The design of targeted therapeutic strategies for cancer has largely been driven by the identification of tumor-specific genetic changes. However, the large number of genetic alterations present in tumor cells means that it is difficult to discriminate between genes that are critical for maintaining the disease state and those that are merely coincidental. Even when critical genes can be identified, directly targeting these is often challenging, meaning that alternative strategies such as exploiting synthetic lethality may be beneficial. To address these issues, we have carried out a functional genetic screen in >30 commonly used models of breast cancer to identify genes critical to the growth of specific breast cancer subtypes. In particular, we describe potential new therapeutic targets for PTEN-mutated cancers and for estrogen receptor-positive breast cancers. We also show that large-scale functional profiling allows the classification of breast cancers into subgroups distinct from established subtypes.
Significance: Despite the wealth of molecular profiling data that describe breast tumors and breast tumor cell models, our understanding of the fundamental genetic dependencies in this disease is relatively poor. Using high-throughput RNA interference screening of a series of pharmacologically tractable genes, we have generated comprehensive functional viability profiles for a wide panel of commonly used breast tumor cell models. Analysis of these profiles identifies a series of novel genetic dependencies, including that of PTEN-null breast tumor cells upon mitotic checkpoint kinases, and provides a framework upon which additional dependencies and candidate therapeutic targets may be identified.