To combat cancer, use at least two drugs at once

We now have a fairly large arsenal of drugs that can fight cancer. Unfortunately, tumor cells have a way of mutating so that they are no longer killed by these drugs. To forestall such problems, researchers from Harvard University and other institutions have come up with a mathematical model for predicting what it would take to eliminate cancer cells from a body. Most of the time, giving two anti-cancer drugs will do the trick.

Solid tumors are notorious for becoming resistant to drugs, so much so that doctors are starting to realize that most tumors probably already contain a few resistant mutants. This means that any treatment regimen that involves a single drug is almost certainly doomed to failure. The few resistant cells will always multiply and form a new tumor. The only way to completely prevent all tumor recurrences is to use more than one drug at a time.

Most of the time, two drugs administered together will be effective in killing all tumor cells. If the two drugs target different metabolic pathways, it’s all the more likely that they’ll be sufficient to cure the disease. The authors are careful to note that the two drugs must be given simultaneously. Giving two drugs sequentially is no better than giving just one drug, which is to say no good at all. This is extremely important because currently it is very common to treat with one drug at a time. A second drug is administered only after the first one fails to deliver the expected results.

As always, I must point out that I’m not a medical doctor and that this blog is not intended to be used to provide medical advice. That said, I think this information could lead to some promising changes in the way cancer is treated. Let’s hope it ends up helping some people.

Bozic I, Reiter JG, Allen B, Antal T, Chatterjee K, Shah P, Moon YS, Yaqubie A, Kelly N, Le DT, Lipson EJ, Chapman PB, Diaz LA Jr, Vogelstein B, & Nowak MA (2013). Evolutionary dynamics of cancer in response to targeted combination therapy. eLife, 2 PMID: 23805382.