Computer models predict effectiveness of colon tumour therapy
17 July 2013
Computer models of the behaviour of colon tumour cells in
response to drugs have shown that a combination of drugs blocks a
survival mechanism triggered by using one drug alone.
The study by Charité – Universitätsmedizin Berlin has been
published in Molecular Systems Biology. 
In most tumours, the communication between the individual cells
is disturbed and the cells permanently receive growth and survival
signals. For this reason, drugs are increasingly used in modern
tumour therapy that targets those molecules to shut down these
faulty signals. Hitherto, however, it has been difficult to predict
the success of such a therapy, since the signal molecules are
integrated into an extremely complex cellular network, which,
moreover, reacts differently for each patient, depending on the
mutations the tumour bears.
The research group headed by Nils Blüthgen, Charité Institute of
Pathology, has now examined how the interconnection of such a
cellular network affects the effectiveness of a therapy. For this
purpose, the scientists created computer models to simulate the
networks of various colon cancer cells.
The models were adapted to quantitative data from cell culture
experiments. When analyzing their computer simulations, the
researchers discovered that the cellular tumour networks exhibited
strong feedback characteristics. This means that the cutting off of
a particular signal molecule activates a receptor, which, in turn,
then switches on signal paths that favour the survival of the tumour
In a further step, the computer model predicted a combination
therapy using two drugs, which prevents the activation of survival
signals, so making for a more effective therapy. The scientists have
tested these predictions on various cell models.
“The remarkable thing is that the combination of two therapies is
effective with a large number of different mutations, including the
mutant oncogene KRAS. This is a gene, which is of key importance for
the regulation of growth and differentiation processes, and for
which no targeted therapy has been possible up to now”, stated Nils
Blüthgen. “However, it is still too early to say whether this
behavior detected in the cell culture model can be applied to
patients. Here, further investigations are necessary”.
This approach undertaken by the researchers to combine computer
models with quantitative data to simulate the behaviour of networks
is called system biology. It is considered a promising method of
examining therapies and diagnostics for complex diseases.
“Particularly when investigating the effect of inhibitors in complex
networks, it is hardly possible to predict the network’s response
without the use of computer models”, according to Blüthgen.
1. Klinger B, et al. Network quantification of EGFR
signaling unveils potential for targeted combination therapy.
Molecular Systems Biology, 9: 673, 2013.