Title: Serum and Urine Metabolite Profiling Reveals Potential Biomarkers of Human Hepatocellular Carcinoma
Abstract: Hepatocellular carcinoma (HCC) is a common malignancy in the world with high morbidity and mortality rate. Identification of novel biomarkers in HCC remains impeded primarily because of the heterogeneity of the disease in clinical presentations as well as the pathophysiological variations derived from underlying conditions such as cirrhosis and steatohepatitis. The aim of this study is to search for potential metabolite biomarkers of human HCC using serum and urine metabolomics approach. Sera and urine samples were collected from patients with HCC (n = 82), benign liver tumor patients (n = 24), and healthy controls (n = 71). Metabolite profiling was performed by gas chromatography time-of-flight mass spectrometry and ultra performance liquid chromatography-quadrupole time of flight mass spectrometry in conjunction with univariate and multivariate statistical analyses. Forty three serum metabolites and 31 urinary metabolites were identified in HCC patients involving several key metabolic pathways such as bile acids, free fatty acids, glycolysis, urea cycle, and methionine metabolism. Differentially expressed metabolites in HCC subjects, such as bile acids, histidine, and inosine are of great statistical significance and high fold changes, which warrant further validation as potential biomarkers for HCC. However, alterations of several bile acids seem to be affected by the condition of liver cirrhosis and hepatitis. Quantitative measurement and comparison of seven bile acids among benign liver tumor patients with liver cirrhosis and hepatitis, HCC patients with liver cirrhosis and hepatitis, HCC patients without liver cirrhosis and hepatitis, and healthy controls revealed that the abnormal levels of glycochenodeoxycholic acid, glycocholic acid, taurocholic acid, and chenodeoxycholic acid are associated with liver cirrhosis and hepatitis. HCC patients with alpha fetoprotein values lower than 20 ng/ml was successfully differentiated from healthy controls with an accuracy of 100% using a panel of metabolite markers. Our work shows that metabolomic profiling approach is a promising screening tool for the diagnosis and stratification of HCC patients. Hepatocellular carcinoma (HCC) is a common malignancy in the world with high morbidity and mortality rate. Identification of novel biomarkers in HCC remains impeded primarily because of the heterogeneity of the disease in clinical presentations as well as the pathophysiological variations derived from underlying conditions such as cirrhosis and steatohepatitis. The aim of this study is to search for potential metabolite biomarkers of human HCC using serum and urine metabolomics approach. Sera and urine samples were collected from patients with HCC (n = 82), benign liver tumor patients (n = 24), and healthy controls (n = 71). Metabolite profiling was performed by gas chromatography time-of-flight mass spectrometry and ultra performance liquid chromatography-quadrupole time of flight mass spectrometry in conjunction with univariate and multivariate statistical analyses. Forty three serum metabolites and 31 urinary metabolites were identified in HCC patients involving several key metabolic pathways such as bile acids, free fatty acids, glycolysis, urea cycle, and methionine metabolism. Differentially expressed metabolites in HCC subjects, such as bile acids, histidine, and inosine are of great statistical significance and high fold changes, which warrant further validation as potential biomarkers for HCC. However, alterations of several bile acids seem to be affected by the condition of liver cirrhosis and hepatitis. Quantitative measurement and comparison of seven bile acids among benign liver tumor patients with liver cirrhosis and hepatitis, HCC patients with liver cirrhosis and hepatitis, HCC patients without liver cirrhosis and hepatitis, and healthy controls revealed that the abnormal levels of