Molecular Signature Predictive of Long-Term Liver Fibrosis Progression to Inform Antifibrotic Drug Development.

BACKGROUND & AIMS: There is a major unmet need to assess the prognostic impact of antifibrotics in clinical trials because of the slow rate of liver fibrosis progression. We aimed to develop a surrogate biomarker to predict future fibrosis progression. METHODS: A fibrosis progression signature (FPS) was defined to predict fibrosis progression within 5 years in patients with hepatitis C virus and nonalcoholic fatty liver disease (NAFLD) with no to minimal fibrosis at baseline (n = 421) and was validated in an independent NAFLD cohort (n = 78). The FPS was used to assess response to 13 candidate antifibrotics in organotypic ex vivo cultures of clinical fibrotic liver tissues (n = 78) and cenicriviroc in patients with nonalcoholic steatohepatitis enrolled in a clinical trial (n = 19, NCT02217475). A serum protein-based surrogate FPS was developed and tested in a cohort of compensated cirrhosis patients (n = 122). RESULTS: A 20-gene FPS was defined and validated in an independent NAFLD cohort (adjusted odds ratio, 10.93; area under the receiver operating characteristic curve, 0.86). Among computationally inferred fibrosis-driving FPS genes, BCL2 was confirmed as a potential pharmacologic target using clinical liver tissues. Systematic ex vivo evaluation of 13 candidate antifibrotics identified rational combination therapies based on epigallocatechin gallate, which were validated for enhanced antifibrotic effect in ex vivo culture of clinical liver tissues. In patients with nonalcoholic steatohepatitis treated with cenicriviroc, FPS modulation was associated with 1-year fibrosis improvement accompanied by suppression of the E2F pathway. Induction of the PPARα pathway was absent in patients without fibrosis improvement, suggesting a benefit of combining PPARα agonism to improve the antifibrotic efficacy of cenicriviroc. A 7-protein serum protein-based surrogate FPS was associated with the development of decompensation in cirrhosis patients. CONCLUSION: The FPS predicts long-term fibrosis progression in an etiology-agnostic manner, which can inform antifibrotic drug development.

A blood-based prognostic liver secretome signature and long-term hepatocellular carcinoma risk in advanced liver fibrosis.

BACKGROUND: Accurate non-invasive prediction of long-term hepatocellular carcinoma (HCC) risk in advanced liver fibrosis is urgently needed for cost-effective HCC screening; however, this currently remains an unmet need. METHODS: A serum-protein-based prognostic liver secretome signature (PLSec) was bioinformatically derived from previously validated hepatic transcriptome signatures and optimized in 79 patients with advanced liver fibrosis. We independently validated PLSec for HCC risk in 331 cirrhosis patients with mixed etiologies (validation set 1 [V1]) and thereafter developed a score with clinical prognostic variables. The score was then validated in two independent cohorts: validation set 2 (V2): 164 patients with advanced liver fibrosis due to hepatitis C virus (HCV) infection cured after direct-acting antiviral therapy; validation set 3 (V3): 146 patients with advanced liver fibrosis with successfully-treated HCC and cured HCV infection. FINDINGS: An 8-protein blood-based PLSec recapitulated transcriptome-based hepatic HCC risk status. In V1, PLSec was significantly associated with incident HCC risk (adjusted hazard ratio [aHR], 2.35; 95% confidence interval [CI], 1.30-4.23). A composite score with serum alpha-fetoprotein (PLSec-AFP) was defined in V1, and validated in V2 (adjusted odds ratio, 3.80 [95%CI, 1.66-8.66]) and V3 (aHR, 3.08 [95%CI, 1.78-5.31]; c-index, 0.74). PLSec-AFP outperformed AFP alone (Brier score, 0.165 vs. 0.186 in V2; 0.196 vs. 0.206 in V3, respectively). CONCLUSIONS: The blood-based PLSec-AFP can accurately stratify patients with advanced liver fibrosis for long-term HCC risk and thereby guide risk-based tailored HCC screening.

MPIC: Molecular Prognostic Indicators in Cirrhosis Database for Clinical Context-Specific in Silico Prognostic Biomarker Validation.

Prognostic biomarkers are vital in the management of progressive chronic diseases such as liver cirrhosis, affecting 1-2% of the global population and causing over 1 million deaths every year. Despite numerous candidate biomarkers in literature, the costly and lengthy process of validation hampers their clinical translation. Existing omics databases are not suitable for in silico validation due to the ignorance of critical factors, i.e., study design, clinical context of biomarker application, and statistical power. To address the unmet need, we have developed the Molecular Prognostic Indicators in Cirrhosis (MPIC) database as a representative example of an omics database tailored for prognostic biomarker validation. MPIC consists of (i) a molecular and clinical database structured by defined disease context and specific clinical outcome and annotated with employed study design and anticipated statistical power by disease domain experts, (ii) a bioinformatics analysis engine for user-provided gene-signature- or gene-based prognostic prediction, and (iii) a user interface for interactive exploration of relevant clinical cohort/scenario and assessment of significance and reliability of the result for prognostic prediction. MPIC assists cost-effective prognostic biomarker development by facilitating the process of validation, and will transform the care of chronic diseases such as cirrhosis. MPIC is freely available at www.mpic-app.org. The website is implemented in Java, Apache, and MySQL with all major browsers supported.

Cell type-specific pharmacological kinase inhibition for cancer chemoprevention.

Safety is prerequisite for preventive medicine, but non-toxic agents are generally ineffective as clinical chemoprevention. Here we propose a strategy overcoming this challenge by delivering molecular-targeted agent specifically to the effector cell type to achieve sufficient potency, while circumventing toxicity in the context of cancer chemoprevention. Hepatic myofibroblasts drive progressive fibrosis that results in cirrhosis and liver cancer. In a rat model of cirrhosis-driven liver cancer, a small molecule epidermal growth factor receptor inhibitor, erlotinib, was delivered specifically to myofibroblasts by a versatile nanoparticle-based system, targeting platelet-derived growth factor receptor-beta uniquely expressed on their surface in the liver. With systemic administration of erlotinib, tumor burden was reduced to 31%, which was further improved to 21% by myofibroblast-targeted delivery even with reduced erlotinib dose (7.3-fold reduction with equivalent erlotinib dose) and less hepatocyte damage. These findings demonstrate a strategy, cell type-specific kinase inhibition, for more effective and safer precision cancer chemoprevention.

Molecular Liver Cancer Prevention in Cirrhosis by Organ Transcriptome Analysis and Lysophosphatidic Acid Pathway Inhibition.

Cirrhosis is a milieu that develops hepatocellular carcinoma (HCC), the second most lethal cancer worldwide. HCC prediction and prevention in cirrhosis are key unmet medical needs. Here we have established an HCC risk gene signature applicable to all major HCC etiologies: hepatitis B/C, alcohol, and non-alcoholic steatohepatitis. A transcriptome meta-analysis of >500 human cirrhotics revealed global regulatory gene modules driving HCC risk and the lysophosphatidic acid pathway as a central chemoprevention target. Pharmacological inhibition of the pathway in vivo reduced tumors and reversed the gene signature, which was verified in organotypic ex vivo culture of patient-derived fibrotic liver tissues. These results demonstrate the utility of clinical organ transcriptome to enable a strategy, namely, reverse-engineering precision cancer prevention.