Cancer Systems Biology: Is the devil in the glycolytic detail?

  • Kathryn Blount

    Student thesis: Phd


    An approach to investigating cancer that has recently seen resurgence of interest is the "Warburg effect". Otto Warburg originally described the altered metabolism of cancer cells and identified that they exhibit an increase in glucose uptake and lactate production. This up-regulation of glycolytic flux and glucose transport is now associated with 90% of cancers.In order to improve the overall understanding of the "Warburg effect" two forms of systems biology have been implemented - comparative in vitro analysis of kinetic activities and dynamic modelling. In this analysis, human breast cancer cell lines MCF-7, MDA-MB-231 and T47D and a non transformed breast cell line MCF-10A were used to identify key similarities and differences in kinetic activities across the glycolytic pathway. Additionally, activities of key glycolytic enzymes hexokinase, pyruvate kinase and lactate dehydrogenase were compared under hypoxic conditions to further understand regulation of cancer cells.The most prominent feature that arose from comparing the kinetic activities of the three malignant and one non-malignant cell line is that each cell line has its own specific set of activities for glycolysis. This indicates that there are differences in regulation across the glycolytic pathway for each of these cell lines. This is of specific interest in the search for therapeutic targets.Further, we determined that despite the prominence of oncogenic HIF signalling activities of hexokinase, pyruvate kinase and lactate dehydrogenase were further modulated by growth under hypoxic conditions.Despite the lack of obvious distinct kinetic differences between the non-cancerous and cancerous cells lines some discernible differences are apparent when modelled in silico.
    Date of Award1 Aug 2014
    Original languageEnglish
    Awarding Institution
    • The University of Manchester
    SupervisorHans Westerhoff (Supervisor) & Kaye Williams (Supervisor)


    • Breast Cancer Cell lines
    • Mathematical Modelling
    • Glycolysis
    • Enzyme Kinetics
    • Metabolomics

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