Mechanistic characterization of oscillatory patterns in unperturbed tumor growth dynamics: The interplay between cancer cells and components of tumor microenvironment
Keywords: 
Mathematical modeling
Materias Investigacion::Matemáticas
Tumor
Issue Date: 
2023
Publisher: 
PLOS
Project: 
info:eurepo/grantAgreement/AEI/Proyectos I+D/PID2020- 116927RB-C22/[ES]/ANALISIS COMPUTACIONAL DEL IMPACTO DE RIESGOS GENETICOS Y CLINICOS EN LA SEÑALIZACION MOLECULAR Y DISFUNCIONES ELECTROFISIOLOGICAS EN FIBRILACION AURICULAR
ISSN: 
1553-7358
Note: 
This is an open access article distributed under the terms of the Creative Commons Attribution License
Citation: 
Sancho-Araiz, A. (Aymara); Parra-Guillen, Z.P. (Zinnia Patricia); Bragard, J. (Jean); et al. "Mechanistic characterization of oscillatory patterns in unperturbed tumor growth dynamics: The interplay between cancer cells and components of tumor microenvironment". Computational Biology. 19 (10), 2023, e1011507
Abstract
Mathematical modeling of unperturbed and perturbed tumor growth dynamics (TGD) in preclinical experiments provides an opportunity to establish translational frameworks. The most commonly used unperturbed tumor growth models (i.e. linear, exponential, Gompertz and Simeoni) describe a monotonic increase and although they capture the mean trend of the data reasonably well, systematic model misspecifications can be identified. This represents an opportunity to investigate possible underlying mechanisms controlling tumor growth dynamics through a mathematical framework. The overall goal of this work is to develop a data-driven semi-mechanistic model describing non-monotonic tumor growth in untreated mice. For this purpose, longitudinal tumor volume profiles from different tumor types and cell lines were pooled together and analyzed using the population approach. After characterizing the oscillatory patterns (oscillator half-periods between 8–11 days) and confirming that they were systematically observed across the different preclinical experiments available (p<10−9), a tumor growth model was built including the interplay between resources (i.e. oxygen or nutrients), angiogenesis and cancer cells. The new structure, in addition to improving the model diagnostic compared to the previously used tumor growth models (i.e. AIC reduction of 71.48 and absence of autocorrelation in the residuals (p>0.05)), allows the evaluation of the different oncologic treatments in a mechanistic way. Drug effects can potentially, be included in relevant processes taking place during tumor growth. In brief, the new model, in addition to describing non-monotonic tumor growth and the interaction between biological factors of the tumor microenvironment, can be used to explore different drug scenarios in monotherapy or combination during preclinical drug development.

Files in This Item:
Thumbnail
File
journal.pcbi.1011507.pdf
Description
Size
2.71 MB
Format
Adobe PDF


Statistics and impact
0 citas en
0 citas en

Items in Dadun are protected by copyright, with all rights reserved, unless otherwise indicated.