PROJECT SUMMARY/ABSTRACT
Cirrhosis and hepatocellular carcinoma are increasing health and economic burdens. Non-alcoholic fatty liver
disease (NAFLD/NASH), alcohol-associated liver disease (AALD), chronic hepatitis (CHC), and autoimmune
hepatitis (AIH) are common etiologies. Unfortunately, many patients do not adhere to recommended life style
modifications, thus, we need better techniques for predicting risk of fibrosis progression and personalizing
therapies prior to development of poor outcomes. Intrahepatic macrophages (Macs), liver sinusoidal endothelial
cells (LSECs), and stellate cells (HSCs) can greatly influence the composition of the hepatic microenvironment
and development of fibrosis. Therapies targeting these initiators of fibrosis are being investigated in phase II-III
clinical trials; however, the underlying hepatic microenvironment and patient variability in these cells and
expression of these targets is not being considered prior to treatment. We use cutting-edge spectral imaging
microscopy combined with NanoString technology to evaluate these cells and associated pro-fibrotic gene
expression profiles in the same patient’s liver biopsy at the time of initial diagnosis. From our liver tissue biobank,
we identified 225 biopsies with different chronic liver diseases (NASH, AALD, CHC, and AIH) that were collected
at the time of diagnosis from patients that had adequate follow-up either with a repeat biopsy or by liver
replacement (for those that later developed cirrhosis). The majority showed no progression of hepatic fibrosis
over time (n = 150) while a portion rapidly developed cirrhosis (n = 75). We use the above platforms to assess
differences in these patients’ hepatic microenvironments in their initial liver biopsies. We propose to test the
hypothesis that patients with definable pro-fibrotic variations in their hepatic microenvironment early in the course
of disease predicts their propensity to develop fibrosis. Preliminary data showed that initial liver biopsies from
patients with a predisposition to rapidly develop cirrhosis have increased profibrotic macrophages (e.g.,
Mac387+ and CD163+, respectively), enhanced cellular interactions of Mac-LSEC-HSCs, increased expression
of therapy-related targets (e.g., CCR2 and galectin 3) and increased pro-inflammatory/pro-fibrotic gene
expression profiles (e.g., CCL2, TNF, and TGF-beta). Imaging and molecular bioinformatics will be used for data
analyses. For Aim 1, we will use three panels to phenotype intrahepatic Macs and examine their interactions
with LSECs and HSCs, and will assess differences in expression of pro-fibrotic therapy-related targets. For Aim
2, we will analyze over 200 Mac-LSEC-HSC-related and pro-fibrotic genes in the other half of the biopsy from
Aim 1. The proposed approach will lay the groundwork for our long-term objective: personalization of targeted
therapies (e.g., cenicriviroc or obeticholic acid), similar to the manner in which the response to immunotherapy
is predicted by staining of tissue in patients with cancer. In this retrospective longitudinal study, we will determine
which platform (Spectral imaging-Aim1 vs. NanoString-Aim 2) is the most performant for determining potential
targets of fibrosis progression and most cost efficient for clinical implementation in the future.