Abstract 1012: Systems analysis of colon cancer cell metabolism rewired by p53 and KRAS mutations

• Published in: Cancer research (Chicago, Ill.) Ill.), 2016-07, Vol.76 (14_Supplement), p.1012-1012
• Main Authors: Salvucci, Manuela, O’Byrne, Robert, Niewidok, Natalia, Kilbride, Séan, Concannon, Caoimhín G., Düssmann, Heiko, Huber, Heinrich H., Prehn, Jochen HM
• Format: Article
• Language: English
• ISSN: 0008-5472; 1538-7445
• DOI: 10.1158/1538-7445.AM2016-1012

Introduction. Somatic mutations in proto-oncogenes and tumour-suppressor genes contribute to rewire the already deregulated metabolic network in cancer cells, resulting in uncontrolled proliferation and oncogenesis. In this study, we set out to establish a dynamic mathematical model of bioenergetics and to exploit it to explore the multifaceted cross-talk between bioenergetics, somatic gene mutations in KRAS and p53, and cell proliferation and survival. Model Development. We have developed an ordinary differential equations-based model of central carbon metabolism in cancer cells which includes glycolysis, pentose phosphate pathway, citric acid cycle and respiratory chain, based on our previous work and published models. The model describes how nutrients (glucose, glutamine, lactate, pyruvate, serine and glycine) from the extracellular micro-environment affect bioenergetics parameters. The resulting model predictions are linked to cell proliferation via a heuristic function. Enzymatic activities regulated by p53 and KRAS mutations were obtained by mining publically available datasets and their regulation by the mutational status was modelled by adapting the corresponding kinetic parameters. To estimate the kinetic parameters, model simulation outputs were fitted to a portfolio of experimental data both generated de novo in house and gathered from the literature in HCT-116 colon cancer cells. Experiments were performed on parental HCT-116 (p53 competent; harbouring a KRAS mutation on exon 2 of codon G13) and three derived mutant cell lines covering all four combinations of p53 and KRAS mutational status to isolate their relative and joint effect on bioenergetics signatures. HCT-116-derived cell lines included: p53 proficient cells with the KRAS allelic mutation silenced by homologous recombination in the presence or absence of p53 knockout by lentiviral shRNA. Results. The model was calibrated against ATP concentrations measured via single-cell microscopy (ATeam probe and TMRM dye) following pharmacological inhibition of respiratory chain complexes (rotenone, sodium azide and oligomycin) as a function of nutrients availability (glucose, lactate, pyruvate). Modelling results revealed that p53 and KRAS mutations drive a shift in metabolic signatures and L-lactate emerged as a pivotal metabolite to stratify the different phenotypes. Systems analysis revealed that in KRAS mutated cells p53 deficiency leads to an increase in glucose uptake and flux through the p