Oncotarget

Research Papers:

Integrating microRNA and mRNA expression profiles of acute promyelocytic leukemia cells to explore the occurrence mechanisms of differentiation syndrome

Yingmei Zhang, Jinxiao Hou, Fei Ge, Fenglin Cao, Haitao Li, Ping Wang, Mengyuan Xu, Peng Song, Xiaoxia Li, Shuye Wang, Jinmei Li, Xueying Han, Yanhong Zhao, Yanhua Su, Yinghua Li, Shengjin Fan, Limin Li and Jin Zhou _

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Oncotarget. 2016; 7:73509-73524. https://doi.org/10.18632/oncotarget.11989

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Abstract

Yingmei Zhang1,*, Jinxiao Hou2,*, Fei Ge2, Fenglin Cao1, Haitao Li2, Ping Wang2,3, Mengyuan Xu2, Peng Song1, Xiaoxia Li2, Shuye Wang2, Jinmei Li2, Xueying Han2, Yanhong Zhao2, Yanhua Su2, Yinghua Li2, Shengjin Fan2, Limin Li2, Jin Zhou1,2

1Central Laboratory, The First Affiliated Hospital, Harbin Medical University, Harbin, China

2Department of Hematology, The First Affiliated Hospital, Harbin Medical University, Harbin, China

3Department of Neonatology, The First Affiliated Hospital, Harbin Medical University, Harbin, China

*These authors have contributed equally to this work

Correspondence to:

Jin Zhou, email: [email protected]

Keywords: acute promyelocytic leukemia, differentiation syndrome, microRNA, mRNA, microarrays

Received: January 08, 2016    Accepted: September 02, 2016    Published: September 13, 2016

ABSTRACT

The pathogenesis of therapy-induced differentiation syndrome (DS) in patients with acute promyelocytic leukemia (APL) remains unclear. In this study, mRNA and microRNA (miRNA) expression profiling of peripheral blood APL cells from patients complicated with vs. without DS were integratively analyzed to explore the mechanisms underlying arsenic trioxide treatment-associated DS. By integrating the differentially expressed data with the data of differentially expressed microRNAs and their computationally predicted target genes, as well as the data of transcription factors and differentially expressed target microRNAs obtained from a literature search, a DS-related genetic regulatory network was constructed. Then using an EAGLE algorithm in clusterViz, the network was subdivided into 10 modules. Using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database the modules were annotated functionally, and three functionally active modules were recognized. The further in-depth analyses on the annotated functions of the three modules and the expression and roles of the related genes revealed that proliferation, differentiation, apoptosis and infiltration capability of APL cells might play important roles in the DS pathogenesis. The results could improve our understanding of DS pathogenesis from a more overall perspective, and could provide new clues for future research.


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