Metabolic modelling links Warburg effect to collagen formation, angiogenesis and inflammation in the tumoral stroma.

Cancer cells are known to express the Warburg effect-increased glycolysis and formation of lactic acid even in the presence of oxygen-as well as high glutamine uptake. In tumors, cancer cells are surrounded by collagen, immune cells, and neoangiogenesis. Whether collagen formation, neoangiogenesis, and inflammation in cancer are associated with the Warburg effect needs to be established. Metabolic modelling has proven to be a tool of choice to understand biological reality better and make in silico predictions. Elementary Flux Modes (EFMs) are essential for conducting an unbiased decomposition of a metabolic model into its minimal functional units. EFMs can be investigated using our tool, aspefm, an innovative approach based on logic programming where biological constraints can be incorporated. These constraints allow networks to be characterized regardless of their size. Using a metabolic model of the human cell containing collagen, neoangiogenesis, and inflammation markers, we derived a subset of EFMs of biological relevance to the Warburg effect. Within this model, EFMs analysis provided more adequate results than parsimonious flux balance analysis and flux sampling. Upon further inspection, the EFM with the best linear regression fit to cancer cell lines exometabolomics data was selected. The minimal pathway, presenting the Warburg effect, collagen synthesis, angiogenesis, and release of inflammation markers, showed that collagen production was possible directly de novo from glutamine uptake and without extracellular import of glycine and proline, collagen's main constituents.