Cargando…
Five lncRNAs Associated With Prostate Cancer Prognosis Identified by Coexpression Network Analysis
Prostate cancer (PCa) is a highly malignant tumor, with increasing incidence and mortality rates worldwide. The aim of this study was to identify the prognostic lncRNAs and construct an lncRNA signature for PCa diagnosis by the interaction network between lncRNAs and protein-coding genes (PCGs). The...
Autores principales: | , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7785998/ https://www.ncbi.nlm.nih.gov/pubmed/33084528 http://dx.doi.org/10.1177/1533033820963578 |
_version_ | 1783632540979953664 |
---|---|
author | Gong, Xiaoyong Ning, Bobin |
author_facet | Gong, Xiaoyong Ning, Bobin |
author_sort | Gong, Xiaoyong |
collection | PubMed |
description | Prostate cancer (PCa) is a highly malignant tumor, with increasing incidence and mortality rates worldwide. The aim of this study was to identify the prognostic lncRNAs and construct an lncRNA signature for PCa diagnosis by the interaction network between lncRNAs and protein-coding genes (PCGs). The differentially expressed lncRNAs (DElncRNAs) and PCGs (DEPCGs) between PCa and normal prostate tissues were screened from The Cancer Genome Atlas (TCGA) database. The DEPCGs were functionally annotated in terms of the enriched pathways. Weighted gene co-expression network analysis (WGCNA) of 104 PCa samples identified 15 co-expression modules, of which the Turquoise module was negatively correlated with cancer and included 5 key lncRNAs and 47 PCGs. KEGG pathway analyses of the core 47 PCGs showed significant enrichment in classic PCa-related pathways, and overlapped with the enriched pathways of the DEPCGs. LINC00857, LINC00900, LINC00908, LINC00900, SNHG3 and FENDRR were significantly associated with the survival of PCa and have not been reported previously. Finally, Multivariable Cox regression analysis was used to establish a prognostic risk formula, and the patients were accordingly stratified into the low- and high-risk groups. The latter had significantly worse OS compared to the low-risk group (P < 0.01), and the area under the receiver operating characteristic curve (ROC) of 14-year OS was 0.829. The accuracy of our prediction model was determined by calculating the corresponding concordance index (C-index) and risk curves. In conclusion, we established a 5-lncRNA prognostic signature that provides insights into the biological and clinical relevance of lncRNAs in PCa. |
format | Online Article Text |
id | pubmed-7785998 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-77859982021-01-14 Five lncRNAs Associated With Prostate Cancer Prognosis Identified by Coexpression Network Analysis Gong, Xiaoyong Ning, Bobin Technol Cancer Res Treat Original Article Prostate cancer (PCa) is a highly malignant tumor, with increasing incidence and mortality rates worldwide. The aim of this study was to identify the prognostic lncRNAs and construct an lncRNA signature for PCa diagnosis by the interaction network between lncRNAs and protein-coding genes (PCGs). The differentially expressed lncRNAs (DElncRNAs) and PCGs (DEPCGs) between PCa and normal prostate tissues were screened from The Cancer Genome Atlas (TCGA) database. The DEPCGs were functionally annotated in terms of the enriched pathways. Weighted gene co-expression network analysis (WGCNA) of 104 PCa samples identified 15 co-expression modules, of which the Turquoise module was negatively correlated with cancer and included 5 key lncRNAs and 47 PCGs. KEGG pathway analyses of the core 47 PCGs showed significant enrichment in classic PCa-related pathways, and overlapped with the enriched pathways of the DEPCGs. LINC00857, LINC00900, LINC00908, LINC00900, SNHG3 and FENDRR were significantly associated with the survival of PCa and have not been reported previously. Finally, Multivariable Cox regression analysis was used to establish a prognostic risk formula, and the patients were accordingly stratified into the low- and high-risk groups. The latter had significantly worse OS compared to the low-risk group (P < 0.01), and the area under the receiver operating characteristic curve (ROC) of 14-year OS was 0.829. The accuracy of our prediction model was determined by calculating the corresponding concordance index (C-index) and risk curves. In conclusion, we established a 5-lncRNA prognostic signature that provides insights into the biological and clinical relevance of lncRNAs in PCa. SAGE Publications 2020-10-21 /pmc/articles/PMC7785998/ /pubmed/33084528 http://dx.doi.org/10.1177/1533033820963578 Text en © The Author(s) 2020 https://creativecommons.org/licenses/by-nc/4.0/ This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Original Article Gong, Xiaoyong Ning, Bobin Five lncRNAs Associated With Prostate Cancer Prognosis Identified by Coexpression Network Analysis |
title | Five lncRNAs Associated With Prostate Cancer Prognosis Identified by Coexpression Network Analysis |
title_full | Five lncRNAs Associated With Prostate Cancer Prognosis Identified by Coexpression Network Analysis |
title_fullStr | Five lncRNAs Associated With Prostate Cancer Prognosis Identified by Coexpression Network Analysis |
title_full_unstemmed | Five lncRNAs Associated With Prostate Cancer Prognosis Identified by Coexpression Network Analysis |
title_short | Five lncRNAs Associated With Prostate Cancer Prognosis Identified by Coexpression Network Analysis |
title_sort | five lncrnas associated with prostate cancer prognosis identified by coexpression network analysis |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7785998/ https://www.ncbi.nlm.nih.gov/pubmed/33084528 http://dx.doi.org/10.1177/1533033820963578 |
work_keys_str_mv | AT gongxiaoyong fivelncrnasassociatedwithprostatecancerprognosisidentifiedbycoexpressionnetworkanalysis AT ningbobin fivelncrnasassociatedwithprostatecancerprognosisidentifiedbycoexpressionnetworkanalysis |