Construction of an immune-related prognostic signature and lncRNA-miRNA-mRNA ceRNA network in acute myeloid leukemia

被引:2
|
作者
Qin, Ling [1 ]
Li, Boya [1 ]
Wang, Shijie [1 ]
Tang, Yulai [2 ]
Fahira, Aamir [2 ]
Kou, Yanqi [1 ]
Li, Tong [1 ]
Hu, Zhigang [3 ,4 ,5 ]
Huang, Zunnan [2 ,4 ,5 ]
机构
[1] Henan Univ Sci & Technol, Affiliated Hosp 1, Coll Clin Med, Dept Hematol, 24 Jinghua Rd, Luoyang 471003, Peoples R China
[2] Guangdong Med Univ, Key Lab Comp Aided Drug Design Dongguan City, Sch Pharm, Key Lab Res & Dev Nat Drugs Guangdong Prov,Key Lab, 1 Xincheng Rd, Dongguan 523808, Guangdong, Peoples R China
[3] Henan Univ Sci & Technol, Sch Med Technol & Engn, 263 Kaiyuan Ave, Luoyang 471000, Peoples R China
[4] Guangdong Med Univ, 1 Xincheng Rd, Dongguan 523808, Peoples R China
[5] Henan Univ Sci & Technol, 263 Kaiyuan Ave, Luoyang 471000, Peoples R China
关键词
acute myeloid leukemia; competing endogenous RNA network; immune-related gene; prognostic signature; ACUTE MYELOGENOUS LEUKEMIA; LONG NONCODING RNAS; REL/NF-KAPPA-B; BIOINFORMATICS ANALYSIS; T-CELLS; EXPRESSION; PROMOTES; PROGRESSION; PATHWAY; GROWTH;
D O I
10.1093/jleuko/qiae041
中图分类号
Q2 [细胞生物学];
学科分类号
071009 ; 090102 ;
摘要
The progression of acute myeloid leukemia (AML) is influenced by the immune microenvironment in the bone marrow and dysregulated intracellular competing endogenous RNA (ceRNA) networks. Our study utilized data from UCSC Xena, The Cancer Genome Atlas Program, the Gene Expression Omnibus, and the Immunology Database and Analysis Portal. Using Cox regression analysis, we identified an immune-related prognostic signature. Genomic analysis of prognostic messenger RNA (mRNA) was conducted through Gene Set Cancer Analysis (GSCA), and a prognostic ceRNA network was constructed using the Encyclopedia of RNA Interactomes. Correlations between signature mRNAs and immune cell infiltration, checkpoints, and drug sensitivity were assessed using R software, gene expression profiling interactive analysis (GEPIA), and CellMiner, respectively. Adhering to the ceRNA hypothesis, we established a potential long noncoding RNA (lncRNA)/microRNA (miRNA)/mRNA regulatory axis. Our findings pinpointed 9 immune-related prognostic mRNAs (KIR2DL1, CSRP1, APOBEC3G, CKLF, PLXNC1, PNOC, ANGPT1, IL1R2, and IL3RA). GSCA analysis revealed the impact of copy number variations and methylation on AML. The ceRNA network comprised 14 prognostic differentially expressed lncRNAs (DE-lncRNAs), 6 prognostic DE-miRNAs, and 3 prognostic immune-related DE-mRNAs. Correlation analyses linked these mRNAs' expression to 22 immune cell types and 6 immune checkpoints, with potential sensitivity to 27 antitumor drugs. Finally, we identified a potential LINC00963/hsa-miR-431-5p/CSRP1 axis. This study offers innovative insights for AML diagnosis and treatment through a novel immune-related signature and ceRNA axis. Identified novel biomarkers, including 2 mRNAs (CKLF, PNOC), 1 miRNA (hsa-miR-323a-3p), and 10 lncRNAs (SNHG25, LINC01857, AL390728.6, AC127024.5, Z83843.1, AP002884.1, AC007038.1, AC112512, AC020659.1, AC005921.3) present promising candidates as potential targets for precision medicine, contributing to the ongoing advancements in the field. Utilizing comprehensive genomic and immune microenvironment analysis, our study unveils a novel immune-related prognostic signature and competing endogenous RNA network in acute myeloid leukemia, shedding light on potential precision medicine targets for improved diagnosis and treatment of this cancer.
引用
收藏
页码:146 / 165
页数:20
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