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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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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