8 research outputs found
Workflow of our GC-MS based untargeted metabolomic and targeted analyses for biomarker discovery.
<p>The number of candidate metabolites analyzed at specific steps is shown in parenthesis.</p
Example of a retrieved EIC for valine.
<p>The inset in the top left shows the expected ratios for the fragments based on the library to guide the visual inspection. The doted vertical lines show the expected and estimated elution time of the analyte. Although, the background signal of 73 from other compounds is reflected in the apex score, its impact on the AUC is diminished by baseline correction.</p
List of nine analytes confirmed by targeted analysis with their expected retention time and molecular weights for quantifier (M1) and qualifier fragments (M2-M3).
<p>* Number of TMS in Fiehn library</p><p>Fragment with a molecular weight of 73 was also monitored by default for all the analytes.</p
Evaluation of the metabolites from targeted analysis using PLS-DA and OPLS-DA.
<p>A: Score plot obtained by PLS-DA with HCC cases labeled by red triangles and patients with liver cirrhosis by blue dots. Stage II & III HCC cases are labeled with solid triangles. B: Loading plot from PLS-DA. C: S-plot obtained by OPLS-DA. The nine metabolites previously selected by univariate analysis are highlighted in B and C.</p
Metabolites with significant changes in their levels in HCC vs. cirrhosis based on targeted analysis of plasma by GC-SIM-MS.
<p>The metabolites in the top two panels show increasing trend with the progression of HCC. The metabolites in the bottom panel are down-regulated in HCC vs. cirrhosis. While lactic acid and citric acid show decreasing trend with the progression of HCC, sorbose is down-regulated overall in HCC vs. cirrhosis.</p
Pathway and network analysis of 24 metabolites recognized by IPA from the candidates discovered by GC-MS and LC-MS based analyses.
<p>A: top 10 canonical pathways based on 24 metabolites. B: network involving 13 out of the 24 metabolites (up-regulated in HCC vs. cirrhosis marked in red, down-regulated in HCC vs. cirrhosis marked in green).</p
LC–MS Based Serum Metabolomics for Identification of Hepatocellular Carcinoma Biomarkers in Egyptian Cohort
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 <b>274</b> monoisotopic ion masses with statistically
significant differences in ion intensities between HCC cases and cirrhotic
controls. Putative identifications were obtained for <b>158</b> 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