Literature DB >> 24374503

Targeting glucose metabolism in patients with cancer.

Shannon E Elf1, Jing Chen.   

Abstract

Nearly a century ago, Otto Warburg made the astute observation that the metabolic properties of cancer cells differ markedly from those of normal cells. Several decades passed before the concept of exploiting cancer cell metabolism came into clinical practice with the advent of chemotherapy, the underlying principle of which is to target rapidly dividing cells by interfering with critical processes that are all, on some level, driven by cell metabolism. Although chemotherapy can be quite effective, success rates are highly variable and the adverse effects associated with treatment often outweigh the benefits due to the fact that chemotherapy is indiscriminately cytotoxic against all rapidly dividing cells, cancerous or healthy. During the past several years, a more intricate understanding of cancer cell metabolism has permitted the development of targeted therapies that aim to specifically target cancer cells and spare healthy tissue by exploiting the altered metabolism of cancer cells. The identification of new metabolic targets and the subsequent development of small-molecule inhibitors of metabolic enzymes have demonstrated the utility and promise of targeting cancer cell metabolism as an anticancer strategy. This review summarizes recent advances in the identification and characterization of several metabolic enzymes as emerging anticancer targets.
© 2013 American Cancer Society.

Entities:  

Keywords:  anticancer targets; cancer metabolism; metabolic enzymes; small-molecule inhibitors; the Warburg effect

Mesh:

Substances:

Year:  2013        PMID: 24374503      PMCID: PMC4507501          DOI: 10.1002/cncr.28501

Source DB:  PubMed          Journal:  Cancer        ISSN: 0008-543X            Impact factor:   6.860


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Journal:  Cancer Biol Ther       Date:  2006-12-26       Impact factor: 4.742

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Review 10.  New antimetabolites in cancer chemotherapy and their clinical impact.

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  42 in total

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Journal:  Pharmacogenomics J       Date:  2016-03-01       Impact factor: 3.550

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Authors:  Jianjun Han; Lu Zhang; Hui Guo; Weiya Z Wysham; Dario R Roque; Adam K Willson; Xiugui Sheng; Chunxiao Zhou; Victoria L Bae-Jump
Journal:  Gynecol Oncol       Date:  2015-06-30       Impact factor: 5.482

4.  Genetic variations in monocarboxylate transporter genes as predictors of clinical outcomes in non-small cell lung cancer.

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5.  Feasibility and antitumor efficacy in vivo, of simultaneously targeting glycolysis, glutaminolysis and fatty acid synthesis using lonidamine, 6-diazo-5-oxo-L-norleucine and orlistat in colon cancer.

Authors:  Diana Cervantes-Madrid; Guadalupe Dominguez-Gomez; Aurora Gonzalez-Fierro; Enrique Perez-Cardenas; Lucia Taja-Chayeb; Catalina Trejo-Becerril; Alfonso Duenas-Gonzalez
Journal:  Oncol Lett       Date:  2017-01-18       Impact factor: 2.967

6.  Proliferation and motility of hepatocellular, pancreatic and gastric cancer cells grown in a medium without glucose and arginine, but with galactose and ornithine.

Authors:  Minoru Tomizawa; Fuminobu Shinozaki; Yasufumi Motoyoshi; Takao Sugiyama; Shigenori Yamamoto; Naoki Ishige
Journal:  Oncol Lett       Date:  2017-01-04       Impact factor: 2.967

7.  Polymorphisms of monocarboxylate transporter genes are associated with clinical outcomes in patients with colorectal cancer.

Authors:  Fei Fei; Xu Guo; Yibing Chen; Xiaonan Liu; Jianfei Tu; Jinliang Xing; Zhinan Chen; Jiansong Ji; Xianli He
Journal:  J Cancer Res Clin Oncol       Date:  2014-12-10       Impact factor: 4.553

Review 8.  Non-coding RNAs: the new central dogma of cancer biology.

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9.  Imaging of Hsp70-positive tumors with cmHsp70.1 antibody-conjugated gold nanoparticles.

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10.  Two-color vibrational imaging of glucose metabolism using stimulated Raman scattering.

Authors:  Rong Long; Luyuan Zhang; Lingyan Shi; Yihui Shen; Fanghao Hu; Chen Zeng; Wei Min
Journal:  Chem Commun (Camb)       Date:  2017-12-08       Impact factor: 6.222

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