glycochenodeoxycholic acid, glycocholic acid, taurocholic acid, and chenodeoxycholic acid are associated with liver cirrhosis and hepatitis. HCC patients with alpha fetoprotein values lower than 20 ng/ml was successfully differentiated from healthy controls with an accuracy of 100% using a panel of metabolite markers. Our work shows that metabolomic profiling approach is a promising screening tool for the diagnosis and stratification of HCC patients. Hepatocelluar carcinoma (HCC) 1The abbreviations used are:HCCHuman hepatocellular carcinomaFDG-PETfluorodeoxyglucose-positron emission tomographyAFPalpha fetoproteinHPLChigh performance liquid chromatographyLC-MSliquid chromatography-mass spectrometryGC-MSgas chromatography-mass spectrometryGC-TOFMSgas chromatography-time-of-flight mass spectrometryUPLC-QTOFMSultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometryOPLS-DAorthogonal partial least squares-discriminant analysisPCAprincipal component analysisUCurea cycleVIPvariable importance of the projectES+positive ion modeES–negative ion modeTMCStrimethylchlorosilaneBSTFABis(trimethylsilyl) trifluoroacetamide. is the fifth most common cancer (1El-Serag H.B. Rudolph K.L. Hepatocellular carcinoma: Epidemiology and molecular carcinogenesis.Gastroenterology. 2007; 132: 2557-2576Abstract Full Text Full Text PDF PubMed Scopus (4514) Google Scholar) and the third leading cause of cancer-related death (2World Health Organization Mortality Database, WHO Statistical Information System.Available at http://www.who.int/whosis/en/Date accessed: March 19, 2008Google Scholar) with a five-year survival rate of less than 7% (3Kassahun W.T. Fangmann J. Harms J. Hauss J. Bartels M. Liver Resection and Transplantation in the Management of Hepatocellular Carcinoma: A Review.Exp. Clin. Transplant. 2006; 4: 549-558PubMed Google Scholar). The morbidity of HCC in Southeast Asia and sub-Saharan Africa is greater than 20 cases per 100,000 population, whereas in North America and Western Europe is much lower, less than 5 per 100,000 population (4Fong T.L. Schoenfield L.J. 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Despite significant progress in cancer diagnosis and treatment, the morbidity and mortality rate of liver cancer remains high because early diagnosis is still a challenge. Early and accurate diagnosis of HCC is of central importance for timely treatment and five-year survival rate (38.1% at stage I, 3.9% at stage IV) (8Onodera H. Ukai K. Minami Y. Hepatocellular-Carcinoma Cases with 5-Year Survival and Prognostic Factors Affecting the Survival-Time.Tohoku J. Exp. Med. 1995; 176: 203-211Crossref PubMed Scopus (14) Google Scholar). Therefore, considerable efforts have been devoted to search for biomarkers for early diagnosis of HCC and patient stratification. Glypican-3, a cell surface-linked heparan sulfate proteoglycan, is one of the potential biomarkers in serum currently under investigation for HCC (9Coston W.M. Loera S. Lau S.K. Ishizawa S. Jiang Z. Wu C.L. Yen Y. Weiss L.M. Chu P.G. Distinction of hepatocellular carcinoma from benign hepatic mimickers using glypican-3 and CD34 immunohistochemistry.Am. J. Surg. Pathol. 2008; 32: 433-444Crossref PubMed Scopus (121) Google Scholar). At present, the most clinically used serum biomarker for HCC is alpha fetoprotein (AFP); however, clinicians are unsatisfied with it because of its high false positive and false negative rates (10Colli A. Fraquelli M. Casazza G. Massironi S. Colucci A. Conte D. Duca P. Accuracy of ultrasonography, spiral CT, magnetic resonance, and alpha-fetoprotein in diagnosing hepatocellular carcinoma: A systematic review.Am. J. Gastroenterol. 2006; 101: 513-523Crossref PubMed Scopus (422) Google Scholar). 