Professor Paul Workman from the Institute of Cancer Research, who was not involved in the study, said: 'This important study sheds light on how human cancer cells are dependent on particular genes. The genes identified could be targets for drug discovery efforts to find new targeted treatments.'
'Much of what has been and continues to be done to characterise cancer has been based on genetics and sequencing. That's given us the parts list,' said study co-senior author Dr William Hahn, a member of both the Broad and Dana-Farber Institutes, and a leader in the Cancer Dependency Map initiative. 'Mapping dependencies ascribes function to the parts and shows you how to reverse engineer the processes that underlie cancer.'
The researchers inactivated thousands of different genes in more than 500 different human cancer cell lines (representing more than 20 different types of cancer), and then monitored cell growth and survival, to investigate which genes the cancers were dependent on. They used RNAi to inactivate the genes, a method of gene silencing which uses small pieces of RNA (siRNAs).
'The simplest thing one can do with perturbed cells is allow them to keep growing over time and see which ones thrive,' said study co-senior author Dr David Root, from the Broad Institute. 'If cells with a certain gene silenced disappear, for example, it means that gene is essential for proliferation.'
After exposing the cells to pools of these siRNAs, and following them for 40 days, the researchers analysed the results using a novel computational tool (DEMETER). This tool allowed researchers to differentiate true dependencies from false positives – a common problem in RNAi-based studies.
Many of the 'dependencies' identified are specific to certain cancer types. However, around 10 percent of them – 76 genes – are common to multiple cancers. This suggests that a relatively small number of therapies targeting these core dependencies might be used to treat a wide range of cancers. Furthermore, around 20 percent of the dependencies link back to genes previously identified as potential drug targets.
'Our results provide a starting point for therapeutic projects to decide where to focus their efforts,' said study co-first author Dr Francisca Vazquez.
However, the dependencies map is not yet all-inclusive. 'These estimates are hard to make, but we are probably 15 to 20 percent away from being complete,' said Dr Hahn.