Yao Xiaoting, Jing Tian, Wang Tianxing, Gu Chenxin, Chen Xi, Chen Fengqiang, Feng Hao, Zhao Huiying, Chen Dekun, Ma Wentao
College of Veterinary Medicine, Northwest A&F University, Xianyang, China.
Front Physiol. 2021 Jul 23;12:694702. doi: 10.3389/fphys.2021.694702. eCollection 2021.
Pulmonary arterial hypertension (PAH) is a life-threatening chronic cardiopulmonary disease. However, there are limited studies reflecting the available biomarkers from separate gene expression profiles in PAH. This study explored two microarray datasets by an integrative analysis to estimate the molecular signatures in PAH. Two microarray datasets (GSE53408 and GSE113439) were exploited to compare lung tissue transcriptomes of patients and controls with PAH and to estimate differentially expressed genes (DEGs). According to common DEGs of datasets, gene and protein overrepresentation analyses, protein-protein interactions (PPIs), DEG-transcription factor (TF) interactions, DEG-microRNA (miRNA) interactions, drug-target protein interactions, and protein subcellular localizations were conducted in this study. We obtained 38 common DEGs for these two datasets. Integration of the genome transcriptome datasets with biomolecular interactions revealed hub genes (HSP90AA1, ANGPT2, HSPD1, HSPH1, TTN, SPP1, SMC4, EEA1, and DKC1), TFs (FOXC1, FOXL1, GATA2, YY1, and SRF), and miRNAs (hsa-mir-17-5p, hsa-mir-26b-5p, hsa-mir-122-5p, hsa-mir-20a-5p, and hsa-mir-106b-5p). Protein-drug interactions indicated that two compounds, namely, nedocromil and SNX-5422, affect the identification of PAH candidate biomolecules. Moreover, the molecular signatures were mostly localized in the extracellular and nuclear areas. In conclusion, several lung tissue-derived molecular signatures, highlighted in this study, might serve as novel evidence for elucidating the essential mechanisms of PAH. The potential drugs associated with these molecules could thus contribute to the development of diagnostic and therapeutic strategies to ameliorate PAH.
肺动脉高压(PAH)是一种危及生命的慢性心肺疾病。然而,反映PAH中不同基因表达谱可用生物标志物的研究有限。本研究通过综合分析探索了两个微阵列数据集,以评估PAH中的分子特征。利用两个微阵列数据集(GSE53408和GSE113439)比较PAH患者和对照的肺组织转录组,并评估差异表达基因(DEG)。根据数据集的共同DEG,本研究进行了基因和蛋白质过度表达分析、蛋白质-蛋白质相互作用(PPI)、DEG-转录因子(TF)相互作用、DEG-微小RNA(miRNA)相互作用、药物-靶蛋白相互作用以及蛋白质亚细胞定位分析。我们为这两个数据集获得了38个共同的DEG。基因组转录组数据集与生物分子相互作用的整合揭示了关键基因(HSP90AA1、ANGPT2、HSPD1、HSPH1、TTN、SPP1、SMC4、EEA1和DKC1)、TF(FOXC1、FOXL1、GATA2、YY1和SRF)以及miRNA(hsa-mir-17-5p、hsa-mir-26b-5p、hsa-mir-122-5p、hsa-mir-20a-5p和hsa-mir-106b-5p)。蛋白质-药物相互作用表明,奈多罗米和SNX-5422这两种化合物会影响PAH候选生物分子的识别。此外,分子特征大多定位于细胞外和细胞核区域。总之,本研究中突出的几种肺组织衍生分子特征可能为阐明PAH的基本机制提供新证据。与这些分子相关的潜在药物可能有助于开发改善PAH的诊断和治疗策略。