4,340 research outputs found
Emergent Properties of Tumor Microenvironment in a Real-life Model of Multicell Tumor Spheroids
Multicellular tumor spheroids are an important {\it in vitro} model of the
pre-vascular phase of solid tumors, for sizes well below the diagnostic limit:
therefore a biophysical model of spheroids has the ability to shed light on the
internal workings and organization of tumors at a critical phase of their
development. To this end, we have developed a computer program that integrates
the behavior of individual cells and their interactions with other cells and
the surrounding environment. It is based on a quantitative description of
metabolism, growth, proliferation and death of single tumor cells, and on
equations that model biochemical and mechanical cell-cell and cell-environment
interactions. The program reproduces existing experimental data on spheroids,
and yields unique views of their microenvironment. Simulations show complex
internal flows and motions of nutrients, metabolites and cells, that are
otherwise unobservable with current experimental techniques, and give novel
clues on tumor development and strong hints for future therapies.Comment: 20 pages, 10 figures. Accepted for publication in PLOS One. The
published version contains links to a supplementary text and three video
file
Blood Vessel Tortuosity Selects against Evolution of Agressive Tumor Cells in Confined Tissue Environments: a Modeling Approach
Cancer is a disease of cellular regulation, often initiated by genetic
mutation within cells, and leading to a heterogeneous cell population within
tissues. In the competition for nutrients and growth space within the tumors
the phenotype of each cell determines its success. Selection in this process is
imposed by both the microenvironment (neighboring cells, extracellular matrix,
and diffusing substances), and the whole of the organism through for example
the blood supply. In this view, the development of tumor cells is in close
interaction with their increasingly changing environment: the more cells can
change, the more their environment will change. Furthermore, instabilities are
also introduced on the organism level: blood supply can be blocked by increased
tissue pressure or the tortuosity of the tumor-neovascular vessels. This
coupling between cell, microenvironment, and organism results in behavior that
is hard to predict. Here we introduce a cell-based computational model to study
the effect of blood flow obstruction on the micro-evolution of cells within a
cancerous tissue. We demonstrate that stages of tumor development emerge
naturally, without the need for sequential mutation of specific genes.
Secondly, we show that instabilities in blood supply can impact the overall
development of tumors and lead to the extinction of the dominant aggressive
phenotype, showing a clear distinction between the fitness at the cell level
and survival of the population. This provides new insights into potential side
effects of recent tumor vasculature renormalization approaches
Multiscale modeling in biology
The 1966 science-fction film Fantastic Voyage captured the public imagination with a clever idea: what fantastic things might we see and do if we could minaturize ourselves and travel through the bloodstream as corpuscles do? (This being Hollywood, the answer was that we'd save a fellow scientist from evildoers.
Tumor growth instability and the onset of invasion
Motivated by experimental observations, we develop a mathematical model of
chemotactically directed tumor growth. We present an analytical study of the
model as well as a numerical one. The mathematical analysis shows that: (i)
tumor cell proliferation by itself cannot generate the invasive branching
behaviour observed experimentally, (ii) heterotype chemotaxis provides an
instability mechanism that leads to the onset of tumor invasion and (iii)
homotype chemotaxis does not provide such an instability mechanism but enhances
the mean speed of the tumor surface. The numerical results not only support the
assumptions needed to perform the mathematical analysis but they also provide
evidence of (i), (ii) and (iii). Finally, both the analytical study and the
numerical work agree with the experimental phenomena.Comment: 12 pages, 8 figures, revtex
Computational modelling of the behaviour of biomarker particles of colorectal cancer in fecal matter
Colorectal adenocarcinoma is one of the carcinogenic diseases that is increasing the morbidity and mortality rates worldwide. The disease initially occurs through the segregation of biomarker substances in the human system without manifesting symptoms that affect the health of the carrier. Early detection would allow the application of more effective treatments, less invasive procedures and reduce the development of cancer. The purpose of this investigation was the elaboration of a mathematical model and the development of computational simulations to visualize the behavior of biomarker particles in transit through the colon. The flow conditions, properties of the viscous medium and biological regions of interest were established. Constitutive models, numerical conditions and solution strategies were determined. A numerical grid was used to represent the model of the colon and the human feces that carry the bioparticles (biomarkers). The results indicated the trajectories of the bioparticles in the fecal mass and the interactive movement with the natural contractions of the colon. The analysis of the movement of the biomarker particles can provide future less invasive alternatives for the detection in real time of the cancer by means of the implantation of biosensors in the walls of the colon
Radiotherapy planning for glioblastoma based on a tumor growth model: Improving target volume delineation
Glioblastoma are known to infiltrate the brain parenchyma instead of forming
a solid tumor mass with a defined boundary. Only the part of the tumor with
high tumor cell density can be localized through imaging directly. In contrast,
brain tissue infiltrated by tumor cells at low density appears normal on
current imaging modalities. In clinical practice, a uniform margin is applied
to account for microscopic spread of disease.
The current treatment planning procedure can potentially be improved by
accounting for the anisotropy of tumor growth: Anatomical barriers such as the
falx cerebri represent boundaries for migrating tumor cells. In addition, tumor
cells primarily spread in white matter and infiltrate gray matter at lower
rate. We investigate the use of a phenomenological tumor growth model for
treatment planning. The model is based on the Fisher-Kolmogorov equation, which
formalizes these growth characteristics and estimates the spatial distribution
of tumor cells in normal appearing regions of the brain. The target volume for
radiotherapy planning can be defined as an isoline of the simulated tumor cell
density.
A retrospective study involving 10 glioblastoma patients has been performed.
To illustrate the main findings of the study, a detailed case study is
presented for a glioblastoma located close to the falx. In this situation, the
falx represents a boundary for migrating tumor cells, whereas the corpus
callosum provides a route for the tumor to spread to the contralateral
hemisphere. We further discuss the sensitivity of the model with respect to the
input parameters. Correct segmentation of the brain appears to be the most
crucial model input.
We conclude that the tumor growth model provides a method to account for
anisotropic growth patterns of glioblastoma, and may therefore provide a tool
to make target delineation more objective and automated
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