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.
Study ID | ST001152 |
Study Title | Metabolomic Analysis of Liver Tissues for Characterization of Hepatocellular Carcinoma |
Study Summary | Hepatocellular 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 |
Department | Oncology |
Laboratory | Ressom Lab |
Last Name | Di Poto |
First Name | Cristina |
Address | 3970 Reservoir Rd. NW, Research Bldg., Room W325 |
cd329@georgetown.edu | |
Phone | 2026872926 |
Submit Date | 2019-03-07 |
Num Groups | 4 |
Total Subjects | 40 |
Raw Data Available | Yes |
Raw Data File Type(s) | cdf, raw(Waters) |
Analysis Type Detail | GC-MS/LC-MS |
Release Date | 2020-03-03 |
Release Version | 1 |
Select appropriate tab below to view additional metadata details:
Project:
Project ID: | PR000771 |
Project DOI: | doi: 10.21228/M8197Z |
Project Title: | Metabolomic Analysis of Liver Tissues for Characterization of Hepatocellular Carcinoma |
Project Summary: | Hepatocellular 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 |
Department: | Oncology |
Laboratory: | Ressom Lab |
Last Name: | Ressom |
First Name: | Habtom |
Address: | 3970 Reservoir Rd., NW, Research Bldg, Room W325, Washington, DC, 20007, USA |
Email: | hwr@georgetown.edu |
Phone: | 2026872283 |
Subject:
Subject ID: | SU001217 |
Subject Type: | Human |
Subject Species: | Homo sapiens |
Taxonomy ID: | 9606 |
Species Group: | Mammals |
Factors:
Subject type: Human; Subject species: Homo sapiens (Factor headings shown in green)
mb_sample_id | local_sample_id | Group | RACE |
---|---|---|---|
SA079912 | HCC/CIRR 07_ADJ/C | ADJ/C | Black |
SA079913 | HCC/CIRR 08_ADJ/C | ADJ/C | Black |
SA079914 | HCC/CIRR 02_ADJ/C | ADJ/C | Black |
SA079915 | HCC/CIRR 01_ADJ/C | ADJ/C | Black |
SA079916 | HCC/CIRR 06_ADJ/C | ADJ/C | Black |
SA079917 | HCC/CIRR 09_ADJ/C | ADJ/C | White |
SA079918 | HCC/CIRR 10_ADJ/C | ADJ/C | White |
SA079919 | HCC/CIRR 05_ADJ/C | ADJ/C | White |
SA079920 | HCC/CIRR 03_ADJ/C | ADJ/C | White |
SA079921 | HCC/CIRR 04_ADJ/C | ADJ/C | White |
SA079922 | HCC/NOR 24_ADJ/N | ADJ/N | Asian |
SA079923 | HCC/NOR 23_ADJ/N | ADJ/N | Asian |
SA079924 | HCC/NOR 30_ADJ/N | ADJ/N | Asian |
SA079925 | HCC/NOR 29_ADJ/N | ADJ/N | Asian |
SA079926 | HCC/NOR 25_ADJ/N | ADJ/N | Asian |
SA079927 | HCC/NOR 27_ADJ/N | ADJ/N | Asian |
SA079928 | HCC/NOR 28_ADJ/N | ADJ/N | Asian |
SA079929 | HCC/NOR 26_ADJ/N | ADJ/N | Asian |
SA079930 | HCC/NOR 17_ADJ/N | ADJ/N | Asian |
SA079931 | HCC/NOR 22_ADJ/N | ADJ/N | Asian |
SA079932 | HCC/NOR 07_ADJ/N | ADJ/N | Black |
SA079933 | HCC/NOR 12_ADJ/N | ADJ/N | Black |
SA079934 | HCC/NOR 08_ADJ/N | ADJ/N | Black |
SA079935 | HCC/NOR 10_ADJ/N | ADJ/N | Black |
SA079936 | HCC/NOR 04_ADJ/N | ADJ/N | Black |
SA079937 | HCC/NOR 16_ADJ/N | ADJ/N | Black |
SA079938 | HCC/NOR 03_ADJ/N | ADJ/N | Black |
