El tema abordado en este trabajo es el estudio in silico de la respuesta de organoides derivados de tumores heterogéneos a la terapia con células CAR-T. El estudio se centra en analizar la eficacia de diferentes estrategias de terapia con células CAR-T sobre las células cancerosas que presentan antígenos dentro de los tumores.
La metodología utilizada en este trabajo involucra el desarrollo de un modelo basado en agentes (ABM) para racionalizar los resultados de diferentes estrategias de terapia con células CAR-T en organoides derivados de tumores heterogéneos. Este modelo computacional permite analizar los efectos de diferentes tratamientos caracterizados por distintas dosis, persistencia de las células CAR-T y especificidad de las mismas, sin dañar tejido sano con terapias que probablemente no produzcan resultados significativos.
Luque, L. M., Carlevaro, C. M., Rodriguez-Lomba, E., & Lomba, E. (2024). In silico study of heterogeneous tumour-derived organoid response to CAR T-cell therapy. Scientific Reports, 14(1), 12307. https://www.nature.com/articles/s41598-024-63125-5
@article{luque2024,
title = {In silico study of heterogeneous tumour-derived organoid response to {CAR} T-cell therapy},
volume = {14},
issn = {2045-2322},
url = {https://www.nature.com/articles/s41598-024-63125-5},
doi = {10.1038/s41598-024-63125-5},
pages = {12307},
number = {1},
journaltitle = {Scientific Reports},
shortjournal = {Sci Rep},
author = {Luque, Luciana Melina and Carlevaro, Carlos Manuel and Rodriguez-Lomba, Enrique and Lomba, Enrique},
urldate = {2024-05-30},
date = {2024-05-29},
year = {2024},
month = may,
langid = {english}
}
Abstract
Chimeric antigen receptor (CAR) T-cell therapy is a promising immunotherapy for treating cancers. This method consists in modifying the patients’ T-cells to directly target antigen-presenting cancer cells. One of the barriers to the development of this type of therapies, is target antigen heterogeneity. It is thought that intratumour heterogeneity is one of the leading determinants of therapeutic resistance and treatment failure. While understanding antigen heterogeneity is important for effective therapeutics, a good therapy strategy could enhance the therapy efficiency. In this work we introduce an agent-based model (ABM), built upon a previous ABM, to rationalise the outcomes of different CAR T-cells therapies strategies over heterogeneous tumour-derived organoids. We found that one dose of CAR T-cell therapy should be expected to reduce the tumour size as well as its growth rate, however it may not be enough to completely eliminate it. Moreover, the amount of free CAR T-cells (i.e. CAR T-cells that did not kill any cancer cell) increases as we increase the dosage, and so does the risk of side effects. We tested different strategies to enhance smaller dosages, such as enhancing the CAR T-cells long-term persistence and multiple dosing. For both approaches an appropriate dosimetry strategy is necessary to produce “effective yet safe” therapeutic results. Moreover, an interesting emergent phenomenon results from the simulations, namely the formation of a shield-like structure of cells with low antigen expression. This shield turns out to protect cells with high antigen expression. Finally we tested a multi-antigen recognition therapy to overcome antigen escape and heterogeneity. Our studies suggest that larger dosages can completely eliminate the organoid, however the multi-antigen recognition increases the risk of side effects. Therefore, an appropriate small dosages dosimetry strategy is necessary to improve the outcomes. Based on our results, it is clear that a proper therapeutic strategy could enhance the therapies outcomes. In that direction, our computational approach provides a framework to model treatment combinations in different scenarios and to explore the characteristics of successful and unsuccessful treatments.