Elsevier

Analytica Chimica Acta

Volume 743, 19 September 2012, Pages 90-100
Analytica Chimica Acta

Utilization of metabolomics to identify serum biomarkers for hepatocellular carcinoma in patients with liver cirrhosis

https://doi.org/10.1016/j.aca.2012.07.013Get rights and content

Abstract

Characterizing the metabolic changes pertaining to hepatocellular carcinoma (HCC) in patients with liver cirrhosis is believed to contribute towards early detection, treatment, and understanding of the molecular mechanisms of HCC. In this study, we compare metabolite levels in sera of 78 HCC cases with 184 cirrhotic controls by using ultra performance liquid chromatography coupled with a hybrid quadrupole time-of-flight mass spectrometry (UPLC–QTOF MS). Following data preprocessing, the most relevant ions in distinguishing HCC cases from patients with cirrhosis are selected by parametric and non-parametric statistical methods. Putative metabolite identifications for these ions are obtained through mass-based database search. Verification of the identities of selected metabolites is conducted by comparing their MS/MS fragmentation patterns and retention time with those from authentic compounds. Quantitation of these metabolites is performed in a subset of the serum samples (10 HCC and 10 cirrhosis) using isotope dilution by selected reaction monitoring (SRM) on triple quadrupole linear ion trap (QqQLIT) and triple quadrupole (QqQ) mass spectrometers. The results of this analysis confirm that metabolites involved in sphingolipid metabolism and phospholipid catabolism such as sphingosine-1-phosphate (S-1-P) and lysophosphatidylcholine (lysoPC 17:0) are up-regulated in sera of HCC vs. those with liver cirrhosis. Down-regulated metabolites include those involved in bile acid biosynthesis (specifically cholesterol metabolism) such as glycochenodeoxycholic acid 3-sulfate (3-sulfo-GCDCA), glycocholic acid (GCA), glycodeoxycholic acid (GDCA), taurocholic acid (TCA), and taurochenodeoxycholate (TCDCA). These results provide useful insights into HCC biomarker discovery utilizing metabolomics as an efficient and cost-effective platform. Our work shows that metabolomic profiling is a promising tool to identify candidate metabolic biomarkers for early detection of HCC cases in high risk population of cirrhotic patients.

Highlights

► We analyzed sera from HCC and cirrhotic patients by LC–MS in three experiments. ► Metabolites with significant and consistent changes in HCC vs. cirrhosis were selected. ► Verification of the identities of selected metabolites was performed by MS/MS. ► Quantitation of candidate metabolites was conducted using isotope dilution by SRM.

Introduction

Hepatocellular carcinoma (HCC) is the fifth most common and one of the deadliest cancers. It has become a significant health issue with more than half a million people diagnosed with HCC per year. In particular, HCC has become the fastest-rising cause of cancer-related death in the United States [1] because of chronic alcohol use and chronic hepatitis C virus (HCV) infection [2]. About one third of HCV carriers develop liver cirrhosis. Patients with cirrhosis have an annual risk of 1–2% for developing HCC, with 80% of HCC inevitably developed from liver cirrhosis. The malignant conversion of cirrhosis to HCC is often fatal in part because adequate biomarkers are not available for diagnosis during the progression stage of HCC. Current approaches for diagnosis of HCC using liver imaging and measurement of serum alpha-fetoprotein (AFP) lack sufficient sensitivity and specificity. Determination of HCC from cirrhosis has become challenging because regenerative nodules may mimic tumors in cirrhotic livers and due to elevated serum levels of alpha-fetoprotein (AFP) in patients with cirrhosis. Therefore, there is an urgent need to identify more reliable and accurate tumor markers that would greatly improve the chances of detecting early stage HCC in high risk population of cirrhotic patients.

Metabolomics (synonymous term as “metabonomics”) is the comprehensive analysis of all metabolites in a biological system, e.g. the studies of changes in metabolic activities in response to pathophysiological stimuli or genetic modifications [3], [4]. It complements transcriptomics and proteomics as it provides a quantitative assessment of low molecular weight analytes (<1800 Da). To achieve appropriate coverage of the metabolome, several different analytic platforms may be needed. Liquid chromatography coupled with mass spectrometry (LC–MS) is one of the commonly used analytical platforms for comprehensive analysis of metabolites at various levels of abundance in biological samples [5], [6]. LC–MS has shown promise in identifying metabolite-based biomarkers in various cancers studies [7], [8], [9], [10], [11]. LC–MS signatures, alone or in combination with AFP levels, have been investigated for identification of early diagnosis biomarkers of HCC through metabolic profiling of serum, plasma, urine and fecal samples [12], [13], [14], [15], [16], [17], [18], where HCC has been successfully differentiated from patients with benign liver tumor and healthy controls. These metabolites are involved in a few key metabolic pathways, e.g. bile acid metabolism, phospholipid metabolism, fatty acids, glycolysis, urea cycle, and methionine metabolism. For example, bile acid and phospholipids metabolites were reported being altered in HCC compared to healthy individuals and patients with live cirrhosis [19]. Tan et al. reported in a recent study that a small panel of marker metabolites (LPE 16:0, TCA, and LPC 22:5) can achieve up to 80% sensitivity and selectivity in discriminating HCC from pre-cancer cirrhosis and chronic hepatitis in a preclinical validation [18]. Also, it is reported that glutathione (GSH) level and the ratios of GSH/GSSG (GSSG as GSH oxidized form) and GSH/total glutathione of the blood samples and liver tissues from HCC patients are significantly lower than those of the controls [20]. GSH works as antioxidant to protect cells from oxidative stress-induced apoptosis caused by reactive oxygen species (ROS), e.g., H2O2. However, discriminating early HCC from liver cirrhosis remains as the most challenging task in diagnosis of HCC partly due to lack of reliable and accurate biomarkers. Current metabolomic studies rely on global profiling using accurate mass measurement by mass spectrometers with high mass accuracy and high resolution such as quadrupole time-of-flight (QTOF), Orbitrap or Fourier-transform ion cyclotron resonance (FT-ICR). However, these platforms can only provide semi-quantitative information on metabolic changes, in which matrix effects such as ion suppression or ion enhancement inevitably affect the accurate detection of metabolites in various abundance levels with diverse chemical properties. Although adequate sample preparation prior to LC separation can be one of the solutions to alleviate this problem, the most effective way to circumvent matrix effects is to combine isotope dilution technique with selected reaction monitoring (SRM) to establish a more reliable calibration curve for absolute quantitation, and to measure real concentration of metabolites by using stable isotope-labeled analogues as internal standards. Meanwhile, the high physical–chemical similarities between stable isotope-labeled analogues and target metabolites can also compensate the effects of degradation during sample preparation and variations in instrumental response [5], [6]. Only few of recent HCC metabolomic studies have reported the combination of ultra performance liquid chromatography (UPLC) coupled with QTOF MS and chemometric analysis for global profiling followed by SRM based absolute quantitation of metabolite candidates for target profiling [17]. We believe that characterizing the metabolic changes in high risk population of cirrhotic patients can help in early detection of HCC, a better understanding of the HCC mechanism at the molecular level as well as its treatment.

