ArticleMolecular genetics & genomic medicine2020
Potential biomarkers screening to predict side effects of dexamethasone in different cancers.
Article in Molecular genetics & genomic medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.
- The Lipocalin Apolipoprotein D Functional Portrait: A Systematic Review.Frontiers in physiology · 2021Pooled it
- EZH2 suppresses the chemosensitivity of diffuse large B cell lymphoma via regulating TP53INP1.Clinical and experimental medicine · 2025Article
- Roles and therapeutic potential of the SLC family in prostate cancer-literature review.BMC urology · 2025Review
- The mRNA MOXD1: Link to oxidative stress and prognostic significance in gastric cancer.Open medicine (Warsaw, Poland) · 2025Article
- The LMCD1-AS1/miR-526b-3p/OSBPL5 axis promotes cell proliferation, migration and invasion in non-small cell lung cancer.BMC pulmonary medicine · 2022Article
- Potential biomarkers screening to predict side effects of dexamethasone in different cancers.Molecular genetics & genomic medicine · 2020Article
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundExcessive or prolonged usage of dexamethasone can cause serious side effects, but few studies reveal the related mechanism. Dexamethasone work differently in blood tumors and solid tumors, and the cause is still obscure. The aims of this study was to identify potential biomarkers associated with the side effects of dexamethasone in different tumors.
methodsGene Expression Omnibus database (GEO) datasets of blood tumors and solid tumors were retrieval to selected microarray data. The differentially expressed genes (DEGs) were identified. Gene ontology (GO) and pathway enrichment analyses, and protein-protein interaction (PPI) network analysis were performed.
resultsOne hundred and eighty dexamethasone-specific DEGs (92 up and 88 downregulated) were obtained in lymphoma cell samples (named as DEGs-lymph), including APOD, TP53INP1, CLIC3, SERPINA9, and C3orf52. One hundred and four specific DEGs (100 up and 4 downregulated) were identified in prostate cancer cell samples (named as DEGs-prostate), including COL6A2, OSBPL5, OLAH, OGFRL1, and SLC39A14. The significantly enriched GO terms of DEGs-lymph contained cellular amino acid metabolic process and cell cycle. The most significantly enriched pathway of DEGs-lymph was cytosolic tRNA aminoacylation. The DEGs-prostate was enriched in 39 GO terms and two pathways, and the pathways were PPARA activates gene expression Homo sapiens, and insulin resistance. The PPI network of DEGs-lymph gathered into two major clusters, WARS1 and CDC25A were representatives for them, respectively. One cluster was mainly involved in cytosolic tRNA aminoacylation, aminoacyl-tRNA biosynthesis and the function of amino acid metabolism; another was associated with cell cycle and cell apoptosis. As for the PPI network of DEGs-prostate, HELZ2 was the top nodes involved in the most protein-protein pairs, which was related to the pathway of "PPARA activates gene expression Homo sapiens."
conclusionsWARS1 and CDC25A might be potential biomarkers for side effects of dexamethasone in lymphoma, and HELZ2 in prostate cancer.
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