Identification of JPX-RABEP1 Pair as an Immune-Related Biomarker and Therapeutic Target in Pulmonary Arterial Hypertension by Bioinformatics and Experimental Analyses.
Qian GongZhewei HuQiao JinYan YanYan LiuJin HeLenan ZhuangHua-Nan WangPublished in: International journal of molecular sciences (2022)
Pulmonary arterial hypertension (PAH) is a pulmonary vascular disease characterized by pulmonary vascular remodeling and right heart enlargement the pathogenesis of PAH is complicated; no biologic-based therapy is available for the treatment of PAH, but recent studies suggest that inflammatory response and abnormal proliferation of pulmonary artery smooth muscle cells are the main pathogenic mechanism, while the role of immune-related long non-coding RNAs (lncRNAs) remains unclear. The aim of this study was to systematically analyze immune-related lncRNAs in PAH. Here, we downloaded a publicly available microarray data from PAH and control patients (GSE113439). A total of 243 up-regulated and 203 down-regulated differentially expressed genes (DEGs) were screened, and immune-related DEGs were further obtained from ImmPort. The immune-related lncRNAs were obtained by co-expression analysis of immune-related mRNAs. Then, immune-related lncRNAs-mRNAs network including 2 lncRNAs and 6 mRNAs was constructed which share regulatory miRNAs and have significant correlation. Among the lncRNA-mRNA pairs, one pair ( JPX-RABEP1 ) was verified in the validating dataset GSE53408 and PAH mouse model. Furthermore, the immune cell infiltration analysis of the GSE113439 dataset revealed that the JPX-RABEP1 pair may participate in the occurrence and development of PAH through immune cell infiltration. Together, our findings reveal that the lncRNA-mRNA pair JPX-RABEP1 may be a novel biomarker and therapeutic target for PAH.
Keyphrases
- pulmonary arterial hypertension
- pulmonary artery
- pulmonary hypertension
- long non coding rna
- polycyclic aromatic hydrocarbons
- coronary artery
- mouse model
- genome wide analysis
- heart failure
- single cell
- transcription factor
- rheumatoid arthritis
- genome wide
- signaling pathway
- risk assessment
- gene expression
- mesenchymal stem cells
- genome wide identification
- dna methylation
- big data
- binding protein
- data analysis