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Microarray profiling and co-expression network analysis of the lncRNAs and mRNAs associated with acute leukemia in adults

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Abstract

Acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML) are common types of acute leukemia in adults and cause low survival rate and poor outcome after 5 years despite high rates of complete remission (CR) with modern chemotherapeutic regimens. To understand the distinct mechanisms in leukemogenesis for ALL and AML and to identify markers for diagnosis and treatment, lncRNA and mRNA expression profiles of AML and ALL patients and healthy controls were generated using microarray analysis. For comparison, the differentially expressed mRNA functions were annotated using gene ontology (GO) and pathway analysis. The microarray revealed that 1011 lncRNAs and 2656 mRNAs differed in AML patients and 6069 lncRNAs and 5338 mRNAs differed in ALL patients from those in healthy controls. The GO terms and KEGG pathway annotation data revealed that the olfactory receptor activity, G-protein coupled receptor activity and olfactory transduction-related genes were significantly associated with AML and ALL. Co-expression network analysis indicated that 108 lncRNAs and 85 mRNAs were included in the co-expression network. This study is the first to explore genome-wide lncRNA expression and co-expression with mRNA patterns in AML and ALL using microarray technology and could provide basic information for new biomarkers or treatment targets to alleviate AML and ALL.

Graphical abstract: Microarray profiling and co-expression network analysis of the lncRNAs and mRNAs associated with acute leukemia in adults

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Publication details

The article was received on 30 Dec 2016, accepted on 28 Mar 2017 and first published on 31 Mar 2017


Article type: Paper
DOI: 10.1039/C6MB00874G
Citation: Mol. BioSyst., 2017, Advance Article
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    Microarray profiling and co-expression network analysis of the lncRNAs and mRNAs associated with acute leukemia in adults

    H. Cheng, C. M. Huang, Y. Wang, X. X. Hu, X. Q. Xu, X. M. Song, G. S. Tang, L. Chen and J. M. Yang, Mol. BioSyst., 2017, Advance Article , DOI: 10.1039/C6MB00874G

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