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Transcriptome analysis reveals a long non-coding RNA signature to improve biochemical recurrence prediction in prostate cancer

Despite highly successful treatments for localized prostate cancer (PCa), prognostic biomarkers are needed to improve patient management and prognosis. Accumulating evidence suggests that long noncoding RNAs (lncRNAs) are key regulators with biological and clinical significance. By transcriptome ana...

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Autores principales: Xu, Jinyuan, Lan, Yujia, Yu, Fulong, Zhu, Shiwei, Ran, Jianrong, Zhu, Jiali, Zhang, Hongyi, Li, Lili, Cheng, Shujun, Xiao, Yun, Li, Xia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals LLC 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5982764/
https://www.ncbi.nlm.nih.gov/pubmed/29861844
http://dx.doi.org/10.18632/oncotarget.25048
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author Xu, Jinyuan
Lan, Yujia
Yu, Fulong
Zhu, Shiwei
Ran, Jianrong
Zhu, Jiali
Zhang, Hongyi
Li, Lili
Cheng, Shujun
Xiao, Yun
Li, Xia
author_facet Xu, Jinyuan
Lan, Yujia
Yu, Fulong
Zhu, Shiwei
Ran, Jianrong
Zhu, Jiali
Zhang, Hongyi
Li, Lili
Cheng, Shujun
Xiao, Yun
Li, Xia
author_sort Xu, Jinyuan
collection PubMed
description Despite highly successful treatments for localized prostate cancer (PCa), prognostic biomarkers are needed to improve patient management and prognosis. Accumulating evidence suggests that long noncoding RNAs (lncRNAs) are key regulators with biological and clinical significance. By transcriptome analysis, we identified a set of consistently dysregulated lncRNAs in PCa across different datasets and revealed an eight-lncRNA signature that significantly associated with the biochemical recurrence (BCR)-free survival. Based on the signature, patients could be classified into high- and low-risk groups with significantly different survival (HR = 2.19; 95% CI = 1.67–2.88; P < 0.0001). Validations in the validation cohorts and another independent cohort confirmed its prognostic value for recurrence prediction. Multivariable analysis showed that the signature was independent of common clinicopathological features and stratified analysis further revealed its role in elevating risk stratification of current prognostic models. Additionally, the eight-lncRNA signature was able to improve on the CAPRA-S score for the prediction of BCR as well as to reflect the metastatic potential of PCa. Functional characterization suggested that these lncRNAs which showed PCa-specific expression patterns may involve in critical processes in tumorigenesis. Overall, our results demonstrated potential application of lncRNAs as novel independent biomarkers. The eight-lncRNA signature may have clinical potential for facilitating further stratification of more aggressive patients who would benefit from adjuvant therapy.
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spelling pubmed-59827642018-06-01 Transcriptome analysis reveals a long non-coding RNA signature to improve biochemical recurrence prediction in prostate cancer Xu, Jinyuan Lan, Yujia Yu, Fulong Zhu, Shiwei Ran, Jianrong Zhu, Jiali Zhang, Hongyi Li, Lili Cheng, Shujun Xiao, Yun Li, Xia Oncotarget Research Paper Despite highly successful treatments for localized prostate cancer (PCa), prognostic biomarkers are needed to improve patient management and prognosis. Accumulating evidence suggests that long noncoding RNAs (lncRNAs) are key regulators with biological and clinical significance. By transcriptome analysis, we identified a set of consistently dysregulated lncRNAs in PCa across different datasets and revealed an eight-lncRNA signature that significantly associated with the biochemical recurrence (BCR)-free survival. Based on the signature, patients could be classified into high- and low-risk groups with significantly different survival (HR = 2.19; 95% CI = 1.67–2.88; P < 0.0001). Validations in the validation cohorts and another independent cohort confirmed its prognostic value for recurrence prediction. Multivariable analysis showed that the signature was independent of common clinicopathological features and stratified analysis further revealed its role in elevating risk stratification of current prognostic models. Additionally, the eight-lncRNA signature was able to improve on the CAPRA-S score for the prediction of BCR as well as to reflect the metastatic potential of PCa. Functional characterization suggested that these lncRNAs which showed PCa-specific expression patterns may involve in critical processes in tumorigenesis. Overall, our results demonstrated potential application of lncRNAs as novel independent biomarkers. The eight-lncRNA signature may have clinical potential for facilitating further stratification of more aggressive patients who would benefit from adjuvant therapy. Impact Journals LLC 2018-05-18 /pmc/articles/PMC5982764/ /pubmed/29861844 http://dx.doi.org/10.18632/oncotarget.25048 Text en Copyright: © 2018 Xu et al. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License 3.0 (http://creativecommons.org/licenses/by/3.0/) (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Paper
Xu, Jinyuan
Lan, Yujia
Yu, Fulong
Zhu, Shiwei
Ran, Jianrong
Zhu, Jiali
Zhang, Hongyi
Li, Lili
Cheng, Shujun
Xiao, Yun
Li, Xia
Transcriptome analysis reveals a long non-coding RNA signature to improve biochemical recurrence prediction in prostate cancer
title Transcriptome analysis reveals a long non-coding RNA signature to improve biochemical recurrence prediction in prostate cancer
title_full Transcriptome analysis reveals a long non-coding RNA signature to improve biochemical recurrence prediction in prostate cancer
title_fullStr Transcriptome analysis reveals a long non-coding RNA signature to improve biochemical recurrence prediction in prostate cancer
title_full_unstemmed Transcriptome analysis reveals a long non-coding RNA signature to improve biochemical recurrence prediction in prostate cancer
title_short Transcriptome analysis reveals a long non-coding RNA signature to improve biochemical recurrence prediction in prostate cancer
title_sort transcriptome analysis reveals a long non-coding rna signature to improve biochemical recurrence prediction in prostate cancer
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5982764/
https://www.ncbi.nlm.nih.gov/pubmed/29861844
http://dx.doi.org/10.18632/oncotarget.25048
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