Mathematical modeling for pharmacological approaches directed to metabolic pathways in "diabetic paradox" in prostate cancer
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10400.22/19852 |
Resumo: | Obesity and diabetes are two metabolic risk factos for cancer. However, there is a metabolic paradox in prostate cancer in which diabetes appears to protect the patient form this type of cancer. The current study aims to develop explanatory models of this contradiction utilizing prostate cancer cell lines, PC3 and LNCaP, in contrast to the metabolismo of normal prostate cells, using bioinformatics methods (HPEpiC). Two of the major routes of prostate metabolism, glycolysis and gluconeogensis, were mathematically manipulated in this study. This mathematical model offers unique and revolutionary implications in personalized medicine since it predicts the Effect, therapeutic dose, and efficacy of medications in varied conditions of the tumor microenvironment and the patient’s metabolismo. As na illustration od the model’s usefulness, a novel anti-tumor drug in the clinical trials phase, 3-bromopyruvate, which has the modeled metabolic pathways as a therapeutic target, was employed. The efficacy od 3-bromopyruvate was investigated, and the IC50 was found to be capable of significantly inhibiting tumor cell lines. When compared to basal metabolismo, its IC50 delayed glycolytic metabolismo by 12 minutes. As a result, the diabetic environment has a slowing Effect on glycolytic metabolismo. The obese environment had no significant diferences in this form os cancer as compared to the healthy environment. Tha value of mathematical modeling is clear, as the Effect of anew drug on metabolismo may be computer evaluated and used as a novel tool to provide a tailored approach to each patient. |
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Mathematical modeling for pharmacological approaches directed to metabolic pathways in "diabetic paradox" in prostate cancerBioinformaticsDiabetesModelingObesityProstate cancerObesity and diabetes are two metabolic risk factos for cancer. However, there is a metabolic paradox in prostate cancer in which diabetes appears to protect the patient form this type of cancer. The current study aims to develop explanatory models of this contradiction utilizing prostate cancer cell lines, PC3 and LNCaP, in contrast to the metabolismo of normal prostate cells, using bioinformatics methods (HPEpiC). Two of the major routes of prostate metabolism, glycolysis and gluconeogensis, were mathematically manipulated in this study. This mathematical model offers unique and revolutionary implications in personalized medicine since it predicts the Effect, therapeutic dose, and efficacy of medications in varied conditions of the tumor microenvironment and the patient’s metabolismo. As na illustration od the model’s usefulness, a novel anti-tumor drug in the clinical trials phase, 3-bromopyruvate, which has the modeled metabolic pathways as a therapeutic target, was employed. The efficacy od 3-bromopyruvate was investigated, and the IC50 was found to be capable of significantly inhibiting tumor cell lines. When compared to basal metabolismo, its IC50 delayed glycolytic metabolismo by 12 minutes. As a result, the diabetic environment has a slowing Effect on glycolytic metabolismo. The obese environment had no significant diferences in this form os cancer as compared to the healthy environment. Tha value of mathematical modeling is clear, as the Effect of anew drug on metabolismo may be computer evaluated and used as a novel tool to provide a tailored approach to each patient.Fernandes, RúbenAlves, MarcoBaylina, PilarRepositório Científico do Instituto Politécnico do PortoSantos, Inês Ribeiro da Silva de Lima2021-12-092024-12-09T00:00:00Z2021-12-09T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10400.22/19852TID:202929787engmetadata only accessinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-03-13T13:14:44Zoai:recipp.ipp.pt:10400.22/19852Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:39:55.443965Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Mathematical modeling for pharmacological approaches directed to metabolic pathways in "diabetic paradox" in prostate cancer |
title |
Mathematical modeling for pharmacological approaches directed to metabolic pathways in "diabetic paradox" in prostate cancer |
spellingShingle |
Mathematical modeling for pharmacological approaches directed to metabolic pathways in "diabetic paradox" in prostate cancer Santos, Inês Ribeiro da Silva de Lima Bioinformatics Diabetes Modeling Obesity Prostate cancer |
title_short |
Mathematical modeling for pharmacological approaches directed to metabolic pathways in "diabetic paradox" in prostate cancer |
title_full |
Mathematical modeling for pharmacological approaches directed to metabolic pathways in "diabetic paradox" in prostate cancer |
title_fullStr |
Mathematical modeling for pharmacological approaches directed to metabolic pathways in "diabetic paradox" in prostate cancer |
title_full_unstemmed |
Mathematical modeling for pharmacological approaches directed to metabolic pathways in "diabetic paradox" in prostate cancer |
title_sort |
Mathematical modeling for pharmacological approaches directed to metabolic pathways in "diabetic paradox" in prostate cancer |
author |
Santos, Inês Ribeiro da Silva de Lima |
author_facet |
Santos, Inês Ribeiro da Silva de Lima |
author_role |
author |
dc.contributor.none.fl_str_mv |
Fernandes, Rúben Alves, Marco Baylina, Pilar Repositório Científico do Instituto Politécnico do Porto |
dc.contributor.author.fl_str_mv |
Santos, Inês Ribeiro da Silva de Lima |
dc.subject.por.fl_str_mv |
Bioinformatics Diabetes Modeling Obesity Prostate cancer |
topic |
Bioinformatics Diabetes Modeling Obesity Prostate cancer |
description |
Obesity and diabetes are two metabolic risk factos for cancer. However, there is a metabolic paradox in prostate cancer in which diabetes appears to protect the patient form this type of cancer. The current study aims to develop explanatory models of this contradiction utilizing prostate cancer cell lines, PC3 and LNCaP, in contrast to the metabolismo of normal prostate cells, using bioinformatics methods (HPEpiC). Two of the major routes of prostate metabolism, glycolysis and gluconeogensis, were mathematically manipulated in this study. This mathematical model offers unique and revolutionary implications in personalized medicine since it predicts the Effect, therapeutic dose, and efficacy of medications in varied conditions of the tumor microenvironment and the patient’s metabolismo. As na illustration od the model’s usefulness, a novel anti-tumor drug in the clinical trials phase, 3-bromopyruvate, which has the modeled metabolic pathways as a therapeutic target, was employed. The efficacy od 3-bromopyruvate was investigated, and the IC50 was found to be capable of significantly inhibiting tumor cell lines. When compared to basal metabolismo, its IC50 delayed glycolytic metabolismo by 12 minutes. As a result, the diabetic environment has a slowing Effect on glycolytic metabolismo. The obese environment had no significant diferences in this form os cancer as compared to the healthy environment. Tha value of mathematical modeling is clear, as the Effect of anew drug on metabolismo may be computer evaluated and used as a novel tool to provide a tailored approach to each patient. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-12-09 2021-12-09T00:00:00Z 2024-12-09T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10400.22/19852 TID:202929787 |
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http://hdl.handle.net/10400.22/19852 |
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TID:202929787 |
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eng |
language |
eng |
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metadata only access info:eu-repo/semantics/openAccess |
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metadata only access |
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openAccess |
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application/pdf |
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RCAAP |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799131486641717248 |