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Plasma Messenger RNAs Identified Through Bioinformatics Analysis are Novel, Non-Invasive Prostate Cancer Biomarkers
AIM: To identify new biomarkers of prostate cancer (PCa) for the diagnosis and prediction of clinical outcomes. MATERIALS AND METHODS: Existing microarray data of PCa tissues in the Oncomine database were analyzed and candidate differentially expressed genes (DEGs) that may be novel and noninvasive...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6974148/ https://www.ncbi.nlm.nih.gov/pubmed/32021296 http://dx.doi.org/10.2147/OTT.S221276 |
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author | Wang, Rui Wu, Yingzi Yu, Jin Yang, Guizhu Yi, Hao Xu, Bin |
author_facet | Wang, Rui Wu, Yingzi Yu, Jin Yang, Guizhu Yi, Hao Xu, Bin |
author_sort | Wang, Rui |
collection | PubMed |
description | AIM: To identify new biomarkers of prostate cancer (PCa) for the diagnosis and prediction of clinical outcomes. MATERIALS AND METHODS: Existing microarray data of PCa tissues in the Oncomine database were analyzed and candidate differentially expressed genes (DEGs) that may be novel and noninvasive biomarkers were obtained. On this basis, plasma mRNA was extracted from PCa patients and healthy donors. Furthermore, plasma mRNA expression of DEGs was evaluated by qRT-PCR. Finally, the diagnostic power of the biomarkers was evaluated in comparison to the clinical characteristics of the patients. RESULTS: In this study, the top five significantly overexpressed mRNA (AMACR, PPP1R14b, PCA3, DLX1, and RPL22L1) and the top five significantly underexpressed mRNA (DUOX1, EFS, GSTP1, S100A16, and NCRNA00087) were selected for further validation in PCa patients and healthy donors by qRT-PCR. The results showed that AMACR, DLX1, PCA3, DUOX1, and GSTP1 mRNA were stably amplified in plasma. Additionally, DLX1, PCA3, DUOX1, and GSTP1 mRNA expression was significantly different between PCa circulating free mRNA samples and healthy donors. These mRNAs may be useful biomarkers for PCa diagnosis. CONCLUSION: Analysis of the expression of genes in the Oncomine database showed that DLX1, PCA3, and DUOX1 expressions have a cancer specific pattern in PCa. Collectively, DLX1, PCA3, and DUOX1 may be useful candidate biomarkers for PCa diagnosis. |
format | Online Article Text |
id | pubmed-6974148 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Dove |
record_format | MEDLINE/PubMed |
spelling | pubmed-69741482020-02-04 Plasma Messenger RNAs Identified Through Bioinformatics Analysis are Novel, Non-Invasive Prostate Cancer Biomarkers Wang, Rui Wu, Yingzi Yu, Jin Yang, Guizhu Yi, Hao Xu, Bin Onco Targets Ther Original Research AIM: To identify new biomarkers of prostate cancer (PCa) for the diagnosis and prediction of clinical outcomes. MATERIALS AND METHODS: Existing microarray data of PCa tissues in the Oncomine database were analyzed and candidate differentially expressed genes (DEGs) that may be novel and noninvasive biomarkers were obtained. On this basis, plasma mRNA was extracted from PCa patients and healthy donors. Furthermore, plasma mRNA expression of DEGs was evaluated by qRT-PCR. Finally, the diagnostic power of the biomarkers was evaluated in comparison to the clinical characteristics of the patients. RESULTS: In this study, the top five significantly overexpressed mRNA (AMACR, PPP1R14b, PCA3, DLX1, and RPL22L1) and the top five significantly underexpressed mRNA (DUOX1, EFS, GSTP1, S100A16, and NCRNA00087) were selected for further validation in PCa patients and healthy donors by qRT-PCR. The results showed that AMACR, DLX1, PCA3, DUOX1, and GSTP1 mRNA were stably amplified in plasma. Additionally, DLX1, PCA3, DUOX1, and GSTP1 mRNA expression was significantly different between PCa circulating free mRNA samples and healthy donors. These mRNAs may be useful biomarkers for PCa diagnosis. CONCLUSION: Analysis of the expression of genes in the Oncomine database showed that DLX1, PCA3, and DUOX1 expressions have a cancer specific pattern in PCa. Collectively, DLX1, PCA3, and DUOX1 may be useful candidate biomarkers for PCa diagnosis. Dove 2020-01-17 /pmc/articles/PMC6974148/ /pubmed/32021296 http://dx.doi.org/10.2147/OTT.S221276 Text en © 2020 Wang et al. http://creativecommons.org/licenses/by-nc/3.0/ This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php). |
spellingShingle | Original Research Wang, Rui Wu, Yingzi Yu, Jin Yang, Guizhu Yi, Hao Xu, Bin Plasma Messenger RNAs Identified Through Bioinformatics Analysis are Novel, Non-Invasive Prostate Cancer Biomarkers |
title | Plasma Messenger RNAs Identified Through Bioinformatics Analysis are Novel, Non-Invasive Prostate Cancer Biomarkers |
title_full | Plasma Messenger RNAs Identified Through Bioinformatics Analysis are Novel, Non-Invasive Prostate Cancer Biomarkers |
title_fullStr | Plasma Messenger RNAs Identified Through Bioinformatics Analysis are Novel, Non-Invasive Prostate Cancer Biomarkers |
title_full_unstemmed | Plasma Messenger RNAs Identified Through Bioinformatics Analysis are Novel, Non-Invasive Prostate Cancer Biomarkers |
title_short | Plasma Messenger RNAs Identified Through Bioinformatics Analysis are Novel, Non-Invasive Prostate Cancer Biomarkers |
title_sort | plasma messenger rnas identified through bioinformatics analysis are novel, non-invasive prostate cancer biomarkers |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6974148/ https://www.ncbi.nlm.nih.gov/pubmed/32021296 http://dx.doi.org/10.2147/OTT.S221276 |
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