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Congratulations to Associate Professor Francesca Buffa who has been awarded a five-year €2M grant by the European Research Council (ERC) to develop computer simulations of cancer cell behaviour, to help us personalise cancer treatment and prevent drug resistance.

In many cases we know which parts of cells go wrong when they divide uncontrollably, leading to cancer. Also, we are becoming better and better at developing drugs which correct each individual problem.

However, cancer cells often depend on more than one thing going wrong (often a gene mutation). This series of changes “rewires” the cancer cell circuitry, and each person’s cancer will have its own combination of re-wiring.  This means that each person will need a different drug or combination of drugs to correct this rewiring and cure their disease.

When tumours no longer respond to drug treatment in the clinic, they have often become resistant by gaining more mutations and switching their circuitry. Then it is difficult for us to know which treatment to give.

To help us understand the flexibility in cancer cell circuitry, Francesca (a mathematical biologist) is constructing ‘virtual’ cancer cells inside a computer from what we know about the mutations that affect real cancer cell behaviour. Effectively, she is turning the cancer cell ‘circuits’ into real electrical circuits inside a computer.

These “in-silico“ cancer cells undergo constant improvements using up-to-date information from cancer cell biologists, until hopefully the cancer cells inside the computer will behave just like real living cancer cells.

The virtual cancer cells will enable us to test the effects of different drugs or drug combinations in a computer rather than in real-world clinical trials. This will dramatically increase the speed and reduce the cost of research.

Eventually, a biopsy from each real tumour could be used to generate an equivalent virtual tumour, which would then be used to quickly identify the best therapy for that patient. This means that Francesca’s work represents a potentially important step towards truly personalised cancer medicine.

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