Microarray-based analysis for hepatocellular carcinoma: From gene expression profiling to new challenges
Accumulation of mutations and alterations in the expression of various genes .result in carcinogenesis, and the development of microarray technology has enabled us to identify the comprehensive gene expression alterations in oncogenesis. Many studies have applied this technology for hepatocellular c...
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| Published in | World Journal of Gastroenterology Vol. 13; no. 10; pp. 1487 - 1492 |
|---|---|
| Main Author | |
| Format | Journal Article |
| Language | English |
| Published |
United States
Baishideng Publishing Group Inc
14.03.2007
Genome Science Division, Research Center for Advanced Science and Technology,The University of Tokyo, Toky HepatoBiliary-Pancreatic Surgery Division, Department of Surgery, The University of Tokyo, Tokyo 113-8655, Japan Genome Science Division, Research Center for Advanced Science and Technology,The University of Tokyo, Tokyo 153-8904, Japan%HepatoBiliary-Pancreatic Surgery Division, Department of Surgery, The University of Tokyo, Tokyo 113-8655, Japan%Genome Science Division, Research Center for Advanced Science and Technology,The University of Tokyo, Toky 153-8904,Japan Baishideng Publishing Group Co., Limited |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1007-9327 2219-2840 |
| DOI | 10.3748/wjg.v13.i10.1487 |
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| Abstract | Accumulation of mutations and alterations in the expression of various genes .result in carcinogenesis, and the development of microarray technology has enabled us to identify the comprehensive gene expression alterations in oncogenesis. Many studies have applied this technology for hepatocellular carcinoma (HCC), and identified a number of candidate genes useful as biomarkers in cancer staging, prediction of recurrence and prognosis, and treatment selection. Some of these target molecules have been used to develop new serum diagnostic markers and therapeutic targets against HCC to benefit patients. Previously, we compared gene expression profiling data with classification based on clinicopathological features, such as hepatitis viral infection or liver cancer .progression. The next era of gene expression analysis will require systematic integration of expression profiles with other types of biological information, such as genomic locus, gene function, and sequence information. We have reported integration between expression profiles and locus information, which is effective in detecting structural genomic abnormalities, such as chromosomal gains and losses, in which we showed that gene expression profiles are subject to chromosomal bias. Furthermore, arraybased comparative genomic hybridization analysis and allelic dosage analysis using genotyping arrays for HCC were also reviewed, with comparison of conventional methods. |
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| AbstractList | R73; Accumulation of mutations and alterations in the expression of various genes result in carcinogenesis, and the development of microarray technology has enabled us to identify the comprehensive gene expression alterations in oncogenesis. Many studies have applied this technology for hepatocellular carcinoma (HCC), and identified a number of candidate genes useful as biomarkers in cancer staging, prediction of recurrence and prognosis, and treatment selection. Some of these target molecules have been used to develop new serum diagnostic markers and therapeutic targets against HCC to benefit patients. Previously, we compared gene expression profiling data with classification based on clinicopathological features, such as hepatitis viral infection or liver cancer progression. The next era of gene expression analysis will require systematic integration of expression profiles with other types of biological information, such as genomic locus, gene function, and sequence information. We have reported integration between expression profiles and locus information, which is effective in detecting structural genomic abnormalities, such as chromosomal gains and losses, in which we showed that gene expression profiles are subject to chromosomal bias. Furthermore, array-based comparative genomic hybridization analysis and allelic dosage analysis using genotyping arrays for HCC were also reviewed, with comparison of conventional methods. Accumulation of mutations and alterations in the expression of various genes result in carcinogenesis, and the development of microarray technology has enabled us to identify the comprehensive gene expression alterations in oncogenesis. Many studies have applied this technology for hepatocellular carcinoma (HCC), and identified a number of candidate genes useful as biomarkers in cancer staging, prediction of recurrence and prognosis, and treatment selection. Some of these target molecules have been used to develop new serum diagnostic markers and therapeutic targets against HCC to benefit patients. Previously, we compared gene expression profiling data with classification based on clinicopathological features, such as hepatitis viral infection or liver cancer progression. The next era of gene expression analysis will require systematic integration of expression profiles with other types of biological information, such as genomic locus, gene function, and sequence information. We have reported integration between expression profiles and locus information, which is effective in detecting structural genomic abnormalities, such as chromosomal gains and losses, in which we showed that gene expression profiles are subject to chromosomal bias. Furthermore, array-based comparative genomic hybridization analysis and allelic dosage analysis using genotyping arrays for HCC were also reviewed, with comparison of conventional methods. Accumulation of mutations and alterations in the expression of various genes .result in carcinogenesis, and the development of microarray