Hepatitis C virus network based classification of hepatocellular cirrhosis and carcinoma.

Hepatitis C virus (HCV) is a main risk factor for liver cirrhosis and hepatocellular carcinoma, particularly to those patients with chronic liver disease or injury. The similar etiology leads to a high correlation of the patients suffering from the disease of liver cirrhosis with those suffering fro...

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Autores principales:	Tao Huang, Junjie Wang, Yu-Dong Cai, Hanry Yu, Kuo-Chen Chou
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2012
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/2d4b36e67226429baab9d22efdbc1a0f
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spelling	oai:doaj.org-article:2d4b36e67226429baab9d22efdbc1a0f2021-11-18T07:23:02ZHepatitis C virus network based classification of hepatocellular cirrhosis and carcinoma.1932-620310.1371/journal.pone.0034460https://doaj.org/article/2d4b36e67226429baab9d22efdbc1a0f2012-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22493692/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203Hepatitis C virus (HCV) is a main risk factor for liver cirrhosis and hepatocellular carcinoma, particularly to those patients with chronic liver disease or injury. The similar etiology leads to a high correlation of the patients suffering from the disease of liver cirrhosis with those suffering from the disease of hepatocellular carcinoma. However, the biological mechanism for the relationship between these two kinds of diseases is not clear. The present study was initiated in an attempt to investigate into the HCV infection protein network, in hopes to find good biomarkers for diagnosing the two diseases as well as gain insights into their progression mechanisms. To realize this, two potential biomarker pools were defined: (i) the target genes of HCV, and (ii) the between genes on the shortest paths among the target genes of HCV. Meanwhile, a predictor was developed for identifying the liver tissue samples among the following three categories: (i) normal, (ii) cirrhosis, and (iii) hepatocellular carcinoma. Interestingly, it was observed that the identification accuracy was higher with the tissue samples defined by extracting the features from the second biomarker pool than that with the samples defined based on the first biomarker pool. The identification accuracy by the jackknife validation for the between-genes approach was 0.960, indicating that the novel approach holds a quite promising potential in helping find effective biomarkers for diagnosing the liver cirrhosis disease and the hepatocellular carcinoma disease. It may also provide useful insights for in-depth study of the biological mechanisms of HCV-induced cirrhosis and hepatocellular carcinoma.Tao HuangJunjie WangYu-Dong CaiHanry YuKuo-Chen ChouPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 7, Iss 4, p e34460 (2012)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Tao Huang Junjie Wang Yu-Dong Cai Hanry Yu Kuo-Chen Chou Hepatitis C virus network based classification of hepatocellular cirrhosis and carcinoma.
description	Hepatitis C virus (HCV) is a main risk factor for liver cirrhosis and hepatocellular carcinoma, particularly to those patients with chronic liver disease or injury. The similar etiology leads to a high correlation of the patients suffering from the disease of liver cirrhosis with those suffering from the disease of hepatocellular carcinoma. However, the biological mechanism for the relationship between these two kinds of diseases is not clear. The present study was initiated in an attempt to investigate into the HCV infection protein network, in hopes to find good biomarkers for diagnosing the two diseases as well as gain insights into their progression mechanisms. To realize this, two potential biomarker pools were defined: (i) the target genes of HCV, and (ii) the between genes on the shortest paths among the target genes of HCV. Meanwhile, a predictor was developed for identifying the liver tissue samples among the following three categories: (i) normal, (ii) cirrhosis, and (iii) hepatocellular carcinoma. Interestingly, it was observed that the identification accuracy was higher with the tissue samples defined by extracting the features from the second biomarker pool than that with the samples defined based on the first biomarker pool. The identification accuracy by the jackknife validation for the between-genes approach was 0.960, indicating that the novel approach holds a quite promising potential in helping find effective biomarkers for diagnosing the liver cirrhosis disease and the hepatocellular carcinoma disease. It may also provide useful insights for in-depth study of the biological mechanisms of HCV-induced cirrhosis and hepatocellular carcinoma.
format	article
author	Tao Huang Junjie Wang Yu-Dong Cai Hanry Yu Kuo-Chen Chou
author_facet	Tao Huang Junjie Wang Yu-Dong Cai Hanry Yu Kuo-Chen Chou
author_sort	Tao Huang
title	Hepatitis C virus network based classification of hepatocellular cirrhosis and carcinoma.
title_short	Hepatitis C virus network based classification of hepatocellular cirrhosis and carcinoma.
title_full	Hepatitis C virus network based classification of hepatocellular cirrhosis and carcinoma.
title_fullStr	Hepatitis C virus network based classification of hepatocellular cirrhosis and carcinoma.
title_full_unstemmed	Hepatitis C virus network based classification of hepatocellular cirrhosis and carcinoma.
title_sort	hepatitis c virus network based classification of hepatocellular cirrhosis and carcinoma.
publisher	Public Library of Science (PLoS)
publishDate	2012
url	https://doaj.org/article/2d4b36e67226429baab9d22efdbc1a0f
work_keys_str_mv	AT taohuang hepatitiscvirusnetworkbasedclassificationofhepatocellularcirrhosisandcarcinoma AT junjiewang hepatitiscvirusnetworkbasedclassificationofhepatocellularcirrhosisandcarcinoma AT yudongcai hepatitiscvirusnetworkbasedclassificationofhepatocellularcirrhosisandcarcinoma AT hanryyu hepatitiscvirusnetworkbasedclassificationofhepatocellularcirrhosisandcarcinoma AT kuochenchou hepatitiscvirusnetworkbasedclassificationofhepatocellularcirrhosisandcarcinoma
_version_	1718423525193154560

Hepatitis C virus network based classification of hepatocellular cirrhosis and carcinoma.

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