2026-08-10T07:23:59Zhttps://repisalud.isciii.es/rest/oai/requestoai:repisalud.isciii.es:20.500.12105/126922025-04-04T10:19:20Zcom_20.500.12105_17008com_20.500.12105_2173com_20.500.12105_2051com_20.500.12105_2052col_20.500.12105_17010col_20.500.12105_19597col_20.500.12105_19617
Repisalud
author
Pérez-García, Víctor M
author
Calvo, Gabriel F
author
Bosque, Jesús J
author
León-Triana, Odelaisy
author
Jiménez, Juan
author
Perez-Beteta, Julián
author
Belmonte-Beitia, Juan
author
Zhu, Lucía
author
García-Gómez, Pedro
author
Sánchez-Gómez, Pilar
author
Hernandez-SanMiguel, Esther
author
Hortigüela, Rafael
author
Azimzade, Youness
author
Molina-García, David
author
Martinez, Álvaro
author
Acosta Rojas, Ángel
author
Ortiz de Mendivil, Ana
author
Vallette, Francois
author
Schucht, Philippe
author
Murek, Michael
author
Pérez-Cano, María
author
Albillo, David
author
Honguero Martínez, Antonio F
author
Jiménez Londoño, Germán A
author
Arana, Estanislao
author
García Vicente, Ana M
author
Valiente, Manuel
funder
James S. McDonnell Foundation
funder
Unión Europea. Fondo Europeo de Desarrollo Regional (FEDER/ERDF)
funder
Regional Government of Castile-La Mancha (España)
funder
Ministerio de Economía y Competitividad (España)
funder
Bristol-Myers Squibb
funder
Beug Foundation for Metastasis Research
funder
Fundación Ramón Areces
funder
Worldwide Cancer Research
funder
Unión Europea. Comisión Europea. H2020
funder
Fundación La Marató TV3
funder
Cancer Research Institute (CRI). Clinic & Laboratory Integration Program (CLIP)
funder
Asociación Española Contra el Cáncer
funder
Fundación La Caixa
funder
Ministerio de Ciencia e Innovación. Centro de Excelencia Severo Ochoa (España)
funder
European Molecular Biology Organization
2021-04-20T07:49:50Z
2021-04-20T07:49:50Z
2020-12-16
Nat Phys. 2020 ;16(12):1232-1237.
10.1038/s41567-020-0978-6
1745-2473
Nature physics
https://pmc.ncbi.nlm.nih.gov/articles/PMC7116451/
33329756
http://hdl.handle.net/20.500.12105/12692
Most physical and other natural systems are complex entities composed of a large number of interacting individual elements. It is a surprising fact that they often obey the so-called scaling laws relating an observable quantity with a measure of the size of the system. Here we describe the discovery of universal superlinear metabolic scaling laws in human cancers. This dependence underpins increasing tumour aggressiveness, due to evolutionary dynamics, which leads to an explosive growth as the disease progresses. We validated this dynamic using longitudinal volumetric data of different histologies from large cohorts of cancer patients. To explain our observations we put forward increasingly-complex biologically-inspired mathematical models that captured the key processes governing tumor growth. Our models predicted that the emergence of superlinear allometric scaling laws is an inherently three-dimensional phenomenon. Moreover, the scaling laws thereby identified allowed us to define a set of metabolic metrics with prognostic value, thus providing added clinical utility to the base findings.
eng
TUMOR-GROWTH
GENERAL-MODEL
EVOLUTION
PREDICTS
SURVIVAL
RATES
PET
Universal scaling laws rule explosive growth in human cancers
preprint
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Universalscalinglawsrule_2020.pdf
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Universalscalinglawsrule_2020.pdf.txt