Summary of Study ST001152

This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR000771. The data can be accessed directly via it's Project DOI: 10.21228/M8197Z This work is supported by NIH grant, U2C- DK119886.

See: https://www.metabolomicsworkbench.org/about/howtocite.php

This study contains a large results data set and is not available in the mwTab file. It is only available for download via FTP as data file(s) here.

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Study IDST001152
Study TitleMetabolomic Analysis of Liver Tissues for Characterization of Hepatocellular Carcinoma
Study SummaryHepatocellular carcinoma (HCC) is the most common type of primary liver cancer causing more than half a million annual deaths world-wide. Understanding the molecular mechanisms contributing to HCC development and progression is highly desirable for improved surveillance, diagnosis and treatment. Liver tissue metabolomics has the potential to reflect the physiological changes behind HCC development. Also, it allows researchers to investigate racial disparities in HCC. The use of both gas chromatography – mass spectrometry (GC-MS) and liquid chromatography – mass spectrometry (LC-MS) platforms helps increase the metabolome coverage, allowing researchers to better unravel the relationships of metabolites and HCC. The objective of this study is to identify HCC-associated metabolites by analysis of liver tissues from HCC patients using both GC-MS and LC-MS platforms. Paired tumor and non-tumor tissues from 40 patients were analyzed by GC-MS and LC-MS. The patients consist of 14 African-Americans (AA), 10 Asian-Americans (AS), and 16 European-Americans (EA). The levels of the metabolites extracted from the solid liver tissue of the HCC area and adjacent non-HCC area were compared. Among the analytes detected by GC-MS and LC-MS with significant alterations, 17 were selected based on availability of putative metabolite identifications. These metabolites belong to TCA cycle, glycolysis, purines, and lipid metabolism, and have been previously reported in liver metabolomics studies where high correlation with HCC progression was implied. We demonstrated that metabolites that are related to HCC pathogenesis can be identified through metabolomics analysis of liver tissues by both GC-MS and LC-MS. In addition, this analysis has led to the identification of metabolites associated with HCC in a race-specific manner.
Institute
Georgetown University
DepartmentOncology
LaboratoryRessom Lab
Last NameDi Poto
First NameCristina
Address3970 Reservoir Rd. NW, Research Bldg., Room W325
Emailcd329@georgetown.edu
Phone2026872926
Submit Date2019-03-07
Num Groups4
Total Subjects40
Raw Data AvailableYes
Raw Data File Type(s)cdf, raw(Waters)
Analysis Type DetailGC-MS/LC-MS
Release Date2020-03-03
Release Version1
Cristina Di Poto Cristina Di Poto
https://dx.doi.org/10.21228/M8197Z
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

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Sample Preparation:

Sampleprep ID:SP001225
Sampleprep Summary:10 mg of liver tissue was homogenized on ice with 1 mL of pre-chilled methanol:water (1:1) containing five internal standards: 0.001 ppm debrisoquine, 0.004 ppm 4-nitro benzoic acid, 0.0004 ppb stearoyl (d35)-2-hydroxy-glycerophosphocholine, 0.2 ppb D-erythro-sphingosine (d7)-1-phosphate, and 2 ppm Myristic-d27 acid. Homogenized samples were centrifuged at 14.500 g, at 4°C for 15 minutes. Supernatant (S1) was collected and divided in two aliquots (one for GC-MS and one for LC-MS analysis), while the remaining pellet (P1) was kept at -80°C until further extraction. For the extraction of medium to polar compounds, 1:1 volume of pre-chilled acetonitrile was added to the two aliquots (GC&LC), vortex-mixed and kept on ice for 20 minutes. Samples were centrifuged again at 14.500 g, at 4°C for 15 minutes, and supernatant (S2) was collected and concentrated to dryness in a speedvac system operated at room temperature. Pellets (P2 and P3) and supernatants were stored at -80°C. For the extraction of low-polar compounds, P1 was resuspended with 500μl of pre-chilled dichloromethane:methanol (3:1) while P2, and P3 with 125 μL of the same mix. Pellets were sonicated on ice for 90sec, combined and centrifuged at 14.500 g, at 4°C for 20 minutes. Supernatant (S3) was collected, split in two aliquots (one for GC-MS and one for LC-MS analysis) and a 1:1 volume of pre-chilled acetonitrile was added to both aliquots (GC&LC), vortexed and kept on ice for 20 minutes. Samples were then centrifuged at 14.500 g for 15 min at 4°C while pellets were kept at -80 °C for protein quantitation. Finally, supernatants (S4) were concentrated to dryness by speedvac and kept at -80°C until the day of analysis. Blank samples were prepared together with the human samples by adding all the reagents to an empty tube and following the same sample preparation steps. Dried supernatant (S2) collected for GC-MS analysis underwent derivatization step. Samples were derivatized in each batch prior to injection following a two-stage process of oximation and trimethylsilylation (-Si(CH3)3). Briefly, 20µL of a 20mg/mL methoxyamine hydrochloride in pyridine were added to the dried extracts, vortexed and incubated at 30°C for 90 minutes. After returning the samples to room temperature, 80µL of MSTFA were added, vortex-mixed and incubated at 30°C for 30 minutes. Samples were then centrifuged at 14,500 g for 15 minutes, and 60µL of the supernatant were transferred into 250µL clear glass autosampler vials. Finally, 20µL of 0.006 µg/µL C18 Methyl Stearate in hexane were added to the vial prior to injection. For quality assessment, Myristic-d27 acid was spiked into the working solution to verify tissue metabolites extraction and derivatization steps. C18 Methyl Stearate was added just before GC-MS analysis to monitor each sample injection. QC samples (QCs) were generated by pooling together the supernatant obtained after derivatization of samples of each biological group in each batch separately. A retention index (RI) standard sample was prepared by mixing fatty acid methyl esters (FAMEs) with alkanes. Specifically, FAMEs C8, C9, C10, C12, C14, C16, C18, C20, C22, C24, C26, C28 and C30 linear chain length were individually dissolved in chloroform at concentrations of 0.8 mg/mL (C8 – C16) and 0.4 mg/ml (C18 – C30) to generate FAME-1 stock solutions. 100 µL of each FAME-1 were mixed together and 1.2 mL of chloroform were added for a final volume of 2.5mL generating FAME-2 solution. Alkanes, containing all even CnH2n+2 from C10 to C40, were purchased as a mixture at a concentration of 50mg/L in n-heptane. Alkane mixture were mixed with FAME-2 markers and hexane at a ratio of 1:2:17 and vortex-mixed prior to injection into the GC-MS. Dried supernatants (S2 & S4) collected from the first and second extraction for LC-MS analysis were reconstituted with 125 μL of methanol:acetonitrile:water (50:25:25) each, and combined for a total volume of 250 μL. d35-lysophosphocholine and d7-sphingosine-1-phosphate were included to determine the quality of the metabolite extraction. Debrisoquine and 4-nitrobenzoic acid were used to assess equipment performance. QCs were generated by pooling together the supernatant obtained after resuspension in appropriate solvent of each biological group.
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