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

Abstract 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 hepa...

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Main Authors: Zhiqiao Zhang, Yanling Ouyang, Yiyan Huang, Peng Wang, Jing Li, Tingshan He, Qingbo Liu
Format: Article
Language:English
Published: BMC 2019-07-01
Series:Cancer Cell International
Subjects:
Online Access:http://link.springer.com/article/10.1186/s12935-019-0890-2
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spelling doaj-520c3b612eb64128a20989646dae7e432020-11-25T03:01:29ZengBMCCancer Cell International1475-28672019-07-0119111510.1186/s12935-019-0890-2Comprehensive bioinformatics analysis reveals potential lncRNA biomarkers for overall survival in patients with hepatocellular carcinoma: an on-line individual risk calculator based on TCGA cohortZhiqiao Zhang0Yanling Ouyang1Yiyan Huang2Peng Wang3Jing Li4Tingshan He5Qingbo Liu6Department of Infectious Diseases, Shunde Hospital, Southern Medical UniversityDepartment of Infectious Diseases, Shunde Hospital, Southern Medical UniversityDepartment of Infectious Diseases, Shunde Hospital, Southern Medical UniversityDepartment of Infectious Diseases, Shunde Hospital, Southern Medical UniversityDepartment of Infectious Diseases, Shunde Hospital, Southern Medical UniversityDepartment of Infectious Diseases, Shunde Hospital, Southern Medical UniversityDepartment of Hepatobiliary Surgery, Shunde Hospital, Southern Medical UniversityAbstract 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/.http://link.springer.com/article/10.1186/s12935-019-0890-2Long non-coding RNAHepatocellular carcinomaOverall survivalPrognosisNomogram
collection DOAJ
language English
format Article
sources DOAJ
author Zhiqiao Zhang
Yanling Ouyang
Yiyan Huang
Peng Wang
Jing Li
Tingshan He
Qingbo Liu
spellingShingle Zhiqiao Zhang
Yanling Ouyang
Yiyan Huang
Peng Wang
Jing Li
Tingshan He
Qingbo Liu
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
Cancer Cell International
Long non-coding RNA
Hepatocellular carcinoma
Overall survival
Prognosis
Nomogram
author_facet Zhiqiao Zhang
Yanling Ouyang
Yiyan Huang
Peng Wang
Jing Li
Tingshan He
Qingbo Liu
author_sort Zhiqiao Zhang
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_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_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_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
publisher BMC
series Cancer Cell International
issn 1475-2867
publishDate 2019-07-01
description Abstract 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/.
topic Long non-coding RNA
Hepatocellular carcinoma
Overall survival
Prognosis
Nomogram
url http://link.springer.com/article/10.1186/s12935-019-0890-2
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