Gene Expression Patterns in Human Liver Cancers

Abstract

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 compared with those seen in nontumor 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.

Comparative and integrative functional genomics of HCC

“…As expected, prediction models based on gene expression profiles successfully discriminate HCC from non-tumor livers with expected high accuracy (Kim et al, 2004;Neo et al, 2004;Nam et al, 2005). Many studies have identified differentially expressed gene sets in HCC that differ according to etiological factors (Okabe et al, 2001), mutations of tumor suppressor genes (Chen et al, 2002), rate of recurrence (Iizuka et al, 2003), intrahepatic metastasis (Ye et al, 2003) and different stages (Nam et al, 2005). The results from these studies demonstrate that genomic-scale gene expression profiles recapitulate the well-known morphological distinctions of the tissues and suggest that the differences in gene expression patterns might be biologically relevant.…”

Identification of SOX4 target genes using phylogenetic footprinting-based prediction from expression microarrays suggests that overexpression of SOX4 potentiates metastasis in hepatocellular carcinoma

“…Molecular analyses have shown that the HCC pathogenesis is a multifactorial and multistep process reflecting alterations derived from epigenetic instability, chromosomal instability and deregulated transcription (Chen et al, 2002;El-Serag and Rudolph, 2007). HCC death has been ranked the third most common cancer death worldwide as a result of poor prognosis due to the disease's heterogeneous nature and the high rate of intrahepatic metastasis that occurs in the dense vasculature of the liver (Tang et al, 2004;Kim et al, 2005).…”

Identification of molecular subtypes of glioblastoma by gene expression profiling

“…Large-scale gene expression profiling provides a powerful approach to identify transcriptional networks associated with upregulated signaling pathways, and to discover previously unrecognized tumor subtypes with distinct molecular and/or clinical phenotypes or responses to therapy (Golub et al, 1999;Alizadeh et al, 2000;Perou et al, 2000;MacDonald et al, 2001;Sorlie et al, 2001;Chen et al, 2002;Pomeroy et al, 2002;Shipp et al, 2002), including GBM (Sallinen et al, 2000;Ljubimova et al, 2001;Rickman et al, 2001;Lal et al, 2002). Gene expression profiling can also be used to detect distinct molecular signatures associated with specific mutations (Hedenfalk et al, 2001).…”