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Abstract：
BACKGROUND: Sepsis is a serious clinical condition with a poor prognosis, despite improvements in diagnosis and treatment.Therefore, novel biomarkers are necessary that can help with estimating prognosis and improving clinical outcomes of patients with sepsis.
METHODS: The gene expression profiles GSE54514 and GSE63042 were downloaded from the GEO database. DEGs were screened by t test after logarithmization of raw data; then, the common DEGs between the 2 gene expression profiles were identified by up-regulation and down-regulation intersection. The DEGs were analyzed using bioinformatics, and a protein-protein interaction (PPI) survival network was constructed using STRING. Survival curves were constructed to explore the relationship between core genes and the prognosis of sepsis patients based on GSE54514 data.
RESULTS: A total of 688 common DEGs were identified between survivors and non-survivors of sepsis, and 96 genes were involved in survival networks. The crucial genes Signal transducer and activator of transcription 5A (STAT5A), CCAAT/enhancer-binding protein beta (CEBPB), Myc proto-oncogene protein (MYC), and REL-associated protein (RELA) were identified and showed increased expression in sepsis survivors. These crucial genes had a positive correlation with patients\' survival time according to the survival analysis.
CONCLUSIONS: Our findings indicate that the genes STAT5A, CEBPB, MYC, and RELA may be important in predicting the prognosis of sepsis patients.
METHODS: The gene expression profiles GSE54514 and GSE63042 were downloaded from the GEO database. DEGs were screened by t test after logarithmization of raw data; then, the common DEGs between the 2 gene expression profiles were identified by up-regulation and down-regulation intersection. The DEGs were analyzed using bioinformatics, and a protein-protein interaction (PPI) survival network was constructed using STRING. Survival curves were constructed to explore the relationship between core genes and the prognosis of sepsis patients based on GSE54514 data.
RESULTS: A total of 688 common DEGs were identified between survivors and non-survivors of sepsis, and 96 genes were involved in survival networks. The crucial genes Signal transducer and activator of transcription 5A (STAT5A), CCAAT/enhancer-binding protein beta (CEBPB), Myc proto-oncogene protein (MYC), and REL-associated protein (RELA) were identified and showed increased expression in sepsis survivors. These crucial genes had a positive correlation with patients\' survival time according to the survival analysis.
CONCLUSIONS: Our findings indicate that the genes STAT5A, CEBPB, MYC, and RELA may be important in predicting the prognosis of sepsis patients.
摘要：
背景：脓毒症是一种严重的临床疾病，预后不良，尽管在诊断和治疗方面有所改善。因此,新的生物标志物是必要的,可以帮助评估脓毒症患者的预后和改善临床结局.
方法：基因表达谱GSE54514和GSE63042从GEO数据库下载。将原始数据对数化后，通过t检验筛选DEGs；然后，2个基因表达谱之间的共同DEGs通过上调和下调交集进行鉴定。使用生物信息学分析DEGs，并使用STRING构建了蛋白质-蛋白质相互作用(PPI)生存网络。基于GSE54514数据构建生存曲线,探讨核心基因与脓毒症患者预后的关系。
结果：在败血症的幸存者和非幸存者之间确定了总共688个常见的DEGs，96个基因参与生存网络。关键基因信号转导和转录激活因子5A（STAT5A），CCAAT/增强子结合蛋白β（CEBPB），Myc原癌基因蛋白（MYC），和REL相关蛋白（RELA）在脓毒症幸存者中的表达增加。根据生存分析，这些关键基因与患者的生存时间呈正相关。
结论：我们的发现表明STAT5A基因，CEBPB,MYC,RELA对预测脓毒症患者的预后有重要意义。
方法：基因表达谱GSE54514和GSE63042从GEO数据库下载。将原始数据对数化后，通过t检验筛选DEGs；然后，2个基因表达谱之间的共同DEGs通过上调和下调交集进行鉴定。使用生物信息学分析DEGs，并使用STRING构建了蛋白质-蛋白质相互作用(PPI)生存网络。基于GSE54514数据构建生存曲线,探讨核心基因与脓毒症患者预后的关系。
结果：在败血症的幸存者和非幸存者之间确定了总共688个常见的DEGs，96个基因参与生存网络。关键基因信号转导和转录激活因子5A（STAT5A），CCAAT/增强子结合蛋白β（CEBPB），Myc原癌基因蛋白（MYC），和REL相关蛋白（RELA）在脓毒症幸存者中的表达增加。根据生存分析，这些关键基因与患者的生存时间呈正相关。
结论：我们的发现表明STAT5A基因，CEBPB,MYC,RELA对预测脓毒症患者的预后有重要意义。
