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Identification of an 11-lncRNA signature with high performance for predicting the prognosis of hepatocellular carcinoma using bioinformatics analysis
Hepatocellular carcinoma (HCC) is a common primary liver cancer with a high incidence and mortality. This study was conducted to identify a long non-coding RNA (lncRNA) signature that may serve as a predictor for HCC prognosis. RNA-seq data were extracted from The Cancer Genome Atlas database. Diffe...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7870215/ https://www.ncbi.nlm.nih.gov/pubmed/33592832 http://dx.doi.org/10.1097/MD.0000000000023749 |
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author | Wang, Anmei Lei, Junhua |
author_facet | Wang, Anmei Lei, Junhua |
author_sort | Wang, Anmei |
collection | PubMed |
description | Hepatocellular carcinoma (HCC) is a common primary liver cancer with a high incidence and mortality. This study was conducted to identify a long non-coding RNA (lncRNA) signature that may serve as a predictor for HCC prognosis. RNA-seq data were extracted from The Cancer Genome Atlas database. Differentially expressed genes, lncRNAs, and miRNAs were identified in HCC (n = 374) and control samples (n = 50) and used to screen prognosis-associated lncRNA signatures. The association of the lncRNA signature with HCC prognosis was analyzed and a competitive endogenous RNA regulatory network involving the lncRNA signature was constructed. A total of 199 mRNAs, 1092 lncRNAs, and 251 miRNAs were differentially expressed between HCC and control samples. Among these lncRNAs, 11 prognosis-associated lncRNAs were used to construct a lncRNA signature. Cox regression analysis showed that patients with higher risk scores of the lncRNA signature were at risk of poor prognosis. Four lncRNAs (including LINC01517, DDX11-AS1, LINC01136, and RP11-20J15.2) and 7 miRNAs (including miR-195, miR-199b, miR-326, miR-424, and let-7c) in the ceRNA network interacted with the upregulated gene E2F2, which was associated with the overall prognosis of patients with HCC. The 11-lncRNA signature might be useful for predicting the prognosis of patients with HCC. |
format | Online Article Text |
id | pubmed-7870215 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-78702152021-02-10 Identification of an 11-lncRNA signature with high performance for predicting the prognosis of hepatocellular carcinoma using bioinformatics analysis Wang, Anmei Lei, Junhua Medicine (Baltimore) 5700 Hepatocellular carcinoma (HCC) is a common primary liver cancer with a high incidence and mortality. This study was conducted to identify a long non-coding RNA (lncRNA) signature that may serve as a predictor for HCC prognosis. RNA-seq data were extracted from The Cancer Genome Atlas database. Differentially expressed genes, lncRNAs, and miRNAs were identified in HCC (n = 374) and control samples (n = 50) and used to screen prognosis-associated lncRNA signatures. The association of the lncRNA signature with HCC prognosis was analyzed and a competitive endogenous RNA regulatory network involving the lncRNA signature was constructed. A total of 199 mRNAs, 1092 lncRNAs, and 251 miRNAs were differentially expressed between HCC and control samples. Among these lncRNAs, 11 prognosis-associated lncRNAs were used to construct a lncRNA signature. Cox regression analysis showed that patients with higher risk scores of the lncRNA signature were at risk of poor prognosis. Four lncRNAs (including LINC01517, DDX11-AS1, LINC01136, and RP11-20J15.2) and 7 miRNAs (including miR-195, miR-199b, miR-326, miR-424, and let-7c) in the ceRNA network interacted with the upregulated gene E2F2, which was associated with the overall prognosis of patients with HCC. The 11-lncRNA signature might be useful for predicting the prognosis of patients with HCC. Lippincott Williams & Wilkins 2021-02-05 /pmc/articles/PMC7870215/ /pubmed/33592832 http://dx.doi.org/10.1097/MD.0000000000023749 Text en Copyright © 2021 the Author(s). Published by Wolters Kluwer Health, Inc. http://creativecommons.org/licenses/by-nc/4.0 This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC), where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc/4.0 |
spellingShingle | 5700 Wang, Anmei Lei, Junhua Identification of an 11-lncRNA signature with high performance for predicting the prognosis of hepatocellular carcinoma using bioinformatics analysis |
title | Identification of an 11-lncRNA signature with high performance for predicting the prognosis of hepatocellular carcinoma using bioinformatics analysis |
title_full | Identification of an 11-lncRNA signature with high performance for predicting the prognosis of hepatocellular carcinoma using bioinformatics analysis |
title_fullStr | Identification of an 11-lncRNA signature with high performance for predicting the prognosis of hepatocellular carcinoma using bioinformatics analysis |
title_full_unstemmed | Identification of an 11-lncRNA signature with high performance for predicting the prognosis of hepatocellular carcinoma using bioinformatics analysis |
title_short | Identification of an 11-lncRNA signature with high performance for predicting the prognosis of hepatocellular carcinoma using bioinformatics analysis |
title_sort | identification of an 11-lncrna signature with high performance for predicting the prognosis of hepatocellular carcinoma using bioinformatics analysis |
topic | 5700 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7870215/ https://www.ncbi.nlm.nih.gov/pubmed/33592832 http://dx.doi.org/10.1097/MD.0000000000023749 |
work_keys_str_mv | AT wanganmei identificationofan11lncrnasignaturewithhighperformanceforpredictingtheprognosisofhepatocellularcarcinomausingbioinformaticsanalysis AT leijunhua identificationofan11lncrnasignaturewithhighperformanceforpredictingtheprognosisofhepatocellularcarcinomausingbioinformaticsanalysis |