Journal article
Modeling cell differentiation in neuroblastoma: insights into development, malignancy, and treatment relapse
- Abstract:
- Neuroblastoma is a paediatric extracranial solid cancer that arises from the developing sympathetic nervous system and is characterised by an abnormal distribution of cell types in tumours compared to healthy infant tissues. In this paper, we propose a new mathematical model of cell differentiation during sympathoadrenal development. By performing Bayesian inference of the model parameters using clinical data from patient samples, we show that the model successfully accounts for the observed differences in cell type heterogeneity among healthy adrenal tissues and four common types of neuroblastomas. Using a phenotypically structured model, we show that alterations in healthy differentiation dynamics are related to cell malignancy, and tumour volume growth. We use this model to analyse the evolution of malignant traits in a tumour. Our findings suggest that normal development dynamics make the embryonic sympathetic nervous system more robust to perturbations and accumulation of malignancies, and that the diversity of differentiation dynamics found in the neuroblastoma subtypes lead to unique risk profiles for neuroblastoma relapse after treatment.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 3.2MB, Terms of use)
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- Publisher copy:
- 10.1016/j.jtbi.2025.112230
Authors
+ Simons Foundation
More from this funder
- Funder identifier:
- https://ror.org/01cmst727
- Grant:
- MP-SIP-00001828
- Publisher:
- Elsevier
- Journal:
- Journal of Theoretical Biology More from this journal
- Volume:
- 614
- Article number:
- 112230
- Publication date:
- 2025-08-07
- Acceptance date:
- 2025-07-25
- DOI:
- EISSN:
-
1095-8541
- ISSN:
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0022-5193
- Language:
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English
- Pubs id:
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2280019
- Local pid:
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pubs:2280019
- Deposit date:
-
2025-08-12
Terms of use
- Copyright holder:
- Martina-Perez et al
- Copyright date:
- 2025
- Rights statement:
- © 2025 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
- Licence:
- CC Attribution (CC BY)
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