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Transcriptome analysis identifies metallothionein as biomarkers to predict recurrence in hepatocellular cacinoma

BACKGROUND: Liver cancer is the fifth most common cancer, and hepatocellular carcinoma (HCC) is the major liver tumor type seen in adults. HCC is usually caused by chronic liver disease such as hepatitis B virus or hepatitis C virus infection. One of the promising treatments for HCC is liver transpl...

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Autores principales: Wang, Sufang, Gribskov, Michael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6565558/
https://www.ncbi.nlm.nih.gov/pubmed/31056863
http://dx.doi.org/10.1002/mgg3.693
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author Wang, Sufang
Gribskov, Michael
author_facet Wang, Sufang
Gribskov, Michael
author_sort Wang, Sufang
collection PubMed
description BACKGROUND: Liver cancer is the fifth most common cancer, and hepatocellular carcinoma (HCC) is the major liver tumor type seen in adults. HCC is usually caused by chronic liver disease such as hepatitis B virus or hepatitis C virus infection. One of the promising treatments for HCC is liver transplantation, in which a diseased liver is replaced with a healthy liver from another person. However, recurrence of HCC after surgery is a significant problem. Therefore, it is important to discover reliable cellular biomarkers that can predict recurrence in HCC. METHODS: We analyzed previously published HCC RNA‐Seq data that includes 21 paired tumor and normal samples, in which nine tumors were recurrent after orthotopic liver transplantation and 12 were nonrecurrent tumors with their paired normal samples. We used both the reference genome and de novo transcriptome assembly based analyses to identify differentially expressed genes (DEG) and used RandomForest to discover biomarkers. RESULTS: We obtained 398 DEG using the Reference approach and 412 DEG using de novo assembly approach. Among these DEG, 258 genes were identified by both approaches. We further identified 30 biomarkers that could predict the recurrence. We used another independent HCC study that includes 50 patients normal and tumor samples. By using these 30 biomarkers, the prediction accuracy was 100% for normal condition and 98% for tumor condition. A group of Metallothionein was specifically discovered as biomarkers in both reference and de novo assembly approaches. CONCLUSION: We identified a group of Metallothionein genes as biomarkers to predict recurrence. The metallothionein genes were all down‐regulated in tumor samples, suggesting that low metallothionein expression may be a promoter of tumor growth. In addition, using de novo assembly identified some unique biomarkers, further confirmed the necessity of conducting a de novo assembly in human cancer study.
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spelling pubmed-65655582019-06-20 Transcriptome analysis identifies metallothionein as biomarkers to predict recurrence in hepatocellular cacinoma Wang, Sufang Gribskov, Michael Mol Genet Genomic Med Original Articles BACKGROUND: Liver cancer is the fifth most common cancer, and hepatocellular carcinoma (HCC) is the major liver tumor type seen in adults. HCC is usually caused by chronic liver disease such as hepatitis B virus or hepatitis C virus infection. One of the promising treatments for HCC is liver transplantation, in which a diseased liver is replaced with a healthy liver from another person. However, recurrence of HCC after surgery is a significant problem. Therefore, it is important to discover reliable cellular biomarkers that can predict recurrence in HCC. METHODS: We analyzed previously published HCC RNA‐Seq data that includes 21 paired tumor and normal samples, in which nine tumors were recurrent after orthotopic liver transplantation and 12 were nonrecurrent tumors with their paired normal samples. We used both the reference genome and de novo transcriptome assembly based analyses to identify differentially expressed genes (DEG) and used RandomForest to discover biomarkers. RESULTS: We obtained 398 DEG using the Reference approach and 412 DEG using de novo assembly approach. Among these DEG, 258 genes were identified by both approaches. We further identified 30 biomarkers that could predict the recurrence. We used another independent HCC study that includes 50 patients normal and tumor samples. By using these 30 biomarkers, the prediction accuracy was 100% for normal condition and 98% for tumor condition. A group of Metallothionein was specifically discovered as biomarkers in both reference and de novo assembly approaches. CONCLUSION: We identified a group of Metallothionein genes as biomarkers to predict recurrence. The metallothionein genes were all down‐regulated in tumor samples, suggesting that low metallothionein expression may be a promoter of tumor growth. In addition, using de novo assembly identified some unique biomarkers, further confirmed the necessity of conducting a de novo assembly in human cancer study. John Wiley and Sons Inc. 2019-05-06 /pmc/articles/PMC6565558/ /pubmed/31056863 http://dx.doi.org/10.1002/mgg3.693 Text en © 2019 The Authors. Molecular Genetics & Genomic Medicine published by Wiley Periodicals, Inc. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Articles
Wang, Sufang
Gribskov, Michael
Transcriptome analysis identifies metallothionein as biomarkers to predict recurrence in hepatocellular cacinoma
title Transcriptome analysis identifies metallothionein as biomarkers to predict recurrence in hepatocellular cacinoma
title_full Transcriptome analysis identifies metallothionein as biomarkers to predict recurrence in hepatocellular cacinoma
title_fullStr Transcriptome analysis identifies metallothionein as biomarkers to predict recurrence in hepatocellular cacinoma
title_full_unstemmed Transcriptome analysis identifies metallothionein as biomarkers to predict recurrence in hepatocellular cacinoma
title_short Transcriptome analysis identifies metallothionein as biomarkers to predict recurrence in hepatocellular cacinoma
title_sort transcriptome analysis identifies metallothionein as biomarkers to predict recurrence in hepatocellular cacinoma
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6565558/
https://www.ncbi.nlm.nih.gov/pubmed/31056863
http://dx.doi.org/10.1002/mgg3.693
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