LC-MS based serum metabolomics for identification of hepatocellular carcinoma biomarkers in Egyptian cohort

Jun Feng Xiao, Rency S Varghese, Bin Zhou, Mohammad R Nezami Ranjbar, Yi Zhao, Tsung-Heng Tsai, Cristina Di Poto, Jinlian Wang, David Goerlitz, Yue Luo, Amrita K Cheema, Naglaa Sarhan, Hanan Soliman, Mahlet G Tadesse, Dina Hazem Ziada, Habtom W Ressom, Jun Feng Xiao, Rency S Varghese, Bin Zhou, Mohammad R Nezami Ranjbar, Yi Zhao, Tsung-Heng Tsai, Cristina Di Poto, Jinlian Wang, David Goerlitz, Yue Luo, Amrita K Cheema, Naglaa Sarhan, Hanan Soliman, Mahlet G Tadesse, Dina Hazem Ziada, Habtom W Ressom

Abstract

Although hepatocellular carcinoma (HCC) has been subjected to continuous investigation and its symptoms are well-known, early stage diagnosis of this disease remains difficult and the survival rate after diagnosis is typically very low (3-5%). Early and accurate detection of metabolic changes in the sera of patients with liver cirrhosis can help improve the prognosis of HCC and lead to a better understanding of its mechanism at the molecular level, thus providing patients with in-time treatment of the disease. In this study, we compared metabolite levels in sera of 40 HCC patients and 49 cirrhosis patients from Egypt by using ultraperformance liquid chromatography coupled with quadrupole time-of-flight mass spectrometer (UPLC-QTOF MS). Following data preprocessing, the most relevant ions in distinguishing HCC cases from cirrhotic controls are selected by statistical methods. Putative metabolite identifications for these ions are obtained through mass-based database search. The identities of some of the putative identifications are verified by comparing their MS/MS fragmentation patterns and retention times with those from authentic compounds. Finally, the serum samples are reanalyzed for quantitation of selected metabolites as candidate biomarkers of HCC. This quantitation was performed using isotope dilution by selected reaction monitoring (SRM) on a triple quadrupole linear ion trap (QqQLIT) coupled to UPLC. Statistical analysis of the UPLC-QTOF data identified 274 monoisotopic ion masses with statistically significant differences in ion intensities between HCC cases and cirrhotic controls. Putative identifications were obtained for 158 ions by mass based search against databases. We verified the identities of selected putative identifications including glycholic acid (GCA), glycodeoxycholic acid (GDCA), 3β, 6β-dihydroxy-5β-cholan-24-oic acid, oleoyl carnitine, and Phe-Phe. SRM-based quantitation confirmed significant differences between HCC and cirrhotic controls in metabolite levels of bile acid metabolites, long chain carnitines and small peptide. Our study provides useful insight into appropriate experimental design and computational methods for serum biomarker discovery using LC-MS/MS based metabolomics. This study has led to the identification of candidate biomarkers with significant changes in metabolite levels between HCC cases and cirrhotic controls. This is the first MS-based metabolic biomarker discovery study on Egyptian subjects that led to the identification of candidate metabolites that discriminate early stage HCC from patients with liver cirrhosis.

Figures

Figure 1
Figure 1
Workflow for analysis of UPLC-QTOF MS data from two batches of samples in four separate experiments.
Figure 2
Figure 2
Verification of metabolite GDCA (A1 and A2), Phe-Phe (B1and B2), Oleyol carnitine (C1 and C2), and 3beta, 6beta-dihydroxy-5beta-cholan-24-oic acid (D1 and D2). MS/MS spectrum of an authentic compound and MS/MS spectrum obtained from a serum sample are presented for each of the four metabolites.
Figure 3
Figure 3
Quantitation of seven candidate metabolites in sera of 40 HCC cases (29 stage I and 8 stage II & III) and 49 cirrhotic controls.

Source: PubMed

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