N6-Methyladenosine-Related lncRNAs Are Novel Prognostic Markers and Predict the Immune Landscape in Acute Myeloid Leukemia - Zhang, Lulu; Ke, Wen; Hu, Pin; Li, Zhangzhi; Geng, Wei; Guo, Yigang; Song, Bin; Jiang, Hua; Zhang, Xia; Wan, Chucheng (Frontiers in Genetics, 2022)
Background: Acute myelocytic leukemia (AML) is one of hematopoietic cancers with an unfavorable prognosis. However, the prognostic value of N 6 -methyladenosine -associated long non-coding RNAs (lncRNAs) in AML remains elusive. Materials and Methods: The transcriptomic data of m6A-related lncRNAs was collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. AML samples were classified into various subgroups according to the expression of m6A-related lncRNAs. The differences in terms of biological function, tumor immune microenvironment, copy number variation (CNV) as well as drug sensitivity in AML between distinct subgroups were investigated. Moreover, a m6A-related lncRNA prognostic model was established to evaluate the prognosis of AML patients. Results: Nine prognosis-related m6A-associated lncRNAs were selected to construct a prognosis model. The accuracy of the model was further determined by Kaplan-Meier analysis and time-dependent receiver operating characteristic (ROC) curve. Then, AML samples were classified into risk-high and -low groups according to the median value of risk scores. Gene set enrichment analysis (GSEA) exhibited that samples with higher risks were featured with aberrant immune-related biological processes and signaling pathway. Notably, high-risk group was significantly correlated with an increased ImmuneScore and StromalScore, and distinct immune cell infiltration. Besides, we discovered that high-risk group harbored higher IC50 values of multiple chemotherapeutics and small molecule anticancer drugs, especially TW.37 and MG.132. In addition, a nomogram was depicted to assess the overall survival (OS) of AML patients. The model-based the median value of risk scores revealed reliable accuracy in predicting prognosis and survival status. Conclusion: The present research had originated a prognostic risk model for AML according to the expression of prognostic m6A-related lncRNAs. Notably, the signature might also serve as a novel biomarker that could guide clinical applications, for example, selecting AML patients who could benefit from immunotherapy.