In a bid to fight cancer with more precise medicine, researchers are developing computer simulations of tumors to predict how an individual patient's cancer is likely to react to specific drugs.
The computer simulations, or ‘virtual tumors’, test the ability of individual drugs to overcome the immune system suppression that cancer can trigger in the patient, allowing doctors to better zero-in on what type of treatment would work best for a particular individual's cancer. The current immunotherapy drugs used to overcome the suppression are only effective in 20 percent of patients
Researchers at the University of Iowa in the US believe they can increase the effectiveness of immunotherapy drugs by making them specific to the genetic makeup of the individual tumor's cells. To develop the approach, they first took the genetic information from a patient's cancer cell and loaded it into the computer simulation to predict the responses of particular drugs to certain immune checkpoints — molecules on immune cells that need to be activated or silenced to start an immune response.
The researchers then grew live cells in the lab with the same genetic makeup to see if the drug produces the same reaction in the cells' immune checkpoints. If the responses from the virtual tumor and the real live cells match, then it means the team has identified a treatment that will work for that individual patient. If the results are different, then more work needs to be done to align the model to the live cells.
Researchers believe that their virtual and live models could also be used to screen combination treatments; for instance, comprising either more than one immunotherapy drug, or where an immunotherapy drug is combined with a chemotherapy drug. They say their tests are currently producing around 85 percent correlation of matches and, they add, their goal is to produce a personalized cancer therapy that cuts treatment time and cost as well as help improve patients' long-term prospects.