Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/200639
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dc.contributor.advisorCascante i Serratosa, Marta-
dc.contributor.advisorAtauri Carulla, Ramón de-
dc.contributor.authorBori Bru, Berta-
dc.date.accessioned2023-07-14T14:47:23Z-
dc.date.available2025-07-14T05:10:08Z-
dc.date.issued2023-06-
dc.identifier.urihttps://hdl.handle.net/2445/200639-
dc.descriptionTreballs Finals de Grau de Química, Facultat de Química, Universitat de Barcelona, Any: 2023, Tutors: Marta Cascante Serratosa, Pedro de Atauri Carullaca
dc.description.abstractColorectal cancer (CRC) is one of the cancers with the most reported cases and mortality rates. Resistance to antitumoral drugs is one of the main reasons for its mortality, leading to the failure of conventional therapies. The understanding of the metabolic changes that encompass metabolic reprogramming upon chemotherapy treatments, such as those with Palbociclib, may unveil new therapeutic targets to enhance Palbociclib effectivity and/or avoid the acquisition of resistance. In this study, we used a mathematical modelling approach based on the reconstruction of tumor cell metabolic network reactions at Genome Scale (GSMMs). The reconstruction was based on a template containing all the possible reactions described in human organisms (Recon3D) and constrained using experimental measurements of tumor cells. Using this approach, first we reconstructed a simplification of the central metabolism, creating a type of GSMM referred to as “toy model”. This step served to understand the correct usage of the algorithms used in the creation of GSMMs, and provided further knowledge to comprehend the key role that transcriptomic data has on constraining and mathematically determining the model. Subsequently, GSMMs for both untreated and Palbociclib-resistant tumor cells were reconstructed using experimental data on consumption and production rates, metabolite concentrations in cell culture media and gene expression information. Linear programming-based algorithms were employed to refine the models. Then, gene knock-out and knock-down techniques were used to identify potential therapeutic targets capable of inducing cellular death or preventing the metabolic reprogramming triggered by Palbociclib. Analysis of the metabolic fluxes estimated from the reconstructed GSMMs showed that Palbociclib-resistant cells exhibit a decrease in glycolytic activity and an increase in cellular respiration, nucleotide metabolism and fatty acid metabolisms. These changes revealed several potential targets, some of which associated with approved drugs, such as cholic acid, Quercetin, Sulfasalazine and Aspirin.ca
dc.format.extent67 p.-
dc.format.mimetypeapplication/pdf-
dc.language.isoengca
dc.rightscc-by-nc-nd (c) Bori, 2023-
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.sourceTreballs Finals de Grau (TFG) - Química-
dc.subject.classificationBioquímica computacionalcat
dc.subject.classificationMetabolismecat
dc.subject.classificationCàncer colorectalcat
dc.subject.classificationTreballs de fi de graucat
dc.subject.otherComputational biochemistryeng
dc.subject.otherMetabolismeng
dc.subject.otherColorectal cancereng
dc.subject.otherBachelor's theseseng
dc.titleMetabolism and drug resistance in colon cancereng
dc.title.alternativeMetabolisme i resistència farmacològica en càncer de colonca
dc.typeinfo:eu-repo/semantics/bachelorThesisca
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess-
Appears in Collections:Treballs Finals de Grau (TFG) - Química

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