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Biology subjects

Paixao, E. A.

Publications and source records attributed to Paixao, E. A..

2 recordsLinked to original sources

Healthy B cells: allies or adversaries of CAR-T cell immunotherapy?

Chimeric antigen receptor (CAR)-T cell immunotherapy has achieved significant success against various haematological cancers, including B-cell malignancies. Its efficacy against B-cell cancers is influenced by the presence of healthy B-cells expressing the target antigen, and B-cell aplasia (BCA) serves as an indicator of successful therapy outcome. However, the precise influence of healthy B-cells on the in vivo dynamics of CAR-T cells and their ultimate impact on therapy outcomes remain unclear. Here, we propose a mathematical model to describe CAR-T cell immunotherapy in B-cell cancer patients. Our model successfully captured the interactions between different CAR-T cell phenotypes, tumour cells, and healthy B cells in patients who achieved a complete response. Using these cases, we constructed virtual scenarios to investigate how variations in baseline tumour and healthy B-cell populations, along with patient-specific factors related to CAR-T cell expansion and B-cell influx from the bone marrow, affect treatment outcomes. Our results suggest that the onset and duration of BCA is a patient-specific feature that depends primarily on the continuous influx of newly generated B cells, their proliferative capacity, and the expansion and cytotoxicity of CAR-T cells. Statement of significanceThis study presents a significant advancement in understanding the dynamics of CAR-T cell immunotherapy in B-cell malignancies by introducing a mathematical model that captures the complex interactions between CAR-T cells, tumour cells, and healthy B cells. The model provides crucial insights into how patient-specific factors, such as baseline tumour burden, B-cell populations, and CAR-T cell expansion, influence treatment outcomes, including the onset and duration of B-cell aplasia (BCA), a key marker of therapeutic success. Healthy B cells can act as allies, adversaries, or have a neutral effect on the therapy, depending on the tumour burden. These findings highlight the importance of personalised approaches in CAR-T cell immunotherapy, offering potential pathways to optimise treatment strategies for improved efficacy and patient outcomes.

cancer biology↗

Mechanisms of Resistance to CAR-T cell Immunotherapy: Insights from a Mathematical Model

Chimeric Antigen Receptor (CAR)-T cell therapy long-term follow-up studies revealed non-durable remissions in a significant number of patients. Some of the mechanisms underlying these relapses include poor CAR T cell cytotoxicity or persistence, as well as antigen loss or lineage switching in tumor cells. In order to investigate how antigen-mediated resistance mechanisms affect therapy outcomes, we develop a mathematical model based on a set of integral-partial differential equations. Using a continuous variable to describe the level of antigen expression of tumor cells, we recapitulated important cellular mechanisms across patients with different therapeutic responses. Fitted with clinical data, the model successfully captured the dynamics of tumor and CAR-T cells for several hematological cancers. Furthermore, the role played by these mechanisms are explored with regard to different biological scenarios, such as pre-existing or acquired mutations, providing a deeper understanding of key factors underlying resistance to CAR-T cell immunotherapy. Statement of significanceOur study introduces the first mathematical model to characterize the influence of a continuous level of antigen expression on the interplay between Chimeric Antigen Receptor (CAR)-T cells and cancer cells. We examine various cellular mechanisms across different hematologic cancers, taking into account both antigen-positive and antigen-negative relapses. Our findings shed light on the role of antigen density in CAR-T cell therapies and provide a valuable framework to investigate resistance with potential to improve patients outcomes.

cancer biology↗