Modelagem matemática da imunoterapia com células CAR T

• Ano de defesa: 2019
• Autor(a) principal: Rodrigues, Brendon de Jesus
• Orientador(a): Almeida, Regina Célia Cerqueira de, Barros, Luciana Rodrigues Carvalho
• Banca de defesa: Barros, Luciana Rodrigues Carvalho, Bonamino, Martrin Hernan, Costa, Michel Iskin da Silveira, Malta, Sandra Mara Cardoso
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Laboratório Nacional de Computação Científica
• Programa de Pós-Graduação: Programa de Pós-Graduação em Modelagem Computacional
• Departamento: Coordenação de Pós-Graduação e Aperfeiçoamento (COPGA)
• País: Brasil
• Palavras-chave em Português: Simulação (Computadores); Equações diferenciais ordinárias; Câncer; Imunoterapia adotiva; Terapia CAR com células T
• Área do conhecimento CNPq: CNPQ::CIENCIAS DA SAUDE::MEDICINA::CLINICA MEDICA::CANCEROLOGIA
• Link de acesso: https://tede.lncc.br/handle/tede/283

Several studies show that cancer is already the leading cause of death in the world. This disease of global impact has boosted great advances in terms of treatment protocols. One of the therapies that has received great attention is immunotherapy, which stimulates the patient’s immune system to induce an anti-tumor response. Adoptive cell therapy, for example, uses cells from the patient’s immune system, more specifically lymphocytes, to effect tumor elimination. Recently immunotherapy has gained great momentum with CAR T-cell therapy. In the CAR T (chimeric antigen receptor) cellular therapy, T lymphocytes are genetically manipulated to recognize the tumor specific antigen to increase elimination efficiency. Although it has proved to be quite effective in combating certain types of cancer, issues such as cost, identification of antigen markers, toxicity, immunological checkpoint inhibitors, resistance to immunotherapy, among others, remain open and are the subject of intense research nowadays. In this work we develop a mathematical model based on ordinary differential equations to describe tumor response to CAR T therapy. We consider interactions between tumor cells and effector cells, and T-cell differentiation into memory cells. We consider the tumor induced immunossupression effect as well as the conversion of memory cells into effector cells in the presence of tumor cells. We partially calibrate the model using data from the literature, and the model was able to represent tumor elimination either after the interaction with the CAR T cells or in case of a challenge due to the memory cells long-term immune protection. By performing simulations and using a simple method of sensitivity analysis we identify three possible immunotherapy results, characterizing the three stages of cancer immu- noediting. The sensitivity analysis allowed us to identify the parameters of the model that most interfere in the elimination, equilibrium and escape of the tumor.