An intelligent combination of mathematics and cell biology could spell death to brain tumours
Combining two separate observations of cells in brain tumours could enable doctors to improve the success rate of radiotherapy. Speaking today (23 January) at the Institute of Physics Simulation and Modelling Applied to Medicine conference in London, chemical engineer Dr Norman Kirkby from the University of Surrey will explain how using the correct time intervals between a sequence of low dose radiotherapy sessions could increase the chance of curing brain cancers that tend to resist treatment.
The work started with the discovery that there is a class of brain cancers (gliomas) that are susceptible to low doses of radiation, but can resist high doses. These cancers can occur in children as well as adults. They are difficult to treat because they do not form solid lumps that can be removed by surgery. Instead they spread in a diffuse manner through the brain.
The question was, would it be possible to find a way of getting the most benefit from giving multiple sessions of low-dose therapy? A team of chemical engineers, cell biologists and clinicians, drawn from the University of Surrey, Addenbrooke’s Hospital in Cambridge and The Gray Cancer Institute at Mount Vernon Hospital in Middlesex, came together to see if they could make some accurate predictions.
Kirkby and colleagues built a mathematical model that described the biology of cancer, and the effect that radiation has on it. Tumours grow when a number of cells multiply. For this to occur, cells take part in a cycle of activity, in which they first produce new copies of the genetic information, then check that the copies have no errors, before finally splitting the cell into two. During the checking phase of the cell cycle they also repair any errors in the genetic code.
Radiotherapy works by damaging each cell’s DNA. But if the therapy is given when cells are in the repair phase of their cycle, they will simply sort out the damage and carry on growing.
The new mathematical model is enabling the team to calculate the best time intervals to leave between doses of radiation, so that the maximum number of cells are caught at a time when they can’t repair the damage. It suggests that a patient should receive small doses at fairly precise times, several times a day. This is new. Standard systems of treatment give larger doses with intervals of a few days.
“The model is convincing, but the challenge will be to find ways of fitting this treatment schedule into the diaries of a working radiotherapy department,” says cancer expert Dr Neil Burnet.
Team member Dr Susan Short hopes that giving low doses of treatment at optimum time intervals will mean that they can destroy the cancer cells in people’s brains without causing excessive damage to the normal brain tissue.
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