ArticleJournal of oncology2022
Development of a Risk Score Model for Osteosarcoma Based on DNA Methylation-Driven Differentially Expressed Genes.
Article in Journal of oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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.
The trial behind it
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
4 citing papers in PubMed, 7 citations in OpenAlex.
- The Role of DNA Methylation in Osteosarcoma Pathogenesis and Therapy.OncoTargets and therapy · 2026Review
- Systemic strategies for osteosarcoma: advances and future directions.Discover oncology · 2025Review
- Develop a Novel Signature to Predict the Survival and Affect the Immune Microenvironment of Osteosarcoma Patients: Anoikis-Related Genes.Journal of immunology research · 2024Article
- Integration of single-cell RNA sequencing and bulk RNA sequencing to reveal an immunogenic cell death-related 5-gene panel as a prognostic model for osteosarcoma.Frontiers in immunology · 2022Article
Corrections and comments
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Authors and funding
11 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Osteosarcoma (OS) is the commonest malignant bone tumor in adolescent patients, and patients face amputation, tumor metastasis, chemotherapy resistance, and even death. We investigated the potential connection between abnormal methylation differentially expressed genes and the survival rate of osteosarcoma patients. GSE36002 and GSE12865 datasets of GEO database were utilized for abnormal methylation differentially expressed genes, followed by function and pathway enrichment analyses, the protein-protein interaction network in the STRING database, and cluster analysis in the MCODE app of Cytoscape. The RNA-seq and clinical data from the TARGET-OS project of TCGA were used for univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analyses to predict the risk genes of osteosarcoma. 1191 hypermethylation-downregulated genes might function through plasma membrane, negative regulation of transcription from the RNA polymerase II promoter, and pathways, including transcriptional misregulation in cancer. 127 hypomethylation-upregulated genes were enriched in proteolysis, negative regulation of the canonical Wnt signaling pathway, and metabolic signaling pathways. The univariate Cox analysis revealed 638 genes (
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What OpenQuestion holds
Registered trials
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