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The liver performs many essential metabolic functions, which can be studied using computational models of hepatocytes. Here we present HepatoDyn, a highly detailed dynamic model of hepatocyte metabolism. HepatoDyn includes a large metabolic network, highly detailed kinetic laws, and is capable of dynamically simulating the redox and energy metabolism of hepatocytes. Furthermore, the model was coupled to the module for isotopic label propagation of the software package IsoDyn, allowing HepatoDyn to integrate data derived from 13C based experiments. As an example of dynamical simulations applied to hepatocytes, we studied the effects of high fructose concentrations on hepatocyte metabolism by integrating data from experiments in which rat hepatocytes were incubated with 20 mM glucose supplemented with either 3 mM or 20 mM fructose. These experiments showed that glycogen accumulation was significantly lower in hepatocytes incubated with medium supplemented with 20 mM fructose than in hepatocytes incubated with medium supplemented with 3 mM fructose. Through the integration of extracellular fluxes and 13C enrichment measurements, HepatoDyn predicted that this phenomenon can be attributed to a depletion of cytosolic ATP and phosphate induced by high fructose concentrations in the medium., Author Summary Despite the key role of hepatocytes in carbohydrate and lipid homeostasis, available dynamic models of hepatocyte metabolism tend to be limited to a single pathway and/or are based on assumptions of constant concentrations of key metabolites involved in redox and energy metabolism (ATP, NAD, NADPH etc.). Furthermore, most dynamic models are unable to integrate information from 13C based experiments. 13C based experiments allow us to infer the relative activity of alternative pathways and hence are highly useful for indicating flux distributions. To overcome these limitations, we developed HepatoDyn, a dynamic model of hepatic metabolism. HepatoDyn uses a large metabolic network including key pathways such as glycolysis, the Krebs cycle, the pentose phosphate pathway and fatty acid metabolism, and dynamically models the concentrations of metabolites involved in the redox and energy metabolism of hepatocytes. In addition, the model was coupled to the label propagation module of the package IsoDyn, allowing it to integrate data from 13C based experiments to assist in the parametrization process. These features make HepatoDyn a powerful tool for studying the dynamics of hepatocyte metabolism.

[eng] Cancer is characterised by the lost of physiological control and the malignant transformation of cells that acquire functional and genetic abnormalities, leading to tumour development and progression. Colon and lung cancer are two of the most common cancers worldwide. In early stages of the disease, surgery is the common choice while chemotherapy is the main treatment for advanced stage cancer. However, the currently available chemotherapeutic treatments exhibit modest efficacy due to their side effects and drug resistance. Therefore, the search for combined chemotherapies with low systemic toxicity and high efficiency holds great promise to decrease the morbidity and mortality of cancer. Tumour cells present common biological capabilities sequentially acquired during the development of cancer that are considered essential to drive malignancy. In particular, tumour cells switch their core metabolism to meet the increased requirements of cell growth and division. Indeed, oncogenic signals converge to reprogram tumour metabolism by enhancing key metabolic pathways such as glycolysis, pentose phosphate pathway (PPP), glutaminolysis and lipid, nucleic acid and amino acid metabolism. Several oncogenes including c-MYC, hypoxia inducible factor 1 (HIF1), phosphoinositide-3-kinase (PI3K), protein kinase B (PBK or Akt) and the mechanistic target of rapamycin (mTOR), have been known to be involved in the regulation of tumour metabolic reprogramming. Then, the study of the tumour metabolic reprogramming and its connection with oncogenic signalling is an essential strategy to identify new targets for cancer therapy. Thus, the main objective of this thesis was to explore new possibilities for cancer treatment and diagnosis. To this end, we have analysed the links between metabolism and tumour progression, the tumour metabolic reprogramming associated to the dysregulation of cell cycle, and the use of combination therapies for cancer treatment. In order to accomplish our main objective, the results of this thesis are divided in three chapters: 1. We have identified glyceraldehyde-3-phosphate dehydrogenase (GAPDH) as a potential predictive biomarker for tumour staging and prognosis of human colorectal cancer. In addition, our results clearly discourage the use of GAPDH as a housekeeping marker in colorectal cancer. 2. We have characterised the metabolic reprogramming associated to the inhibition of cyclin-dependent kinases 4 and 6 (CDK4/6) in colon cancer cells. CDK4/6 inhibition causes a shift towards enhanced metabolism of glucose, glutamine and amino acids by increasing mitochondrial metabolism and function as well as glycolytic flux. Fluxomics and transcriptomics integrated data analysis revealed that this metabolic reprogramming is directed by MYC, which is accumulated when CDK4/6 are inhibited. In fact, the identification of the tumour metabolic adaptations associated to CDK4/6 inhibition reveals potential metabolic vulnerabilities that can be exploited in combination therapies with CDK4/6 inhibitors. Accordingly, we have obtained synergistic and selective antiproliferative effects in vitro by inhibiting mTOR, PI3K/Akt axis or MYC target genes in combination with CDK4/6 inhibitors. Therefore, we propose new combination therapies that simultaneously target cell cycle and metabolism of cancer cells. 3. We have determined the molecular mechanism of action of the selenium compound methylseleninic acid (MSA) in cancer cells. MSA effects are associated with the inhibition of the Akt pathway, leading to dephosphorylation of FOXO transcription factors and their nuclear translocation which, in turn, activate the expression of FOXO target genes. By targeting the PI3K/Akt/FOXO pathway, MSA synergises with cisplatin in combination therapies to reduce the commonly observed toxicity and overcome the resistance of cisplatin-based chemotherapy. The completion of these objectives has shed new light on the understanding of tumour metabolic reprogramming as well as the mechanisms of action of compounds potentially useful as antitumour agents. We have used this information to develop new strategies complementing conventional and existing chemotherapies, providing new approaches for cancer treatment and diagnosis.