Construction of a 13‐microRNA‐based signature and prognostic nomogram for predicting overall survival in patients with hepatocellular carcinoma

Aim Hepatocellular carcinoma (HCC) is a common malignancy associated with a poor prognosis due to difficulties in reliably estimating overall survival (OS). MicroRNAs (miRNAs) play critical roles in HCC initiation, progression, and metastasis and are highly correlated with patient prognosis. Thus, m...

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Published inHepatology research Vol. 50; no. 10; pp. 1151 - 1163
Main Authors Zheng, Zhihua, Wen, Yi, Nie, Kechao, Tang, Shuting, Chen, Xu, Lan, Shaoyang, Pan, Jinglin, Jiang, Kailin, Jiang, Xiaotao, Liu, Peng, Yan, Yanhua, Liu, Fengbin, Liu, Yufeng, Li, Peiwu
Format Journal Article
LanguageEnglish
Published Hoboken Wiley Subscription Services, Inc 01.10.2020
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Abstract Aim Hepatocellular carcinoma (HCC) is a common malignancy associated with a poor prognosis due to difficulties in reliably estimating overall survival (OS). MicroRNAs (miRNAs) play critical roles in HCC initiation, progression, and metastasis and are highly correlated with patient prognosis. Thus, miRNA‐based risk signatures and nomograms are urgently required for predicting OS in patients with HCC. Methods We constructed a 13‐miRNA‐based signature and prognostic nomogram using 408 HCC samples and 58 normal tissues with miRNA sequencing data and clinical data from 323 patients downloaded from The Cancer Genome Atlas. A total of 195 patients were assigned as the internal validation cohort for verification and testing. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis was applied to investigate pathway enrichment for the signature. Results We identified and validated a 13‐miRNA risk signature highly associating with the OS of HCC patients. The signature showed good performances by calculating C‐index, area under the curve, and calibration curves. After verification and testing using an internal validation cohort, the results yielded a miRNA‐based signature and a prognostic nomogram with reliable predictive accuracy. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis indicated that various genes and multiple pathways were closely related to the mechanisms of HCC proliferation and metastasis. Conclusion We successfully identified a 13‐miRNA‐based signature and prognostic nomogram that are capable of predicting OS in patients with HCC.
AbstractList AimHepatocellular carcinoma (HCC) is a common malignancy associated with a poor prognosis due to difficulties in reliably estimating overall survival (OS). MicroRNAs (miRNAs) play critical roles in HCC initiation, progression, and metastasis and are highly correlated with patient prognosis. Thus, miRNA‐based risk signatures and nomograms are urgently required for predicting OS in patients with HCC.MethodsWe constructed a 13‐miRNA‐based signature and prognostic nomogram using 408 HCC samples and 58 normal tissues with miRNA sequencing data and clinical data from 323 patients downloaded from The Cancer Genome Atlas. A total of 195 patients were assigned as the internal validation cohort for verification and testing. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis was applied to investigate pathway enrichment for the signature.ResultsWe identified and validated a 13‐miRNA risk signature highly associating with the OS of HCC patients. The signature showed good performances by calculating C‐index, area under the curve, and calibration curves. After verification and testing using an internal validation cohort, the results yielded a miRNA‐based signature and a prognostic nomogram with reliable predictive accuracy. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis indicated that various genes and multiple pathways were closely related to the mechanisms of HCC proliferation and metastasis.ConclusionWe successfully identified a 13‐miRNA‐based signature and prognostic nomogram that are capable of predicting OS in patients with HCC.
