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利用生物信息学分析鉴定急性髓系白血病相关的枢纽基因和通路

Identification of the hub genes and pathways involved in acute myeloid leukemia using bioinformatics analysis.

作者信息

Tan Youping, Zheng Liling, Du Yuanyuan, Zhong Qi, Zhu Yangmin, Liu Zhi, Liu Shuang, Zhang Qing

机构信息

Department of Hematology, Guangdong Second Provincial General Hospital, Guangzhou, Guangdong Province, P. R. China.

出版信息

Medicine (Baltimore). 2020 Aug 28;99(35):e22047. doi: 10.1097/MD.0000000000022047.

DOI:10.1097/MD.0000000000022047
PMID:32871963
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7458232/
Abstract

BACKGROUND

We identified the hub genes and pathways dysregulated in acute myeloid leukemia and the potential molecular mechanisms involved.

METHODS

We downloaded the GSE15061 gene expression dataset from the Gene Expression Omnibus database and used weighted gene co-expression network analysis to identify hub genes. Differential expression of the genes was evaluated using the limma package in R software. Subsequently, we built a protein-protein interaction network followed by functional enrichment analysis. Then, the prognostic significance of gene expression was explored in terms of overall survival. Finally, transcription factor-mRNA (ribonucleic acid) and microRNA-mRNA interaction analysis was also explored.

RESULTS

We identified 100 differentially expressed hub genes. Functional enrichment analysis indicated that the genes were principally involved in immune system regulation, host defense, and negative regulation of apoptosis and myeloid cell differentiation. We identified 4 hub genes, the expression of which was significantly correlated with overall survival. Finally, 26 key regulators for hub genes and 38 microRNA-mRNA interactions were identified.

CONCLUSION

We performed a comprehensive bioinformatics analysis of hub genes potentially involved in acute myeloid leukemia development. Further molecular biological experiments are required to confirm the roles played by these genes.

摘要

背景

我们确定了急性髓系白血病中失调的枢纽基因和通路以及其中潜在的分子机制。

方法

我们从基因表达综合数据库下载了GSE15061基因表达数据集,并使用加权基因共表达网络分析来识别枢纽基因。使用R软件中的limma包评估基因的差异表达。随后,我们构建了蛋白质-蛋白质相互作用网络,接着进行功能富集分析。然后,从总生存期方面探讨基因表达的预后意义。最后,还探讨了转录因子-信使核糖核酸(mRNA)和微小RNA-mRNA相互作用分析。

结果

我们确定了100个差异表达的枢纽基因。功能富集分析表明,这些基因主要参与免疫系统调节、宿主防御以及细胞凋亡和髓系细胞分化的负调控。我们确定了4个枢纽基因,其表达与总生存期显著相关。最后,确定了26个枢纽基因的关键调节因子和38个微小RNA-mRNA相互作用。

结论

我们对可能参与急性髓系白血病发生发展的枢纽基因进行了全面的生物信息学分析。需要进一步的分子生物学实验来证实这些基因所起的作用。

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