Cancer Research AACR Legacy  Jordan
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Cancer Research Clinical Cancer Research
Cancer Epidemiology Biomarkers & Prevention Molecular Cancer Therapeutics
Molecular Cancer Research Cancer Prevention Research
Cancer Prevention Journals Portal Cancer Reviews Online
Annual Meeting Education Book Meeting Abstracts Online

This Article
Right arrow Full Text
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Midorikawa, Y.
Right arrow Articles by Aburatani, H.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Midorikawa, Y.
Right arrow Articles by Aburatani, H.
[Cancer Research 64, 7263-7270, October 15, 2004]
© 2004 American Association for Cancer Research


Regular Articles

Distinct Chromosomal Bias of Gene Expression Signatures in the Progression of Hepatocellular Carcinoma

Yutaka Midorikawa1,3, Shuichi Tsutsumi1, Kunihiro Nishimura2, Naoko Kamimura1, Makoto Kano2, Hirohiko Sakamoto4, Masatoshi Makuuchi3 and Hiroyuki Aburatani1

1 Genome Science Division, 2 Intelligent Cooperative Systems Division, Research Center for Advanced Science and Technology, and 3 Hepato-Biliary-Pancreatic Surgery Division, The University of Tokyo, Tokyo; and 4 Department of Surgery, Saitama Cancer Center, Saitama, Japan

To identify the chromosomal aberrations associated with the progression of liver cancer, we applied expression imbalance map analysis to gene expression data from 31 hepatocellular carcinomas and 19 noncancerous tissues. Expression imbalance map analysis, which detects mRNA expression imbalance correlated with chromosomal regions, showed that expression gains of 1q21-23 (74%), 8q13-21 (48%), 12q23-24 (41%), 17q12-21(48%), 17q25 (25%), and 20q11 (22%) and losses of 4q13 (48%), 8p12-21 (32%), 13q14 (32%), and 17p13 (29%) were significantly associated with hepatocellular carcinoma. Most regions with altered expression identified by expression imbalance map were also identified in previous reports using comparative genomic hybridization. We demonstrated chromosomal copy number gain in 1q21-23 and loss in 17p13 by genomic quantitative PCR, suggesting that gene expression profiles reflect chromosomal alterations. Furthermore, expression imbalance map analysis revealed that more poorly differentiated hepatocellular carcinoma contain more chromosomal alterations, which are accumulated in a stepwise manner in the course of hepatocellular carcinoma progression: expression imbalance of 1q, 8p, 8q, and 17p occur as early events in hepatocarcinogenesis, and 12q, 17q25 and 20q occur as later events. In particular, expression gain of 17q12-21 and loss of 4q were seen to accumulate constantly through the dedifferentiation process. Our data suggest that gene expression profiles are subject to chromosomal bias and that expression imbalance map can correlate gene expression to gene loci with high resolution and sensitivity.




This article has been cited by other articles:


Home page
Cancer Res.Home page
Y. Hoshida, S. M.B. Nijman, M. Kobayashi, J. A. Chan, J.-P. Brunet, D. Y. Chiang, A. Villanueva, P. Newell, K. Ikeda, M. Hashimoto, et al.
Integrative Transcriptome Analysis Reveals Common Molecular Subclasses of Human Hepatocellular Carcinoma
Cancer Res., September 15, 2009; 69(18): 7385 - 7392.
[Abstract] [Full Text] [PDF]


Home page
Cancer Res.Home page
E. A. Maher, C. Brennan, P. Y. Wen, L. Durso, K. L. Ligon, A. Richardson, D. Khatry, B. Feng, R. Sinha, D. N. Louis, et al.
Marked Genomic Differences Characterize Primary and Secondary Glioblastoma Subtypes and Identify Two Distinct Molecular and Clinical Secondary Glioblastoma Entities
Cancer Res., December 1, 2006; 66(23): 11502 - 11513.
[Abstract] [Full Text] [PDF]


Home page
BioinformaticsHome page
A. Callegaro, D. Basso, and S. Bicciato
A locally adaptive statistical procedure (LAP) to identify differentially expressed chromosomal regions
Bioinformatics, November 1, 2006; 22(21): 2658 - 2666.
[Abstract] [Full Text] [PDF]




HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Cancer Research Clinical Cancer Research
Cancer Epidemiology Biomarkers & Prevention Molecular Cancer Therapeutics
Molecular Cancer Research Cancer Prevention Research
Cancer Prevention Journals Portal Cancer Reviews Online
Annual Meeting Education Book Meeting Abstracts Online
Copyright © 2004 by the American Association for Cancer Research.