Development of model-driven approaches for metaboic flux analysis and anticancer drug discovery
- Autores: Carles Foguet Coll
- Directores de la Tesis: Marta Cascante Serratosa (dir. tes.), Pedro de Atauri (codir. tes.)
- Lectura: En la Universitat de Barcelona ( España ) en 2019
- Idioma: español
- Tribunal Calificador de la Tesis: Francesc Mas (presid.), Marta Casado Pinna (secret.), Maria Klapa (voc.)
- Programa de doctorado: Programa de Doctorado en Biotecnología por la Universidad de Barcelona
- Materias:
- Enlaces
- Tesis en acceso abierto en: TDX
- Resumen
Metabolism is a hallmark of life and underlies most biological processes in both health and disease. For instance, dysregulation of liver metabolism underlies multifactorial disorders such as diabetes or obesity. Similarly, cancer progression involves a reprogramming of metabolism to support unchecked proliferation, metastatic spread and other facets of the cancer phenotype. Hence, the study of metabolism is of great biomedical interest.
The metabolic phenotype emerges from the complex interactions of metabolites, enzymes, and the signaling cascades regulating their expression and thus must be studied following a holistic approach. With this aim, Systems Biology formulates the interactions between the molecular components of metabolism as a set of mathematical expressions, termed metabolic models, and uses them as a framework to integrate multiple layers of data (e.g., transcriptomics, proteomics and metabolomics) and simulate the emergent metabolic phenotype. The Systems Biology toolbox for the analysis of metabolism consists of several complementary model-based approaches, each with its strengths and limitations. For instance, constraint-based modeling can predict flux distributions at a genome-scale, whereas kinetic modeling and 13C metabolic flux analysis (13C MFA) can more accurately model central carbon metabolism.
As part of this Ph.D. thesis, we have expanded this toolbox through the development of new model-based approaches for computing both detailed metabolic maps of central carbon metabolism and genome-scale flux maps. With this aim, we developed HepatoDyn, a highly detailed kinetic model of hepatocyte metabolism capable of dynamic 13C MFA and used it to characterize the negative effects of fructose in hepatic metabolic function. Similarly, we also developed Iso2Flux, a novel steady-state 13C MFA software, and parsimonious 13C MFA, a new 13C MFA algorithm that can integrate transcriptomics to trace flux through large metabolic networks. Even more, we developed r2MTA a constraint-based modeling algorithm to robustly identify the optimal interventions to induce a transition towards a therapeutically desirable metabolic state. Finally, we also developed a workflow for integrating transcriptomics, metabolomics, gene dependencies, and 13C MFA to predict genome-scale flux maps.
Furthermore, we apply the systems biology toolbox, using both newly developed and existing tools, to the genome-scale analysis of the molecular drivers underlying cancer stem cells (CSC) and metastasis in prostate and colorectal cancer, respectively.
We determine that the CSC gene expression program in prostate cancer is likely supported by a partial Epithelial-Mesenchymal transition (EMT) phenotype mediated by a complex balance between pro-EMT and anti-EMT factors. We also identify several putative drivers of the cancer stem cell phenotype that are suppressed by a complete EMT such as TSPAN8, REG4 or VEGFC. Remarkably, we observe that the CSC metabolic gene expression program is largely disassociated from EMT. Nevertheless, we identify several putative metabolic targets which can induce a metabolic reprogramming from a CSC-like to a non-CSC metabolic phenotype such as MTHFD2 and PYCR1.
Concerning the colorectal cancer metastasis cell populations, we determine that the metastatic populations are selectively vulnerable to the inhibition of cystine import and folate metabolism. Furthermore, we find that the metastatic cell lines have a reduced concentration of the antiproliferative peptide carnosine which can be putatively increased through the inhibition of citrate synthase.
Together, the work presented here can contribute to the development of new therapies capable of selectively targeting metastatic and CSC populations in colorectal and prostate cancer.
