Abstracts Category : Other

Analysis of metabolic activity in breast cancer cell lines via untargeted metabolomics

by Sbastien Dubuis

During tumorigenesis, metabolism of cancer cells is altered and fluxes in central metabolism are rerouted. Under the influence of oncogenes and tumor suppressors that modulate the expression of multiple enzymes, cancer cells increase fermentative metabolism of glucose to lactate independent of oxygenation, i.e. the so-called Warburg effect. Simultaneously, they activate glutaminolysis, upregulate serine synthesis or deregulate fatty acid synthesis. All these alterations allow cancer cells to grow by providing the essential building blocks necessary for proliferation. Yet, aberrant metabolic activity renders cancer cells more susceptible than normal tissue to drugs that target metabolic enzymes and hence provide potential therapeutic targets. However, the intertwined influences of oncogenes and the tumors microenvironment result in large heterogeneity in the metabolic alterations. For this reason, targeting cancer cell metabolism requires methods that allow investigation of intracellular metabolic fluxes. Intracellular metabolic fluxes cannot be measured directly and are inferred indirectly from metabolite levels and in silico models. However, approaches such as 13C metabolic flux analysis (MFA) or flux balance analysis (FBA) are poorly suited to calculate fluxes in mammalian cells or animal models. Alternatively, enzyme centric measurements, such as proteomics or transcriptomics, can be used to monitor the regulatory responses of cells, but fail to reveal the functional outcome, i.e. the impact on the metabolic fluxes. In this thesis, we set out to explore the pertinence of metabolomics as a tool to discover metabolic alterations in cancer cells. By comprehensively measuring the metabolic content of cells, we aim at discovering functional change, i.e. change in the metabolic fluxes. By using both top down (chapter 2) and data-driven (chapter 3 and 4) approaches we provide substantial evidences that changes in the metabolic pools revealed by untargeted metabolomics mirror changes in intracellular fluxes.For thorough investigation of the variability found in the metabolome content of cancer cells, we analyzed the intracellular metabolome of 18 breast cell lines using non-targeted mass spectrometry-based metabolomics in chapter 2. The cell lines were clinically well-characterized in terms of subtypes, which were relevant to breast cancer treatments, but no prior knowledge existed at a metabolic level. The expectations were that the intracellular metabolome of these cell lines is governed by clinical subtypes that are known to broadly affect cellular transcription. Contrary to the expectations, the metabolome patterns were not associated with any of the known clinical classes and we discovered that the cell lines have cell-specific metabolome patterns. To assess whether these patterns can reveal changes in metabolic fluxes, we measured extracellular fluxes and subsequently showed that some metabolic pools indeed correlate with the extracellular fluxes. This indicated that, despite not correlating with clinicalAdvisors/Committee Members: Zamboni, Nicola, Sauer, Uwe, Claassen, Manfred.