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A long non-coding RNA signature to improve prognosis prediction of colorectal cancer

Increasing evidence suggests long non-coding RNAs (lncRNAs) are frequently aberrantly expressed in cancers, however, few related lncRNA signatures have been established for prediction of cancer prognosis. We aimed to develop a lncRNA signature to improve prognosis prediction of colorectal cancer (CR...

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Detalles Bibliográficos
Autores principales: Hu, Ye, Chen, Hao-Yan, Yu, Chen-Yang, Xu, Jie, Wang, Ji-Lin, Qian, Jin, Zhang, Xi, Fang, Jing-Yuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals LLC 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4039159/
https://www.ncbi.nlm.nih.gov/pubmed/24809982
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author Hu, Ye
Chen, Hao-Yan
Yu, Chen-Yang
Xu, Jie
Wang, Ji-Lin
Qian, Jin
Zhang, Xi
Fang, Jing-Yuan
author_facet Hu, Ye
Chen, Hao-Yan
Yu, Chen-Yang
Xu, Jie
Wang, Ji-Lin
Qian, Jin
Zhang, Xi
Fang, Jing-Yuan
author_sort Hu, Ye
collection PubMed
description Increasing evidence suggests long non-coding RNAs (lncRNAs) are frequently aberrantly expressed in cancers, however, few related lncRNA signatures have been established for prediction of cancer prognosis. We aimed to develop a lncRNA signature to improve prognosis prediction of colorectal cancer (CRC). Using a lncRNA-mining approach, we performed lncRNA expression profiling in large CRC cohorts from Gene Expression Ominus (GEO), including GSE39582 test series(N=436), internal validation series (N=117); and two independent validation series GSE14333 (N=197) and GSE17536(N=145). We established a set of six lncRNAs that were significantly correlated with the disease free survival (DFS) in the test series. Based on this six-lncRNA signature, the test series patients could be classified into high-risk and low-risk subgroups with significantly different DFS (HR=2.670; P<0.0001). The prognostic value of this six-lncRNA signature was confirmed in the internal validation series and another two independent CRC sets. Gene set enrichment analysis (GSEA) analysis suggested that risk score positively correlated with several cancer metastasis related pathways. Functional experiments demonstrated three dysregulated lncRNAs, AK123657, BX648207 and BX649059 were required for efficient invasion and proliferation suppression in CRC cell lines. Our results might provide an efficient classification tool for clinical prognosis evaluation of CRC.
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spelling pubmed-40391592014-06-10 A long non-coding RNA signature to improve prognosis prediction of colorectal cancer Hu, Ye Chen, Hao-Yan Yu, Chen-Yang Xu, Jie Wang, Ji-Lin Qian, Jin Zhang, Xi Fang, Jing-Yuan Oncotarget Research Paper Increasing evidence suggests long non-coding RNAs (lncRNAs) are frequently aberrantly expressed in cancers, however, few related lncRNA signatures have been established for prediction of cancer prognosis. We aimed to develop a lncRNA signature to improve prognosis prediction of colorectal cancer (CRC). Using a lncRNA-mining approach, we performed lncRNA expression profiling in large CRC cohorts from Gene Expression Ominus (GEO), including GSE39582 test series(N=436), internal validation series (N=117); and two independent validation series GSE14333 (N=197) and GSE17536(N=145). We established a set of six lncRNAs that were significantly correlated with the disease free survival (DFS) in the test series. Based on this six-lncRNA signature, the test series patients could be classified into high-risk and low-risk subgroups with significantly different DFS (HR=2.670; P<0.0001). The prognostic value of this six-lncRNA signature was confirmed in the internal validation series and another two independent CRC sets. Gene set enrichment analysis (GSEA) analysis suggested that risk score positively correlated with several cancer metastasis related pathways. Functional experiments demonstrated three dysregulated lncRNAs, AK123657, BX648207 and BX649059 were required for efficient invasion and proliferation suppression in CRC cell lines. Our results might provide an efficient classification tool for clinical prognosis evaluation of CRC. Impact Journals LLC 2014-04-11 /pmc/articles/PMC4039159/ /pubmed/24809982 Text en Copyright: © 2014 Hu et al. http://creativecommons.org/licenses/by/2.5/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Paper
Hu, Ye
Chen, Hao-Yan
Yu, Chen-Yang
Xu, Jie
Wang, Ji-Lin
Qian, Jin
Zhang, Xi
Fang, Jing-Yuan
A long non-coding RNA signature to improve prognosis prediction of colorectal cancer
title A long non-coding RNA signature to improve prognosis prediction of colorectal cancer
title_full A long non-coding RNA signature to improve prognosis prediction of colorectal cancer
title_fullStr A long non-coding RNA signature to improve prognosis prediction of colorectal cancer
title_full_unstemmed A long non-coding RNA signature to improve prognosis prediction of colorectal cancer
title_short A long non-coding RNA signature to improve prognosis prediction of colorectal cancer
title_sort long non-coding rna signature to improve prognosis prediction of colorectal cancer
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4039159/
https://www.ncbi.nlm.nih.gov/pubmed/24809982
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