Cargando…
Comprehensive bioinformatics analysis reveals potential lncRNA biomarkers for overall survival in patients with hepatocellular carcinoma: an on-line individual risk calculator based on TCGA cohort
BACKGROUND: Accumulated evidences have demonstrated that long non-coding RNAs (lncRNAs) are correlated with prognosis of patients with hepatocellular carcinoma. The current study aimed to develop and validate a prognostic lncRNA signature to improve the prediction of overall survival in hepatocellul...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6611026/ https://www.ncbi.nlm.nih.gov/pubmed/31312112 http://dx.doi.org/10.1186/s12935-019-0890-2 |
_version_ | 1783432615272906752 |
---|---|
author | Zhang, Zhiqiao Ouyang, Yanling Huang, Yiyan Wang, Peng Li, Jing He, Tingshan Liu, Qingbo |
author_facet | Zhang, Zhiqiao Ouyang, Yanling Huang, Yiyan Wang, Peng Li, Jing He, Tingshan Liu, Qingbo |
author_sort | Zhang, Zhiqiao |
collection | PubMed |
description | BACKGROUND: Accumulated evidences have demonstrated that long non-coding RNAs (lncRNAs) are correlated with prognosis of patients with hepatocellular carcinoma. The current study aimed to develop and validate a prognostic lncRNA signature to improve the prediction of overall survival in hepatocellular carcinoma patients. METHODS: The study cohort involved 348 hepatocellular carcinoma patients with lncRNA expression information and overall survival information. Through gene mining approach, the current study established a prognostic lncRNA signature (named LncRNA risk prediction score) for predicting the overall survival of hepatocellular carcinoma patients. RESULTS: The current study built a predictive nomogram based on ten prognostic lncRNA predictors through Cox regression analysis. In model group, the Harrell’s concordance indexes of LncRNA risk prediction score were 0.811 (95% CI 0.769–0.853) for 1-year overall survival, 0.814 (95% CI 0.772–0.856) for 3-year overall survival and 0.796 (95% CI 0.754–0.838) for 5-year overall survival respectively. In validation cohort, the Harrell’s concordance indexes of LncRNA risk prediction score were 0.779 (95% CI 0.737–0.821), 0.828 (95% CI 0.786–0.870) and 0.796 (95%CI 0.754–0.838) for 1-year survival, 3-year survival and 5-year survival respectively. LncRNA risk prediction score could stratify hepatocellular carcinoma patients into low risk group and high risk group. Further survival curve analysis demonstrated that the overall survival rate of high risk patients was significantly poorer than that of low risk patients (P < 0.001). CONCLUSIONS: In conclusion, the current study developed and validated a prognostic signature to predict the individual mortality risk for hepatocellular carcinoma patients. LncRNA risk prediction score is helpful to identify the patients with high mortality risk and optimize the individualized treatment decision. The web calculator can be used by click the following URL: https://zhangzhiqiao2.shinyapps.io/Smart_cancer_predictive_system_HCC_3/. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12935-019-0890-2) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6611026 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-66110262019-07-16 Comprehensive bioinformatics analysis reveals potential lncRNA biomarkers for overall survival in patients with hepatocellular carcinoma: an on-line individual risk calculator based on TCGA cohort Zhang, Zhiqiao Ouyang, Yanling Huang, Yiyan Wang, Peng Li, Jing He, Tingshan Liu, Qingbo Cancer Cell Int Primary Research BACKGROUND: Accumulated evidences have demonstrated that long non-coding RNAs (lncRNAs) are correlated with prognosis of patients with hepatocellular carcinoma. The current study aimed to develop and validate a prognostic lncRNA signature to improve the prediction of overall survival in hepatocellular carcinoma patients. METHODS: The study cohort involved 348 hepatocellular carcinoma patients with lncRNA expression information and overall survival information. Through gene mining approach, the current study established a prognostic lncRNA signature (named LncRNA risk prediction score) for predicting the overall survival of hepatocellular carcinoma patients. RESULTS: The current study built a predictive nomogram based on ten prognostic lncRNA predictors through Cox regression analysis. In model group, the Harrell’s concordance indexes of LncRNA risk prediction score were 0.811 (95% CI 0.769–0.853) for 1-year overall survival, 