Characterisation of hepatic fibrosis by genetic profiling of in vitro activated human stellate cells

Murray Ej Walker, F., Price, G., Mann, D., Benyon RC Arthur MJP Wilkinson SE Bottomley, K., Wise, L. and Nixon JS Iredale JP, B. (2008) Characterisation of hepatic fibrosis by genetic profiling of in vitro activated human stellate cells. conference; gb; 2008-09-01, London, United Kingdom. 376A-376A .

Abstract

Hepatic fibrosis is a progressive debilitating disease which if left unchecked leads to cirrhosis and liver failure. To date, transplantation remains the only clinical treatment. The molecular mechanisms which lead to fibrosis represent an area of intensive study and it is now clear that hepatic stellate cells (HSCs) play a pivotal role in this process. As a first step to developing an effective anti-fibrotic chemotherapy, we have undertaken a global genetic analysis of HSC activation using Affymetrix GeneChip™ HG-U95A, which represents up to 11 000 characterised human genes.

We have analysed pairwise, matched HSCs either freshly isolated (designated as “quiescent”), or activated by culture on plastic in the presence of 16% serum, from three independent healthy human liver samples at n=>4 for each condition. All three datasets show uniform host control gene expression and hybridisation controls. Our three datasets exhibit a consistent number of expressed genes (4000–5000 active in both quiescent and activated HSCs). In addition, ~2200 genes are consistently modulated upon activation, of which ~1000 genes are upregulated and ~1200 are downregulated. Furthermore, 900 gene modulations (~40%) are common to all three samples which is extremely high agreement when compared to other gene profiling studies using established or transformed cell lines.

Finally, further analysis shows that ~400 genes are consistently and significantly upregulated during HSC activation. Many of the collagen genes are represented in the upregulated genes as expected for a model for fibrosis. Other identified genes which are modulated include those for cell motility, growth factors/receptors, TGF signalling, ECM remodelling, and those genes which are established markers for activation—for example, ?-smooth muscle actin.

We intend using these datasets to target pathways for therapeutic intervention to help prevent hepatic fibrosis caused, for example by chronic HCV infection. Such an anti-fibrotic therapy, allied to an anti-HCV viral therapy, would meet an urgent clinical need

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