A computer model has uncovered a hitherto unknown combination of two drugs, potentially effective in the treatment of triple negative breast cancer, a disease so far incurable.
Even for triple negative breast cancers (without any known markers, editor’s note), it is possible to find new treatments thanks to computers and genomics. It is the result ofa new study, published in the journal PLOS Computational Biology.
Triple negative breast cancer currently has no drug treatment. For those patients who suffer from it, the only hope is chemotherapy. If it doesn’t work, the survival rate is only 12 months. To deal with the disease, researchers have used genetic data from either triple-negative cancer cells grown in the lab or from female patients.
Triple negative breast cancer cells can develop resistance to a drug over a period of days, sometimes hours, mainly by rerouting signaling pathways inside cells. “It’s like when there is a car accident: the traffic manages to redirect itself without causing a traffic jam,” explains the study’s lead author, Dr. Nguyen, also an oncologist in Boston. His team has thus developed a computer model aimed at predicting how the network reroutes itself in response to a drug agent.
Different combinations of drugs
These predictions then allowed them to rank the different combinations of drugs most likely to beat cancer, by blocking the new pathway taken by cancer cells. Using data from the Cancer Genome Atlas, the researchers tested their ranking chart of drug combinations to determine their success in people who survived triple negative breast cancer. They then discovered a hitherto unknown combination of two drugs, which could be effective in the treatment of this hitherto incurable disease. “We hope this new combination will be in clinical trials within two to five years,” said Dr Nguyen.
This computer model can be adapted and used to determine effective drug combinations for other serious cancers, such as lung cancer and melanoma. In these last two cases, a rerouting of the network to avoid the effect of the drug was also observed.
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