Prediction and validation of avascular tumor growth pattern in different metabolic conditions using in silico and in vitro models
In recent years, scientists have taken many efforts for and modeling of cancerous tumors. In fact, three-dimensional (3D) cultures of multicellular tumor spheroids (MCTSs) are good validators for computational results. The goal of this study is to simulate the 3D early growth of avascular tumors usi...
Saved in:
Published in | Journal of bioinformatics and computational biology Vol. 19; no. 5; p. 2150024 |
---|---|
Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Singapore
01.10.2021
|
Subjects | |
Online Access | Get more information |
Cover
Loading…
Summary: | In recent years, scientists have taken many efforts for
and
modeling of cancerous tumors. In fact, three-dimensional (3D) cultures of multicellular tumor spheroids (MCTSs) are good validators for computational results. The goal of this study is to simulate the 3D early growth of avascular tumors using MCTSs and to compare the
models with the results and predictions of a specific computational modeling framework. Using these two types of models, the importance of metabolic condition on tumor growth behavior and necrosis could be predicted.
We took advantage of a previously developed computational model of tumor growth (constructed by integrating a generic metabolic network model of cancer cells with a multiscale agent-based framework). Among the computational predictions is the importance of glucose accessibility on tumor growth behavior. To study the effect of glucose concentration experimentally, MCTSs were grown in high and low glucose culture media. After that, tumor growth pattern was analyzed by MTT assay, cell counting and propidium iodide (PI) staining.
We obviously observed that the rate of necrosis increases and the rate of tumor growth and cell activity decreases as the glucose availability reduces, which is in line with the computational model prediction. |
---|---|
ISSN: | 1757-6334 |
DOI: | 10.1142/S0219720021500244 |