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A seven-lncRNA signature for predicting prognosis in breast carcinoma

BACKGROUND: Long non-coding RNAs (lncRNAs) play an important part in tumorigenesis and cancer metastasis and can serve as a potential biosignature for cancer prognosis. However, the use of lncRNA signatures to predict survival in breast carcinoma is yet unreported. METHODS: The lncRNA expression pro...

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Detalles Bibliográficos
Autores principales: Xu, Min, Chen, Ziyan, Lin, Bangyi, Zhang, Sina, Qu, Jinmiao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8797290/
https://www.ncbi.nlm.nih.gov/pubmed/35116701
http://dx.doi.org/10.21037/tcr-21-747
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author Xu, Min
Chen, Ziyan
Lin, Bangyi
Zhang, Sina
Qu, Jinmiao
author_facet Xu, Min
Chen, Ziyan
Lin, Bangyi
Zhang, Sina
Qu, Jinmiao
author_sort Xu, Min
collection PubMed
description BACKGROUND: Long non-coding RNAs (lncRNAs) play an important part in tumorigenesis and cancer metastasis and can serve as a potential biosignature for cancer prognosis. However, the use of lncRNA signatures to predict survival in breast carcinoma is yet unreported. METHODS: The lncRNA expression profiles and homologous clinical data of 913 breast carcinoma samples from the Cancer Genome Atlas (TCGA), were analyzed to obtain 2,547 differentially expressed lncRNAs. Univariate Cox proportional risk regression was applied to both the training and testing datasets to screen the common prognostic lncRNAs. Potential prognostic LncRNAs were screened by multivariate Cox proportional risk regression in the training data set of the selected LncRNAs. RESULTS: Seven lncRNAs (LINC02037, MAPT-AS1, RP1-37C10.3, RP11-344E13.4, RP11-454P21.1, RP11-616M22.1, SPACA6P-AS) were prominently associated with overall survival. Kaplan-Meier analysis and receiver operating characteristic (ROC) curves indicated that these indicators were sensitive and specific for survival prediction. The areas under the ROC curve of the seven-lncRNA signature in predicting 3- and 5-year survival rates were 0.771 and 0.780 respectively in the combined cohort. Furthermore, enrichment analysis revealed that these seven lncRNAs might participate multiple pathways related to tumorigenesis and prognosis. CONCLUSIONS: The proposed seven-lncRNA signature could serve as a latent prognostic biomarker for survival prediction in patients with breast carcinoma.
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spelling pubmed-87972902022-02-02 A seven-lncRNA signature for predicting prognosis in breast carcinoma Xu, Min Chen, Ziyan Lin, Bangyi Zhang, Sina Qu, Jinmiao Transl Cancer Res Original Article BACKGROUND: Long non-coding RNAs (lncRNAs) play an important part in tumorigenesis and cancer metastasis and can serve as a potential biosignature for cancer prognosis. However, the use of lncRNA signatures to predict survival in breast carcinoma is yet unreported. METHODS: The lncRNA expression profiles and homologous clinical data of 913 breast carcinoma samples from the Cancer Genome Atlas (TCGA), were analyzed to obtain 2,547 differentially expressed lncRNAs. Univariate Cox proportional risk regression was applied to both the training and testing datasets to screen the common prognostic lncRNAs. Potential prognostic LncRNAs were screened by multivariate Cox proportional risk regression in the training data set of the selected LncRNAs. RESULTS: Seven lncRNAs (LINC02037, MAPT-AS1, RP1-37C10.3, RP11-344E13.4, RP11-454P21.1, RP11-616M22.1, SPACA6P-AS) were prominently associated with overall survival. Kaplan-Meier analysis and receiver operating characteristic (ROC) curves indicated that these indicators were sensitive and specific for survival prediction. The areas under the ROC curve of the seven-lncRNA signature in predicting 3- and 5-year survival rates were 0.771 and 0.780 respectively in the combined cohort. Furthermore, enrichment analysis revealed that these seven lncRNAs might participate multiple pathways related to tumorigenesis and prognosis. CONCLUSIONS: The proposed seven-lncRNA signature could serve as a latent prognostic biomarker for survival prediction in patients with breast carcinoma. AME Publishing Company 2021-09 /pmc/articles/PMC8797290/ /pubmed/35116701 http://dx.doi.org/10.21037/tcr-21-747 Text en 2021 Translational Cancer Research. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.
spellingShingle Original Article
Xu, Min
Chen, Ziyan
Lin, Bangyi
Zhang, Sina
Qu, Jinmiao
A seven-lncRNA signature for predicting prognosis in breast carcinoma
title A seven-lncRNA signature for predicting prognosis in breast carcinoma
title_full A seven-lncRNA signature for predicting prognosis in breast carcinoma
title_fullStr A seven-lncRNA signature for predicting prognosis in breast carcinoma
title_full_unstemmed A seven-lncRNA signature for predicting prognosis in breast carcinoma
title_short A seven-lncRNA signature for predicting prognosis in breast carcinoma
title_sort seven-lncrna signature for predicting prognosis in breast carcinoma
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8797290/
https://www.ncbi.nlm.nih.gov/pubmed/35116701
http://dx.doi.org/10.21037/tcr-21-747
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