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A five-pseudouridylation-associated-LncRNA classifier for primary prostate cancer prognosis prediction
Background: Prostate cancer (PCa) is one of the most common cancers in males around the globe, and about one-third of patients with localized PCa will experience biochemical recurrence (BCR) after radical prostatectomy or radiation therapy. Reportedly, a proportion of patients with BCR had a poor pr...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9871836/ https://www.ncbi.nlm.nih.gov/pubmed/36704346 http://dx.doi.org/10.3389/fgene.2022.1110799 |
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author | Zheng, Pengxiang Long, Zining Gao, Anding Lu, Jianming Wang, Shuo Zhong, Chuanfan Lai, Houhua Guo, Yufei Wang, Ke Fang, Chen Mao, Xiangming |
author_facet | Zheng, Pengxiang Long, Zining Gao, Anding Lu, Jianming Wang, Shuo Zhong, Chuanfan Lai, Houhua Guo, Yufei Wang, Ke Fang, Chen Mao, Xiangming |
author_sort | Zheng, Pengxiang |
collection | PubMed |
description | Background: Prostate cancer (PCa) is one of the most common cancers in males around the globe, and about one-third of patients with localized PCa will experience biochemical recurrence (BCR) after radical prostatectomy or radiation therapy. Reportedly, a proportion of patients with BCR had a poor prognosis. Cumulative studies have shown that RNA modifications participate in the cancer-related transcriptome, but the role of pseudouridylation occurring in lncRNAs in PCa remains opaque. Methods: Spearman correlation analysis and univariate Cox regression were utilized to determine pseudouridylation-related lncRNAs with prognostic value in PCa. Prognostic pseudouridylation-related lncRNAs were included in the LASSO (least absolute shrinkage and selection operator) regression algorithm to develop a predictive model. KM (Kaplan-Meier) survival analysis and ROC (receiver operating characteristic) curves were applied to validate the constructed model. A battery of biological cell assays was conducted to confirm the cancer-promoting effects of RP11-468E2.5 in the model. Results: A classifier containing five pseudouridine-related lncRNAs was developed to stratify PCa patients on BCR and named the “ψ-lnc score.” KM survival analysis showed patients in the high ψ-lnc score group experienced BCR more than those in the low ψ-lnc score group. ROC curves demonstrated that ψ-lnc score outperformed other clinical indicators in BCR prediction. An external dataset, GSE54460, was utilized to validate the predictive model’s efficacy and authenticity. A ceRNA (competitive endogenous RNA) network was constructed to explore the model’s potential molecular functions and was annotated through GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analyses. RP11-468E2.5 was picked for further investigation, including pan-cancer analysis and experimental validation. Preliminarily, RP11-468E2.5 was confirmed as a tumor promoter. Conclusion: We provide some evidence that pseudouridylation in lncRNA played a role in the development of PCa and propose a novel prognostic classifier for clinical practice. |
format | Online Article Text |
id | pubmed-9871836 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-98718362023-01-25 A five-pseudouridylation-associated-LncRNA classifier for primary prostate cancer prognosis prediction Zheng, Pengxiang Long, Zining Gao, Anding Lu, Jianming Wang, Shuo Zhong, Chuanfan Lai, Houhua Guo, Yufei Wang, Ke Fang, Chen Mao, Xiangming Front Genet Genetics Background: Prostate cancer (PCa) is one of the most common cancers in males around the globe, and about one-third of patients with localized PCa will experience biochemical recurrence (BCR) after radical prostatectomy or radiation therapy. Reportedly, a proportion of patients with BCR had a poor prognosis. Cumulative studies have shown that RNA modifications participate in the cancer-related transcriptome, but the role of pseudouridylation occurring in lncRNAs in PCa remains opaque. Methods: Spearman correlation analysis and univariate Cox regression were utilized to determine pseudouridylation-related lncRNAs with prognostic value in PCa. Prognostic pseudouridylation-related lncRNAs were included in the LASSO (least absolute shrinkage and selection operator) regression algorithm to develop a predictive model. KM (Kaplan-Meier) survival analysis and ROC (receiver operating characteristic) curves were applied to validate the constructed model. A battery of biological cell assays was conducted to confirm the cancer-promoting effects of RP11-468E2.5 in the model. Results: A classifier containing five pseudouridine-related lncRNAs was developed to stratify PCa patients on BCR and named the “ψ-lnc score.” KM survival analysis showed patients in the high ψ-lnc score group experienced BCR more than those in the low ψ-lnc score group. ROC curves demonstrated that ψ-lnc score outperformed other clinical indicators in BCR prediction. An external dataset, GSE54460, was utilized to validate the predictive model’s efficacy and authenticity. A ceRNA (competitive endogenous RNA) network was constructed to explore the model’s potential molecular functions and was annotated through GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analyses. RP11-468E2.5 was picked for further investigation, including pan-cancer analysis and experimental validation. Preliminarily, RP11-468E2.5 was confirmed as a tumor promoter. Conclusion: We provide some evidence that pseudouridylation in lncRNA played a role in the development of PCa and propose a novel prognostic classifier for clinical practice. Frontiers Media S.A. 2023-01-10 /pmc/articles/PMC9871836/ /pubmed/36704346 http://dx.doi.org/10.3389/fgene.2022.1110799 Text en Copyright © 2023 Zheng, Long, Gao, Lu, Wang, Zhong, Lai, Guo, Wang, Fang and Mao. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Zheng, Pengxiang Long, Zining Gao, Anding Lu, Jianming Wang, Shuo Zhong, Chuanfan Lai, Houhua Guo, Yufei Wang, Ke Fang, Chen Mao, Xiangming A five-pseudouridylation-associated-LncRNA classifier for primary prostate cancer prognosis prediction |
title | A five-pseudouridylation-associated-LncRNA classifier for primary prostate cancer prognosis prediction |
title_full | A five-pseudouridylation-associated-LncRNA classifier for primary prostate cancer prognosis prediction |
title_fullStr | A five-pseudouridylation-associated-LncRNA classifier for primary prostate cancer prognosis prediction |
title_full_unstemmed | A five-pseudouridylation-associated-LncRNA classifier for primary prostate cancer prognosis prediction |
title_short | A five-pseudouridylation-associated-LncRNA classifier for primary prostate cancer prognosis prediction |
title_sort | five-pseudouridylation-associated-lncrna classifier for primary prostate cancer prognosis prediction |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9871836/ https://www.ncbi.nlm.nih.gov/pubmed/36704346 http://dx.doi.org/10.3389/fgene.2022.1110799 |
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