Hepatocellular carcinoma (HCC) is a common malignancy associated with a poor prognosis due to difficulties in reliably estimating overall survival (OS). MicroRNAs (miRNAs) play critical roles in HCC initiation, progression, and metastasis and are highly correlated with patient prognosis. Thus, miRNA-based risk signatures and nomograms are urgently required for predicting OS in patients with HCC.AIMHepatocellular carcinoma (HCC) is a common malignancy associated with a poor prognosis due to difficulties in reliably estimating overall survival (OS). MicroRNAs (miRNAs) play critical roles in HCC initiation, progression, and metastasis and are highly correlated with patient prognosis. Thus, miRNA-based risk signatures and nomograms are urgently required for predicting OS in patients with HCC.We constructed a 13-miRNA-based signature and prognostic nomogram using 408 HCC samples and 58 normal tissues with miRNA sequencing data and clinical data from 323 patients downloaded from The Cancer Genome Atlas. A total of 195 patients were assigned as the internal validation cohort for verification and testing. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis was applied to investigate pathway enrichment for the signature.METHODSWe constructed a 13-miRNA-based signature and prognostic nomogram using 408 HCC samples and 58 normal tissues with miRNA sequencing data and clinical data from 323 patients downloaded from The Cancer Genome Atlas. A total of 195 patients were assigned as the internal validation cohort for verification and testing. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis was applied to investigate pathway enrichment for the signature.We identified and validated a 13-miRNA risk signature highly associating with the OS of HCC patients. The signature showed good performances by calculating C-index, area under the curve, and calibration curves. After verification and testing using an internal validation cohort, the results yielded a miRNA-based signature and a prognostic nomogram with reliable predictive accuracy. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis indicated that various genes and multiple pathways were closely related to the mechanisms of HCC proliferation and metastasis.RESULTSWe identified and validated a 13-miRNA risk signature highly associating with the OS of HCC patients. The signature showed good performances by calculating C-index, area under the curve, and calibration curves. After verification and testing using an internal validation cohort, the results yielded a miRNA-based signature and a prognostic nomogram with reliable predictive accuracy. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis indicated that various genes and multiple pathways were closely related to the mechanisms of HCC proliferation and metastasis.We successfully identified a 13-miRNA-based signature and prognostic nomogram that are capable of predicting OS in patients with HCC.CONCLUSIONWe successfully identified a 13-miRNA-based signature and prognostic nomogram that are capable of predicting OS in patients with HCC.
Aim Hepatocellular carcinoma (HCC) is a common malignancy associated with a poor prognosis due to difficulties in reliably estimating overall survival (OS). MicroRNAs (miRNAs) play critical roles in HCC initiation, progression, and metastasis and are highly correlated with patient prognosis. Thus, miRNA‐based risk signatures and nomograms are urgently required for predicting OS in patients with HCC. Methods We constructed a 13‐miRNA‐based signature and prognostic nomogram using 408 HCC samples and 58 normal tissues with miRNA sequencing data and clinical data from 323 patients downloaded from The Cancer Genome Atlas. A total of 195 patients were assigned as the internal validation cohort for verification and testing. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis was applied to investigate pathway enrichment for the signature. Results We identified and validated a 13‐miRNA risk signature highly associating with the OS of HCC patients. The signature showed good performances by calculating C‐index, area under the curve, and calibration curves. After verification and testing using an internal validation cohort, the results yielded a miRNA‐based signature and a prognostic nomogram with reliable predictive accuracy. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis indicated that various genes and multiple pathways were closely related to the mechanisms of HCC proliferation and metastasis. Conclusion We successfully identified a 13‐miRNA‐based signature and prognostic nomogram that are capable of predicting OS in patients with HCC.
Author Liu, Yufeng
Nie, Kechao
Yan, Yanhua
Jiang, Xiaotao
Liu, Fengbin
Chen, Xu
Li, Peiwu
Pan, Jinglin
Jiang, Kailin
Tang, Shuting
Liu, Peng
Zheng, Zhihua
Lan, Shaoyang
Wen, Yi
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  organization: Guangzhou University of Chinese Medicine
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  email: doctorlipw@gzucm.edu.cn, wenrenly2008@163.com
  organization: The first Affiliated Hospital of Guangzhou University of Chinese Medicine
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Copyright 2020 The Japan Society of Hepatology
2020 The Japan Society of Hepatology.
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Notes The authors have no conflict of interest.
Conflict of interest
Zhihua Zheng, Yi Wen, and Kecao Nie contributed equally to this work.
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Snippet Aim Hepatocellular carcinoma (HCC) is a common malignancy associated with a poor prognosis due to difficulties in reliably estimating overall survival (OS)....
AimHepatocellular carcinoma (HCC) is a common malignancy associated with a poor prognosis due to difficulties in reliably estimating overall survival (OS)....
Hepatocellular carcinoma (HCC) is a common malignancy associated with a poor prognosis due to difficulties in reliably estimating overall survival (OS)....
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SubjectTerms Genes
Genomes
Hepatocellular carcinoma
Liver cancer
Malignancy
Medical prognosis
Metastases
Metastasis
microRNA
MicroRNAs
miRNA
miRNA‐based risk signature
Ontology
overall survival
Prognosis
prognostic nomogram
Survival
Title Construction of a 13‐microRNA‐based signature and prognostic nomogram for predicting overall survival in patients with hepatocellular carcinoma
URI https://onlinelibrary.wiley.com/doi/abs/10.1111%2Fhepr.13538
https://www.proquest.com/docview/2451600663
https://www.proquest.com/docview/2415838071
Volume 50
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