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Microarray-based identification of genes associated with cancer progression and prognosis in hepatocellular carcinoma

BACKGROUND: Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related deaths. The average survival and 5-year survival rates of HCC patients still remains poor. Thus, there is an urgent need to better understand the mechanisms of cancer progression in HCC and to identify useful bio...

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Autores principales: Yin, Fuqiang, Shu, Lipei, Liu, Xia, Li, Ting, Peng, Tao, Nan, Yueli, Li, Shu, Zeng, Xiaoyun, Qiu, Xiaoqiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5002170/
https://www.ncbi.nlm.nih.gov/pubmed/27567667
http://dx.doi.org/10.1186/s13046-016-0403-2
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author Yin, Fuqiang
Shu, Lipei
Liu, Xia
Li, Ting
Peng, Tao
Nan, Yueli
Li, Shu
Zeng, Xiaoyun
Qiu, Xiaoqiang
author_facet Yin, Fuqiang
Shu, Lipei
Liu, Xia
Li, Ting
Peng, Tao
Nan, Yueli
Li, Shu
Zeng, Xiaoyun
Qiu, Xiaoqiang
author_sort Yin, Fuqiang
collection PubMed
description BACKGROUND: Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related deaths. The average survival and 5-year survival rates of HCC patients still remains poor. Thus, there is an urgent need to better understand the mechanisms of cancer progression in HCC and to identify useful biomarkers to predict prognosis. METHODS: Public data portals including Oncomine, The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) profiles were used to retrieve the HCC-related microarrays and to identify potential genes contributed to cancer progression. Bioinformatics analyses including pathway enrichment, protein/gene interaction and text mining were used to explain the potential roles of the identified genes in HCC. Quantitative real-time polymerase chain reaction analysis and Western blotting were used to measure the expression of the targets. The data were analysed by SPSS 20.0 software. RESULTS: We identified 80 genes that were significantly dysregulated in HCC according to four independent microarrays covering 386 cases of HCC and 327 normal liver tissues. Twenty genes were consistently and stably dysregulated in the four microarrays by at least 2-fold and detection of gene expression by RT-qPCR and western blotting showed consistent expression profiles in 11 HCC tissues compared with corresponding paracancerous tissues. Eleven of these 20 genes were associated with disease-free survival (DFS) or overall survival (OS) in a cohort of 157 HCC patients, and eight genes were associated with tumour pathologic PT, tumour stage or vital status. Potential roles of those 20 genes in regulation of HCC progression were predicted, primarily in association with metastasis. INTS8 was specifically correlated with most clinical characteristics including DFS, OS, stage, metastasis, invasiveness, diagnosis, and age. CONCLUSION: The significantly dysregulated genes identified in this study were associated with cancer progression and prognosis in HCC, and might be potential therapeutic targets for HCC treatment or potential biomarkers for diagnosis and prognosis. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13046-016-0403-2) contains supplementary material, which is available to authorized users.
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spelling pubmed-50021702016-08-28 Microarray-based identification of genes associated with cancer progression and prognosis in hepatocellular carcinoma Yin, Fuqiang Shu, Lipei Liu, Xia Li, Ting Peng, Tao Nan, Yueli Li, Shu Zeng, Xiaoyun Qiu, Xiaoqiang J Exp Clin Cancer Res Research BACKGROUND: Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related deaths. The average survival and 5-year survival rates of HCC patients still remains poor. Thus, there is an urgent need to better understand the mechanisms of cancer progression in HCC and to identify useful biomarkers to predict prognosis. METHODS: Public data portals including Oncomine, The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) profiles were used to retrieve the HCC-related microarrays and to identify potential genes contributed to cancer progression. Bioinformatics analyses including pathway enrichment, protein/gene interaction and text mining were used to explain the potential roles of the identified genes in HCC. Quantitative real-time polymerase chain reaction analysis and Western blotting were used to measure the expression of the targets. The data were analysed by SPSS 20.0 software. RESULTS: We identified 80 genes that were significantly dysregulated in HCC according to four independent microarrays covering 386 cases of HCC and 327 normal liver tissues. Twenty genes were consistently and stably dysregulated in the four microarrays by at least 2-fold and detection of gene expression by RT-qPCR and western blotting showed consistent expression profiles in 11 HCC tissues compared with corresponding paracancerous tissues. Eleven of these 20 genes were associated with disease-free survival (DFS) or overall survival (OS) in a cohort of 157 HCC patients, and eight genes were associated with tumour pathologic PT, tumour stage or vital status. Potential roles of those 20 genes in regulation of HCC progression were predicted, primarily in association with metastasis. INTS8 was specifically correlated with most clinical characteristics including DFS, OS, stage, metastasis, invasiveness, diagnosis, and age. CONCLUSION: The significantly dysregulated genes identified in this study were associated with cancer progression and prognosis in HCC, and might be potential therapeutic targets for HCC treatment or potential biomarkers for diagnosis and prognosis. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13046-016-0403-2) contains supplementary material, which is available to authorized users. BioMed Central 2016-08-27 /pmc/articles/PMC5002170/ /pubmed/27567667 http://dx.doi.org/10.1186/s13046-016-0403-2 Text en © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Yin, Fuqiang
Shu, Lipei
Liu, Xia
Li, Ting
Peng, Tao
Nan, Yueli
Li, Shu
Zeng, Xiaoyun
Qiu, Xiaoqiang
Microarray-based identification of genes associated with cancer progression and prognosis in hepatocellular carcinoma
title Microarray-based identification of genes associated with cancer progression and prognosis in hepatocellular carcinoma
title_full Microarray-based identification of genes associated with cancer progression and prognosis in hepatocellular carcinoma
title_fullStr Microarray-based identification of genes associated with cancer progression and prognosis in hepatocellular carcinoma
title_full_unstemmed Microarray-based identification of genes associated with cancer progression and prognosis in hepatocellular carcinoma
title_short Microarray-based identification of genes associated with cancer progression and prognosis in hepatocellular carcinoma
title_sort microarray-based identification of genes associated with cancer progression and prognosis in hepatocellular carcinoma
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5002170/
https://www.ncbi.nlm.nih.gov/pubmed/27567667
http://dx.doi.org/10.1186/s13046-016-0403-2
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