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Metabonomic studies of human hepatocellular carcinoma using high-resolution magic-angle spinning 1H NMR spectroscopy in conjunction with multivariate data analysis.J. Proteome Res. 2007; 6: 2605-2614Crossref PubMed Scopus (220) Google Scholar) and a panel of 13 differential tissue metabolites, including alanine, leucine and glucose were identified. Several serum and urine metabolites as potential markers in a small number of HCC patients (n = 20) were identified by gas chromatography mass spectrometry (GC-MS, LC-MS) (20Xue R. Lin Z. Deng C. Dong L. Liu T. Wang J. Shen X. A serum metabolomic investigation on hepatocellular carcinoma patients by chemical derivatization followed by gas chromatography/mass spectrometry.Rapid Commun. Mass Spectrom. 2008; 22: 3061-3068Crossref PubMed Scopus (84) Google Scholar, 21Wu H. Xue R. Dong L. Liu T. Deng C. Zeng H. Shen X. Metabolomic profiling of human urine in hepatocellular carcinoma patients using gas chromatography/mass spectrometry.Anal. Chim. Acta. 2009; 648: 98-104Crossref PubMed Scopus (144) Google Scholar), including nucleosides, butanoic acid, ethanimidic acid, glycerol, isoleucine, valine, aminomalonic acid, glycine, tyrosine, threonine, etc. It is generally accepted that a single analytical technique could only identify a limited number of the metabolites, and therefore, multiple complementary analytical platforms are needed for an enhanced metabolic visualization. We reported an enhanced metabolomic profiling study using a combined GC-MS and LC-MS analytical platform in 2007 on the metabolic disruption associated with nephrotoxicity by aristolochic acid intervention in a rat model (22Ni Y. Su M. Qiu Y. Chen M. Liu Y. Zhao A. Jia W. Metabolic profiling using combined GC-MS and LC-MS provides a systems understanding of aristolochic acid-induced nephrotoxicity in rat.FEBS Lett. 2007; 581: 707-711Crossref PubMed Scopus (112) Google Scholar). We have recently demonstrated that a combination of gas chromatography time-of-flight mass spectrometry (GC-TOFMS) and ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-QTOFMS) significantly increased the number of serum metabolite markers identified in a clinical metabolomic study of colorectal cancer (23Qiu Y. Cai G. Su M. Chen T. Zheng X. Xu Y. Ni Y. Zhao A. Xu L.X. Cai S. Jia W. Serum Metabolite Profiling of Human Colorectal Cancer Using GC-TOFMS and UPLC-QTOFMS.J. Proteome Res. 2009; 8: 4844-4850Crossref PubMed Scopus (329) Google Scholar). In this study, we conducted a comprehensive analysis of the serum and urine metabolites in 177 participants (71 healthy individuals, 24 benign liver tumor patients, and 82 HCC patients diagnosed as stage I, II, III, and IV, detailed information is listed in Table I) using GC-TOFMS and UPLC-QTOFMS. The metabolic variations in HCC patients with different cancer stages were comprehensively investigated. The differential metabolites identified in HCC patients were cross checked by the two analytical methods as well as by the results from two biological specimens, serum, and urine.Table IClinical information of study cohortsHCC patients (n = 82)Benign liver tumor patientsa24 benign liver tumor patients include 8 with hemangioma, 6 with focal nodular hyperplasia of liver, 4 with liver cirrhosis, 2 with liver cyst, 1 with intrahepatic bile duct stone and 1 with recurrent hemangioma after surgery. (n = 24)Healthy control (n = 71)Age (Mean, range)55, 29–7644, 18–6555, 42–65 Male/Female55/2713/1139/32Stage IbTNM Classification.33 (M21/F12)//Stage IIbTNM Classification.20 (M16/F4)//Stage IIIbTNM Classification.22 (M13/F9)//Stage IVbTNM Classification.7 (M5/F2)//AFP value (mean, range)cAFP values were provided for 52 (M34/F18) among a total of 82 HCC patients, and 9(M5/F4) among the 24 benign liver tumor patients, others were labeled as “Negative” or “Positive” but without a specific AFP value; M, male; F, female.5010.84, 1.30–60500.0060.74, 1.20–288.20/ALT47.1333.87/AST52.7339.04/ Liver cirrhosis (%)80.7725.00/HBsAg (positive %)66.6745.80/a 24 benign liver tumor patients include 8 with hemangioma, 6 with focal nodular hyperplasia of liver, 4 with liver cirrhosis, 2 with liver cyst, 1 with intrahepatic bile duct stone and 1 with recurrent hemangioma after surgery.b TNM Classification.c