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P41 Liver disease-specific gene expression profile in hepatocellular carcinoma
  1. A Marshall
  1. Addenbrooke's Hospital, Cambridge, UK

Abstract

Introduction In the UK, hepatocellular carcinoma (HCC) has the largest increase in cancer mortality of all cancers over the last decade. Although it is well known that the most important risk factor for HCC development is liver cirrhosis, the specific role of liver disease aetiology in promoting cancer development remains under-explored. We hypothesised that different liver diseases might drive HCC development by expression of different sets of genes. Identification of liver disease-specific genes could be applied to developing disease-specific diagnostic markers or therapeutic targets.

Aim To compare global gene expression profiles from HCC arising in different liver diseases, using our own and publicly available data.

Method Fresh-frozen liver samples were collected from normal liver (4) and both background liver (7) and HCC (7) from patients with haemochromatosis (HH) undergoing liver transplantation or resection for HCC. RNA was extracted using a phenol-chloroform method, assessed for quality then hybridised to Affymetrix U133Plus2.0 gene expression arrays. Public microarray databases ArrayExpress and Gene Expression Omnibus were mined for liver gene expression data measured using Affymetrix U133Plus2.0 array platform. Annotations for all identified liver samples were curated and relevant samples selected for RMA normalisation. Principal component analysis and differential gene expression analysis were carried out using R Bioconductor. The lists of differentially expressed genes were created by separate comparison of each disease group against normal liver samples. The lists of p value corrected statistically significant genes were further filtered for twofold expression change. Disease specific gene lists were created. Genes identified as highly expressed in HH-related HCC were validated using quantitative RT-PCR.

Results Public databases yielded gene expression data on normal liver (n=51), HCV/cirrhosis (n=59), HCV-related HCC (n=126), HBV/cirrhosis (n=4), and HBV-related HCC (n=5). Principal component analysis showed clustering of normal, cirrhosis and HCC samples. Using a twofold cut-off, 16 genes were differentially expressed in HH-related HCC compared to normal liver, 502 genes in HBV-related HCC and 29 genes in HCV-related HCC (Abstract P41 figure 1). No differentially-expressed genes were common to all three groups. Genes CD109 and SPP1 were identified as highly expressed in HH-related HCC compared to all other groups (Abstract P41 figure 2) and their expression in normal and HH samples were confirmed with quantitative RT-PCR.

Abstract P41 Figure 1

Venn diagram showing number of differentially expressed genes in HCV, HBV and HH related HCC compared to normal liver.

Abstract P41 Figure 2

Expression level of SPP1 and CD109 in normal liver and HCV, HBV and HH related cirrhosis and HCC.

Conclusion Comparison of global gene expression profiles yielded sets of differentially expressed genes specific to liver disease aetiology in HCC related to HCV, HBV and haemochromatosis. Two genes highly expressed in haemochromatosis-related HCC were identified that might be useful as disease-specific markers.

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