (PAH) is characterized by a progressive increase in pulmonary vascular resistance and pulmonary arterial pressure, with complex etiology, difficult treatment and poor prognosis. The objective of this study was to investigate the potential biomarkers for PAH based on bioinformatics analysis. Methods The GSE117261 datasets were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified by screening PAH patients and controls. Then the DEGs were analyzed using a Weighted Gene Co-expression Network Analysis (WGCNA) and the key modules were determined, and to further explore their potential biological functions via Gene Ontology analysis (GO), Kyoto Encyclopedia of Genes and Genomes Pathway analysis (KEGG), and Gene Set Enrichment Analysis (GSEA). Moreover, Protein–protein interaction (PPI) networks were constructed to identify hub gene candidates in the key modules. Finally, real-time quantitative polymerase chain reaction was supplied to detect the expressions of hub genes in human pulmonary arterial smooth cells treated with cobalt chloride (COCl 2 ) which was used to mimic hypoxia. Results There were 2299 DEGs identified. WGCNA indicated that yellow module was the key one correlated with PAH. GO and KEGG analysis demonstrated that genes in the yellow module were mainly enriched in ‘Pathways in cancer’. GSEA revealed that ‘HALLMARK_MYC_TARGETS_V1’ was remarkably enriched in PAH. Based on the PPI network, vascular endothelial growth factor A, proto-oncogene receptor tyrosine kinase ( KIT ), PNN interacting serine and arginine rich protein ( PNISR ) and heterogeneous nuclear ribonucleoprotein H1 ( HNRNPH1 ) were identified as the hub genes. Additionally, the PCR indicated that the elevated expressions of PNISR and HNRNPH1 were in line with the bioinformatics analysis. ROC analysis determined that PNISR and HNRNPH1 may be potential biomarkers to provide better diagnosis of PAH. Conclusion PNISR and HNRNPH1 were potential biomarkers to diagnosis PAH. In summary, the identified DEGs, modules, pathways, and hub genes provide clues and shed light on the potential molecular mechanisms of PAH.
科研通智能强力驱动
Strongly Powered by AbleSci AI