2026-05-17T01:16:09Zhttps://repisalud.isciii.es/rest/oai/requestoai:repisalud.isciii.es:20.500.12105/255232025-12-18T12:53:14Zcom_20.500.12105_2327com_20.500.12105_2290col_20.500.12105_16991
Repisalud
author
Ocaña-Tienda, Beatriz
author
Pérez-Beteta, Julián
author
Jiménez-Sánchez, Juan
author
Molina-García, David
author
Ortiz de Mendivil, Ana
author
Asenjo, Beatriz
author
Albillo, David
author
Pérez-Romasanta, Luis A
author
Valiente, Manuel
author
Zhu, Lucía
author
García-Gómez, Pedro
author
González-Del Portillo, Elisabet
author
Llorente, Manuel
author
Carballo, Natalia
author
Arana, Estanislao
author
Pérez-García, Víctor M
funder
Ministerio de Ciencia e Innovación (España)
funder
Regional Government of Castile-La Mancha (España)
funder
James S. Mc. Donnell Foundation (USA
2024-11-18T12:23:03Z
2024-11-18T12:23:03Z
2023-07-21
NPJ Syst Biol Appl . 2023 Jul 21;9(1):35.
NPJ Sustems biology and apllications
37479705
https://hdl.handle.net/20.500.12105/25523
Tumor growth is the result of the interplay of complex biological processes in huge numbers of individual cells living in changing environments. Effective simple mathematical laws have been shown to describe tumor growth in vitro, or simple animal models with bounded-growth dynamics accurately. However, results for the growth of human cancers in patients are scarce. Our study mined a large dataset of 1133 brain metastases (BMs) with longitudinal imaging follow-up to find growth laws for untreated BMs and recurrent treated BMs. Untreated BMs showed high growth exponents, most likely related to the underlying evolutionary dynamics, with experimental tumors in mice resembling accurately the disease. Recurrent BMs growth exponents were smaller, most probably due to a reduction in tumor heterogeneity after treatment, which may limit the tumor evolutionary capabilities. In silico simulations using a stochastic discrete mesoscopic model with basic evolutionary dynamics led to results in line with the observed data.
eng
BREAST-CANCER
GENERAL-MODEL
HETEROGENEITY
TRASTUZUMAB
LAWS
Growth exponents reflect evolutionary processes and treatment response in brain metastases.
research article
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URL
https://repisalud.isciii.es/bitstreams/424aa6d7-a15f-4229-9fe2-d50978fafc9e/download
File
MD5
cf8fc1b922a28ef69be11c06e1acd013
1467204
application/pdf
Growthexponentsreflectevolutionary_2023.pdf