0.814 (95% CI 0.772–0.856) for 3-year overall survival and 0.796 (95% CI 0.754–0.838) for 5-year overall survival respectively. In validation cohort, the Harrell’s concordance indexes of LncRNA risk prediction score were 0.779 (95% CI 0.737–0.821), 0.828 (95% CI 0.786–0.870) and 0.796 (95%CI 0.754–0.838) for 1-year survival, 3-year survival and 5-year survival respectively. LncRNA risk prediction score could stratify hepatocellular carcinoma patients into low risk group and high risk group. Further survival curve analysis demonstrated that the overall survival rate of high risk patients was significantly poorer than that of low risk patients (P < 0.001). CONCLUSIONS: In conclusion, the current study developed and validated a prognostic signature to predict the individual mortality risk for hepatocellular carcinoma patients. LncRNA risk prediction score is helpful to identify the patients with high mortality risk and optimize the individualized treatment decision. The web calculator can be used by click the following URL: https://zhangzhiqiao2.shinyapps.io/Smart_cancer_predictive_system_HCC_3/. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12935-019-0890-2) contains supplementary material, which is available to authorized users. BioMed Central 2019-07-04 /pmc/articles/PMC6611026/ /pubmed/31312112 http://dx.doi.org/10.1186/s12935-019-0890-2 Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Primary Research Zhang, Zhiqiao Ouyang, Yanling Huang, Yiyan Wang, Peng Li, Jing He, Tingshan Liu, Qingbo Comprehensive bioinformatics analysis reveals potential lncRNA biomarkers for overall survival in patients with hepatocellular carcinoma: an on-line individual risk calculator based on TCGA cohort |
title | Comprehensive bioinformatics analysis reveals potential lncRNA biomarkers for overall survival in patients with hepatocellular carcinoma: an on-line individual risk calculator based on TCGA cohort |
title_full | Comprehensive bioinformatics analysis reveals potential lncRNA biomarkers for overall survival in patients with hepatocellular carcinoma: an on-line individual risk calculator based on TCGA cohort |
title_fullStr | Comprehensive bioinformatics analysis reveals potential lncRNA biomarkers for overall survival in patients with hepatocellular carcinoma: an on-line individual risk calculator based on TCGA cohort |
title_full_unstemmed | Comprehensive bioinformatics analysis reveals potential lncRNA biomarkers for overall survival in patients with hepatocellular carcinoma: an on-line individual risk calculator based on TCGA cohort |
title_short | Comprehensive bioinformatics analysis reveals potential lncRNA biomarkers for overall survival in patients with hepatocellular carcinoma: an on-line individual risk calculator based on TCGA cohort |
title_sort | comprehensive bioinformatics analysis reveals potential lncrna biomarkers for overall survival in patients with hepatocellular carcinoma: an on-line individual risk calculator based on tcga cohort |
topic | Primary Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6611026/ https://www.ncbi.nlm.nih.gov/pubmed/31312112 http://dx.doi.org/10.1186/s12935-019-0890-2 |
work_keys_str_mv | AT zhangzhiqiao comprehensivebioinformaticsanalysisrevealspotentiallncrnabiomarkersforoverallsurvivalinpatientswithhepatocellularcarcinomaanonlineindividualriskcalculatorbasedontcgacohort AT ouyangyanling comprehensivebioinformaticsanalysisrevealspotentiallncrnabiomarkersforoverallsurvivalinpatientswithhepatocellularcarcinomaanonlineindividualriskcalculatorbasedontcgacohort AT huangyiyan comprehensivebioinformaticsanalysisrevealspotentiallncrnabiomarkersforoverallsurvivalinpatientswithhepatocellularcarcinomaanonlineindividualriskcalculatorbasedontcgacohort AT wangpeng comprehensivebioinformaticsanalysisrevealspotentiallncrnabiomarkersforoverallsurvivalinpatientswithhepatocellularcarcinomaanonlineindividualriskcalculatorbasedontcgacohort AT lijing comprehensivebioinformaticsanalysisrevealspotentiallncrnabiomarkersforoverallsurvivalinpatientswithhepatocellularcarcinomaanonlineindividualriskcalculatorbasedontcgacohort AT hetingshan comprehensivebioinformaticsanalysisrevealspotentiallncrnabiomarkersforoverallsurvivalinpatientswithhepatocellularcarcinomaanonlineindividualriskcalculatorbasedontcgacohort AT liuqingbo comprehensivebioinformaticsanalysisrevealspotentiallncrnabiomarkersforoverallsurvivalinpatientswithhepatocellularcarcinomaanonlineindividualriskcalculatorbasedontcgacohort |