ArticleFrontiers in immunology2023
Construction of an acute myeloid leukemia prognostic model based on m6A-related efferocytosis-related genes.
Article in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.
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31 citing papers in PubMed, 18 citations in OpenAlex.
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- Identification of a biologically coherent three gene immune signature predictive of immunotherapy benefit in gastric adenocarcinoma.Discover oncology · 2026Article
- IGF2BP3 Promoted the Overproliferation of AML Cells via Stability ofTurkish journal of haematology : official journal of Turkish Society of Haematology · 2026Article
- M6A modification-related genes characterize prognostic risk and immune regulation in lung adenocarcinoma.BMC cancer · 2026Article
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- Exploring Matrix Stiffness-Related Gene in Periodontitis: A Comprehensive Multidataset Analysis.Mediators of inflammation · 2026Article
- Interpretable machine learning-driven multi-omics risk stratification and drug repurposing nominates Treg/Th17 with gluconeogenesis/lactylation integration as a prognostic and druggable biomarker for glioblastoma patients.Frontiers in oncology · 2026Article
- Revealing the Diagnostic Potential of Three RHO GTPase-Related Genes in Osteoarthritis Based on Single-Cell RNA Sequencing and GEO Dataset Analysis.International journal of genomics · 2026Article
- Network Pharmacology and Validation Experiments Reveal Cryptotanshinone Inhibits Acute Myeloid Leukemia Progression by Activating Endoplasmic Reticulum Stress.Current medicinal chemistry · 2026Article
- Structure-based virtual screening identifies ethyl rosmarinate as a SLC1A6-targeted therapeutic candidate for bladder cancer.Frontiers in pharmacology · 2026Article
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- Exploring prognostic genes related to lactylation and programmed cell death in pancreatic ductal adenocarcinoma: a comprehensive study combining bulk transcriptomics and experimental verification.Frontiers in genetics · 2026Article
- Single-Cell and Multi-Omics-Based Characterization of Gastric Cancer Identifies TPP1 as a Potential Target for Gastric Cancer Progression and Treatment.Oncology research · 2026Article
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7 authors at 2 institutions in 1 country.
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Abstract
Background: One of the most prevalent hematological system cancers is acute myeloid leukemia (AML). Efferocytosis-related genes (ERGs) and N6-methyladenosine (m6A) have an important significance in the progression of cancer, and the metastasis of tumors. Methods: The AML-related data were collected from The Cancer Genome Atlas (TCGA; TCGA-AML) database and Gene Expression Omnibus (GEO; GSE9476, GSE71014, and GSE13159) database. The "limma" R package and Venn diagram were adopted to identify differentially expressed ERGs (DE-ERGs). The m6A related-DE-ERGs were obtained by Spearman analysis. Subsequently, univariate Cox and Least Absolute Shrinkage and Selection Operator (LASSO) were used to construct an m6A related-ERGs risk signature for AML patients. The possibility of immunotherapy for AML was explored. The pRRophetic package was adopted to calculate the IC50 of drugs for the treatment of AML. Finally, the expression of characterized genes was validated by quantitative reverse transcription-PCR (qRT-PCR). Results: Based on m6A related-DE-ERGs, a prognostic model with four characteristic genes (UCP2, DOCK1, SLC14A1, and SLC25A1) was constructed. The risk score of model was significantly associated with the immune microenvironment of AML, with four immune cell types, 14 immune checkpoints, 20 HLA family genes and, immunophenoscore (IPS) all showing differences between the high- and low-risk groups. A total of 56 drugs were predicted to differ between the two groups, of which Erlotinib, Dasatinib, BI.2536, and bortezomib have been reported to be associated with AML treatment. The qRT-PCR results showed that the expression trends of DOCK1, SLC14A1 and SLC25A1 were consistent with the bioinformatics analysis. Conclusion: In summary, 4 m6A related- ERGs were identified and the corresponding prognostic model was constructed for AML patients. This prognostic model effectively stratified the risk of AML patients.
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