SA079939 | HCC/NOR 21_ADJ/N | ADJ/N | Black |
SA079940 | HCC/NOR 19_ADJ/N | ADJ/N | Black |
SA079941 | HCC/NOR 20_ADJ/N | ADJ/N | White |
SA079942 | HCC/NOR 01_ADJ/N | ADJ/N | White |
SA079943 | HCC/NOR 13_ADJ/N | ADJ/N | White |
SA079944 | HCC/NOR 09_ADJ/N | ADJ/N | White |
SA079945 | HCC/NOR 15_ADJ/N | ADJ/N | White |
SA079946 | HCC/NOR 14_ADJ/N | ADJ/N | White |
SA079947 | HCC/NOR 18_ADJ/N | ADJ/N | White |
SA079948 | HCC/NOR 11_ADJ/N | ADJ/N | White |
SA079949 | HCC/NOR 06_ADJ/N | ADJ/N | White |
SA079950 | HCC/NOR 05_ADJ/N | ADJ/N | White |
SA079951 | HCC/NOR 02_ADJ/N | ADJ/N | White |
SA079952 | Blank_B | Blank | - |
SA079953 | Blank_A | Blank | - |
SA079954 | Blank_C | Blank | - |
SA079955 | Blank_D | Blank | - |
SA079956 | Blank_E | Blank | - |
SA079957 | HCC/CIRR 02_HCC/C | HCC/C | Black |
SA079958 | HCC/CIRR 08_HCC/C | HCC/C | Black |
SA079959 | HCC/CIRR 07_HCC/C | HCC/C | Black |
SA079960 | HCC/CIRR 01_HCC/C | HCC/C | Black |
SA079961 | HCC/CIRR 06_HCC/C | HCC/C | Black |
SA079962 | HCC/CIRR 10_HCC/C | HCC/C | White |
SA079963 | HCC/CIRR 09_HCC/C | HCC/C | White |
SA079964 | HCC/CIRR 05_HCC/C | HCC/C | White |
SA079965 | HCC/CIRR 04_HCC/C | HCC/C | White |
SA079966 | HCC/CIRR 03_HCC/C | HCC/C | White |
SA079967 | HCC/NOR 23_HCC/N | HCC/N | Asian |
SA079968 | HCC/NOR 30_HCC/N | HCC/N | Asian |
SA079969 | HCC/NOR 29_HCC/N | HCC/N | Asian |
SA079970 | HCC/NOR 24_HCC/N | HCC/N | Asian |
SA079971 | HCC/NOR 27_HCC/N | HCC/N | Asian |
SA079972 | HCC/NOR 26_HCC/N | HCC/N | Asian |
SA079973 | HCC/NOR 25_HCC/N | HCC/N | Asian |
SA079974 | HCC/NOR 28_HCC/N | HCC/N | Asian |
SA079975 | HCC/NOR 22_HCC/N | HCC/N | Asian |
SA079976 | HCC/NOR 17_HCC/N | HCC/N | Asian |
SA079977 | HCC/NOR 07_HCC/N | HCC/N | Black |
SA079978 | HCC/NOR 12_HCC/N | HCC/N | Black |
SA079979 | HCC/NOR 08_HCC/N | HCC/N | Black |
SA079980 | HCC/NOR 10_HCC/N | HCC/N | Black |
SA079981 | HCC/NOR 04_HCC/N | HCC/N | Black |
SA079982 | HCC/NOR 16_HCC/N | HCC/N | Black |
SA079983 | HCC/NOR 03_HCC/N | HCC/N | Black |
SA079984 | HCC/NOR 21_HCC/N | HCC/N | Black |
SA079985 | HCC/NOR 19_HCC/N | HCC/N | Black |
SA079986 | HCC/NOR 02_HCC/N | HCC/N | White |
SA079987 | HCC/NOR 09_HCC/N | HCC/N | White |
SA079988 | HCC/NOR 05_HCC/N | HCC/N | White |
SA079989 | HCC/NOR 06_HCC/N | HCC/N | White |
SA079990 | HCC/NOR 01_HCC/N | HCC/N | White |
SA079991 | HCC/NOR 18_HCC/N | HCC/N | White |
SA079992 | HCC/NOR 11_HCC/N | HCC/N | White |
SA079993 | HCC/NOR 15_HCC/N | HCC/N | White |
SA079994 | HCC/NOR 14_HCC/N | HCC/N | White |
SA079995 | HCC/NOR 13_HCC/N | HCC/N | White |
SA079996 | HCC/NOR 20_HCC/N | HCC/N | White |
SA079997 | QC_ADJ/C_4 | QC_ADJ/C | - |
SA079998 | QC_ADJ/C_3 | QC_ADJ/C | - |
SA079999 | QC_ADJ/C_1 | QC_ADJ/C | - |
SA080000 | QC_ADJ/C_5 | QC_ADJ/C | - |
SA080001 | QC_ADJ/C_2 | QC_ADJ/C | - |
SA080002 | QC_ADJ/C_6 | QC_ADJ/C | - |
