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Development and validation of 9-long Non-coding RNA signature to predicting survival in hepatocellular carcinoma
Primary hepatic carcinoma is 1 of the most common malignant tumors globally, of which hepatocellular carcinoma (HCC) accounts for 85% to 90%. Due to the high degree of deterioration and low early detection rate of HCC, most patients are diagnosed when they are already in the middle and advanced stag...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer Health
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7249897/ https://www.ncbi.nlm.nih.gov/pubmed/32481346 http://dx.doi.org/10.1097/MD.0000000000020422 |
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author | Deng, Benyuan Yang, Min Wang, Ming Liu, Zhongwu |
author_facet | Deng, Benyuan Yang, Min Wang, Ming Liu, Zhongwu |
author_sort | Deng, Benyuan |
collection | PubMed |
description | Primary hepatic carcinoma is 1 of the most common malignant tumors globally, of which hepatocellular carcinoma (HCC) accounts for 85% to 90%. Due to the high degree of deterioration and low early detection rate of HCC, most patients are diagnosed when they are already in the middle and advanced stages, and the prognosis are always poor. RNA sequencing data from the cancer genome atlas was used to explore differences in lncRNA expression profiles. LncRNA was extracted by gdcRNAtools in R package. Multivariate cox analysis was performed on the screened lncRNAs. The relationship between the lncRNA model and prognosis as well as clinical characteristics of patients with HCC was analyzed. Finally, a predictive nomogram in the the cancer genome atlas cohort was established and verified internally Based on the RNA sequencing survival analysis, a 9- lncRNAs prognosis model, including TMCC1-AS1, AC008892.1, AL031985.3, L34079.2, U95743.1, KDM4A-AS1, SACS-AS1, AC005534.1, LINC01116 was established. The 9-lncRNA prognosis model was a reliable tool for predicting prognosis of HCC, and the nomogram of this prognosis model could help clinicians to choose personalized treatment for HCC patients This model was significant to complement clinic characteristics of HCC and to promote personalized management of patients, it also provided a new idea for researches on the prognosis of HCC. |
format | Online Article Text |
id | pubmed-7249897 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Wolters Kluwer Health |
record_format | MEDLINE/PubMed |
spelling | pubmed-72498972020-06-15 Development and validation of 9-long Non-coding RNA signature to predicting survival in hepatocellular carcinoma Deng, Benyuan Yang, Min Wang, Ming Liu, Zhongwu Medicine (Baltimore) 5700 Primary hepatic carcinoma is 1 of the most common malignant tumors globally, of which hepatocellular carcinoma (HCC) accounts for 85% to 90%. Due to the high degree of deterioration and low early detection rate of HCC, most patients are diagnosed when they are already in the middle and advanced stages, and the prognosis are always poor. RNA sequencing data from the cancer genome atlas was used to explore differences in lncRNA expression profiles. LncRNA was extracted by gdcRNAtools in R package. Multivariate cox analysis was performed on the screened lncRNAs. The relationship between the lncRNA model and prognosis as well as clinical characteristics of patients with HCC was analyzed. Finally, a predictive nomogram in the the cancer genome atlas cohort was established and verified internally Based on the RNA sequencing survival analysis, a 9- lncRNAs prognosis model, including TMCC1-AS1, AC008892.1, AL031985.3, L34079.2, U95743.1, KDM4A-AS1, SACS-AS1, AC005534.1, LINC01116 was established. The 9-lncRNA prognosis model was a reliable tool for predicting prognosis of HCC, and the nomogram of this prognosis model could help clinicians to choose personalized treatment for HCC patients This model was significant to complement clinic characteristics of HCC and to promote personalized management of patients, it also provided a new idea for researches on the prognosis of HCC. Wolters Kluwer Health 2020-05-22 /pmc/articles/PMC7249897/ /pubmed/32481346 http://dx.doi.org/10.1097/MD.0000000000020422 Text en Copyright © 2020 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 Deng, Benyuan Yang, Min Wang, Ming Liu, Zhongwu Development and validation of 9-long Non-coding RNA signature to predicting survival in hepatocellular carcinoma |
title | Development and validation of 9-long Non-coding RNA signature to predicting survival in hepatocellular carcinoma |
title_full | Development and validation of 9-long Non-coding RNA signature to predicting survival in hepatocellular carcinoma |
title_fullStr | Development and validation of 9-long Non-coding RNA signature to predicting survival in hepatocellular carcinoma |
title_full_unstemmed | Development and validation of 9-long Non-coding RNA signature to predicting survival in hepatocellular carcinoma |
title_short | Development and validation of 9-long Non-coding RNA signature to predicting survival in hepatocellular carcinoma |
title_sort | development and validation of 9-long non-coding rna signature to predicting survival in hepatocellular carcinoma |
topic | 5700 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7249897/ https://www.ncbi.nlm.nih.gov/pubmed/32481346 http://dx.doi.org/10.1097/MD.0000000000020422 |
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