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Accessing cancer metabolic pathways by the use of microarray technology.

Abstract
Cancer metabolism is currently re-evaluated by the research community with the aim to investigate possible opportunities for the development of targeted therapies. Firstly discovered by Warburg et al. in the beginning of the last century, it is now a widely accepted hypothesis that cancer cells possess a severely deregulated form of glycolysis also under aerobic conditions. Accompanied by a deregulated glycolysis is an increasing dependence on glucose and glutamine, this characteristic offers a striking opportunity for new kinds of anti-cancer drugs. A feasible approach in this endeavour is the combined use of metabolic and transcriptomic information. Microarrays provide nowadays a reliable way for accessing the transcriptomic layer, even higher layers of biological information are in the scope. In this review we present the possibilities and also the limitations of this technique starting from the early phase of the microarray to the modern concepts of bioinformatics and systems biology. By highlighting also clinicopathological possibilities it is demonstrated that microarray technology is able to integrate various layers of biological information. Case studies incorporating aspects of cancer metabolism into therapy relevant applications and some potential new targets of cancer metabolism for novel cancer therapies are pointed out. These new cancer therapies can lead to the establishment of personalized medicine by use of custom based microarray platforms introducing treatment options in clinical decision making.
AuthorsMartin Koch, Michael Wiese
JournalCurrent pharmaceutical design (Curr Pharm Des) Vol. 19 Issue 4 Pg. 790-805 ( 2013) ISSN: 1873-4286 [Electronic] United Arab Emirates
PMID23016863 (Publication Type: Journal Article, Review)
Chemical References
  • Antineoplastic Agents
  • Glucose
Topics
  • Antineoplastic Agents (pharmacology)
  • Computational Biology (methods)
  • Drug Design
  • Glucose (metabolism)
  • Glycolysis
  • Humans
  • Microarray Analysis (methods)
  • Molecular Targeted Therapy
  • Neoplasms (drug therapy, metabolism)
  • Precision Medicine
  • Systems Biology (methods)

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