28 June 2016
Many tumours are able to adapt to attack by anti-cancer drugs, rendering the drugs ineffective and resulting in the continued spread of the disease. A team of bioengineers, biologists, and mathematicians have devised a nanotech based approach they hope will offer more effective delivery for combination drugs to block this ‘adaptive resistance’ of tumour cells.
Using a model developed by the maths team comprising algorithms that describe genetic changes to individual tumour cells as they were subjected to chemotherapy, researchers were able to predict the cellular pathways and signals via which tumour cells developed resistance.
The advantage of this predictive model is that it allows researchers to anticipate the most probable changes cells will undergo to evade a cancer drug, allowing them to provide multi-drug combination treatments that attack the cancer on different fronts.
It also suggests that a key limitation of current combination therapies may be that, to be effective, both drugs have to be active in the same cell and at the same time.
Using the same mathematical model, the research team pinpointed a key culprit in the development of a tumour cell’s drug resistance - the PI3K/AKT kinase. At this point the bioengineers stepped up to create a nanoparticle that could deliver a combination of two drugs that simultaneously target the tumour cell using different mechanisms (including in this instance one that acts via the PI3K/AKT kinase inhibitors) to prevent the cell from evading the first drug.
“We were inspired by the mathematical understanding that a cancer cell rewires the mechanisms of resistance in a very specific order and time-sensitive manner,” said Professor Aaron Goldman, who worked on the study “By developing a 2-in-1 nanomedicine, we could ensure the cell that was acquiring this new resistance saw the lethal drug combination, shutting down the survival program and eliminating the evidence of resistance". Ultimately, continued Professor Goldman: ”This approach could redefine how clinicians deliver combinations of drugs in the clinic.”
The results of using the mathematical modelling to predict an effective combination therapy have been demonstrated in mouse models of aggressive breast cancer.