Project description: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.

Project description: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.

Project description:Prostate cancer incidence and related mortality are disproportionately higher in African American (AA) men than European American (EA) men, but the molecular mechanisms contributing to racial disparities are not fully elucidated. To identify molecular factors that can contribute to disease biology in prostate cancer from AA and EA men, we utilized a multi-omics approach to measure and integrate DNA methylation with gene expression changes. We compared and contrasted results from adjacent non-tumor and tumor tissues from AA and EA men. We found that hypermethylated regions are enriched for PRC2 and H3K27me3 pathways and EZH2/SUZ12 cofactors in a race-independent manner. On the other hand, hypomethylated regions in prostate tumors from AA men were enriched for olfactory/ribosomal pathways as well as distinct cofactors such as CTCF and KMT2A. DNA methylation at transcription start sites and 5’-UTR at GATA3, an androgen receptor (AR) coregulator, is associated with decreased gene expression in prostate tumors of AA men. Our analysis also showed an inverse correlation between DNA methylation and RNA expression of AR transcriptional targets, such as TRIM63, in prostate tumors of AA men. Our observations suggest a dysregulation of the AR signaling pathway in prostate cancer from AA men. To determine whether targeting AR results in race-specific gene expression changes, we utilized a prostate-cancer-specific Boolean network. Our simulation revealed that prolonged AR inhibition results in significant dysregulation in TGF-β, IDH1, and cell cycle pathways in prostate cancer of AA men. We expanded our observation of gene expression changes in the Boolean network and investigated RNA-sequencing data to better understand overall transcriptional alterations occurring in prostate tumors from AA and EA men. We found that gene expression changes related to microtubules, a subset of immune-related, and TMPRSS2-fusion pathways were dysregulated in prostate tumors of AA men and corresponded with progression-free survival of AA men. Altogether, the current study dissects complex signaling networks that are clinically actionable in prostate cancer from AA and EA men.

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Identification of Race-Associated Metabolite Biomarkers for Hepatocellular Carcinoma

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