MicroRNA and transcription factor co-regulatory network analysis reveals miR-19 inhibits CYLD in T-cell acute lymphoblastic leukemia

T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive hematological malignancy. The understanding of its gene expression regulation and molecular mechanisms still remains elusive. Started from experimentally verified T-ALL-related miRNAs and genes, we obtained 120 feed-forward loops (FFLs) am...

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Bibliographic Details
Main Authors: Ye, Huashan, Liu, Xiaowen, Lv, Meng, Wu, Yuliang, Kuang, Shuzhen, Gong, Jing, Yuan, Ping, Zhong, Zhaodong, Li, Qiubai, Jia, Haibo, Sun, Jun, Chen, Zhichao, Guo, An-Yuan
Format: Online
Language:English
Published: Oxford University Press 2012
Online Access:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3384304/
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Summary:T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive hematological malignancy. The understanding of its gene expression regulation and molecular mechanisms still remains elusive. Started from experimentally verified T-ALL-related miRNAs and genes, we obtained 120 feed-forward loops (FFLs) among T-ALL-related genes, miRNAs and TFs through combining target prediction. Afterwards, a T-ALL miRNA and TF co-regulatory network was constructed, and its significance was tested by statistical methods. Four miRNAs in the miR-17–92 cluster and four important genes (CYLD, HOXA9, BCL2L11 and RUNX1) were found as hubs in the network. Particularly, we found that miR-19 was highly expressed in T-ALL patients and cell lines. Ectopic expression of miR-19 represses CYLD expression, while miR-19 inhibitor treatment induces CYLD protein expression and decreases NF-κB expression in the downstream signaling pathway. Thus, miR-19, CYLD and NF-κB form a regulatory FFL, which provides new clues for sustained activation of NF-κB in T-ALL. Taken together, we provided the first miRNA-TF co-regulatory network in T-ALL and proposed a model to demonstrate the roles of miR-19 and CYLD in the T-cell leukemogenesis. This study may provide potential therapeutic targets for T-ALL and shed light on combining bioinformatics with experiments in the research of complex diseases.