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

Abstract

Background Acute myeloid leukemia is a genetically, biologically and clinically heterogeneous hematopoietic malignancy that is highly dependent on the bone marrow microenvironment. Infiltrated immune cells and stromal cells are an important part of the bone marrow microenvironment and significantly affect the progression of acute myeloid leukemia. 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 acute myeloid leukemia cohort were obtained from The Cancer Genome Atlas 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 to identify the modules most relevant to the immune microenvironment of acute myeloid leukemia. 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.Conclusions In summary, we identified a novel immune-related mRNA-miRNA-lncRNA competing endogenous RNA network associated with the prognosis of acute myeloid leukemia, which may contribute to better understanding of the development and progression of acute myeloid leukemia and to serve as novel therapeutic targets.

Immune‐relatedlncRNAs can predict the prognosis of acute myeloid leukemia

“…Previous IRL-related study explored the immunerelated competing endogenous RNA network and their association with AML prognosis. 18 Using the ESTIMATE algorithm, they divided AML patients into low-risk and high-risk groups based on immune and stromal scores. 19 Differentially expressed genes including mRNA, miRNA, and lncRNA were identified and these genes were subjected to construct a competing endogenous RNA network.…”

“…Previous IRL‐related study explored the immune‐related competing endogenous RNA network and their association with AML prognosis 18 . Using the ESTIMATE algorithm, they divided AML patients into low‐risk and high‐risk groups based on immune and stromal scores 19 .…”