ArticleOncology letters2022
Identification of differentially expressed genes induced by aberrant methylation in acute myeloid leukemia using integrated bioinformatics analyses.
Article in Oncology letters, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed, 7 citations in OpenAlex.
- Advances in measurable residual disease assessment for acute myeloid leukemia: from cytogenetics and molecular biology to assessment of the methylation pattern and surface-enhanced Raman scattering as emerging technologies.Biomarker research · 2025Review
- Integrative Transcriptomic and Proteomic Analysis RevealsAnimals : an open access journal from MDPI · 2025Article
- ITGAM sustains MAPK signaling and serves as an adverse prognostic factor and therapeutic target in acute myeloid leukemia.Translational cancer research · 2024Article
- Role of epigenetic in cancer biology, in hematologic malignancies and in anticancer therapy.Frontiers in molecular medicine · 2024Review
- Targeting DNA Methylation in Leukemia, Myelodysplastic Syndrome, and Lymphoma: A Potential Diagnostic, Prognostic, and Therapeutic Tool.International journal of molecular sciences · 2022Review
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Acute myeloid leukemia (AML) is a life-threatening hematological malignant disease. Methylation plays a crucial role in the etiology and pathogenesis of AML. The aim of the present study was to identify the aberrantly methylated differentially expressed genes (DEGs) in AML and determine the underlying mechanisms of tumorigenesis by conducting integrated bioinformatics analyses. Gene expression profiles (GSE109179, GSE142699, GSE49665 and GSE14772) and a gene methylation profile (GSE42042) were analyzed to identify the aberrantly methylated DEGs. Functional enrichment analyses of identified genes were conducted based on the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases, and protein-protein interaction networks were established. Finally, the DEGs were validated by the reverse transcription-quantitative PCR analysis of patient samples. A total of seven downregulated hypermethylated genes and eight upregulated hypomethylated genes were validated. The differentially methylated DEGs were enriched in GO biological process terms associated with control of the immune response and the KEGG analysis indicated they were involved in AML, ferroptosis, TGF-β signaling and necroptosis pathways. Additionally, five downregulated hypermethylated genes that were also tumor suppressor genes (TSGs) were identified.
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