Poster Presentation The Australasian Society for Immunology 2017 Annual Scientific Meeting

Identification of gene signatures associated with liver fibrosis by RNA-sequencing analysis of biopsies from chronic liver disease patients (#337)

Divya Ramnath 1 2 , Katharine M Irvine 3 , Leigh U Horsfall 3 , Samuel W Lukowski 1 , Ken Loh 1 2 , Preya Patel 3 , Andrew D Clouston 3 , David P Fairlie 1 2 , Jennifer L Stow 1 2 , Kate Schroder 1 2 , Joseph E Powell 1 , Elizabeth E Powell 3 , Matthew J Sweet 1 2
  1. Institute for Molecular Bioscience, University of Queensland, St Lucia, Queensland, Australia
  2. IMB Centre for Inflammation and Disease Research, University of Queensland, St Lucia, Queensland, Australia
  3. School of Medicine, University of Queensland, Brisbane, Queensland, Australia

Immune cell infiltration and activation contributes to injury- and inflammation-driven production and accumulation of extracellular matrix proteins in liver fibrosis, which is characteristic of most type of chronic liver diseases (CLD). Although our understanding of the cellular and molecular mechanisms of liver fibrosis has greatly advanced, current methods for diagnosing and treating liver fibrosis are limited. Existing non-invasive methods of liver fibrosis diagnosis involve transient elastography and certain serologic tests such as the enhanced liver fibrosis (ELF) score; however, these methods are not able to reliably detect fibrosis stage. Liver biopsy still remains the only effective way to accurately determine the stage of fibrosis, but it is an invasive procedure, which can be accompanied by complications such as internal bleeding. In this study, we aimed to identify the core gene signature associated with liver fibrosis using liver tissue RNA from 69 chronic liver disease patients at different stages of fibrosis and with different aetiologies. RNA-sequencing analysis identified 171 genes that were differentially expressed between early versus advanced stages of fibrosis, 60 of which encoded extracellular proteins. By gene correlation analysis with matched patient ELF score data, we identified 52 genes that strongly correlate with active fibrosis. One such gene represents a candidate master transcriptional regulator of the pro-fibrogenic gene signature associated with liver fibrosis. By comparing gene profiles of HCV or HCV with steatohepatitis patient biopsies, we also identified a steatohepatitis-specific set of genes associated with progressive fibrosis. In summary, our approach of using samples from patients with different CLD aetiologies has enabled us to deconvolute the inherit heterogeneity that exists within clinical samples, and has led to the identification of a core set of liver fibrosis-associated genes. Several of these encode immune-related proteins that may represent tractable targets and/or biomarkers for chronic liver disease.