Cancer as a complex adaptive system : Mathematical models of tumor ecology, evolution and development

Despite decades of scientific effort, cancer remains a major cause of death worldwide. Through the accumulation of genome alterations, tumor populations evolve the capacity to circumvent the selective barriers of tissue homeostasis, eventually adapting to resist therapeutic stress. Furthermore, exte...

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Detalles Bibliográficos
Autor: Aguadé Gorgorió, Guim
Tipo de recurso: tesis doctoral
Estado:Versión publicada
Fecha de publicación:2021
País:España
Institución:CBUC, CESCA
Repositorio:TDR. Tesis Doctorales en Red
OAI Identifier:oai:www.tdx.cat:10803/672400
Acceso en línea:http://hdl.handle.net/10803/672400
Access Level:acceso abierto
Palabra clave:Cancer complexity
Mathematical modeling
Genome instability
Immunotherapy
Differentaiation therapy
Complexitat en càncer
Modelització matemàtica
Inestabilitat genòmica
Immunoteràpia
Teràpia de diferenciació
616
Descripción
Sumario:Despite decades of scientific effort, cancer remains a major cause of death worldwide. Through the accumulation of genome alterations, tumor populations evolve the capacity to circumvent the selective barriers of tissue homeostasis, eventually adapting to resist therapeutic stress. Furthermore, extensive Darwinian evolution is accompanied by an ecological engineering of the surrounding tissue micro-environment together with the alteration of cellular maturation hierarchies. To understand cancer complexity, therefore, we need a picture that spans through the domains of ecology, evolution and development. In an effort to gain understanding of the underlying patterns of treatment resistance, the present PhD thesis introduces a mathematical approach to cancer complexity that takes into account its dynamical nature across these three axes. The resulting modeling endeavor is focused on two major fields of current research: immunotherapy and cancer epigenetics and differentiation, with the aim of providing both treatment design rationale and a comprehensive perspective that merges cancer ecological, evolutionary and developmental complexity.