Extensive drug pairing identifies new cancer treatments

Sometimes there are no short cuts. Of the roughly 100 cancer drugs currently approved by the US Food and Drug Administration (FDA), many are best used in combination, partly because cancers can become resistant to individual drugs. But finding effective pairings is hard because of the sheer number of potential combinations. So Susan Holbeck at the National Cancer Institute in Rockville, Maryland, and colleagues tried them all.

In a two-year study, her team systematically tested all 4950 possible pairings of 100 cancer drugs on 60 different types of human cancer cell. They also tested each pairing at various different concentrations. Team member James Doroshow at the National Cancer Institute in Bethesda, Maryland, estimates that the study involved around 1.5 million separate tests. This systematic approach allowed the team to investigate drug combinations that might otherwise be overlooked. Indeed, about 0.1 per cent of the tests produced positive results that were completely unexpected, says Doroshow.

The team tested the new combinations in human tumours grafted into mice and found they were more effective than the most active doses of single drugs.

The team now need to work out why the unexpected combinations worked well. "There are hundreds of examples that need to be followed up," says Doroshow.

Holbeck points out that they have a headstart since the cells are all well understood, so it should be easier to work out what is going on at the molecular level.

Further trials are needed to learn more about the new combinations, but since all the drugs are FDA-approved, progress to the next stage of trials should be quick. The team presented the study this week at the Symposium on Molecular Targets and Cancer Therapeutics in Dublin, Ireland.

Holbeck and her team plan to make all their data public as a resource for other researchers. This should make further validation easier. "Ideally, this needs to be done in hundreds of cell lines," says Paul Workman , head of the Division of Cancer Therapeutics at the Institute of Cancer Research in Sutton, UK. "This data-driven and unbiased way to identify promising combinations is better than the old more ad hoc approach."

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