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Identification of Prognostic Biomarkers Associated with Cancer Stem Cell Features in Prostate Adenocarcinoma

BACKGROUND: Prostate adenocarcinoma (PRAD) is the second most common malignancy in males and the fifth leading cause of cancer mortality. Cancer stem cells (CSCs) play an important role in the occurrence and development of PRAD, however, the prognostic biomarkers associated with CSC features have no...

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Autores principales: Zhang, Dehua, Zhang, Muchun, Zhang, Qifu, Zhao, Zhiyi, Nie, Yong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: International Scientific Literature, Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7418486/
https://www.ncbi.nlm.nih.gov/pubmed/32735556
http://dx.doi.org/10.12659/MSM.924543
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author Zhang, Dehua
Zhang, Muchun
Zhang, Qifu
Zhao, Zhiyi
Nie, Yong
author_facet Zhang, Dehua
Zhang, Muchun
Zhang, Qifu
Zhao, Zhiyi
Nie, Yong
author_sort Zhang, Dehua
collection PubMed
description BACKGROUND: Prostate adenocarcinoma (PRAD) is the second most common malignancy in males and the fifth leading cause of cancer mortality. Cancer stem cells (CSCs) play an important role in the occurrence and development of PRAD, however, the prognostic biomarkers associated with CSC features have not been identified in PRAD. MATERIAL/METHODS: In order to identify the prognostic stemness-related genes (SRGs) of PRAD, the RNA sequencing data of patients with PRAD were retrieved from The Cancer Genome Atlas (TCGA) databases. The mRNA expression-based stemness index (mRNAsi) and the differential expressed genes (DEGs) were evaluated and identified. The associations between the mRNAsi and tumorigenesis, overall survival (OS), prostate-specific antigen (PSA) value, and Gleason score were also established by nonparametric test and Kaplan-Meier survival analysis. The SRGs were identified as the overlapped DEGs of PRAD-associated DEGs and the mRNAsi-associated DEGs. Based on the prognostic SRGs, the predict model was constructed. Its accuracy was tested by the area under the curve (AUC) of the receiver operator characteristic (ROC) curve and the risk score. RESULTS: A total of 6005 PRAD-associated DEGs and 2462 mRNAsi-associated DEGs were identified. The mRNAsi was significantly upregulated in PRAD and associated with the PSA value and Gleason score. A total of 1631 SRGs were identified, with 36 prognostic SRGs screened by the univariate Cox analysis. Based on the prognostic SRGs, the predict model was constructed with the AUC of 0.986. Moreover, the risk score of the model was proved to be an independent prognostic factor, indicating its significant applicability. CONCLUSIONS: Our data demonstrate the mRNAsi as a reliable index for the tumorigenesis, PSA value, and Gleason score of PRAD. Additionally, this study provides a well-applied model for predicting the OS for patients with PRAD based on prognostic SRGs.
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spelling pubmed-74184862020-08-31 Identification of Prognostic Biomarkers Associated with Cancer Stem Cell Features in Prostate Adenocarcinoma Zhang, Dehua Zhang, Muchun Zhang, Qifu Zhao, Zhiyi Nie, Yong Med Sci Monit Database Analysis BACKGROUND: Prostate adenocarcinoma (PRAD) is the second most common malignancy in males and the fifth leading cause of cancer mortality. Cancer stem cells (CSCs) play an important role in the occurrence and development of PRAD, however, the prognostic biomarkers associated with CSC features have not been identified in PRAD. MATERIAL/METHODS: In order to identify the prognostic stemness-related genes (SRGs) of PRAD, the RNA sequencing data of patients with PRAD were retrieved from The Cancer Genome Atlas (TCGA) databases. The mRNA expression-based stemness index (mRNAsi) and the differential expressed genes (DEGs) were evaluated and identified. The associations between the mRNAsi and tumorigenesis, overall survival (OS), prostate-specific antigen (PSA) value, and Gleason score were also established by nonparametric test and Kaplan-Meier survival analysis. The SRGs were identified as the overlapped DEGs of PRAD-associated DEGs and the mRNAsi-associated DEGs. Based on the prognostic SRGs, the predict model was constructed. Its accuracy was tested by the area under the curve (AUC) of the receiver operator characteristic (ROC) curve and the risk score. RESULTS: A total of 6005 PRAD-associated DEGs and 2462 mRNAsi-associated DEGs were identified. The mRNAsi was significantly upregulated in PRAD and associated with the PSA value and Gleason score. A total of 1631 SRGs were identified, with 36 prognostic SRGs screened by the univariate Cox analysis. Based on the prognostic SRGs, the predict model was constructed with the AUC of 0.986. Moreover, the risk score of the model was proved to be an independent prognostic factor, indicating its significant applicability. CONCLUSIONS: Our data demonstrate the mRNAsi as a reliable index for the tumorigenesis, PSA value, and Gleason score of PRAD. Additionally, this study provides a well-applied model for predicting the OS for patients with PRAD based on prognostic SRGs. International Scientific Literature, Inc. 2020-08-31 /pmc/articles/PMC7418486/ /pubmed/32735556 http://dx.doi.org/10.12659/MSM.924543 Text en © Med Sci Monit, 2020 This work is licensed under Creative Common Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) )
spellingShingle Database Analysis
Zhang, Dehua
Zhang, Muchun
Zhang, Qifu
Zhao, Zhiyi
Nie, Yong
Identification of Prognostic Biomarkers Associated with Cancer Stem Cell Features in Prostate Adenocarcinoma
title Identification of Prognostic Biomarkers Associated with Cancer Stem Cell Features in Prostate Adenocarcinoma
title_full Identification of Prognostic Biomarkers Associated with Cancer Stem Cell Features in Prostate Adenocarcinoma
title_fullStr Identification of Prognostic Biomarkers Associated with Cancer Stem Cell Features in Prostate Adenocarcinoma
title_full_unstemmed Identification of Prognostic Biomarkers Associated with Cancer Stem Cell Features in Prostate Adenocarcinoma
title_short Identification of Prognostic Biomarkers Associated with Cancer Stem Cell Features in Prostate Adenocarcinoma
title_sort identification of prognostic biomarkers associated with cancer stem cell features in prostate adenocarcinoma
topic Database Analysis
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7418486/
https://www.ncbi.nlm.nih.gov/pubmed/32735556
http://dx.doi.org/10.12659/MSM.924543
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