Integrated metabolomic profiling of hepatocellular carcinoma in hepatitis C cirrhosis through GC/MS and UPLC/MS-MS.

2014 
Hepatocellular carcinoma (HCC) is the world’s third most lethal cancer, possessing a 5-year survival rate of 10% that results in between 2 50 000 to 1 000 000 deaths per year (1, 2). HCC culminates from a pre-existing long-term condition of cirrhosis in 90% of cases (3). Despite the risk factors being well characterized, the early detection of HCC that is crucial for curative intervention remains a significant challenge. This is in part because of the limited understanding of the mechanisms involved in the emergence of cancerous lesions within the cirrhotic microenvironment. Consequently, the majority of HCC patients are diagnosed after the cancer has already progressed to an advanced stage that possesses a grim outlook for curative intervention (4). Given that the risk factors for hepatocellular carcinoma are well known, studies comparing molecular phenotypes of patients with HCC and patients with cirrhosis can help improve the understanding of the pathophysiology of HCC and lay early groundwork for improved strategies in the monitoring of the at-risk population for HCC. Recent advances in analytical chemistry have placed metabolomics at the frontier of disease phenotype characterization and lead marker generation. Metabolomics is the identification and quantification of all small molecules <1 kD in a tissue sample (5). Metabolomics couples liquid or gas chromatography/mass spectrometry (LC/MS, GC/MS) or nuclear magnetic resonance (NMR) with mass spectral and biostatistical analysis software to provide a validated and high-throughput method for obtaining and comparing the full complement of metabolites in tissue samples between groups. Because the liver is the principal organ of amino acid, lipid and carbohydrate metabolism and given the stepwise hepatocarcinogenic process involving a transition from cirrhosis to HCC, HCC is an ideal candidate for metabolomic profiling studies. HCC metabolomics has gained traction in recent years and at least 17 human HCC metabolomics studies have been reported (6-22). While these studies show possible roles for lysophospholipids (LPC), amino acids and glutathione metabolites in HCC development, significant heterogeneity in metabolomic data exists among these studies, likely attributable to differences in study design. Most of these studies identify metabolite expression profile differences between HCC patients and healthy volunteers, with only seven of these studies reporting the metabolomic profile differences between HCC patients and patients with cirrhosis (6, 7, 9, 14-17). Because greater than 90% of HCCs are diagnosed in patients with cirrhosis and given that HCC disease-monitoring paradigms target individuals with advanced fibrosis or cirrhosis, the metabolomic profile comparison of HCC vs. cirrhosis may be a more clinically relevant comparison than HCC patients vs. healthy subjects. Only three previous metabolomics studies reported Model of End-Stage Liver Disease (MELD) and Child–Pugh liver function scores (14, 15, 18), leaving unrestrained the potential influence of decompensated liver function on metabolomic data. Body mass index (BMI), a parameter directly related to metabolite expression levels, was also unaccounted for in all but one HCC metabolomics study (21), likely further confounding interpretation of metabolomic data. The previous metabolomics studies also employed a single technology of GC/MS or LC/MS or NMR. Because no single platform can provide global metabolomic coverage, an integrated metabolomics approach harnessing multiple platforms is needed to achieve a comprehensive identification of the metabolic underpinnings of hepatocarcinogenesis. In this study, we characterized the metabolic disturbances associated with the presence of HCC using an integrated non-targeted metabolomics approach that employed both gas chromatography/mass spectrometry (GC/MS) and ultrahigh-performance liquid chromatography electrospray ionization tandem mass spectrometry (UPLC/MS-MS). The global serum metabolomes of a well-characterized and matched cohort of patients with HCC arising from hepatitis C (HCV)-associated cirrhosis, HCV-cirrhosis disease control patients (DC) and normal healthy controls (NHC) were determined through combined serum analysis with these platforms. The random forest supervised class prediction model, significance testing, false discovery rate, fold difference comparisons and receiver operator characteristic analysis were performed to identify metabolite expression trends most closely associated with HCC presence. We focused the metabolomic comparisons on HCC vs. DC to identify pathways most reflective of hepatocarcinogenesis in the environment of cirrhosis. In addition, through comparison of DC and NHC metabolomes, we identified metabolic pathways potentially contributing to the presence of cirrhosis. We also performed receiver operator characteristic (ROC) analysis to further gauge the ability of metabolites that were most significantly associated with HCC and cirrhosis to accurately place subjects into their appropriate groups. Our study reveals significant aberrations in a number of pathways potentially involved in the progression from hepatitis C-associated cirrhosis to HCC including reactive oxygen species homoeostasis pathways, lipid signalling cascades, cell turnover regulation pathways and pathways of amino acid metabolism. We also identified possible signatures of HCV-cirrhosis that included pathways of bile acid, dicarboxylic acid and fibrinogen cleavage metabolism.
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