Upregulation of Natural Killer Cells Proliferation by Cytokine Stimulation

Pencheva-Demireva, Magdalena; El‐Darawish, Yosif; Kavaldzhieva, Katerina; Mladenov, Nikola; Lazarov, Vladislav V.; Dimitrova-Dikanarova, Dimitrina; Markova, Tzvetanka; Nikolov, Roumen; Okamura, Haruki

doi:10.1089/mab.2019.0009

Cited by 2 publications

(1 citation statement)

References 21 publications

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“…Low expression of cluster of differentiation 69 ( CD69 ) was found to propagate enhanced inflammatory responses and worsen brain damage after ischemic stroke in animal models through immune cells [ 25 ]. Interestingly, here, the expanded natural killer cells showed significant upregulation of CD69 [ 26 ]. Consistently, clinical data from two independent cohorts of patients indicated that increased CD69 expression in peripheral blood cells after acute myocardial infarction was associated with a lower risk of rehospitalization for heart failure after 2.5 years of follow-up [ 27 ].…”

Section: Discussionmentioning

confidence: 99%

Analysis of Inflammation-Related Genes in Patients with Stanford Type A Aortic Dissection

Lin

Zeng

Yagublu

et al. 2023

JPM

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Background: Aortic dissection (AD) is a life-threatening cardiovascular disease. Pathophysiologically, it has been shown that aortic wall inflammation promotes the occurrence and development of aortic dissection. Thus, the aim of the current research was to determine the inflammation-related biomarkers in AD. Methods: In this study, we conducted differentially expressed genes (DEGs) analysis using the GSE153434 dataset containing 10 type A aortic dissection (TAAD) and 10 normal samples downloaded from the Gene Expression Omnibus (GEO) database. The intersection of DEGs and inflammation-related genes was identified as differential expressed inflammation-related genes (DEIRGs). Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed for DEIRGs. We then constructed the protein–protein interaction (PPI) network using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database and identified hub genes using the Cytoscape plugin MCODE. Finally, least absolute shrinkage and selection operator (LASSO) logistic regression was used to construct a diagnostic model. Results: A total of 1728 DEGs were identified between the TAAD and normal samples. Thereafter, 61 DEIRGs are obtained by taking the intersection of DEGs and inflammation-related genes. The GO indicated that DEIRGs were mainly enriched in response to lipopolysaccharide, in response to molecules of bacterial origin, secretory granule membrane, external side of plasma, receptor ligand activity, and signaling receptor activator activity. KEGG analysis indicated that DEIRGs were mainly enriched in cytokine–cytokine receptor interaction, TNF signaling pathway, and proteoglycans in cancer. We identified MYC, SELL, HIF1A, EDN1, SERPINE1, CCL20, IL1R1, NOD2, TLR2, CD69, PLAUR, MMP14, and HBEGF as hub genes using the MCODE plug-in. The ROC indicated these genes had a good diagnostic performance for TAAD. Conclusion: In conclusion, our study identified 13 hub genes in the TAAD. This study will be of significance for the future development of a preventive therapy of TAAD.

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Section: Discussionmentioning

confidence: 99%