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Long non-coding RNA-based signature for predicting prognosis of hepatocellular carcinoma

Long non-coding RNAs (lncRNAs), as one common type of non-coding RNAs, play a critical role in the tumorigenesis and development of hepatocellular carcinoma (HCC). In the current study, we aimed to assess the correlation between lncRNAs expression levels and prognosis of HCC patients. A lncRNA-based...

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Autores principales: Cao, Jie, Wu, Lili, Lei, Xin, Shi, Keqing, Shi, Liang, Shi, Yifen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8291889/
https://www.ncbi.nlm.nih.gov/pubmed/33622186
http://dx.doi.org/10.1080/21655979.2021.1878763
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author Cao, Jie
Wu, Lili
Lei, Xin
Shi, Keqing
Shi, Liang
Shi, Yifen
author_facet Cao, Jie
Wu, Lili
Lei, Xin
Shi, Keqing
Shi, Liang
Shi, Yifen
author_sort Cao, Jie
collection PubMed
description Long non-coding RNAs (lncRNAs), as one common type of non-coding RNAs, play a critical role in the tumorigenesis and development of hepatocellular carcinoma (HCC). In the current study, we aimed to assess the correlation between lncRNAs expression levels and prognosis of HCC patients. A lncRNA-based signature was also developed to predict the prognosis of HCC in this work. The lncRNAs expression profiles in tissues of tumor and para-carcinoma were obtained from The Cancer Genome Atlas (TCGA) database. The lncRNA-based prognostic model was established by least absolute shrinkage and selection operator (LASSO). The multivariate Cox-regression analysis was applied to identify the independent risk factors and subsequently developed a prognostic nomogram. Based on the co-expression analyses, we identified the lncRNA-related mRNAs and performed the biological function analysis. Between HCC and para-carcinoma tissues, 220 differentially expressed lncRNAs were filtered. Among these lncRNAs, 19 lncRNAs were identified as prognostic factors and were used to build a prognostic signature of overall survival (OS). Furthermore, a nomogram with high performance for predicting the OS of HCC patients (C-index: 0.779) by combining the 19-lncRNA signature (P < 0.001) and clinicopathologic factors including HBV (P = 0.005) and stage (P =0.017) was established. Functional enrichment analysis revealed that 19 lncRNAs had potential effects on tumor cell proliferation in HCC. In summary, we established a 19-lncRNA signature to predict the prognosis of HCC patients, which may perform a crucial role in guiding the management of HCC.
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spelling pubmed-82918892021-09-01 Long non-coding RNA-based signature for predicting prognosis of hepatocellular carcinoma Cao, Jie Wu, Lili Lei, Xin Shi, Keqing Shi, Liang Shi, Yifen Bioengineered Research Paper Long non-coding RNAs (lncRNAs), as one common type of non-coding RNAs, play a critical role in the tumorigenesis and development of hepatocellular carcinoma (HCC). In the current study, we aimed to assess the correlation between lncRNAs expression levels and prognosis of HCC patients. A lncRNA-based signature was also developed to predict the prognosis of HCC in this work. The lncRNAs expression profiles in tissues of tumor and para-carcinoma were obtained from The Cancer Genome Atlas (TCGA) database. The lncRNA-based prognostic model was established by least absolute shrinkage and selection operator (LASSO). The multivariate Cox-regression analysis was applied to identify the independent risk factors and subsequently developed a prognostic nomogram. Based on the co-expression analyses, we identified the lncRNA-related mRNAs and performed the biological function analysis. Between HCC and para-carcinoma tissues, 220 differentially expressed lncRNAs were filtered. Among these lncRNAs, 19 lncRNAs were identified as prognostic factors and were used to build a prognostic signature of overall survival (OS). Furthermore, a nomogram with high performance for predicting the OS of HCC patients (C-index: 0.779) by combining the 19-lncRNA signature (P < 0.001) and clinicopathologic factors including HBV (P = 0.005) and stage (P =0.017) was established. Functional enrichment analysis revealed that 19 lncRNAs had potential effects on tumor cell proliferation in HCC. In summary, we established a 19-lncRNA signature to predict the prognosis of HCC patients, which may perform a crucial role in guiding the management of HCC. Taylor & Francis 2021-02-23 /pmc/articles/PMC8291889/ /pubmed/33622186 http://dx.doi.org/10.1080/21655979.2021.1878763 Text en © 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Paper
Cao, Jie
Wu, Lili
Lei, Xin
Shi, Keqing
Shi, Liang
Shi, Yifen
Long non-coding RNA-based signature for predicting prognosis of hepatocellular carcinoma
title Long non-coding RNA-based signature for predicting prognosis of hepatocellular carcinoma
title_full Long non-coding RNA-based signature for predicting prognosis of hepatocellular carcinoma
title_fullStr Long non-coding RNA-based signature for predicting prognosis of hepatocellular carcinoma
title_full_unstemmed Long non-coding RNA-based signature for predicting prognosis of hepatocellular carcinoma
title_short Long non-coding RNA-based signature for predicting prognosis of hepatocellular carcinoma
title_sort long non-coding rna-based signature for predicting prognosis of hepatocellular carcinoma
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8291889/
https://www.ncbi.nlm.nih.gov/pubmed/33622186
http://dx.doi.org/10.1080/21655979.2021.1878763
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