A Novel Immune-Related Competing Endogenous RNA Network Predicts Prognosis of Acute Myeloid Leukemia

Shujuan Wang; Lu Yang; Yajun Liu; Yan Xu; Danfeng Zhang; Zhongxing Jiang; Chong Wang; Yanfang Liu

doi:10.3389/fonc.2020.01579

A Novel Immune-Related Competing Endogenous RNA Network Predicts Prognosis of Acute Myeloid Leukemia

Front Oncol. 2020 Aug 11:10:1579. doi: 10.3389/fonc.2020.01579. eCollection 2020.

Authors

Shujuan Wang¹, Lu Yang¹, Yajun Liu², Yan Xu¹, Danfeng Zhang¹, Zhongxing Jiang¹, Chong Wang¹, Yanfang Liu¹

Affiliations

¹ Department of Hematology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
² Department of Orthopaedics, Rhode Island Hospital, Warren Alpert Medical School, Brown University, Providence, RI, United States.

Abstract

Background: Acute myeloid leukemia (AML) is a genetically, biologically and clinically heterogeneous hematopoietic malignancy that is highly dependent on the bone marrow (BM) microenvironment. Infiltrated immune cells and stromal cells are an important part of the BM microenvironment and significantly affect the progression of AML. Recently, the competing endogenous RNA hypothesis has gained great interests in the study of molecular and biological mechanisms of tumor occurrence and progression. However, research on how competing endogenous RNA relates to leukemia tumor microenvironment remains uninvestigated.

Methods: In this study, mRNA, miRNA and lncRNA data and clinical information of the AML cohort were obtained from The Cancer Genome Atlas (TCGA) database, and the immune and stromal scores were calculated using the ESTIMATE algorithm.

Results: We found that immune scores were significantly correlated with cytogenetic risk and overall survival, and also identified microenvironment-related mRNAs, miRNAs, and lncRNAs based on the immune and stromal scores. Differentially expressed mRNAs and lncRNAs were applied to weighted correlation network analysis (WGCNA) to identify the modules most relevant to the immune microenvironment of AML. Using miRNA database to predict miRNA-targeted genes, we established the immune-related competing endogenous RNA network consisting of 33 lncRNAs, 21 miRNAs and 135 mRNAs. Prognostic analysis was performed on the genes in the immune-related competing endogenous RNA network to screen out 15 lncRNAs, 2 miRNAs and 31 mRNAs with prognostic values.

Conclusion: In summary, we identified a novel immune-related mRNA-miRNA-lncRNA competing endogenous RNA network associated with the prognosis of AML, which may contribute to better understanding of the development and progression of AML and to serve as novel therapeutic targets.

Keywords: acute myeloid leukemia; competing endogenous RNA network; immune microenvironment; prognosis.; weighted gene coexpression network analysis.