Integrated bioinformatics analysis of the crucial candidate genes and pathways associated with glucocorticoid resistance in acute lymphoblastic leukemia
Integrated bioinformatics analysis of the crucial candidate genes and pathways associated with glucocorticoid resistance in acute lymphoblastic leukemia
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急性淋巴细胞白血病糖皮质激素耐药相关关键候选基因和通路的综合生物信息学分析
DOI：
10.1002/cam4.2934
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发表时间：
2020-02-25
期刊：
影响因子：
4
通讯作者：
Hu, Jianda
中科院分区：
文献类型：
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作者：
Chen, Yanxin;Jiang, Peifang;Hu, Jianda
糖皮质激素（GC）是急性淋巴细胞白血病（ALL）化疗方案的基础。然而，在ALL复发患者中，GC耐药比其他化疗药物耐药更常见。此外，ALL中GC耐药性发生的机制尚未完全揭示。在本研究中，我们采用生物信息学分析方法整合了ALL中参与GC耐药的候选基因和途径，并通过体外细胞实验验证了生物信息学研究结果。通过整合两个基因谱数据集，包括GC敏感和GC耐药样本，确定了99个与GC耐药相关的显著共同差异表达基因（DEGs）。利用京都基因与基因组百科全书（KEGG）和REACTOME通路分析，对DEGs显著富集的信号通路进行聚类。GC抗性相关的生物功能相互作用被可视化为DEG相关的蛋白-蛋白相互作用（PPI）网络复合物，具有98个节点和127个边。在PPI网络中，MYC节点的连通性最高，被突出显示为核心基因。在阿霉素耐药的BALL - 1/ADR细胞中观察到C‐MYC表达增加，我们证明了它也对地塞米松耐药。这些结果勾勒出一个将孤立和分散的实验结果整合和扩展的全景。与此同时，研究人员还发现了参与ALL GC耐药的候选途径和基因的潜在靶点。
Glucocorticoids (GC) are the foundation of the chemotherapy regimen in acute lymphoblastic leukemia (ALL). However, resistance to GC is observed more frequently than resistance to other chemotherapy agents in patients with ALL relapse. Moreover, the mechanism underlying the development of GC resistance in ALL has not yet been fully uncovered. In this study, we used bioinformatic analysis methods to integrate the candidate genes and pathways participating in GC resistance in ALL and subsequently verified the bioinformatics findings with in vitro cell experiments. Ninety‐nine significant common differentially expressed genes (DEGs) associated with GC resistance were determined by integrating two gene profile datasets, including GC‐sensitive and ‐resistant samples. Using Kyoto Encyclopedia of Genes and Genomes (KEGG) and REACTOME pathways analysis, the signaling pathways in which DEGs were significantly enriched were clustered. The GC resistance‐related biologically functional interactions were visualized as DEG‐associated Protein–Protein Interaction (PPI) network complexes, with 98 nodes and 127 edges. MYC, a node which displayed the highest connectivity in all edges, was highlighted as the core gene in the PPI network. Increased C‐MYC expression was observed in adriamycin‐resistant BALL‐1/ADR cells, which we demonstrated was also resistant to dexamethasone. These results outlined a panorama in which the solitary and scattered experimental results were integrated and expanded. The potential promising target of the candidate pathways and genes involved in GC resistance of ALL was concomitantly revealed.