SA080003 | QC_ADJ/N_7 | QC_ADJ/N | - |
SA080004 | QC_ADJ/N_8 | QC_ADJ/N | - |
SA080005 | QC_ADJ/N_6 | QC_ADJ/N | - |
SA080006 | QC_ADJ/N_4 | QC_ADJ/N | - |
SA080007 | QC_ADJ/N_3 | QC_ADJ/N | - |
SA080008 | QC_ADJ/N_5 | QC_ADJ/N | - |
SA080009 | QC_ADJ/N_9 | QC_ADJ/N | - |
SA080010 | QC_ADJ/N_1 | QC_ADJ/N | - |
SA080011 | QC_ADJ/N_15 | QC_ADJ/N | - |
Collection:
Collection ID: | CO001211 |
Collection Summary: | Adult patients were recruited at MedStar Georgetown University Hospital (MGUH). All participants provided informed consent to a protocol approved by the Institutional Review Board (IRB) at Georgetown University. Following the participant’s informed consent signature and enrollment, tissue samples were collected at the time of the surgical procedure and stored under liquid nitrogen until the day of metabolite extraction. HCC cases were diagnosed based on well-established diagnostic imaging criteria and/or histology. Clinical stages for HCC cases were determined based on the TNM staging system. |
Sample Type: | Liver |
Treatment:
Treatment ID: | TR001232 |
Treatment Summary: | Tissue samples were collected at the time of the surgical procedure and stored under liquid nitrogen until the day of metabolite extraction. |
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. |
Combined analysis:
Analysis ID | AN001900 | AN001901 | AN001902 |
---|---|---|---|
Analysis type | MS | MS | MS |
Chromatography type | GC | Reversed phase | Reversed phase |
Chromatography system | Agilent 7890A | Waters Acquity | Waters Acquity |
Column | Agilent DB5-MS (30m x 0.25mm, 0.25um) | Waters Acquity CSH C18 (100 x 2.1mm,1.7um) | Waters Acquity CSH C18 (100 x 2.1mm,1.7um) |
MS Type | EI | ESI | ESI |
MS instrument type | GC-TOF | QTOF | QTOF |
MS instrument name | Leco Pegasus HT TOF | Waters Synapt-G2-Si | Waters Synapt-G2-Si |
Ion Mode | POSITIVE | POSITIVE | NEGATIVE |
Units | Da | Da | Da |
Chromatography:
Chromatography ID: | CH001376 |
Instrument Name: | Agilent 7890A |
Column Name: | Agilent DB5-MS (30m x 0.25mm, 0.25um) |
Chromatography Type: | GC |
Chromatography ID: | CH001377 |
Instrument Name: | Waters Acquity |
Column Name: | Waters Acquity CSH C18 (100 x 2.1mm,1.7um) |
Chromatography Type: | Reversed phase |
MS:
MS ID: | MS001756 |
Analysis ID: | AN001900 |
Instrument Name: | Leco Pegasus HT TOF |
Instrument Type: | GC-TOF |
MS Type: | EI |
MS Comments: | Software Chromatof |
Ion Mode: | POSITIVE |
MS ID: | MS001757 |
Analysis ID: | AN001901 |
Instrument Name: | Waters Synapt-G2-Si |
Instrument Type: | QTOF |
MS Type: | ESI |
MS Comments: | Software XCMS |
Ion Mode: | POSITIVE |
MS ID: | MS001758 |
Analysis ID: | AN001902 |
Instrument Name: | Waters Synapt-G2-Si |
Instrument Type: | QTOF |
MS Type: | ESI |
MS Comments: | Software XCMS |
Ion Mode: | NEGATIVE |