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Differentiating Hepatocellular Carcinoma from Hepatitis C Using Metabolite Profiling
Hepatocellular carcinoma (HCC) accounts for most liver cancer cases worldwide. Contraction of the hepatitis C virus (HCV) is considered a major risk factor for liver cancer. In order to identify the risk of cancer, metabolic profiling of serum samples from patients with HCC (n=40) and HCV (n=22) was...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3901236/ https://www.ncbi.nlm.nih.gov/pubmed/24957758 http://dx.doi.org/10.3390/metabo2040701 |
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author | Wei, Siwei Suryani, Yuliana Gowda, G. A. Nagana Skill, Nicholas Maluccio, Mary Raftery, Daniel |
author_facet | Wei, Siwei Suryani, Yuliana Gowda, G. A. Nagana Skill, Nicholas Maluccio, Mary Raftery, Daniel |
author_sort | Wei, Siwei |
collection | PubMed |
description | Hepatocellular carcinoma (HCC) accounts for most liver cancer cases worldwide. Contraction of the hepatitis C virus (HCV) is considered a major risk factor for liver cancer. In order to identify the risk of cancer, metabolic profiling of serum samples from patients with HCC (n=40) and HCV (n=22) was performed by (1)H nuclear magnetic resonance spectroscopy. Multivariate statistical analysis showed a distinct separation of the two patient cohorts, indicating a distinct metabolic difference between HCC and HCV patient groups based on signals from lipids and other individual metabolites. Univariate analysis showed that three metabolites (choline, valine and creatinine) were significantly altered in HCC. A PLS-DA model based on these three metabolites showed a sensitivity of 80%, specificity of 71% and an area under the receiver operating curve of 0.83, outperforming the clinical marker alpha-fetoprotein (AFP). The robustness of the model was tested using Monte-Carlo cross validation (MCCV). This study showed that metabolite profiling could provide an alternative approach for HCC screening in HCV patients, many of whom have high risk for developing liver cancer. |
format | Online Article Text |
id | pubmed-3901236 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-39012362014-05-27 Differentiating Hepatocellular Carcinoma from Hepatitis C Using Metabolite Profiling Wei, Siwei Suryani, Yuliana Gowda, G. A. Nagana Skill, Nicholas Maluccio, Mary Raftery, Daniel Metabolites Article Hepatocellular carcinoma (HCC) accounts for most liver cancer cases worldwide. Contraction of the hepatitis C virus (HCV) is considered a major risk factor for liver cancer. In order to identify the risk of cancer, metabolic profiling of serum samples from patients with HCC (n=40) and HCV (n=22) was performed by (1)H nuclear magnetic resonance spectroscopy. Multivariate statistical analysis showed a distinct separation of the two patient cohorts, indicating a distinct metabolic difference between HCC and HCV patient groups based on signals from lipids and other individual metabolites. Univariate analysis showed that three metabolites (choline, valine and creatinine) were significantly altered in HCC. A PLS-DA model based on these three metabolites showed a sensitivity of 80%, specificity of 71% and an area under the receiver operating curve of 0.83, outperforming the clinical marker alpha-fetoprotein (AFP). The robustness of the model was tested using Monte-Carlo cross validation (MCCV). This study showed that metabolite profiling could provide an alternative approach for HCC screening in HCV patients, many of whom have high risk for developing liver cancer. MDPI 2012-10-10 /pmc/articles/PMC3901236/ /pubmed/24957758 http://dx.doi.org/10.3390/metabo2040701 Text en © 2012 by the authors; licensee MDPI, Basel, Switzerland. http://creativecommons.org/licenses/by/3.0/ This article is an open-access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/). |
spellingShingle | Article Wei, Siwei Suryani, Yuliana Gowda, G. A. Nagana Skill, Nicholas Maluccio, Mary Raftery, Daniel Differentiating Hepatocellular Carcinoma from Hepatitis C Using Metabolite Profiling |
title | Differentiating Hepatocellular Carcinoma from Hepatitis C Using Metabolite Profiling |
title_full | Differentiating Hepatocellular Carcinoma from Hepatitis C Using Metabolite Profiling |
title_fullStr | Differentiating Hepatocellular Carcinoma from Hepatitis C Using Metabolite Profiling |
title_full_unstemmed | Differentiating Hepatocellular Carcinoma from Hepatitis C Using Metabolite Profiling |
title_short | Differentiating Hepatocellular Carcinoma from Hepatitis C Using Metabolite Profiling |
title_sort | differentiating hepatocellular carcinoma from hepatitis c using metabolite profiling |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3901236/ https://www.ncbi.nlm.nih.gov/pubmed/24957758 http://dx.doi.org/10.3390/metabo2040701 |
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