Computational Modelling of Metastasis Development in Renal Cell Carcinoma
Abstract
To improve our understanding of the biology of the metastatic colonization process, we
conducted a modelling study based on multi-modal data from an orthotopic murine experimental
system of metastatic renal cell carcinoma. The standard theory of metastatic colonization usually
assumes that secondary tumours, once established at a distant site, grow independently from each
other and from the primary tumour. Using a mathematical model describing the metastatic
population dynamics under this assumption, we challenged the theory against our data that
included: 1) dynamics of primary tumour cells in the kidney and metastatic cells in the lungs,
retrieved by green fluorescent protein tracking, and 2) magnetic resonance images (MRI) informing
on the number and size of macroscopic lesions. While the model could fit the primary tumour and
total metastatic burden, the predicted size distribution was not in agreement with the MRI
observations. Moreover, the model was incompatible with the growth rates of individual metastatic
tumours.
To explain the observed metastatic patterns, we hypothesised that metastatic foci derived
from one or a few cells could aggregate, resulting in a similar total mass but a smaller number of
metastases. This was indeed observed in our data and led us to investigate the effect of spatial
interactions on the dynamics of the global metastatic burden. We derived a novel mathematical
model for spatial tumour growth, where the intra-tumour increase in pressure is responsible for the
slowdown of the growth rate. The model could fit the growth of lung metastasis visualized by
magnetic resonance imaging. As a non-trivial outcome from this analysis, the model predicted that
the net growth of two neighbouring tumour lesions that enter in contact is considerably impaired (of
31% ± 1.5%, mean ± standard deviation), as compared to the growth of two independent tumours.
Together, our results have implications for theories of metastatic development and suggest that
global dynamics of metastasis development is dependent on spatial interactions between metastatic
lesions.
Fichier principal
journal.pcbi.1004626.pdf (1.2 Mo)
Télécharger le fichier
S1_Fig.tif (404.87 Ko)
Télécharger le fichier
S1_File.avi (9.6 Mo)
Télécharger le fichier
S2_Fig.tif (1 Mo)
Télécharger le fichier
S2_File.avi (2.48 Mo)
Télécharger le fichier
S3_Fig.tif (3.15 Mo)
Télécharger le fichier
S3_File.avi (4.32 Mo)
Télécharger le fichier
S4_Fig.tif (1.56 Mo)
Télécharger le fichier
S5_Fig.tif (1.42 Mo)
Télécharger le fichier
S6_Fig.tif (91.43 Ko)
Télécharger le fichier
S7_Fig.tif (517.92 Ko)
Télécharger le fichier
Origin : Publication funded by an institution
Origin : Files produced by the author(s)
Origin : Files produced by the author(s)
Origin : Files produced by the author(s)
Origin : Files produced by the author(s)
Origin : Files produced by the author(s)
Origin : Files produced by the author(s)
Origin : Files produced by the author(s)
Origin : Files produced by the author(s)
Origin : Files produced by the author(s)
Origin : Files produced by the author(s)
Loading...