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A more recent version of this article appeared on June 1, 2002
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Submitted on November 26, 2001
Revised on February 19, 2002
Accepted on March 18, 2002
1 Department of Biochemistry and Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, CA 94305
2 Department of Surgery, The University of Hong Kong, Hong Kong, China
3 Department of Surgery, Stanford University School of Medicine, Stanford, CA 94305
4 Department of Pathology, Stanford University School of Medicine, Stanford, CA 94305
5 Department of Surgery, Beijing Cancer Hospital, Beijing, China
6 Department of Biochemistry, Stanford University School of Medicine, Stanford, CA 94305
7 Department of Pathology, The University of Hong Kong, Hong Kong, China
8 Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305
* Corresponding author. E-mail address: botstein{at}genome.stanford.edu.
* Corresponding author. E-mail address: pbrown{at}cmgm.stanford.edu.
Hepatocellular Carcinoma (HCC) is a leading cause of death worldwide. Using cDNA microarrays to characterize patterns of gene expression in HCC, we found consistent differences between the expression patterns in HCC as compared with those seen in non-tumor liver tissues. The expression patterns in HCC were also readily distinguished from those associated with tumors metastatic to liver. The global gene expression patterns intrinsic to each tumor were sufficiently distinctive that multiple tumor nodules from the same patient could usually be recognized and distinguished from all the others in the large sample set on the basis of their gene expression patterns alone. The distinctive gene expression patterns are characteristic of the tumors and not the patient - the expression programs seen in clonally independent tumor nodules in the same patient were no more similar than those in tumors from different patients. Moreover, clonally related tumor masses that showed distinct expression profiles were also distinguished by genotypic differences. Some features of the gene expression patterns were associated with specific phenotypic and genotypic characteristics of the tumors, including growth rate, vascular invasion and p53 overexpression.
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