1. ¹Department of Biopharmaceutical Sciences, University of California, San Francisco, CA 94143, USA
2. ²Department of Surgery and Asian Liver Center, Stanford University, Stanford, CA 94305, USA
3. ³Department of Genetics, Stanford University, Stanford, CA 94305, USA
4. ⁴Department of Surgery and Center for the Study of Liver Disease, University of Hong Kong, Hong Kong, China
5. ⁵Liver Center, University of California, San Francisco, CA 94143, USA

Correspondence: Professor Samuel So, Department of Surgery and the Asian Liver Center, 300 Pasteur Drive, H3680, Stanford University, Stanford, CA 94305, USA. E-mail: [email protected]

X Chen, Department of Biopharmaceutical Sciences, 513 Parnassus Avenue, University of California, San Francisco, CA 94143-0446, USA. E-mail: [email protected]

⁶These authors contributed equally to this work and are listed in random order

Received 22 October 2004; Revised 14 December 2004; Accepted 27 December 2004; Published online 21 February 2005.

Abstract

Hepatocellular carcinoma (HCC) is one of the major causes of cancer deaths worldwide. New diagnostic and therapeutic options are needed for more effective and early detection and treatment of this malignancy. We identified 703 genes that are highly expressed in HCC using DNA microarrays, and further characterized them in order to uncover novel tumor markers, oncogenes, and therapeutic targets for HCC. Using Gene Ontology annotations, genes with functions related to cell proliferation and cell cycle, chromatin, repair, and transcription were found to be significantly enriched in this list of highly expressed genes. We also identified a set of genes that encode secreted (e.g. GPC3, LCN2, and DKK1) or membrane-bound proteins (e.g. GPC3, IGSF1, and PSK-1), which may be attractive candidates for the diagnosis of HCC. A significant enrichment of genes highly expressed in HCC was found on chromosomes 1q, 6p, 8q, and 20q, and we also identified chromosomal clusters of genes highly expressed in HCC. The microarray analyses were validated by RT−PCR and PCR. This approach of integrating other biological information with gene expression in the analysis helps select aberrantly expressed genes in HCC that may be further studied for their diagnostic or therapeutic utility.