Study of the metabolism of cancer cells using exometabolomics by NMR

During the three years of my Ph.D., my main project was to study cancer cell metabolism using exometabolomics by NMR. The experimental design of an exometabolomics study encompasses several key steps (Figure 1). It begins with culturing cells in two- and/or three-dimensional experiments, followed by preparing cell media samples. These samples are then subjected to acquisition using NMR spectroscopy. Subsequently, metabolites of interest are quantified through deconvolution techniques, obtaining Exchange Rates representing the data on which to perform analysis. Statistical analysis is then performed using targeted chemometrics techniques depending on the specific study question. Finally, the results undergo biochemical analysis to draw conclusions and insights. This thesis aims to employ exometabolomics to comprehensively explore cellular metabolism in the context of cancer, applying this study to three different cancers. In detail, Chapter 1 explores the metabolic changes induced by etoposide treatment on PC3 (Prostate Cancer cell line) cells, simulating the chemotherapy-induced Cancer Repopulation and Acquired Cell-Resistance (CRAC) model. The primary objective is to understand the impact of chemotherapy on cancer metabolism and identify potential targets to prevent post-remission relapse. Chapter 2 is divided into two exometabolomics studies that were conducted similarly. Chapter 2A aims to integrate exometabolomics and endometabolomics techniques, providing a comprehensive approach to studying cellular metabolism. This involves delineating extracellular and intracellular metabolic profiles to try to provide a method for integrating this information into the characterization of the metabolism of three intrahepatic cholangiocarcinoma cell lines cultured with two different culture modes, two-dimensional and three-dimensional. Chapter 2B aims to analyze the metabolism of six bladder cancer cell lines cultivated in two-dimensional and three-dimensional cultures, representing varying stages and grades of cancer. Employing a multi-omics approach that integrates genomics, proteomics, transcriptomics, and exo/endometabolomics, the aim is to identify metabolic markers indicative of tumor progression. The emphasis lies in comparing different culture modes and exploring for the two-dimensional (2D) culture the correlations between FGFR3 mutation and pathology grade with cellular metabolism in BCcls.