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An integrated data analysis approach to characterize genes highly expressed in hepatocellular carcinoma

Oncogene volume 24, pages 3737–3747 (2005)Cite this article

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.

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Acknowledgements

We are grateful to Stanford Functional Genomic Center and Stanford Microarray database for their support. This work is supported by a grant to the Asian Liver Center at Stanford University by the HM Lui Foundation (to M-SC, RL and SS), the UCSF Liver Center (DK26743-22) pilot/feasibility project award and NCI K01 award (to XC) and grants from the National Foundation for Cancer Research and the Defense Advanced Projects Research Agency (DARPA) (to SNC). K-H Pan is supported by a Stanford Graduate Fellowship.

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Author notes

  1. Supplementary Information accompanies the paper on Oncogene website (http://www.nature.com/onc)

  2. 6 Patil Mohini A, Chua Mei-Sze and Pan Kuang-Hung contributed equally to this work and are listed in random order

Authors and Affiliations

  1. Department of Biopharmaceutical Sciences, University of California, San Francisco, CA, 94143, USA

    Mohini A Patil, Coral Ho & Xin Chen

  2. Department of Surgery and Asian Liver Center, Stanford University, Stanford, CA, 94305, USA

    Mei-Sze Chua, Rui Li & Samuel So

  3. Department of Genetics, Stanford University, Stanford, CA, 94305, USA

    Kuang-Hung Pan, Richard Lin, Chih-Jian Lih & Stanley N Cohen

  4. Department of Surgery and Center for the Study of Liver Disease, University of Hong Kong, Hong Kong, China

    Siu-Tim Cheung & Sheung-Tat Fan

  5. Liver Center, University of California, San Francisco, CA, 94143, USA

    Xin Chen

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  1. Mohini A Patil
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Patil, M., Chua, MS., Pan, KH. et al. An integrated data analysis approach to characterize genes highly expressed in hepatocellular carcinoma. Oncogene 24, 3737–3747 (2005). https://doi.org/10.1038/sj.onc.1208479

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