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Metabolomic Analysis of Liver Tissues for Characterization of Hepatocellular Carcinoma

ABSTRACT: 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.

ORGANISM(S): Human Homo Sapiens

TISSUE(S): Liver

DISEASE(S): Cancer

SUBMITTER: Cristina Di Poto

PROVIDER: ST001152 | MetabolomicsWorkbench | Thu Mar 07 00:00:00 GMT 2019

REPOSITORIES: MetabolomicsWorkbench

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Project description:Purpose: We generated extensive transcriptional and proteomic profiles from a Her2-driven mouse model of breast cancer that closely recapitulates human breast cancer. This report makes these data publicly available in raw and processed forms, as a resource to the community. Importantly, we previously made biospecimens from this same mouse model freely available through a sample repository, so researchers can obtain samples to test biological hypotheses without the need of breeding animals and collecting biospecimens. Experimental design: Twelve datasets are available, encompassing 841 LC-MS/MS experiments (plasma and tissues) and 255 microarray analyses of multiple tissues (thymus, spleen, liver, blood cells, and breast). Cases and controls were rigorously paired to avoid bias. Results: In total, 18,880 unique peptides were identified (PeptideProphet peptide error rate â¤1%), with 3884 and 1659 non-redundant protein groups identified in plasma and tissue datasets, respectively. Sixty-one of these protein groups overlapped between cancer plasma and cancer tissue. Conclusions and clinical relevance: These data are of use for advancing our understanding of cancer biology, for software and quality control tool development, investigations of analytical variation in MS/MS data, and selection of proteotypic peptides for MRM-MS. The availability of these datasets will contribute positively to clinical proteomics. Affymetrix GeneChip Mouse Genome 430 2.0 microarrays were used to profile whole tissues from 5 different tissue types of 25 tumor-bearing and 25 control mice of the Her2/Neu breast cancer mouse model. The 5 tissues tested were from breast, liver, spleen, blood cell, and thymus. The tumor-bearing mice were bitransgenic for MMTV-rtTA/TetO-NeuNT, and the control mice were transgenic for TetO-NeuNT only. The control mice were age- and cage-matched to the tumor-bearing mice. All samples were lysed and total RNA isolated and amplified prior to hybridization.

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Metabolomic Analysis of Liver Tissues for Characterization of Hepatocellular Carcinoma

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