Europe PMC

This website requires cookies, and the limited processing of your personal data in order to function. By using the site you are agreeing to this as outlined in our privacy notice and cookie policy.

Glucose catabolism in the rabbit VX2 tumor model for liver cancer: characterization and targeting hexokinase.

Author information

Affiliations

  • 1. Department of Biological Chemistry, Johns Hopkins University, School of Medicine, 725 North Wolfe Street, Baltimore, MD 21205-2185, USA.
      Authors
    • Ko YH 1
    (1 author)

Cancer Letters, 01 Nov 2001, 173(1):83-91
https://doi.org/10.1016/s0304-3835(01)00667-x PMID: 11578813 

Abstract 

The rabbit VX2 tumor when implanted in the liver has proven convenient as a model for studying hepatocellular carcinomas. However, its metabolic properties have not been well studied. Significantly, studies described here show that the VX2 tumor exhibits a high glycolytic/high hexokinase phenotype that is retained following implantation and growth in rabbit liver. In addition, results of a limited screen show that the glycolytic rate is inhibited best by 2-deoxyglucose (2DOG) and 3-bromopyruvate (3BrPA), the former compound of which is phosphorylated by hexokinase but not further metabolized, while the latter directly inhibits hexokinase. Finally, when tested on hepatoma cells in culture both inhibitors facilitated cell death. These studies underscore the usefulness of the VX2 tumor model for the study of advanced liver cancer and for selecting anti-hepatoma agents.

Full text links 

Read article at publisher's site: https://doi.org/10.1016/s0304-3835(01)00667-x

References 

Articles referenced by this article (19)

Show 9 more references (10 of 19)

Citations & impact 

Impact metrics

208
Citations
Jump to Citations

Citations of article over time

Alternative metrics

Altmetric item for https://www.altmetric.com/details/3519988
Altmetric
Discover the attention surrounding your research
https://www.altmetric.com/details/3519988

Article citations

Go to all (208) article citations

Similar Articles 

To arrive at the top five similar articles we use a word-weighted algorithm to compare words from the Title and Abstract of each citation.

Funding 

Funders who supported this work.

NCI NIH HHS (1)