Better Data on Gene Interactions Could Improve Cancer Treatments
Network algorithms can improve cancer treatment effectiveness by better determining how genes interact, researchers from the University of Sussex have found. The scientists’ algorithm, Slant, uses current data to find patterns associated with being part of a synthetic lethal interaction.
Current cancer treatments such as chemotherapy are limited in effect and often mean difficult side-effects for the patient. While other therapies which exploit the relationship between genes are currently being developed, currently few such interactions have been identified.
Synthetically lethal genetic relationships can survive so long as either one of its proteins stop working, but die if both fail. Such relationships can be used to determine potential locations for drugs to target which will leave healthy cells unharmed, creating a more effective and precise treatment.
Slant works by looking at an expansive protein network for patterns, and using that data to predict new synthetically lethal pairs. Once validated in the lab, the predictions were made publically-available on a new database called Slorth, where clinicians can look for a particular gene or drug and find relevant synthetic lethal interaction.