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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Taylor & Francis
2021
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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. |
format | Online Article Text |
id | pubmed-8291889 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Taylor & Francis |
record_format | MEDLINE/PubMed |
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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