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Recolector de Ciencia Abierta, RECOLECTA
Bachelor thesis . 2016
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Estudio y desarrollo de modelos matemáticos de resistencia celular a la quimioterapia.

Authors: Olvera Collantes, Lucía;

Estudio y desarrollo de modelos matemáticos de resistencia celular a la quimioterapia.

Abstract

El cáncer es un conjunto de más de cien tipos de enfermedades relacionadas caracterizadas por la proliferación ininterrumpida de células y su capacidad de extenderse a otros tejidos, formando metástasis. Actualmente, se trata de una de las principales causas de mortalidad en todo el mundo. Por este motivo, se están llevando a cabo numerosos estudios para comprender mejor su comportamiento en el organismo y poder combatirlo de manera eficaz. Una línea interesante de investigación la representa el estudio de la resistencia a múltiples drogas (MDR), pues es la mayor causa de fracaso del tratamiento contra el cáncer. En los últimos años se está potenciando el interés por aplicar técnicas matemáticas en el análisis de problemas biológicos. Debido a la importancia de las enfermedades oncológicas, en este trabajo de investigación se ha desarrollado un modelo matemático de ecuaciones diferenciales que describe el proceso de transferencia de la resistencia a la quimioterapia en mezclas de dos poblaciones de células tumorales: resistentes y sensibles. Además, se han estimado los parámetros de dicho modelo utilizando los datos experimentales de ensayos de proliferación celular in vitro y se han realizado simulaciones numéricas para la validación del modelo, haciendo uso del software matemático Matlab. Como resultados de la investigación, hay que destacar que el modelo representa la proliferación in vitro de células cancerígenas sensibles, resistentes y de sus cultivos mixtos. Esto permitirá continuar con la investigación a niveles de complejidad superior, permitiendo la obtención de conclusiones de interés para la biología del cáncer.

Cancer is an ensemble consisting of over a hundred kinds of related diseases characterized by the unrestrained proliferation of cells and their ability to spread to other tissues, forming metastases. It is one of the leading causes of mortality worldwide. For this reason, numerous studies are conducted for a better understanding of their behaviour in the body and to confront them effectively. The study of multidrug resistance (MDR) is an interesting line of research, as it is the major cause of failure of cancer treatment. In recent years, the interest in applying mathematical techniques to analyze biological problems has been boosted. Because of the importance of oncological diseases, this research has developed a mathematical model based on differential equations for describing the chemotherapy resistance transfer process in mixtures of two tumor cell populations: resistant and sensitive cells. Moreover, semi-empirical models parametrized with experimental data from cell proliferation essays and numerical simulations have been performed to validate the model, using the mathematical software Matlab. As a result of the investigation, it is not worthy that the model represents the in vitro proliferation of sensitive and resistant cancer cells and their mixed cultures. This will allow research to continue on higher levels of complexity and to draw relevant conclusions for Cancer Biology.

Country
Spain
Related Organizations
Keywords

Validación, Resistencia, Modelo Matemático, P-gp, Quimioterapia, Transferencia, Cáncer

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green
Related to Research communities
Cancer Research