ArticleEpigenetics2015
Identification of differentially methylated markers among cytogenetic risk groups of acute myeloid leukemia.
Article in Epigenetics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 30 citations in OpenAlex.
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- Maternal-infant interaction quality is associated with child NR3C1 CpG site methylation at 7 years of age.American journal of human biology : the official journal of the Human Biology Council · 2023Article
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- Altered genome‑wide hydroxymethylation analysis for neoadjuvant chemoradiotherapy followed by surgery in esophageal cancer.Experimental and therapeutic medicine · 2023Article
- Novel UHRF1-MYC Axis in Acute Lymphoblastic Leukemia.Cancers · 2022Article
- Bayesian variable selection for high-dimensional data with an ordinal response: identifying genes associated with prognostic risk group in acute myeloid leukemia.BMC bioinformatics · 2021Article
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- Maintenance and pharmacologic targeting of ROR1 protein levels via UHRF1 in t(1;19) pre-B-ALL.Oncogene · 2018Article
- Exploring the Role of Fallopian Ciliated Cells in the Pathogenesis of High-Grade Serous Ovarian Cancer.International journal of molecular sciences · 2018Review
- MN1 overexpression is driven by loss of DNMT3B methylation activity in inv(16) pediatric AML.Oncogene · 2018Article
- Targeting microRNA/UHRF1 pathways as a novel strategy for cancer therapy.Oncology letters · 2018Article
- DNA methylation profile in chronic myelomonocytic leukemia associates with distinct clinical, biological and genetic features.Epigenetics · 2018Article
- MicroRNA-181 as a prognostic biomarker for survival in acute myeloid leukemia: a meta-analysis.Oncotarget · 2017Article
- Article
- Signalling pathways in UHRF1-dependent regulation of tumor suppressor genes in cancer.Journal of experimental & clinical cancer research : CR · 2016Review
- Childhood abuse, promoter methylation of leukocyte NR3C1 and the potential modifying effect of emotional support.Epigenomics · 2016Article
Corrections and comments
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Authors and funding
9 authors at 4 institutions in 2 countries.
Funding
Abstract
Aberrant DNA methylation is known to occur in cancer, including hematological malignancies such as acute myeloid leukemia (AML). However, less is known about whether specific methylation profiles characterize specific subcategories of AML. We examined this issue by using comprehensive high-throughput array-based relative methylation analysis (CHARM) to compare methylation profiles among patients in different AML cytogenetic risk groups. We found distinct profiles in each group, with the high-risk group showing overall increased methylation compared with low- and mid-risk groups. The differentially methylated regions (DMRs) distinguishing cytogenetic risk groups of AML were enriched in the CpG island shores. Specific risk-group associated DMRs were located near genes previously known to play a role in AML or other malignancies, such as MN1, UHRF1, HOXB3, and HOXB4, as well as TRIM71, the function of which in cancer is not well characterized. These findings were verified by quantitative bisulfite pyrosequencing and by comparison with results available at the TCGA cancer genome browser. To explore the potential biological significance of the observed methylation changes, we correlated our findings with gene expression data available through the TCGA database. The results showed that decreased methylation at HOXB3 and HOXB4 was associated with increased gene expression of both HOXB genes specific to the mid-risk AML, while increased DNA methylation at DCC distinctive to the high-risk AML was associated with increased gene expression. Our results suggest that the differential impact of cytogenetic changes on AML prognosis may, in part, be mediated by changes in methylation.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.