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Modeling Patient-Specific CAR-T Cell Dynamics: Multiphasic Kinetics via Phenotypic Differentiation

SIMPLE SUMMARY: We present the first mathematical model to describe the multiphasic dynamical treatment response in CAR-T cell kinetics through the differentiation of functional (distributed and effector), memory, and exhausted phenotypes, integrated with the dynamics of cancer cells. The CAR-T cell...

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Detalles Bibliográficos
Autores principales: Paixão, Emanuelle A., Barros, Luciana R. C., Fassoni, Artur C., Almeida, Regina C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9688514/
https://www.ncbi.nlm.nih.gov/pubmed/36428671
http://dx.doi.org/10.3390/cancers14225576
Descripción
Sumario:SIMPLE SUMMARY: We present the first mathematical model to describe the multiphasic dynamical treatment response in CAR-T cell kinetics through the differentiation of functional (distributed and effector), memory, and exhausted phenotypes, integrated with the dynamics of cancer cells. The CAR-T cell kinetics are evaluated for various hematological cancers and therapy outcomes, providing insights into promising parameters for long-term therapy investigation. ABSTRACT: Chimeric Antigen Receptor (CAR)-T cell immunotherapy revolutionized cancer treatment and consists of the genetic modification of T lymphocytes with a CAR gene, aiming to increase their ability to recognize and kill antigen-specific tumor cells. The dynamics of CAR-T cell responses in patients present multiphasic kinetics with distribution, expansion, contraction, and persistence phases. The characteristics and duration of each phase depend on the tumor type, the infused product, and patient-specific characteristics. We present a mathematical model that describes the multiphasic CAR-T cell dynamics resulting from the interplay between CAR-T and tumor cells, considering patient and product heterogeneities. The CAR-T cell population is divided into functional (distributed and effector), memory, and exhausted CAR-T cell phenotypes. The model is able to describe the diversity of CAR-T cell dynamical behaviors in different patients and hematological cancers as well as their therapy outcomes. Our results indicate that the joint assessment of the area under the concentration-time curve in the first 28 days and the corresponding fraction of non-exhausted CAR-T cells may be considered a potential marker to classify therapy responses. Overall, the analysis of different CAR-T cell phenotypes can be a key aspect for a better understanding of the whole CAR-T cell dynamics.