ArticleOncology letters2018
Identification and analysis of key genes in osteosarcoma using bioinformatics.
Article in Oncology letters, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed, 43 citations in OpenAlex.
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- Integrated bioinformatics analysis of biomarkers and pathways to explore the mechanisms and molecular targets related to allergic rhinitis and pyroptosis.Scientific reports · 2025Article
- Exploring the role of CBLB in acute myocardial infarction: transcriptomic, microbiomic, and metabolomic analyses.Journal of translational medicine · 2024Article
- Genome-wide analysis reveals genomic diversity and signatures of selection in Qinchuan beef cattle.BMC genomics · 2024Article
- Complete Mitochondrial Genomes ofAnimals : an open access journal from MDPI · 2024Article
- Low FHL1 expression indicates a good prognosis and drug sensitivity in ovarian cancer.Functional & integrative genomics · 2024Article
- Identification of diagnostic signature, molecular subtypes, and potential drugs in allergic rhinitis based on an inflammatory response gene set.Frontiers in immunology · 2024Article
- Combined analysis of 16S rDNA sequencing and metabolomics to find biomarkers of drug-induced liver injury.Scientific reports · 2023Article
- Uncovering ferroptosis in Parkinson's disease via bioinformatics and machine learning, and reversed deducing potential therapeutic natural products.Frontiers in genetics · 2023Article
- Comparative transcriptome analysis identifies candidate genes related to seed coat color in rapeseed.Frontiers in plant science · 2023Article
- Molecular Genomic Study of Inhibin Molecule Production through Granulosa Cell Gene Expression in Inhibin-Deficient Mice.Molecules (Basel, Switzerland) · 2022Article
- Osteosarcoma-Specific Genes as a Diagnostic Tool and Clinical Predictor of Tumor Progression.Biology · 2022Article
- Identification of Melanoma Subsets Based on DNA Methylation Sites and Construction of a Prognosis Evaluation Model.Journal of oncology · 2022Article
- Identification and validation of immunotherapy for four novel clusters of colorectal cancer based on the tumor microenvironment.Frontiers in immunology · 2022Article
- MicroRNA miR-23b-3p promotes osteosarcoma by targeting ventricular zone expressed PH domain-containing 1 (VEPH1)/phosphatidylinositol 3-kinase/protein kinase B (PI3K/AKT) pathway.Bioengineered · 2021Article
- 12 Survival-related differentially expressed genes based on the TARGET-osteosarcoma database.Experimental biology and medicine (Maywood, N.J.) · 2021Article
- Immunological Significance of Prognostic DNA Methylation Sites in Hepatocellular Carcinoma.Frontiers in molecular biosciences · 2021Article
- Identification of the subtypes of gastric cancer based on DNA methylation and the prediction of prognosis.Clinical epigenetics · 2020Article
- Identification of Lysosome-Associated Protein Transmembrane-4 as a Novel Therapeutic Target for Osteosarcoma Treatment.Orthopaedic surgery · 2020Article
- Identification of Pathogenic Genes and Transcription Factors in Osteosarcoma.Pathology oncology research : POR · 2020Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Osteosarcoma (OS) is an invasive malignant neoplasm of the bones. The present study identified and analyzed key genes associated with OS. Expression profiling of the dataset GSE49003, which included 6 metastatic and 6 non-metastatic OS cell lines and was obtained from the Gene Expression Omnibus, was performed. Following data preprocessing, the differentially expressed genes (DEGs) were selected using the limma package in R. Subsequently, bidirectional hierarchical clustering using the pheatmap package in R and an unpaired Students' t-test was performed for the DEGs. Based on the Search Tool for the Retrieval of Interacting Genes database and Cytoscape software, a protein-protein interaction (PPI) network for the DEGs was constructed. Using Database for Annotation, Visualization and Integrated Discovery software and the Kyoto Encyclopedia of Genes and Genomes Orthology Based Annotation System server, functional and pathway enrichment analyses were performed for the DEGs corresponding to the proteins of the network. In addition, the transcription factors (TFs) and CpG islands of the gene promoter were searched for using the TRANSFAC database and CpG Island Searcher software, respectively. A total of 323 DEGs were identified between the metastatic and non-metastatic samples. In the PPI network, upregulated epidermal growth factor receptor (EGFR) exhibits a high degree and was therefore highly interconnected with other proteins. Enrichment analysis revealed that EGFR was enriched in cytoskeleton organization, organic substance response and the signaling pathway of focal adhesion. The TFs early growth response 1, nuclear factor-κB complex subunits, peroxisome proliferator activated receptor α, signal transducer and activator of transcription 3 and MYC proto-oncogene were identified in the EGFR promoter region. Furthermore, multiple CpG islands, starting from the 400 bp of the EGFR promoter sequence, were predicted. Methylated modification of the CpG islands in the EGFR promoter may help to regulate EGFR expression. The TFs identified in the EGFR promoter may function in the progression of OS.
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