This study applies LC–MS based serum metabolomics for HCC biomarker discovery using non-targeted global profiling through a semi-quantitative method followed by absolute quantitation of targeted metabolites. Specifically, we use UPLC–QTOF MS for semi-quantitative analysis of serum samples from patients with HCC and cirrhosis. Putative identifications obtained by mass-based search are verified by comparing their MS/MS fragmentation patterns with those from authentic compounds. Absolute quantitation of candidate metabolic biomarkers is performed using isotope dilution based SRM on triple quadrupole linear ion trap (QqQLIT) and triple quadrupole (QqQ) mass spectrometers, each coupled to a UPLC. The results of this study illustrate the power of accurate mass measurement by UPLC–electrospray ionization (ESI)-QTOFMS, combined with the targeted quantitative analysis by UPLC–ESI-SRM-MS for a comprehensive serum metabolomic analysis to investigate changes in metabolite levels between HCC cases and patients with liver cirrhosis.

Section snippets

Study population

The participants in this study comprised adult patients, who were prospectively recruited from the hepatology clinics at Georgetown University Hospital (GUH), Washington, DC. All patients provided informed consent and the study was approved by the Institutional Review Board at Georgetown University. All patients were diagnosed to have liver cirrhosis on the basis of established clinical, laboratory and/or imaging criteria. Cases were diagnosed to have HCC based on well-established diagnostic

Chemicals and reagents

Ammonium acetate, sphingosine-1-phosphate (S-1-P), taurocholic acid (TCA), taurodeoxycholic acid (TDCA), glycodeoxycholic acid (GDCA), glycodeoxycholic acid (GCA), glycodeoxycholic-2,2,4,4-d 4 acid (D4-GDCA), glycodeoxycholic-2,2,4,4-d 4 acid (D4-GCA) were purchased from Sigma–Aldrich (St. Louis, MO). Glycochenodeoxycholic acid 3-sulfate (3 sulfo-GCDCA) was synthesized by PharmAgra Labs (Brevard, NC). Lysophosphatidylcholine (LysoPC 16:0), LysoPC 17:0, D31_LysoPC 16:0 and D7_S-1-P were

Data preprocessing

Data matrices of ion intensities were obtained by preprocessing each of the three UPLC–QTOF MS datasets separately. In Exp. 1, Exp. 2, and Exp. 3, we detected 1587, 3231, and 613 ions in the positive mode, respectively. In the negative mode, 942, 1210, and 392 ions were detected in Exp. 1, Exp. 2, and Exp. 3, respectively.

Ion annotation

Using CAMERA software, we annotated ions detected in the three data matrices in two steps. In the first step, the detected ions with similar RT are roughly grouped together

Discussion

We analyzed 262 serum samples from patients with HCC and cirrhosis in three experiments using UPLC–QTOF-MS under positive and negative detection modes. The data were first preprocessed to detect peaks, match the peaks, and correct RT drifts. The most relevant ions in distinguishing HCC cases from patients with cirrhosis were selected by parametric and non-parametric statistical methods. Specifically, an ion-annotation-assisted approach is used to identify ions with significant and consistent

Conclusion

In this study, we characterized the metabolic changes pertaining to HCC in patients with cirrhosis using both semi-quantitative and absolute quantitative approaches by UPLC–MS/MS. The candidate biomarkers we identified in this study include: (1) bile acid related and liver-specific metabolites down-regulated in HCC vs. cirrhosis; and (2) metabolites such as S-1-P and LysoPC 17:0 up-regulated in HCC vs. cirrhosis. The accumulation of conjugated bile acids in cirrhosis or chronic hepatitis could

Acknowledgements

This work was supported by the National Institutes of Health (NIH) Grant R21CA153176. Serum sample collection was supported by NIH Grant R01CA115625. The UPLC–QTOF MS data presented in the manuscript were generated through the Proteomics and Metabolomics Shared Resource at the Lombardi Comprehensive Cancer Center, supported by NIH/NCI Grant P30-CA051008. We would like to thank David Broadhurst (University of Alberta) for his suggestions in quality assessment and preprocessing of the UPLC–QTOF

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