Research Paper Volume 11, Issue 10 pp 3333—3347
Prediction of competing endogenous RNA coexpression network as prognostic markers in AML
- 1 Department of Hematology, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- 2 Institute of Hematology, Sun Yat-sen University, Guangzhou, China
- 3 Department of Hematology, Nanfang Hospital, Southern Medical University, Guangzhou, China
- 4 Institute of Cancer Stem Cell, Dalian Medical University, Dalian, China
Received: December 3, 2018 Accepted: May 19, 2019 Published: May 31, 2019
https://doi.org/10.18632/aging.101985How to Cite
Copyright: Wang et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Recently, competing endogenous RNAs (ceRNAs) hypothesis has gained a great interest in the study of molecular biological mechanisms of cancer occurrence and progression. However, studies on leukemia are limited, and there is still a lack of comprehensive analysis of lncRNA-miRNA-mRNA ceRNA regulatory network of AML based on high-throughput sequencing and large-scale sample size. We obtained RNA-Seq data and compared the expression profiles between 407 normal whole blood (GTEx) and 151 bone marrows of AML (TCGA). The similarity between two sets of genes with trait in the network was analyzed by weighted correlation network analysis (WGCNA). MiRcode, starBase, miRTarBase, miRDB and TargetScan was used to predict interactions between lncRNAs, miRNAs and target mRNAs. At last, we identified 108 lncRNAs, 10 miRNAs and 8 mRNAs to construct a lncRNA-miRNA-mRNA ceRNA network, which might act as prognostic biomarkers of AML. Among the network, a survival model with 8 target mRNAs (HOXA9+INSR+KRIT1+MYB+SPRY2+UBE2V1+WEE1+ZNF711) was set up by univariate and multivariate cox proportional hazard regression analysis, of which the AUC was 0.831, indicating its sensitivity and specificity in AML prognostic prediction. CeRNA networks could provide further insight into the study on gene regulation and AML prognosis.