Have you seen our new ‘How I treat…’ features? Become a member (it’s free!) and discover the latest advice from fellow clinicians here >>>

Mapping cancer’s ‘social networks’ identifies new molecular targets

In ground-breaking research funded by Cancer Research UK, scientists from The Institute of Cancer Research (London, UK), have developed a computer model that identifies novel methods of treating cancer utilizing techniques developed to analyze existing social networks, such as Facebook.

The published research, which is publicly available in PLOS Computational Biology, could speed up advances in cancer drug discovery.

To create the model, cancer-causing proteins and their interactions were compared with members of an enormous protein social network. The scientists analyzed the unique behaviour of cancer-related proteins to predict which proteins may be effectively targeted. From this information, molecular targets for new therapeutic agents were mapped out.

Bissan Al-Lazikani, Team Leader in Computational Biology and Cancer Research UK-funded scientist at The Institute of Cancer Research commented: “Our study is the first to identify the rules of social behaviour of cancer proteins and use it to predict new targets for potential cancer drugs. It shows that cancer drug targets behave very differently from normal proteins and often have a complex web of social interactions, like a Facebook super-user.”

The team reported many molecular pathway interactions within their model that contributed to the development of cancer. Particular ‘social’ characteristics were identified in cancer-causing proteins that have already been successfully targeted with cancer drugs.

The research suggests that previously unexplored cancer proteins with similar characteristics may also make effective drug targets.

Al-Lazikani continued: “Finding new targets is one of the most important steps in drug discovery. But it can be a lengthy, expensive process. The map that we’ve made 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.”

Source: Cancer Research UK press release