Advancements in tissue engineering combined with the disease seeking nature of stem cells have provided new grounds for targeted therapy of cancer. However the discrepancies found in existing literature on the role of un-modified stem cells at tumour sites (Klopp et al. 2011), indicates the need for further research.
In vitro approaches provide an insight into actual cell behaviour under given conditions. However these methods are limited by factors such as cost, time and technological advancements in available protocols. In silico tools provide means for quantitative analysis of accumulated data in addition to exploring scenarios and queries otherwise impossible to create in the lab. However these tools can lack in accuracy and realistic correlation with actual biological behaviour. The combination of both in vitro and in silico methods results in a powerful tool that compensates for the limitations of both approaches.
An agent-based model (ABM) is a bottom-up approach that uses information regarding cell behaviour at the single cell level to generate emergent cell population results. Through the development of an agent-based model, the resulting effects of known and hypothesised rules regarding individual cell characteristics and cell-to-cell interactions will be simulated. Where possible, the model rules will be informed and the final model predictions validated using results and observations obtained from cell culture experiments run simultaneously, allowing for a one-to-one mapping of in vitro and in silico results.
Computational modelling coupled with cell culture experiments will provide an insight into the mechanisms behind stem cell and cancer cell interactions, taking us one step closer to using stem cells as a method of cancer treatment