AFP values were provided for 52 (M34/F18) among a total of 82 HCC patients, and 9(M5/F4) among the 24 benign liver tumor patients, others were labeled as “Negative” or “Positive” but without a specific AFP value; M, male; F, female. Open table in a new tab A total of 82 HCC patients, 52 males and 30 females, aged 29 to 76 years old, and 24 benign, 13 males and 11 females, aged 18 to 65 years old, were enrolled in this study. The proportion of females in this cohort is higher than the national average number (the ratio of males/females is about 3:1) in favor of males. No significance is attached to the high proportion of females in the study population because the patients were taken from sequentially presenting patients in a single unit. Patient characteristics, staging of disease and other parameters are shown in Table I. The clinical diagnosis and pathological reports of all the patients were obtained from Zhongshan Hospital, Fudan University, Shanghai, China. Control samples were collected from a total of 71 healthy volunteers (39 males and 32 females, aged 42 to 65 years old) using the same sample collection protocol, and any subjects with inflammatory conditions, steatohepatitis, or gastrointestinal tract disorders were excluded. The average level of serum AFP in the HCC group is 5010.84 ng/ml ranging from 1.3 to 60,500 ng/ml, any AFP values higher than 60,500 ng/ml were recorded as 60,500 ng/ml. Ten serum enzyme levels correlating to liver function for HCC patients and benign liver tumor patients were measured (detailed information is provided in supplemental Table S1 and S2). Tumor invasion of neighboring organs, lesion nature and dimension, and presence of angiolymphatic or perineural invasion were also recorded. Serum and urine samples were collected in the morning before breakfast from all the participants. Serum samples were placed into clean tubes and kept at −80 °C until analysis. The collected urine samples were centrifuged at 3000 rpm for 10 min at 4 °C to remove suspended debris, and the resulting supernatants were immediately stored at −80 °C without any preservatives. The protocol was approved by the Zhongshan Hospital Institutional Review Board and written consents were signed by all participants before the study. Serum samples were derivatized and subsequently analyzed by GC-TOFMS following our previously published protocols (23Qiu Y. Cai G. Su M. Chen T. Zheng X. Xu Y. Ni Y. Zhao A. Xu L.X. Cai S. Jia W. Serum Metabolite Profiling of Human Colorectal Cancer Using GC-TOFMS and UPLC-QTOFMS.J. Proteome Res. 2009; 8: 4844-4850Crossref PubMed Scopus (329) Google Scholar). A 100 μl aliquot of serum sample was spiked with two internal standards (10 μl l-2-chlorophenylalanine in water, 0.3 mg/ml; 10 μl heptadecanoic acid in methanol, 1 mg/ml) and vortexed for 10 s. The mixed solution was extracted with 300 μl of methanol/chloroform (3:1) and vortexed for 30 s. After storing for 10 min at −20 °C, the samples were centrifuged at 10,000 rpm for 10 min. An aliquot of the 300 μl supernatant was transferred to a glass sampling vial to vacuum dry at room temperature. The residue was derivatized using a two-step procedure. First, 80 μl methoxyamine (15 mg/ml in pyridine,) was added to the vial and kept at 30 °C for 90 min followed by 80 μl BSTFA (1%TMCS) at 70 °C for 60 min. Each 1 μl aliquot of the derivatized solution was injected in spitless mode into an Agilent 6890N gas chromatography coupled with a Pegasus HT time-of-flight mass spectrometer (Leco Corporation, St Joseph, MI). Separation was achieved on a DB-5MS capillary column (30 m × 250 μm I.D., 0.25-μm film thickness; (5%-phenyl)-methylpolysiloxane bonded and crosslinked; Agilent J&W Scientific, Folsom, CA) with helium as the carrier gas at a constant flow rate of 1.0 ml/min. The temperature of injection, transfer interface, and ion source was set to 270 °C, 260 °C, and 200 °C, respectively. The GC temperature programming was set to 2 min isothermal heating at 80 °C, followed by 10 °C/min oven