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Identification of Enzalutamide Resistance-Related circRNA-miRNA-mRNA Regulatory Networks in Patients with Prostate Cancer
PURPOSE: This study aimed to identify enzalutamide resistant-related (EnzR-related) circRNAs and to characterize and validate circRNA-miRNA-mRNA ceRNA regulatory network and corresponding prognostic signature of prostate cancer patients. METHODS: We obtained circRNA expression microarray from the Ge...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8232970/ https://www.ncbi.nlm.nih.gov/pubmed/34188491 http://dx.doi.org/10.2147/OTT.S309917 |
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author | Yu, JunJie Sun, Si Mao, WeiPu Xu, Bin Chen, Ming |
author_facet | Yu, JunJie Sun, Si Mao, WeiPu Xu, Bin Chen, Ming |
author_sort | Yu, JunJie |
collection | PubMed |
description | PURPOSE: This study aimed to identify enzalutamide resistant-related (EnzR-related) circRNAs and to characterize and validate circRNA-miRNA-mRNA ceRNA regulatory network and corresponding prognostic signature of prostate cancer patients. METHODS: We obtained circRNA expression microarray from the Gene Expression Omnibus (GEO) database and performed differential expression analysis to identify EnzR-related circRNAs using the limma package. The miRNA and mRNA expression profiling were downloaded and performed differential expression analysis, then overlapped with predicted candidates. Next, we established circRNA-miRNA-mRNA ceRNA network and PPI network utilized Cytoscape software and STRING database, respectively. In addition, univariate and Lasso Cox regression analyses were applied to generate a prognostic signature. Receiver operating characteristic (ROC) curves and Kaplan–Meier analysis were used to evaluate the reliability and sensitivity of the signature. Ultimately, we chose hsa_circ_0047641 to validate the feasibility of the EnzR-related ceRNA regulatory pathway using qRT-PCR, CCK8 and Transwell assays. RESULTS: We identified 13 EnzR-related circRNAs and constructed a ceRNA regulatory network that contained two downregulated circRNAs (has-circ-00000919 and has-circ-0000036) and two upregulated circRNAs (has-circ-0047641 and has-circ-0068697), and their sponged 6 miRNAs and 167 targeted mRNAs. Subsequently, these targeted mRNAs were performed to implement PPI analysis and to identify 10 Hub genes. Functional enrichment analysis provided new ways to seek potential biological functions. Besides, we established a prognostic signature of PCa patients based on 8 prognostic-associated mRNAs. We confirmed that the survival rates of PCa patients with high-risk subgroup were slightly lower than those with low-risk subgroup in the TCGA dataset (p<0.001), and ROC curves revealed that the AUC value for prognostic signature was 0.816. Finally, the functional analysis suggested that knockdown of hsa_circ_0047641 could inhibit the progression of PCa and could reverse Enz-resistance in vitro. CONCLUSION: We identified 13 EnzR-related circRNAs, and constructed and confirmed that EnzR-related circRNA-miRNA-mRNA ceRNA network and corresponding prognostic signature could be a useful prognostic biomarker and therapeutic target. |
format | Online Article Text |
id | pubmed-8232970 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Dove |
record_format | MEDLINE/PubMed |
spelling | pubmed-82329702021-06-28 Identification of Enzalutamide Resistance-Related circRNA-miRNA-mRNA Regulatory Networks in Patients with Prostate Cancer Yu, JunJie Sun, Si Mao, WeiPu Xu, Bin Chen, Ming Onco Targets Ther Original Research PURPOSE: This study aimed to identify enzalutamide resistant-related (EnzR-related) circRNAs and to characterize and validate circRNA-miRNA-mRNA ceRNA regulatory network and corresponding prognostic signature of prostate cancer patients. METHODS: We obtained circRNA expression microarray from the Gene Expression Omnibus (GEO) database and performed differential expression analysis to identify EnzR-related circRNAs using the limma package. The miRNA and mRNA expression profiling were downloaded and performed differential expression analysis, then overlapped with predicted candidates. Next, we established circRNA-miRNA-mRNA ceRNA network and PPI network utilized Cytoscape software and STRING database, respectively. In addition, univariate and Lasso Cox regression analyses were applied to generate a prognostic signature. Receiver operating characteristic (ROC) curves and Kaplan–Meier analysis were used to evaluate the reliability and sensitivity of the signature. Ultimately, we chose hsa_circ_0047641 to validate the feasibility of the EnzR-related ceRNA regulatory pathway using qRT-PCR, CCK8 and Transwell assays. RESULTS: We identified 13 EnzR-related circRNAs and constructed a ceRNA regulatory network that contained two downregulated circRNAs (has-circ-00000919 and has-circ-0000036) and two upregulated circRNAs (has-circ-0047641 and has-circ-0068697), and their sponged 6 miRNAs and 167 targeted mRNAs. Subsequently, these targeted mRNAs were performed to implement PPI analysis and to identify 10 Hub genes. Functional enrichment analysis provided new ways to seek potential biological functions. Besides, we established a prognostic signature of PCa patients based on 8 prognostic-associated mRNAs. We confirmed that the survival rates of PCa patients with high-risk subgroup were slightly lower than those with low-risk subgroup in the TCGA dataset (p<0.001), and ROC curves revealed that the AUC value for prognostic signature was 0.816. Finally, the functional analysis suggested that knockdown of hsa_circ_0047641 could inhibit the progression of PCa and could reverse Enz-resistance in vitro. CONCLUSION: We identified 13 EnzR-related circRNAs, and constructed and confirmed that EnzR-related circRNA-miRNA-mRNA ceRNA network and corresponding prognostic signature could be a useful prognostic biomarker and therapeutic target. Dove 2021-06-21 /pmc/articles/PMC8232970/ /pubmed/34188491 http://dx.doi.org/10.2147/OTT.S309917 Text en © 2021 Yu et al. https://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/ (https://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 Yu, JunJie Sun, Si Mao, WeiPu Xu, Bin Chen, Ming Identification of Enzalutamide Resistance-Related circRNA-miRNA-mRNA Regulatory Networks in Patients with Prostate Cancer |
title | Identification of Enzalutamide Resistance-Related circRNA-miRNA-mRNA Regulatory Networks in Patients with Prostate Cancer |
title_full | Identification of Enzalutamide Resistance-Related circRNA-miRNA-mRNA Regulatory Networks in Patients with Prostate Cancer |
title_fullStr | Identification of Enzalutamide Resistance-Related circRNA-miRNA-mRNA Regulatory Networks in Patients with Prostate Cancer |
title_full_unstemmed | Identification of Enzalutamide Resistance-Related circRNA-miRNA-mRNA Regulatory Networks in Patients with Prostate Cancer |
title_short | Identification of Enzalutamide Resistance-Related circRNA-miRNA-mRNA Regulatory Networks in Patients with Prostate Cancer |
title_sort | identification of enzalutamide resistance-related circrna-mirna-mrna regulatory networks in patients with prostate cancer |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8232970/ https://www.ncbi.nlm.nih.gov/pubmed/34188491 http://dx.doi.org/10.2147/OTT.S309917 |
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