Researchers at the Institute for Research in Biomedicine (IRB Barcelona) have recently identified 10 new possible combination therapies to treat breast cancer based using an in silico method to analyze cell signaling networks and 64 known drug pairings currently used to treat the disease, according to an advance publication of the result in the journal Cancer Research.
Of the 10 combinations tested in breast tumor cells in vitro, seven showed a high level of synergy (the joint effect is greater than the sum of the individual effects) and one has been validated in mice. The combination used in the mouse study, raloxifene and cabozantinib, are two drugs commonly prescribed by oncologists. When combined, IRB Barcelona researchers said the drugs “dramatically" boosted the anti-tumor effects of each of the two drugs.
“We identify many more synergistic combinations in silico than combinatorial assays do—until now—with high-performance lab techniques, and we can provide experimental details,” said Patrick Aloy, Ph.D., head of the structural bioinformatics and network biology lab at IRB Barcelona. “This implies that prior computational analyses give better results and are more reliable."
The researchers noted that in 70% of the combinations tested, the joint effects of the two drugs are "much much greater" than the effects of each alone, and therefore the same effect could be achieved with a smaller dose. When the researchers tested the combined raloxifene and cabozantinib treatment in mice, tumors shrank by 60%, compared to the individual effect of each drug, that merely prevented further tumor growth.
Further, the combination allowed significantly smaller doses of each drug in combination than typically prescribed when used alone (three-times smaller for raloxifene and 25-times smaller for cabozantinib).
"This in itself is very important, because drugs are in fact toxic and are used to kill cells. If, by using a smaller dose, a greater—or even the same—chemotherapeutic effect is achieved, it is a significant advantage with respect to reducing the side effects experienced by patients," said Dr. Aloy.
As part of the study, the researchers also examined the mechanisms of drug resistance and how to better predict when current therapeutic approaches may become less effective. The resistance to drugs arises due to random mutations within cancer cells that effectively allow the cancer to “learn” how to evade the treatment. In 15% of cases, alternative molecular signaling pathways are activated to allow the tumor cells to divide again or to evade programmed cell death.
Combination therapies have emerged as one of the promising approaches that can overcome this kind of drug resistance.
"Our analyses have allowed us to predict the signaling pathways that are inactivated by the joint action of two drugs," noted Samira Jaeger, postdoctoral fellows and first author of the study. "By combining drugs, we aim to attack the tumor cell simultaneously from various flanks, thus making it more difficult for the cell to resist treatment, as the pathways that allow it to survive and proliferate will be knocked out the same time."
Having validated their computational network model, IRB Barcelona researchers aim to use the approach for continuing studies in three separate areas: