LC–MS Based Serum Metabolomics for Identification of Hepatocellular Carcinoma Biomarkers in Egyptian Cohort

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 ultra-performance 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 along with other metabolites previously selected 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), 3beta, 6beta-dihydroxy-5beta-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.

UPLC-based metabonomic applications for discovering biomarkers of diseases in clinical chemistry

“…The results indicated that patients with HCC had decreased LPCs, increased long-chain and decreased medium-chain acylcarnitines, and increased aromatic and decreased branched-chain amino acid [30]. UPLC-QTOF/MS and UPLC triple quadrupole linear ion trap MS approaches were performed on qualitative and quantitative comparisons of metabolite levels in sera of HCC patients and cirrhosis patients from Egypt [31]. The metabolites including GCA, GDCA, 3β,6β-dihydroxy-5β-cholan-24-oic acid, oleoyl carnitine and Phe-Phe were identified by UPLC-QTOF/MS.…”

Lipid Metabolism in Liver Cancer

“…This phonotype was evidenced by the following metabolic changes including the decrease in glucose, citrate, and glycerol 3-phosphate but the increase in lactic acid and pyruvate [64][65][66][67][68][69]. On the other hand, the common induction of beta-oxidation was exemplified by the elevation of 2-oxoglutarate and reduction of free fatty acids, carnitine and carnitine esters [61,64,66,68,[70][71][72][73]. This theme will be further explored in the next section.…”

Optimal Algorithm for Metabolomics Classification and Feature Selection varies by Dataset

“…4 groups) rumen fluid dataset investigating the impact of altered diets of cows (Ametaj et al, 2010). The MS explores potential biomarkers of Hepatocellular Carcinoma in serum samples (Xiao et al 2012) and was accessed from the open source metabolomics data repository Metabolights (Haug et al, 2013) accession number MTBLS19.…”