temperature ramps to 180 °C, 5 °C/min to 240 °C, and 25 °C/min to 290 °C, and a final 9 min maintenance at 290 °C. Electron impact ionization (70 eV) at full scan mode (m/z 30–600) was used, with an acquisition rate of 20 spectrum/second in the TOFMS setting. Urine samples for GC-TOFMS analysis was processed according to our previously published protocol (24Qiu Y. Su M. Liu Y. Chen M. Gu J. Zhang J. Jia W. Application of ethyl chloroformate derivatization for gas chromatography-mass spectrometry based metabonomic profiling.Anal. Chim. Acta. 2007; 583: 277-283Crossref PubMed Scopus (159) Google Scholar). Each 600 μl aliquot of standard mixture or diluted urine sample (urine/water = 1:1, v/v) was added to a screw-top glass tube. After adding 100 μl of l-2-chlorophenylalanine (0.1 mg/ml), 400 μl of anhydrous ethanol, and 100 μl of pyridine to the urine sample, 50 μl of ethyl chloroformate was added for first derivatization at 20.0 ± 0.1 °C. The pooled mixtures were sonicated at 40 kHz for 60 s. Subsequently, extraction was performed using 300 μl of chloroform, with the aqueous layer pH carefully adjusted to 9–10 using 100 μl of NaOH (7 m). The derivatization procedure was repeated with the addition of 50 μl ethyl chloroformate into the aforementioned products. After the two successive derivatization steps, the overall mixtures were vortexed for 30 s and centrifuged for 3 min at 3,000 rpm. The aqueous layer was aspirated off, whereas the remaining chloroform layer containing derivatives were isolated and dried with anhydrous sodium sulfate and subsequently subjected to GC-TOFMS analysis. The derivatized extracts were analyzed with an Agilent 6890N gas chromatography coupled with a Pegasus HT time-of-flight mass spectrometer (Leco Corporation). A 1-μl extract aliquot of the extracts was injected into a DB-5MS capillary column coated with 5% diphenyl cross-linked 95% dimethylpolysiloxane (30m × 250 μm i.d., 0.25-μm film thickness; Agilent J&W Scientific, Folsom, CA) in the split mode (3:1). Either the injection temperature or the interface temperature was set to 260 °C; and the ion source temperature was adjusted to 200 °C. Initial GC oven temperature was 80 °C; 2 min after injection, the GC oven temperature was raised to 140 °C with 10 °C/min, to 240 °C at a rate of 10 °C/min, to 290 °C with 15 °C/min again, and finally held at 290 °C for 3 min. Helium was the carrier gas with a flow rate set at 1 ml/min. The measurements were made with electron impact ionization (70 eV) in the full scan mode (m/z 30–550). Serum sample preparation and analysis with UPLC-QTOFMS was performed according to our published report (23Qiu Y. Cai G. Su M. Chen T. Zheng X. Xu Y. Ni Y. Zhao A. Xu L.X. Cai S. Jia W. Serum Metabolite Profiling of Human Colorectal Cancer Using GC-TOFMS and UPLC-QTOFMS.J. Proteome Res. 2009; 8: 4844-4850Crossref PubMed Scopus (329) Google Scholar). Each 100 μl of serum was used for metabolite extraction before UPLC-QTOFMS analysis. The metabolite extraction procedure was carried out after adding 100 μl of water (containing 0.1 mg/ml l-2-chlorophenylalanine as the internal standard) and 400 μl of a mixture of methanol and acetonitrile (5:3) to 100 μl of serum. After vortexing for 2 min, the mixture was stored at room temperature for 10 min, centrifuged at 12,000 rpm for 20 min. The supernatant was filtered through a syringe filter (0.22 μm) and transferred into the sampling vial pending UPLC-QTOFMS analysis. A 5 μl aliquot of the filtrate was subjected at a random order into a 100 mm × 2.1 mm, 1.7 μm BEH C18 column (Waters, Milford, MA) held at 40 °C using an ultra performance liquid chromatography system (Waters). The column was eluted with a linear gradient of 1–20% B over 0–1 min, 20–70% B over 1–3 min, 70–85% B over 3–8 min, 85–100% B over 8–9 min, the composition was held at 100% B for 0.5 min. For positive ion mode (ES+) where A = water with 0.1% formic acid and B = acetonitrile with 0.1% formic acid, whereas A = water and B = acetonitrile for negative ion