2026-05-17T01:16:05Zhttps://repisalud.isciii.es/rest/oai/request

oai:repisalud.isciii.es:20.500.12105/255232025-12-18T12:53:14Zcom_20.500.12105_2327com_20.500.12105_2290col_20.500.12105_16991

00925njm 22002777a 4500 dc 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 author 2023-07-21 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. NPJ Syst Biol Appl . 2023 Jul 21;9(1):35. NPJ Sustems biology and apllications 37479705 https://hdl.handle.net/20.500.12105/25523 BREAST-CANCER GENERAL-MODEL HETEROGENEITY TRASTUZUMAB LAWS Growth exponents reflect evolutionary processes and treatment response in brain metastases.