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Potential biomarkers screening to predict side effects of dexamethasone in different cancers

BACKGROUND: Excessive 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 associa...

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Autores principales: Jiang, Da, Jin, Hui, Zuo, Jing, Kong, Yan, Zhang, Xue, Dong, Qian, Xu, Zhihong, Li, Ying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7196465/
https://www.ncbi.nlm.nih.gov/pubmed/32048780
http://dx.doi.org/10.1002/mgg3.1160
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author Jiang, Da
Jin, Hui
Zuo, Jing
Kong, Yan
Zhang, Xue
Dong, Qian
Xu, Zhihong
Li, Ying
author_facet Jiang, Da
Jin, Hui
Zuo, Jing
Kong, Yan
Zhang, Xue
Dong, Qian
Xu, Zhihong
Li, Ying
author_sort Jiang, Da
collection PubMed
description BACKGROUND: Excessive 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. METHODS: Gene 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. RESULTS: One 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.” CONCLUSIONS: WARS1 and CDC25A might be potential biomarkers for side effects of dexamethasone in lymphoma, and HELZ2 in prostate cancer.
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spelling pubmed-71964652020-05-04 Potential biomarkers screening to predict side effects of dexamethasone in different cancers Jiang, Da Jin, Hui Zuo, Jing Kong, Yan Zhang, Xue Dong, Qian Xu, Zhihong Li, Ying Mol Genet Genomic Med Original Articles BACKGROUND: Excessive 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. METHODS: Gene 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. RESULTS: One 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.” CONCLUSIONS: WARS1 and CDC25A might be potential biomarkers for side effects of dexamethasone in lymphoma, and HELZ2 in prostate cancer. John Wiley and Sons Inc. 2020-02-12 /pmc/articles/PMC7196465/ /pubmed/32048780 http://dx.doi.org/10.1002/mgg3.1160 Text en © 2020 The Authors. Molecular Genetics & Genomic Medicine published by Wiley Periodicals, Inc. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Original Articles
Jiang, Da
Jin, Hui
Zuo, Jing
Kong, Yan
Zhang, Xue
Dong, Qian
Xu, Zhihong
Li, Ying
Potential biomarkers screening to predict side effects of dexamethasone in different cancers
title Potential biomarkers screening to predict side effects of dexamethasone in different cancers
title_full Potential biomarkers screening to predict side effects of dexamethasone in different cancers
title_fullStr Potential biomarkers screening to predict side effects of dexamethasone in different cancers
title_full_unstemmed Potential biomarkers screening to predict side effects of dexamethasone in different cancers
title_short Potential biomarkers screening to predict side effects of dexamethasone in different cancers
title_sort potential biomarkers screening to predict side effects of dexamethasone in different cancers
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7196465/
https://www.ncbi.nlm.nih.gov/pubmed/32048780
http://dx.doi.org/10.1002/mgg3.1160
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