mode (ES-). The flow rate was 0.4 ml/min. All the samples were kept at 4 °C during the analysis. The mass spectrometric data were collected using a Waters Q-TOF premier (Manchester, UK) equipped with an electrospray source operating in either positive or negative ion mode. The source temperature was set at 120 °C with a cone gas flow of 50 L/h, a desolvation gas temperature of 300 °C with a desolvation gas flow of 600 L/h. In the case of positive and negative ion mode the capillary voltage was set to 3.2 kV and 3 kV, and the cone voltage of 35 V and 50 V, respectively. Centroid data were collected from 50 to 1000 m/z with a scan time of 0.3 s and interscan delay of 0.02 s over a 9.5 min analysis time. MassLynx software (Waters) was used for system controlling and data acquisition. Leucine enkephalin was used as the lock mass (m/z 556.2771 in ES+ and 554.2615 in ES-) at a concentration of 100 ng/ml and flow rate of 0.2 ml/min for all analyses. Urine sample preparation was processed according to our previous work (25Xie G.X. Ye M. Wang Y.G. Ni Y. Su M.M. Huang H. Qiu M.F. Zhao A.H. Zheng X.J. Chen T.L. Jia W. Characterization of Pu-erh Tea Using Chemical and Metabolic Profiling Approaches.J. Agri. Food Chem. 2009; 57: 3046-3054Crossref PubMed Scopus (110) Google Scholar). The collected urine samples were centrifuged at 13,000 rpm for 10 min at 4 °C, and the resulting supernatants were immediately stored at −80 °C pending UPLC-QTOFMS analysis. Ultrapure water (500 μl) was added to urine (500 μl) and vortexed for 1 min, and then filtered through a syringe filter (0.22 μm) for UPLC-QTOFMS analysis. A 5 μl aliquot of the filtrate was injected into a 100 mm × 2.1 mm, 1.7 μm BEH C18 column (Waters) held at 40 °C using an ultra performance liquid chromatography system (Waters). The column was eluted with a linear gradient of 1–20% B over 0–1 min, 20–70% B over 1–3 min, 70–85% B over 3–8 min, 85–100% B over 8–9 min, the composition was held at 100% B for 0.5 min. For positive ion mode (ES+) where A = water with 0.1% formic acid and B = acetonitrile with 0.1% formic acid, whereas A = water and B = acetonitrile for negative ion mode (ES-). The flow rate was 0.4 ml/min. All the samples were kept at 4 °C during the analysis. The mass spectrometric data was collected using a Waters Q-TOF premier (Manchester, UK) equipped with an electrospray ion source operating in either positive or negative ion mode. The source temperature was set at 120 °C with a cone gas flow of 50 L/h, a desolvation gas temperature of 300 °C with a desolvation gas flow of 600 L/h. In the case of positive and negative ion modes the capillary voltage was set to 3.2 kV and 3 kV, and the cone voltage of 35 V and 50 V, respectively. Centroid data was collected from 50 to 1000 m/z with a scan time of 0.3 s and interscan delay of 0.02 s over a 9.5 min analysis time. Leucine enkephalin was used as the lock mass (m/z 556.2771 in ES+ mode and 554.2615 in ES- mode) at a concentration of 100 ng/ml and flow rate of 0.2 ml/min for all analyses. To verify the linearity, the spiked standard solution including chenodeoxycholic acid, deoxycholic acid, taurocholic acid, cholic acid, glycochenodeoxycholic acid, lithocholic acid, and glycocholic acid was prepared and diluted to appropriate concentration ranges for the establishment of calibration curves. The limit of detection (signal to noise ratio (S/N) = 3) and limit of quantitation (S/N = 9) were determined, respectively. Serum and urine samples were prepared as the method for UPLC-QTOFMS metabolomics analysis described in above section. The concentration of each metabolite was subsequently determined from the corresponding calibration curve. The acquired MS data from GC-TOFMS and UPLC-QTOFMS were analyzed according to our previously published work (23Qiu Y. Cai G. Su M. Chen T. Zheng X. Xu Y. Ni Y. Zhao A. Xu L.X. Cai S. Jia W. Serum Metabolite Profiling of Human Colorectal Cancer Using GC-TOFMS and UPLC-QTOFMS.J. 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