Literature DB >> 31773292

Clinical and metabolomics analysis of hepatocellular carcinoma patients with diabetes mellitus.

Hongping Xia1,2, Jianxiang Chen3, Karthik Sekar4, Ming Shi5, Tian Xie3, Kam M Hui6,7,8,9,10,11.   

Abstract

INTRODUCTION: Diabetes and cancer are among the most frequent causes of death worldwide. Recent epidemiological findings have indicated a link between diabetes and cancer in several organs, particularly the liver. A number of epidemiological studies have demonstrated that diabetes is an established independent risk factor for hepatocellular carcinoma (HCC). However, the metabolites connecting diabetes and HCC remains less well understood.
OBJECTIVES: The study aimed to identify clinical and metabolomics differences of HCC from patients with/without diabetes using comprehensive global metabolomics analysis.
METHODS: Metabolite profiling was conducted with the Metabolon platform for 120 human diabetes/non-diabetes HCC tumor/normal tissues. Standard statistical analyses were performed using the Partek Genomics Suite on log-transformed data. Principal component analysis (PCA) was conducted using all and dysregulated metabolites.
RESULTS: We identified a group of metabolites that are differentially expressed in the tumor tissues of diabetes HCC compared to non-diabetes HCC patients. Meanwhile, we also identified a group of metabolites that are differentially expressed in the matched normal liver tissues of diabetes HCC compared to non-diabetes HCC patients. Some metabolites are consistently dysregulated in the tumor or matched normal tissues of HCC with or without diabetes. However, some metabolites, including 2-hydroxystearate, were only overexpressed in the tumor tissues of HCC with diabetes and associated with the glucose level.
CONCLUSION: Metabolic profiling identifies distinct dysregulated metabolites in HCC patients with/without diabetes.

Entities:  

Keywords:  Diabetes; Hepatocellular carcinoma; Metabolites; Metabolomics; Principal component analysis

Mesh:

Substances:

Year:  2019        PMID: 31773292     DOI: 10.1007/s11306-019-1619-x

Source DB:  PubMed          Journal:  Metabolomics        ISSN: 1573-3882            Impact factor:   4.290


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