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Dnmt3a regulates T-cell development and suppresses T-ALL transformation.Dnmt3a调节T细胞发育并抑制T-ALL转化。
Leukemia. 2017 Nov;31(11):2479-2490. doi: 10.1038/leu.2017.89. Epub 2017 Mar 21.
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The genetics and molecular biology of T-ALL.T 细胞急性淋巴细胞白血病的遗传学与分子生物学
Blood. 2017 Mar 2;129(9):1113-1123. doi: 10.1182/blood-2016-10-706465. Epub 2017 Jan 23.
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Pediatric T-cell acute lymphoblastic leukemia.小儿T细胞急性淋巴细胞白血病
Genes Chromosomes Cancer. 2017 Feb;56(2):89-116. doi: 10.1002/gcc.22416. Epub 2016 Oct 25.
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[T细胞急性淋巴细胞白血病关键基因的筛选与验证]

[Screening and verification of key genes in T-cell acute lymphoblastic leukemia].

作者信息

Jiang Guang-Jie, Chen Yan-Hua, Guo Wei, Zhang Hang, Zou Lin

机构信息

Center for Clinical Molecular Medicine, Children's Hospital of Chongqing Medical University/Ministry of Education Key Laboratory of Child Development and Disorders/Key Laboratory of Pediatrics in Chongqing/Chongqing International Science and Technology Cooperation Center for Child Development and Disorders, Chongqing 400014, China. E-mail:

出版信息

Nan Fang Yi Ke Da Xue Xue Bao. 2018 Mar 20;38(3):261-267. doi: 10.3969/j.issn.1673-4254.2018.03.04.

DOI:10.3969/j.issn.1673-4254.2018.03.04
PMID:29643030
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6744169/
Abstract

OBJECTIVE

To explore the key genes in T-cell acute lymphoblastic leukemia (T-ALL) using bioinformatics method to better understand the pathogenic mechanisms of T-ALL.

METHODS

The gene expression profiles of GSE14317 were obtained from Gene Expression Omnibus database. The differentially expressed genes (DEGs) in T-ALL were analyzed using R package Limma. The online analysis tool DAVID was used to perform the functional and pathway enrichment analysis. The protein-protein interaction network was constructed by STRING and visualized by Cytoscape. Based on the JASPAR database, the transcription factors (TFs) of the hub genes were obtained. RT-PCR was used to test the mRNA expression level of the key genes.

RESULTS

A total of 1443 DEGs were identified, including 800 up-regulated genes and 643 down-regulated genes. These DEGs were significantly enriched in the cell cycle, hematopoietic cell lineage, cytokine-cytokine receptor interaction and T cell receptor signaling pathway. The top 10 hub genes identified from the PPI networks included CDK1, PIK3R1, CCNB1, CCNA2, CDC20, JUN, GNG11, PLK1, PCNA and CCNB2, which were enriched in chemokine signaling pathway, ubiquition mediated proteolysis and cell cycle. In the TF-target gene network, 42 differentially expressed TFs were identified, among which ELF5, HIC2 and MEISI had binding sites with 9 of the candidate hub genes. RT-PCR showed that the mRNA expression level of all the candidate hub genes except for GNG11 were consistent with the gene expression profiles.

CONCLUSION

The hub genes CDK1, PIK3R1, CCNB1, CCNA2, CDC20, JUN, PLK1, PCNA, CCNB2, ELF5, HIC2 and MEISI participate in the occurrence of T-ALL. Our finding provides new insights into the pathogenesis of T-ALL.

摘要

目的

运用生物信息学方法探索T细胞急性淋巴细胞白血病(T-ALL)中的关键基因,以更好地理解T-ALL的致病机制。

方法

从基因表达综合数据库获取GSE14317的基因表达谱。使用R包Limma分析T-ALL中的差异表达基因(DEG)。利用在线分析工具DAVID进行功能和通路富集分析。通过STRING构建蛋白质-蛋白质相互作用网络,并由Cytoscape进行可视化。基于JASPAR数据库,获取枢纽基因的转录因子(TF)。采用RT-PCR检测关键基因的mRNA表达水平。

结果

共鉴定出1443个DEG,其中上调基因800个,下调基因643个。这些DEG在细胞周期、造血细胞谱系、细胞因子-细胞因子受体相互作用和T细胞受体信号通路中显著富集。从PPI网络中鉴定出的前10个枢纽基因包括CDK1、PIK3R1、CCNB1、CCNA2、CDC20、JUN、GNG11、PLK1、PCNA和CCNB2,它们在趋化因子信号通路、泛素介导的蛋白水解和细胞周期中富集。在TF-靶基因网络中,鉴定出42个差异表达的TF,其中ELF5、HIC2和MEISI与9个候选枢纽基因具有结合位点。RT-PCR显示,除GNG11外,所有候选枢纽基因的mRNA表达水平与基因表达谱一致。

结论

枢纽基因CDK1、PIK3R1、CCNB1、CCNA2、CDC20、JUN、PLK1、PCNA、CCNB2、ELF5、HIC2和MEISI参与T-ALL的发生。我们的发现为T-ALL的发病机制提供了新的见解。