4.5 Article

Targeted Cancer Therapeutics: Biosynthetic and Energetic Pathways Characterized by Metabolomics and the Interplay with Key Cancer Regulatory Factors

期刊

CURRENT PHARMACEUTICAL DESIGN
卷 20, 期 15, 页码 2637-2647

出版社

BENTHAM SCIENCE PUBL LTD
DOI: 10.2174/13816128113199990489

关键词

Cancer; energy reprogramming; hypoxia; metabolomics; targeted therapy development

资金

  1. Canadian Cancer Society Research Institute
  2. Canadian Cancer Society
  3. Canada Research Chairs award

向作者/读者索取更多资源

Reprogramming of energy metabolism has recently been added to the list of hallmarks that define cancer. Cellular metabolism plays a central role in cancer initiation and progression to metastatic disease. Genotypic and phenotypic metabolic alterations are seen throughout tumourigenesis, allowing cancer cells to sustain increased rates of proliferation. Furthermore, this shift fuels necessary substrates for nucleotide, protein, and lipid synthesis to support cell growth. Beyond the 'Warburg effect', the widely observed increase in the glycolytic processing of glucose in cancer cells, numerous other metabolic changes have been characterized in cancer. Metabolomics provides a valuable platform for the investigation of the metabolic perturbations that occur in different disease states using a systems biology approach to determine metabolic profiles of biological samples. As cell metabolism is a complex network of interdependent pathways, local alterations will have an impact on overall tumor metabolism. In this review, we will highlight particular pathways, including glycolysis, nucleotide biosynthesis, lipid metabolism, and bioenergetics with an eye towards selected metabolic targets that may provide a novel approach to therapeutic development. Specific regulatory factors, including Myc, p53, HIF-1 and mTOR are briefly highlighted, as well as the key signaling pathways that can affect cellular metabolism. To demonstrate the powerful utility of high-throughput metabolite profiling techniques, we present a practical example of the metabolomic profiling of metastatic cells derived from a lung cancer metastasis model.

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