基于高通量芯片对小儿急性髓系白血病的生物信息学分析

doi:10.13481/j.1671-587x.20200522

吉林大学学报(医学版) ›› 2020, Vol. 46 ›› Issue (05): 1036-1042.doi: 10.13481/j.1671-587x.20200522

• 临床研究 • 上一篇

基于高通量芯片对小儿急性髓系白血病的生物信息学分析

张曦¹, 翟丽¹, 孙运艳², 杨伟¹, 高艳章¹, 雷鸣¹, 潘玉卿³

1. 云南省肿瘤医院·昆明医科大学第三附属医院检验科, 云南昆明 650118;
2. 云南省肿瘤医院·昆明医科大学第三附属医院血液科, 云南昆明 650118;
3. 昆明医科大学第一附属医院检验科云南省实验诊断研究所云南省检验医学重点实验室, 云南昆明 650032

收稿日期:2019-12-27 发布日期:2020-10-23
通讯作者: 潘玉卿,检验师(Tel:0871-65324888,E-mail:panyuqing@kmmu.edu.cn);高艳章,副主任技师(Tel:0871-68179518,E-mail:2826169302@88.com) E-mail:panyuqing@kmmu.edu.cn;2826169302@88.com
作者简介:张曦(1986-),男,云南省昆明市人,主管检验师,医学硕士,主要从事肿瘤的分子机制等方面的研究。
基金资助:
云南省科技厅-昆明医科大学联合专项资助课题（2015FB070）；云南省教育厅科学研究基金项目资助课题（2019J1276）

Bioinformatics analysis of pediatric acute myeloid leukemia based on high-throughput microarray

ZHANG Xi¹, ZHAI Li¹, SUN Yunyan², YANG Wei¹, GAO Yanzhang¹, LEI Ming¹, PAN Yuqing³

1. Department of Clinical Laboratory, Caner Hospital of Yunnan Province, Third Affiliated Hospital, Kunming Medical University, Kunming 650118, China;
2. Department of Hematology, Caner Hospital of Yunnan Province, Third Affiliated Hospital, Kunming Medical University, Kunming 650118, China;
3. Department of Clinical Laboratory, First Affiliated Hospital, Kunming Medical University, Yunnan Institute of Experimental Diagnosis, Yunnan Key Laboratory of Laboratory Medicine, Kunming 650032, China

Received:2019-12-27 Published:2020-10-23

摘要/Abstract

摘要： 目的：通过生物信息学工具筛选小儿急性髓系白血病（AML）相关的差异表达基因（DEGs），探讨小儿AML的核心基因并阐明其发病机制。方法：从基因表达数据库（GEO）下载符合本研究要求的小儿AML的转录组数据，采用基因表达分析工具（GEO2R）进行DEGs的筛选。利用基因本体功能注释（GO）及京都基因与基因组百科全书（KEGG）分析DEGs功能及通路富集情况；利用STRING数据库构建蛋白质互作网络（PPI）并利用Cytoscape软件及插件iRegulon筛选相关的核心基因（Hub genes）及转录因子，通过生物技术信息基因云（GCBI）在线数据库分析前5位的核心基因。结果：本研究共筛选出600个DEGs，其中407个基因上调，193个基因下调。GO分析，相关的DEGs主要参与细胞成分的组成，包括核浆、细胞质、核膜和核斑点。KEGG分析，DEGs主要在肿瘤坏死因子（TNF）、细胞因子受体相互作用及Jak激酶/信号转导与转录激活子（Jak-STAT）信号通路中富集。通过STRING数据库及Cytoscape软件共筛选出甲酰肽受体2（FPR2）、磷酸肌醇3激酶调节亚单位1（PIK3R1）、E1A结合蛋白p300（EP300）、热休克蛋白90α家族（HSP90AA1）和NRAS原癌基因（NRAS）等前20个连接度最高的核心基因，其中EP300、HSP90AA1和NRAS参与了白血病的发生发展。iRegulon共筛选出TP63、NFE2L1和TBX等55个作用于Hub基因的转录因子。结论：筛选出的核心基因和转录因子可能参与小儿AML的发生发展，并可能成为小儿AML的治疗新靶点。

关键词: 生物信息学, 急性髓系白血病, 差异基因, 基因芯片

Abstract: Objective: To screen the differentially expressed genes (DEGs) related to pediatric acute myeloid leukemia (AML) with bioinformatics tools, and to explore the core genes of AML and clarify its pathogenesis. Methods: The transcriptional data of pediatric AML met the requirement were obtained from Gene Expression Omnibus (GEO) database. The DEGs were further screened out using GEO2R web tool, and the functional annotation of Gene Ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) were used to analyze the function and pathway enrichment of the DEGs. STRING database was used to construct protein-protein interaction (PPI) network, and the relative Hub genes and transcription factors were screened with Cytoscape software and iRegulon. The top five core genes were analyzed through Gene-Cloud of Biotechnology Information (GCBI) online database. Results: A total of 600 DEGs were identified, of which 407 genes were up-regulated and 193 genes were down-regulated. The GO analysis results showed that most of DEGs were associated with cellular components including nucleoplasm, cytosol, membrane and nuclear speck. The KEGG analysis demonstrated that the DEGs were mainly enriched in the tumor necrosis factor(TNF) signaling pathway, cytokine-cytokine receptor interaction, and Jak-STAT signaling pathway. Through STRING database and Cytoscape software, a total of the top 20 core genes with the highest connection were screened out, including FPR2, PIK3R1, EP300, HSP90AA1, and NRAS. Among them, Ep300, HSP90AA1,and NRAS were associated with the development of leukemia. Moreover, iRegulon tool screened 55 transcription factors which targeted to the Hub genes such as TP63, NFE2L1 and TBX. Conclusion: The selected Hub genes and transcription factors maybe participate in the occurrence and development of pediatric AML and may be used as new therapeutic target for the disease.

Key words: bioinformatics, acute myeloid leukemia, differential genes, gene chip

中图分类号:

R733.7

张曦, 翟丽, 孙运艳, 杨伟, 高艳章, 雷鸣, 潘玉卿. 基于高通量芯片对小儿急性髓系白血病的生物信息学分析[J]. 吉林大学学报(医学版), 2020, 46(05): 1036-1042.

ZHANG Xi, ZHAI Li, SUN Yunyan, YANG Wei, GAO Yanzhang, LEI Ming, PAN Yuqing. Bioinformatics analysis of pediatric acute myeloid leukemia based on high-throughput microarray[J]. Journal of Jilin University(Medicine Edition), 2020, 46(05): 1036-1042.

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基于高通量芯片对小儿急性髓系白血病的生物信息学分析

Bioinformatics analysis of pediatric acute myeloid leukemia based on high-throughput microarray

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