A computer model that applies techniques used to analyze social networks has been developed to identify new ways of treating cancer. The model analyses the unique behaviors of cancer-causing proteins, spotting what makes them different from normal proteins and mapping out molecular targets for new potential drugs that could be developed to treat cancer.
Scientists at The Institute of Cancer Research, London, compared proteins inside cells to members of an enormous social network, mapping the ways they interact. This allowed them to predict which proteins will be most effectively targeted with drugs.
‘Cancer-causing proteins tended to have particular 'social' characteristics that differ from non-cancer proteins. This suggests that previously unexplored cancer proteins with similar characteristics could also make good drug targets.’
The researchers have made this map publicly available. It could provide drug discovery scientists with a shortcut to finding new drugs for many different types of cancer. The team found that there are many molecular pathways that interact to affect the development of cancer.
Cancer-causing proteins, which have already been successfully targeted with drugs, tended to have particular 'social' characteristics that differ from non-cancer proteins, suggesting that previously unexplored cancer proteins with similar characteristics could also make good drug targets. 'Hub-like' proteins which 'communicate' with lots of other proteins - like a super-Facebook user with thousands of friends - were more likely to cause cancer.
Study leader Bissan Al-Lazikani said, "This map will help researchers design better new drugs, more quickly, saving time and money. It also sheds light on how resistance to treatments may occur, and in just a few years could help doctors choose the best drug combinations to suit individual patients."
The study is published in PLOS Computational Biology.