ArticleFrontiers in oncology2020
Integrative Analysis of Multi-Omics Identified the Prognostic Biomarkers in Acute Myelogenous Leukemia.
Article in Frontiers in oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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28 citing papers in PubMed, 27 citations in OpenAlex.
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- Integrative Bulk and Single-Cell Transcriptomic Analysis Identifies a Hypoxia- and Lipid Metabolism-Related Prognostic Signature in Oral Squamous Cell Carcinoma: A Retrospective Study.International journal of molecular sciences · 2026Article
- Single-cell and bulk transcriptomic analyses identify B-cell senescence-associated biomarkers in papillary thyroid carcinoma.Translational cancer research · 2026Article
- Probing uric acid-related prognostic genes and their molecular mechanisms in prostate cancer based on transcriptomic data.Discover oncology · 2026Article
- Identification and validation of prognostic genes associated with integrative stress response in lung adenocarcinoma and construction of the risk models.Scientific reports · 2026Article
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- Exploration of potential mechanisms and biomarkers related to ERS-associated RCD in steroid-induced osteonecrosis of the femoral head based on bioinformatics, with experimental validation.Frontiers in endocrinology · 2026Article
- Evolocumab Alters Transcriptomic Signatures and Identifies Inflammatory Biomarkers in Brain-Heart Syndrome with Coronary Heart Disease History.International journal of general medicine · 2026Article
- Identification and Validation of the Prognostic Value of PTTG1-Related Genes in Hepatocellular Carcinoma by Mendelian Randomization and Single-Cell Transcriptome Analysis.Iranian journal of biotechnology · 2026Article
- Association and Mechanistic Insights Linking Bisphenol A to Psoriasis: Integrative Analysis of Bulk Transcriptomics, Network Toxicology, Mendelian Randomization and Single‑cell RNA Sequencing.Clinical, cosmetic and investigational dermatology · 2026Article
- Transcriptomics-based identification of shared biomarkers across type 2 diabetes, mild cognitive impairment, and uric acid metabolism.Experimental biology and medicine (Maywood, N.J.) · 2026Article
- Bioinformatics identification of mitochondrial dynamics-related potential biomarkers in kawasaki disease and prediction of potential regulatory correlations.Frontiers in cardiovascular medicine · 2026Article
- Transcriptomic exploration combined with experimental validation: uncovering the potential value of biomarkers related to ammonia-induced cell death in hepatic ischemia-reperfusion injury.European journal of medical research · 2025Article
- A machine learning and deep learning-based integrated multi-omics technique for leukemia prediction.Heliyon · 2024Article
- Expression of small nucleolar RNA SNORA51 and its clinical significance in hepatocellular carcinoma.Oncology letters · 2024Article
- Article
- Identification and validation of subclusters of papillary thyroid carcinoma based on Human Phenotype Ontology.Gland surgery · 2023Article
- Extracellular vesicle small RNA cargo discriminates non-cancer donors from pediatric B-lymphoblastic leukemia patients.Frontiers in oncology · 2023Article
- Identification of molecular classification and gene signature for predicting prognosis and immunotherapy response in HNSCC using cell differentiation trajectories.Scientific reports · 2022Article
- Identification of Prognostic and Tumor Microenvironment by Shelterin Complex-Related Signatures in Oral Squamous Cell Carcinoma.Oxidative medicine and cellular longevity · 2022Article
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAcute myelogenous leukemia (AML) is a common pediatric malignancy in children younger than 15 years old. Although the overall survival (OS) has been improved in recent years, the mechanisms of AML remain largely unknown. Hence, the purpose of this study is to explore the differentially methylated genes and to investigate the underlying mechanism in AML initiation and progression based on the bioinformatic analysis.
methodsMethylation array data and gene expression data were obtained from TARGET Data Matrix. The consensus clustering analysis was performed using ConsensusClusterPlus R package. The global DNA methylation was analyzed using methylationArrayAnalysis R package and differentially methylated genes (DMGs), and differentially expressed genes (DEGs) were identified using Limma R package. Besides, the biological function was analyzed using clusterProfiler R package. The correlation between DMGs and DEGs was determined using psych R package. Moreover, the correlation between DMGs and AML was assessed using varElect online tool. And the overall survival and progression-free survival were analyzed using survival R package.
resultsAll AML samples in this study were divided into three clusters at k = 3. Based on consensus clustering, we identified 1,146 CpGs, including 40 hypermethylated and 1,106 hypomethylated CpGs in AML. Besides, a total 529 DEGs were identified, including 270 upregulated and 259 downregulated DEGs in AML. The function analysis showed that DEGs significantly enriched in AML related biological process. Moreover, the correlation between DMGs and DEGs indicated that seven DMGs directly interacted with AML. CD34, HOXA7, and CD96 showed the strongest correlation with AML. Further, we explored three CpG sites cg03583857, cg26511321, cg04039397 of CD34, HOXA7, and CD96 which acted as the clinical prognostic biomarkers.
conclusionOur study identified three novel methylated genes in AML and also explored the mechanism of methylated genes in AML. Our finding may provide novel potential prognostic markers for AML.
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