Cargando…
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...
Autores principales: | , |
---|---|
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 |
_version_ | 1783426669635174400 |
---|---|
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. |
format | Online Article Text |
id | pubmed-6565558 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT wangsufang transcriptomeanalysisidentifiesmetallothioneinasbiomarkerstopredictrecurrenceinhepatocellularcacinoma AT gribskovmichael transcriptomeanalysisidentifiesmetallothioneinasbiomarkerstopredictrecurrenceinhepatocellularcacinoma |