Speaker
Description
Relapse in acute lymphoblastic leukemia (ALL) remains a clinical challenge, affecting ~15\% of pediatric patients despite effective therapies. Understanding the population dynamics underlying treatment response and resistance is central in mathematical oncology.
Within the LEUKODOMICS project, we develop a stochastic population framework to model leukemic cell dynamics under multi-drug therapy. The model is a discrete probabilistic process describing proliferation, natural death, and drug-induced cytotoxicity, incorporating multiple leukemic subpopulations with distinct resistance profiles. Resistance to different therapeutic agents can evolve independently during treatment, following the SEHOP-PETHEMA 2013 pediatric protocol.
This approach enables simulation of heterogeneous clonal dynamics and exploration of relapse as an evolutionary and stochastic process. The framework integrates clinical and molecular information, supporting patient-specific digital twins capable of reproducing individual disease trajectories.
Mechanomic variables from chromatin motion analysis provide insights on nuclear organization and cellular mechanical behavior. These features, alongside transcriptomic, proteomic, and clinical data, are being evaluated to refine model parameterization.
Overall, stochastic multi-population models combined with multi-scale data support predictive modeling of leukemia progression and the development of digital twins for precision pediatric oncology.
Bibliography
@article{molina_chromosomal_2023,
title = {Chromosomal instability in aneuploid acute lymphoblastic leukemia associates with disease progression},
volume = {16},
issn = {1757-4684},
url = {https://link.springer.com/article/10.1038/s44321-023-00006-w},
doi = {10.1038/s44321-023-00006-w},
abstract = {Abstract
Chromosomal instability (CIN) lies at the core of cancer development leading to aneuploidy, chromosomal copy-number heterogeneity (chr-CNH) and ultimately, unfavorable clinical outcomes. Despite its ubiquity in cancer, the presence of CIN in childhood B-cell acute lymphoblastic leukemia (cB-ALL), the most frequent pediatric cancer showing high frequencies of aneuploidy, remains unknown. Here, we elucidate the presence of CIN in aneuploid cB-ALL subtypes using single-cell whole-genome sequencing of primary cB-ALL samples and by generating and functionally characterizing patient-derived xenograft models (cB-ALL-PDX). We report higher rates of CIN across aneuploid than in euploid cB-ALL that strongly correlate with intraclonal chr-CNH and overall survival in mice. This association was further supported by in silico mathematical modeling. Moreover, mass-spectrometry analyses of cB-ALL-PDX revealed a “CIN signature” enriched in mitotic-spindle regulatory pathways, which was confirmed by RNA-sequencing of a large cohort of cB-ALL samples. The link between the presence of CIN in aneuploid cB-ALL and disease progression opens new possibilities for patient stratification and offers a promising new avenue as a therapeutic target in cB-ALL treatment.},
language = {en},
number = {1},
urldate = {2026-03-11},
journal = {EMBO Molecular Medicine},
author = {Molina, Oscar and Ortega-Sabater, Carmen and Thampi, Namitha and Fernández-Fuentes, Narcís and Guerrero-Murillo, Mercedes and Martínez-Moreno, Alba and Vinyoles, Meritxell and Velasco-Hernández, Talía and Bueno, Clara and Trincado, Juan L and Granada, Isabel and Campos, Diana and Giménez, Carles and Boer, Judith M and Den Boer, Monique L and Calvo, Gabriel F and Camós, Mireia and Fuster, Jose-Luis and Velasco, Pablo and Ballerini, Paola and Locatelli, Franco and Mullighan, Charles G and Spierings, Diana C J and Foijer, Floris and Pérez-García, Víctor M and Menéndez, Pablo},
month = dec,
year = {2023},
pages = {64--92},
}
@article{aragones_variable_2024,
title = {Variable selection for nonlinear dimensionality reduction of biological datasets through bootstrapping of correlation networks},
volume = {168},
issn = {00104825},
url = {https://linkinghub.elsevier.com/retrieve/pii/S0010482523012921},
doi = {10.1016/j.compbiomed.2023.107827},
language = {en},
urldate = {2026-03-11},
journal = {Computers in Biology and Medicine},
author = {Aragones, David G. and Palomino-Segura, Miguel and Sicilia, Jon and Crainiciuc, Georgiana and Ballesteros, Iván and Sánchez-Cabo, Fátima and Hidalgo, Andrés and Calvo, Gabriel F.},
month = jan,
year = {2024},
pages = {107827},
}
@article{nino-lopez_mathematical_2023,
title = {Mathematical modeling of leukemia chemotherapy in bone marrow},
volume = {18},
copyright = {https://creativecommons.org/licenses/by/4.0},
issn = {0973-5348, 1760-6101},
url = {https://www.mmnp-journal.org/10.1051/mmnp/2023022},
doi = {10.1051/mmnp/2023022},
abstract = {Acute Lymphoblastic Leukemia (ALL) accounts for the 80\% of leukemias when coming down to pediatric ages. Survival of these patients has increased by a considerable amount in recent years. However, around 15 20\% of treatments are unsuccessful. For this reason, it is definitely required to come up with new strategies to study and select which patients are at higher risk of relapse. Thus the importance to monitor the amount of leukemic cells to predict relapses in the first treatment phase. In this work, we develop a mathematical model describing the behavior of ALL, examining the evolution of a leukemic clone when treatment is applied. In the study of this model it can be observed how the risk of relapse is connected with the response in the first treatment phase. This model is able to simulate cell dynamics without treatment, representing a virtual patient bone marrow behavior. Furthermore, several parameters are related to treatment dynamics, therefore proposing a basis for future works regarding childhood ALL survival improvement.},
urldate = {2026-03-11},
journal = {Mathematical Modelling of Natural Phenomena},
author = {Niño-López, Ana and Chulián, Salvador and Martínez-Rubio, Álvaro and Blázquez-Goñi, Cristina and Rosa, María},
year = {2023},
pages = {21},
}
