Eytan Ruppin, who serves at Blavatnik School of Computer Science and Sackler Faculty of Medicine in Tel Aviv University and his co-researchers have developed the cancer cell metabolism’s first computerized genome-size model that can be utilized to foresee the lethality of drugs affecting the functionality of the metabolism of a cancer cell.
Eytan Ruppin
It is possible to hinder the specific metabolic signatures of cancer cells, due to which the cells are destroyed in a selective and precise pattern.The research team has demonstrated the method’s efficiency in both lab and computer models for kidney cancer. Cancer cells metabolize nutrients in a unique manner for their energy and growth when compared to normal cells. The team developed the computer model based on numerous metabolic reactions that differentiate cancer cells.
The research team could differentiate the metabolism of cancer cells and normal cells by comparing the computer model with a pre-existing model of the metabolism of a normal human cell. It could then detect drug targets that have the capability to influence the unique, specific properties of cancer metabolism.
To study its predictions, the research team decided to target a particular kind of renal cancer cells. Ruppin said that in this renal cancer, the research team’s prediction was to use a drug that could hinder the enzyme HMOX participating in Heme metabolism, which in turn would kill cancer cells effectively and specifically without affecting normal cells. The team’s computer model directed it to predict that the Heme pathway was vital for the metabolism of the cancer cells.
Ruppin further said that his team will develop more models for other kinds of cancer and look for selective drug therapies to kill them. This multi-field method, which needs the results of experimental clinical trials as well as the forecast of a computer model, could develop more efficient and selective cancer therapies.