FYN and CD247: Key Genes for Septic Shock Based on Bioinformatics and Meta-Analysis.

Septic shock is sepsis accompanied by hemodynamic instability and high clinical mortality. GSE95233, GSE57065, GSE131761 gene-expression profiles of healthy control subjects and septic shock patients were downloaded from the Gene-Expression Omnibus (GEO) database, and differences of expression profiles and their intersection were analysed using GEO2R. Function and pathway enrichment analysis was performed on common differentially expressed genes (DEG), and key genes for septic shock were screened using a protein-protein interaction network created with STRING. Also, data from the GEO database were used for survival analysis for key genes, and a meta-analysis was used to explore expression trends of core genes. Finally, high-throughput sequencing using the blood of a murine sepsis model was performed to analyse the expression of CD247 and FYN in mice. A total of 539 DEGs were obtained (p < 0.05). Gene ontology analysis showed that key genes were enriched in functions, such as immune response and T cell activity, and DEGs were enriched in signal pathways, such as T cell receptors. FYN and CD247 are in the centre of the protein-protein interaction network, and survival analysis found that they are positively correlated with survival from sepsis. Further, meta-analysis results showed that FYN could be useful for the prognosis of patients, and CD247 might distinguish between sepsis and systemic inflammatory response syndrome patients. Finally, RNA sequencing using a mouse septic shock model showed low expression of CD247 and FYN in this model. FYN and CD247 are expected to become new biomarkers of septic shock. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.

Citation

Yue Jiang, Qian Miao, Lin Hu, Tingyan Zhou, Yingchun Hu, Ye Tian. FYN and CD247: Key Genes for Septic Shock Based on Bioinformatics and Meta-Analysis. Combinatorial chemistry & high throughput screening. 2022;25(10):1722-1730

Mesh Tags

PMID: 34397323

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