A major challenge in cancer therapeutics is to kill tumour cells without harming other cells in the body. One means to achieve this is to exploit the genetic changes that distinguish cancer cells from normal cells and that may leave them vulnerable to targeted treatments. A promising approach to developing such targetted treatments is the identification of genetic dependencies – genes whose function is only essential in the presence of specific cancer-associated mutations. To this end a number of research groups have carried out loss-of-function experiments to identify genetic dependencies in cancer cell lines with a particular mutation. These experiments are expensive to carry out and often produce large quantities of data. In effect the results of these experiments are hypothesis generating resources (e.g. in patients with mutation X gene Y will be a good drug target) that serve as a starting point for more targetted research (e.g. testing a drug in a mouse model). However, typically the resulting datasets are difficult to analyse for those without extensive bioinformatics skills, and consequently they are underutilised. There is currently no way for cancer researchers interested in a specific gene to identify the experimentally determined genetic dependencies (candidate drug targets) associated with their gene of interest. Here we propose to build an easy to query online database that will permit those researchers without bioinformatics expertise to retrieve the dependencies identified for their gene of interest.
