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Construction and Validation of Novel Diagnostic and Prognostic DNA Methylation Signatures for Hepatocellular Carcinoma
Hepatocellular carcinoma (HCC) is one of the most prevalent life-threatening human cancers and the leading cause of cancer-related mortality, with increased global incidence within the last decade. Identification of effective diagnostic and prognostic biomarkers would enable reliable risk stratifica...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7456968/ https://www.ncbi.nlm.nih.gov/pubmed/32922438 http://dx.doi.org/10.3389/fgene.2020.00906 |
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author | Li, Ran Shui, Liyan Jia, Junling Wu, Chao |
author_facet | Li, Ran Shui, Liyan Jia, Junling Wu, Chao |
author_sort | Li, Ran |
collection | PubMed |
description | Hepatocellular carcinoma (HCC) is one of the most prevalent life-threatening human cancers and the leading cause of cancer-related mortality, with increased global incidence within the last decade. Identification of effective diagnostic and prognostic biomarkers would enable reliable risk stratification and efficient screening of high-risk patients, thereby facilitating clinical decision-making. Herein, we performed a comprehensive, robust DNA methylation analysis based on genome-wide DNA methylation profiling. We constructed a diagnostic signature with five DNA methylation markers, which precisely distinguished HCC patients from normal controls. Cox regression and LASSO analysis were applied to construct a prognostic signature with four DNA methylation markers. A one-to-one correlation analysis was carried out between genes of the whole genome and our prognostic signature. Exploration of the biological function and the role of the underlying significantly correlated genes was conducted. A mixed dataset of 463 HCC patients and 253 normal controls, derived from six independent datasets, was used to valid the diagnostic signature. Results showed a specificity of 96.84% and sensitivity of 96.77%. Class scores for the diagnostic signature were significantly different between normal controls, individuals with liver diseases, and HCC patients. The present signature has the potential to serve as a biomarker to monitor health in normal controls. Additionally, HCC patients were successfully separated into low-risk and high-risk groups by the prognostic signature, with a better prognosis for patients in the low-risk group. Kaplan-Meier and ROC analysis confirmed that the prognostic signature performed well. We found eight of the top ten genes to positively correlate with risk scores of the prognostic signature, and to be involved in cell cycle regulation. This eight-gene panel also served as a prognostic signature. The robust evidence presented in this study therefore demonstrates the effectiveness of the prognostic signature. In summary, we constructed diagnostic and prognostic signatures, which have potential for use in diagnosis, surveillance, and prognostic prediction for HCC patients. Eight genes that were significantly and positively correlated with the prognostic signature were strongly associated with cell cycle processes. Therefore, the prognostic signature can be used as a guide by which to measure responsiveness to cell-cycle-targeting agents. |
format | Online Article Text |
id | pubmed-7456968 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-74569682020-09-11 Construction and Validation of Novel Diagnostic and Prognostic DNA Methylation Signatures for Hepatocellular Carcinoma Li, Ran Shui, Liyan Jia, Junling Wu, Chao Front Genet Genetics Hepatocellular carcinoma (HCC) is one of the most prevalent life-threatening human cancers and the leading cause of cancer-related mortality, with increased global incidence within the last decade. Identification of effective diagnostic and prognostic biomarkers would enable reliable risk stratification and efficient screening of high-risk patients, thereby facilitating clinical decision-making. Herein, we performed a comprehensive, robust DNA methylation analysis based on genome-wide DNA methylation profiling. We constructed a diagnostic signature with five DNA methylation markers, which precisely distinguished HCC patients from normal controls. Cox regression and LASSO analysis were applied to construct a prognostic signature with four DNA methylation markers. A one-to-one correlation analysis was carried out between genes of the whole genome and our prognostic signature. Exploration of the biological function and the role of the underlying significantly correlated genes was conducted. A mixed dataset of 463 HCC patients and 253 normal controls, derived from six independent datasets, was used to valid the diagnostic signature. Results showed a specificity of 96.84% and sensitivity of 96.77%. Class scores for the diagnostic signature were significantly different between normal controls, individuals with liver diseases, and HCC patients. The present signature has the potential to serve as a biomarker to monitor health in normal controls. Additionally, HCC patients were successfully separated into low-risk and high-risk groups by the prognostic signature, with a better prognosis for patients in the low-risk group. Kaplan-Meier and ROC analysis confirmed that the prognostic signature performed well. We found eight of the top ten genes to positively correlate with risk scores of the prognostic signature, and to be involved in cell cycle regulation. This eight-gene panel also served as a prognostic signature. The robust evidence presented in this study therefore demonstrates the effectiveness of the prognostic signature. In summary, we constructed diagnostic and prognostic signatures, which have potential for use in diagnosis, surveillance, and prognostic prediction for HCC patients. Eight genes that were significantly and positively correlated with the prognostic signature were strongly associated with cell cycle processes. Therefore, the prognostic signature can be used as a guide by which to measure responsiveness to cell-cycle-targeting agents. Frontiers Media S.A. 2020-08-13 /pmc/articles/PMC7456968/ /pubmed/32922438 http://dx.doi.org/10.3389/fgene.2020.00906 Text en Copyright © 2020 Li, Shui, Jia and Wu. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Li, Ran Shui, Liyan Jia, Junling Wu, Chao Construction and Validation of Novel Diagnostic and Prognostic DNA Methylation Signatures for Hepatocellular Carcinoma |
title | Construction and Validation of Novel Diagnostic and Prognostic DNA Methylation Signatures for Hepatocellular Carcinoma |
title_full | Construction and Validation of Novel Diagnostic and Prognostic DNA Methylation Signatures for Hepatocellular Carcinoma |
title_fullStr | Construction and Validation of Novel Diagnostic and Prognostic DNA Methylation Signatures for Hepatocellular Carcinoma |
title_full_unstemmed | Construction and Validation of Novel Diagnostic and Prognostic DNA Methylation Signatures for Hepatocellular Carcinoma |
title_short | Construction and Validation of Novel Diagnostic and Prognostic DNA Methylation Signatures for Hepatocellular Carcinoma |
title_sort | construction and validation of novel diagnostic and prognostic dna methylation signatures for hepatocellular carcinoma |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7456968/ https://www.ncbi.nlm.nih.gov/pubmed/32922438 http://dx.doi.org/10.3389/fgene.2020.00906 |
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