Methodology article

Detection of the inferred interaction network in hepatocellular carcinoma from EHCO (Encyclopedia of Hepatocellular Carcinoma genes Online)

Chun-Nan Hsu^{* 1} , Jin-Mei Lai^{* 2} , Chia-Hung Liu^{* 1} , Huei-Hun Tseng^{* 3} , Chih-Yun Lin^{* 4} , Kuan-Ting Lin^{* 1} , Hsu-Hua Yeh³ , Ting-Yi Sung¹ , Wen-Lian Hsu¹ , Li-Jen Su⁴ , Sheng-An Lee^4,5 , Chang-Han Chen^3,4 , Gen-Cher Lee^1,5 , DT Lee^1,5 , Yow-Ling Shiue⁶ , Chang-Wei Yeh⁷ , Chao-Hui Chang⁴ , Cheng-Yan Kao⁵ and Chi-Ying F Huang^3,4,5,8,9

¹Institute of Information Science, Academia Sinica, Taipei 115, Taiwan, R. O. C

²Department of Life Science, Fu-Jen Catholic University, Taipei Hsien 242, Taiwan, R. O. C

³Division of Molecular and Genomic Medicine, National Health Research Institutes, Miaoli County 350, Taiwan, R. O. C

⁴Institute of Cancer Research, National Health Research Institutes, Taipei 114, Taiwan, R. O. C

⁵Department of Computer Science and Information Engineering, National Taiwan University, Taipei 106, Taiwan, R. O. C

⁶Institute of Biomedical Science, National Sun Yat-Sen University, Kaohsiung 804, Taiwan, R. O. C

⁷National Center for High-performance Computing, Hsinchu 300, Taiwan, R. O. C

⁸Institute of Bio-Pharmaceutical Sciences, National Yang-Ming University, Taipei 112, Taiwan, R. O. C

⁹Institute of Biotechnology in Medicine, National Yang-Ming University, Taipei 112, Taiwan, R. O. C

author email corresponding author email* Contributed equally

BMC Bioinformatics 2007, 8:66doi:10.1186/1471-2105-8-66

Published:	27 February 2007

Abstract

Background

The significant advances in microarray and proteomics analyses have resulted in an exponential increase in potential new targets and have promised to shed light on the identification of disease markers and cellular pathways. We aim to collect and decipher the HCC-related genes at the systems level.

Results

Here, we build an integrative platform, the Encyclopedia of Hepatocellular Carcinoma genes Online, dubbed EHCO http://ehco.iis.sinica.edu.tw webcite, to systematically collect, organize and compare the pileup of unsorted HCC-related studies by using natural language processing and softbots. Among the eight gene set collections, ranging across PubMed, SAGE, microarray, and proteomics data, there are 2,906 genes in total; however, more than 77% genes are only included once, suggesting that tremendous efforts need to be exerted to characterize the relationship between HCC and these genes. Of these HCC inventories, protein binding represents the largest proportion (~25%) from Gene Ontology analysis. In fact, many differentially expressed gene sets in EHCO could form interaction networks (e.g. HBV-associated HCC network) by using available human protein-protein interaction datasets. To further highlight the potential new targets in the inferred network from EHCO, we combine comparative genomics and interactomics approaches to analyze 120 evolutionary conserved and overexpressed genes in HCC. 47 out of 120 queries can form a highly interactive network with 18 queries serving as hubs.

Conclusion

This architectural map may represent the first step toward the attempt to decipher the hepatocarcinogenesis at the systems level. Targeting hubs and/or disruption of the network formation might reveal novel strategy for HCC treatment.