Dataset Information

Integration of Gene Expression Profile Data to Verify Hub Genes of Patients with Stanford A Aortic Dissection.

ABSTRACT: Thoracic aortic dissection (TAD) is a catastrophic disease worldwide, but the pathogenic genes and pathways are largely unclear. This study aims at integrating two gene expression profile datasets and verifying hub genes and pathways involved in TAD as well as exploring potential molecular mechanisms. We will combine our mRNAs expression profile (6 TAD tissues versus 6 non-TAD tissues) and GSE52093 downloaded from the Gene Expression Omnibus (GEO) database. The two mRNAs expression profiles contained 13 TAD aortic tissues and 11 non-TAD tissues. The two expression profile datasets were integrated and we found out coexpression of differentially expressed genes (DEGs) using bioinformatics methods. The gene ontology and pathway enrichment of DEGs were performed by DAVID and Kyoto Encyclopedia of Genes and Genomes online analyses, respectively. The protein-protein interaction networks of the DEGs were constructed according to the data from the STRING database. Cytohubber calculating result shows the top 10 hub genes with CDC20, AURKA, RFC4, MCM4, TYMS, MCM2, DLGAP5, FANCI, BIRC5, and POLE2. Module analysis revealed that TAD was associated with significant pathways including cell cycle, vascular smooth muscle contraction, and adrenergic signaling in cardiomyocytes. The qRT-PCR result showed that the expression levels of all the hub genes were significantly increased in OA samples (p < 0.05), and these candidate genes could be used as potential diagnostic biomarkers and therapeutic targets of TAD.

SUBMITTER: Wang W

PROVIDER: S-EPMC6662449 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Integration of Gene Expression Profile Data to Verify Hub Genes of Patients with Stanford A Aortic Dissection.

Wang Weitie W Wang Tiance T Wang Yong Y Piao Hulin H Li Bo B Zhu Zhicheng Z Xu Rihao R Li Dan D Liu Kexiang K

BioMed research international 20190714

Thoracic aortic dissection (TAD) is a catastrophic disease worldwide, but the pathogenic genes and pathways are largely unclear. This study aims at integrating two gene expression profile datasets and verifying hub genes and pathways involved in TAD as well as exploring potential molecular mechanisms. We will combine our mRNAs expression profile (6 TAD tissues versus 6 non-TAD tissues) and GSE52093 downloaded from the Gene Expression Omnibus (GEO) database. The two mRNAs expression profiles cont ...[more]

PMID: 31380418

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Project description:Background: Stanford type A aortic dissection (AAD) is a catastrophic disease. An immune infiltrate has been found within the aortic wall of dissected aortic specimens. The recall and activation of macrophages are key events in the early phases of AAD. Herein, the immune filtration profile of AAD was uncovered. Methods: Gene expression data from the GSE52093, GSE98770 and GSE153434 datasets were downloaded from the Gene Expression Omnibus (GEO). The differentially expressed genes (DEGs) of each dataset were calculated and then integrated. A protein-protein interaction (PPI) network was established with the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), and the hub genes were identified in Cytoscape. Furthermore, gene ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of hub genes were performed. Finally, we set GSE52093 and GSE98770 as the training set and GSE153434 as the validation set to assess immune infiltration in AAD using CIBERSORTx and analyzed the correlations between immune cells and hub genes in both the training and validation sets. Results: Sixty-one integrated DEGs were identified. The top 10 hub genes were selected from the PPI network, and 140 biological process (BP) terms and 12 pathways were enriched among the top 10 hub genes. The proportions of monocytes and macrophages were significantly higher in AAD tissues than in normal tissues. Notably, this result was consistent in the training set and the validation set. In addition, we found that among the hub genes, CA9, CXCL5, GDF15, VEGFA, CCL20, HMOX1, and SPP1 were positively correlated with CD14, a cell marker of monocytes, while CA9, CXCL5, GDF15, and VEGFA were positively correlated with CD68, a cell marker of macrophages in the training set. Finally, according to the results of the GO and KEGG analysis of hub genes, we found that the monocyte/macrophage-related genes were involved in immune-inflammatory responses through degradation of the extracellular matrix, endothelial cell apoptosis, hypoxia and the interaction of cytokines and chemokines. Conclusion: The monocyte-macrophage system plays a major role in immune-inflammatory responses in the development of AAD. Several hub genes are involved in this process via diverse mechanisms.

Project description:Background: Stanford type A aortic dissection (ATAAD) is a common life-threatening event in the aorta. Recently, immune disorder has been linked to the risk factors that cause ATAAD at the molecular level. However, the specific immune-related gene signature during the progression is unclear. Methods: The GSE52093 and GSE98770 datasets related to ATAAD from the Gene Expression Omnibus (GEO) database were acquired. The immune gene expression levels were analyzed by single sample gene set enrichment analysis (ssGSEA). The correlations between gene networks and immune scores were determined by weighted gene correlation network analysis (WGCNA). The different immune subgroups were finally divided by consensus clustering. The differentially expressed genes (DEGs) were identified and subsequent functional enrichment analyses were conducted. The hub genes were identified by protein-protein interaction (PPI) network and functional similarities analyses. The immune cell infiltration proportion was determined by the CIBERSORT algorithm. Results: According to the ssGSEA results, the 13 ATAAD samples from the GEO database were divided into high- and low-immune subgroups according to the ssGSEA, WGCNA, and consensus clustering analysis results. Sixty-eight immune-related DEGs (IRDEGs) between the two subgroups were enriched in inflammatory-immune response biological processes, including leukocyte cell-cell adhesion, mononuclear cell migration, and myeloid leukocyte migration. Among these IRDEGs, 8 genes (CXCR4, LYN, CCL19, CCL3L3, SELL, F11R, DPP4, and VAV3) were identified as hub genes that represented immune-related signatures in ATAAD after the PPI and functional similarities analyses. The proportions of infiltrating CD8 T cells and M1 macrophages were significantly higher in ATAAD patients in the immune-high group than the immune-low group. Conclusion: Eight immune-related genes were identified as hub genes representing potential biomarkers and therapeutic targets linked to the immune response in ATAAD patients.

Dataset Information

Integration of Gene Expression Profile Data to Verify Hub Genes of Patients with Stanford A Aortic Dissection.

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Integration of Gene Expression Profile Data to Verify Hub Genes of Patients with Stanford A Aortic Dissection.

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