technology has enabled us to identify the comprehensive gene expression alterations in oncogenesis. Many studies have applied this technology for hepatocellular carcinoma (HCC), and identified a number of candidate genes useful as biomarkers in cancer staging, prediction of recurrence and prognosis, and treatment selection. Some of these target molecules have been used to develop new serum diagnostic markers and therapeutic targets against HCC to benefit patients. Previously, we compared gene expression profiling data with classification based on clinicopathological features, such as hepatitis viral infection or liver cancer .progression. The next era of gene expression analysis will require systematic integration of expression profiles with other types of biological information, such as genomic locus, gene function, and sequence information. We have reported integration between expression profiles and locus information, which is effective in detecting structural genomic abnormalities, such as chromosomal gains and losses, in which we showed that gene expression profiles are subject to chromosomal bias. Furthermore, arraybased comparative genomic hybridization analysis and allelic dosage analysis using genotyping arrays for HCC were also reviewed, with comparison of conventional methods. Accumulation of mutations and alterations in the expression of various genes result in carcinogenesis, and the development of microarray technology has enabled us to identify the comprehensive gene expression alterations in oncogenesis. Many studies have applied this technology for hepatocellular carcinoma (HCC), and identified a number of candidate genes useful as biomarkers in cancer staging, prediction of recurrence and prognosis, and treatment selection. Some of these target molecules have been used to develop new serum diagnostic markers and therapeutic targets against HCC to benefit patients. Previously, we compared gene expression profiling data with classification based on clinicopathological features, such as hepatitis viral infection or liver cancer progression. The next era of gene expression analysis will require systematic integration of expression profiles with other types of biological information, such as genomic locus, gene function, and sequence information. We have reported integration between expression profiles and locus information, which is effective in detecting structural genomic abnormalities, such as chromosomal gains and losses, in which we showed that gene expression profiles are subject to chromosomal bias. Furthermore, array-based comparative genomic hybridization analysis and allelic dosage analysis using genotyping arrays for HCC were also reviewed, with comparison of conventional methods.Accumulation of mutations and alterations in the expression of various genes result in carcinogenesis, and the development of microarray technology has enabled us to identify the comprehensive gene expression alterations in oncogenesis. Many studies have applied this technology for hepatocellular carcinoma (HCC), and identified a number of candidate genes useful as biomarkers in cancer staging, prediction of recurrence and prognosis, and treatment selection. Some of these target molecules have been used to develop new serum diagnostic markers and therapeutic targets against HCC to benefit patients. Previously, we compared gene expression profiling data with classification based on clinicopathological features, such as hepatitis viral infection or liver cancer progression. The next era of gene expression analysis will require systematic integration of expression profiles with other types of biological information, such as genomic locus, gene function, and sequence information. We have reported integration between expression profiles and locus information, which is effective in detecting structural genomic abnormalities, such as chromosomal gains and losses, in which we showed that gene expression profiles are subject to chromosomal bias. Furthermore, array-based comparative genomic hybridization analysis and allelic dosage analysis using genotyping arrays for HCC were also reviewed, with comparison of conventional methods. |
| Author | Yutaka Midorikawa Masatoshi Makuuchi Wei Tang Hiroyuki Aburatani |
| AuthorAffiliation | Hepato- Biliary-Pancreatic Surgery Division, Department of Surgery, The University of Tokyo, Tokyo 113-8655, Japan Yutaka Midorikawa, Genome Science Division, Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo 153-8904, Japan |
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| Copyright | Copyright © Wanfang Data Co. Ltd. All Rights Reserved. 2007 Baishideng Publishing Group Co., Limited. All rights reserved. 2007 |
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| Notes | Liver cancer IVlicroarray Liver cancer; IVlicroarray R735.7 14-1219/R ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 ObjectType-Review-3 content type line 23 Correspondence to: Yutaka Midorikawa, Hepato-Biliary-Pancreatic Surgery Division, Department of Surgery, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan. mido-tky@umin.ac.jp Author contributions: All authors contributed equally to the work. Telephone: +81-3-3815-5411 Fax: +81-3-5684-3989 |
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| SubjectTerms | Carcinoma, Hepatocellular Carcinoma, Hepatocellular - genetics DNA, Neoplasm DNA, Neoplasm - genetics Gene Expression Regulation, Neoplastic Genetic Therapy Humans Karyotyping Karyotyping - methods Liver Neoplasms Liver Neoplasms - genetics Multigene Family Multigene Family - genetics Oligonucleotide Array Sequence Analysis Oligonucleotide Array Sequence Analysis - methods Oligonucleotide Array Sequence Analysis - trends Polymorphism, Single Nucleotide Polymorphism, Single Nucleotide - genetics Topic Highlight 基因表达 微阵列分析 病理特征 聚类分析 肝细胞癌 |
| Title | Microarray-based analysis for hepatocellular carcinoma: From gene expression profiling to new challenges |
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