School of BioSciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India.
Department of Biotechnology, Sri Ramachandra Institute of Higher Education and Research (DU), Porur, Chennai, Tamil Nadu, India.
Adv Protein Chem Struct Biol. 2021;127:315-342. doi: 10.1016/bs.apcsb.2021.02.004. Epub 2021 Apr 15.
Lung Emphysema is an abnormal enlargement of the air sacs followed by the destruction of alveolar walls without any prominent fibrosis. This study primarily identifies the differentially expressed genes (DEGs), interactions between them, and their significant involvement in the activated signaling cascades. The dataset with ID GSE1122 (five normal lung tissue samples, five of usual emphysema, and five of alpha-1 antitrypsin deficiency-related emphysema) from the gene expression omnibus (GEO) was analyzed using the GEO2R tool. The physical association between the DEGs were mapped using the STRING tool and was visualized in the Cytoscape software. The enriched functional processes were identified with the ClueGO plugin's help from Cytoscape. Further integrative functional annotation was performed by implying the GeneGo Metacore™ to distinguish the enriched pathway maps, process networks, and GO processes. The results from this analysis revealed the critical signaling cascades that have been either activated or inhibited due to identified DEGs. We found the activated pathways such as immune response IL-1 signaling pathway, positive regulation of smooth muscle migration, BMP signaling pathway, positive regulation of leukocyte migration, NIK/NF-kappB signaling, and cytochrome-c oxidase activity. Finally, we mapped four crucial genes (CCL5, ALK, TAC1, CD74, and HLA-DOA) by comparing the functional annotations that could be significantly influential in emphysema molecular pathogenesis. Our study provides insights into the pathogenesis of emphysema and helps in developing potential drug targets against emphysema.
肺大泡是一种肺泡壁破坏的空气囊异常增大，没有明显的纤维化。本研究主要鉴定差异表达基因（DEGs）、它们之间的相互作用及其在激活信号级联中的重要作用。该数据集的 ID 为 GSE1122（来自基因表达综合数据库（GEO）的五个正常肺组织样本、五个普通肺气肿样本和五个α-1 抗胰蛋白酶缺乏相关肺气肿样本），使用 GEO2R 工具进行分析。使用 STRING 工具绘制 DEGs 之间的物理关联，并在 Cytoscape 软件中可视化。使用 Cytoscape 中的 ClueGO 插件识别丰富的功能过程。通过引入 GeneGo Metacore™进一步进行综合功能注释，以区分丰富的途径图、过程网络和 GO 过程。通过这项分析，我们发现了由于鉴定的 DEGs 而被激活或抑制的关键信号级联。我们发现了激活的途径，如免疫反应的 IL-1 信号通路、平滑肌迁移的正调控、BMP 信号通路、白细胞迁移的正调控、NIK/NF-kappB 信号通路和细胞色素-c 氧化酶活性。最后，我们通过比较功能注释映射了四个关键基因（CCL5、ALK、TAC1、CD74 和 HLA-DOA），这些功能注释可能对肺气肿的分子发病机制有重要影响。我们的研究为肺气肿的发病机制提供了深入的了解，并有助于开发针对肺气肿的潜在药物靶点。
