ArticleJournal of bone oncology2017
An integrative analysis of DNA methylation in osteosarcoma.
Article in Journal of bone oncology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
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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
12 citing papers in PubMed, 23 citations in OpenAlex.
- The Role of DNA Methylation in Osteosarcoma Pathogenesis and Therapy.OncoTargets and therapy · 2026Review
- Epigenetic Modifications in Osteosarcoma: Mechanisms and Therapeutic Strategies.Life (Basel, Switzerland) · 2025Review
- Systemic strategies for osteosarcoma: advances and future directions.Discover oncology · 2025Review
- Identification of the shared gene signatures in retinoblastoma and osteosarcoma by machine learning.Scientific reports · 2024Article
- SELPLG Expression Was Potentially Correlated With Metastasis and Prognosis of Osteosarcoma.Pathology oncology research : POR · 2022Article
- Development and Verification of a Hypoxic Gene Signature for Predicting Prognosis, Immune Microenvironment, and Chemosensitivity for Osteosarcoma.Frontiers in molecular biosciences · 2021Article
- Identification of a 7-mRNA signature as a prognostic biomarker in pediatric osteosarcoma.Translational cancer research · 2020Article
- Biology and pathogenesis of human osteosarcoma.Oncology letters · 2020Review
- Overexpression of FES might inhibit cell proliferation, migration, and invasion of osteosarcoma cells.Cancer cell international · 2020Article
- Survival analysis and functional annotation of long non-coding RNAs in lung adenocarcinoma.Journal of cellular and molecular medicine · 2019Article
- Activation of Estrogen Receptor Alpha by Decitabine Inhibits Osteosarcoma Growth and Metastasis.Cancer research · 2019Article
- Potential Regulatory Effects of miR-182-3p in Osteosarcoma via Targeting EBF2.BioMed research international · 2019Article
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe study aimed to analyze aberrantly methylated genes, relevant pathways and transcription factors (TFs) in osteosarcoma (OS) development.
methodsBased on the DNA methylation microarray data GSE36002 that were downloaded from GEO database, the differentially methylated genes in promoter regions were identified between OS and normal samples. Pathway and function enrichment analyses of differentially methylated genes was performed. Subsequently, protein-protein interaction (PPI) network was constructed, followed by identification of cancer-associated differentially methylated genes and significant differentially methylated TFs.
resultsA total of 1379 hyper-methylation regions and 169 hypo-methylation regions in promoter regions were identified in OS samples compared to normal samples. The differentially hyper-methylated genes were significantly enriched in Neuroactive ligand-receptor interaction pathway, and Peroxisome proliferator activated receptor (PPAR) signaling pathway. The differentially hypo-methylated genes were significantly enriched in Toll-like receptor signaling pathway. In PPI network, signal transducers and activators of transcription (STAT3) had high degree (degree=21). MAX interactor 1, dimerization protein (MXI1), STAT3 and T-cell acute lymphocytic leukemia 1 (TAL1) were significant TFs enriched with target genes in OS samples. They were found to be cancer-associated and hyper-methylated in OS samples.
conclusionNeuroactive ligand-receptor interaction, PPAR signaling, Toll-like receptor signaling pathways are implicated in OS. MXI1, STAT3, and TAL1 may be important TFs involved in OS development.
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Registered trials
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.