Assessing BIM expression as a cause and marker for resistance to targeted therapi

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DESCRIPTION (provided by applicant): Over, the past several years, we have learned that subsets of genetically defined cancers require an activated kinase for their growth and survival. In these cancers, the kinase is often directly activated by genetic alteration; mutation, amplification or translocation. These cancer cells are "addicted" to the genetically activated kinase, and they die, via apoptosis, upon inhibition of the kinase. This is known as "targeted therapy." These findings have already had a transformative impact on cancer therapeutics. In 2009, Massachusetts General Hospital (MGH) created a Translational Research Laboratory to perform multiplexed genetic analyses on the lung cancers of all patients being treated at MGH, and we have genotyped over 600 cases in the past year. This technology is quickly being implemented at many other cancer centers throughout the country, highlighting the importance of this burgeoning field. Intriguingly, while many of these genetically defined cancers (such as EGFR mutant and ALK translocated) have dramatic responses following targeted therapies, some have either poor responses or no responses, for largely unknown reasons. While resistance in some of these cancers are thought to be caused by secondary mutations that result in sustained intracellular signaling in the presence of targeted therapy, a large population of patients, whom do not carry these mutations in their cancers, are resistant for unknown reasons. We have found that targeted therapies are most effective when they induce both growth arrest and cell death (apoptosis). When they fail to, responses are mitigated. The inadequacy of targeted therapies to induce apoptosis may be caused by a deficiency in the pro-apoptotic protein, BIM. In this application, we propose that, in the setting of oncogene addiction, resistance arises when targeted therapies fail to induce apoptosis in oncogene-addicted cancers, despite downregulation of the intracellular signaling and posit that these cancers fail to undergo apoptosis because of deficiencies in the expression of BIM. We highlight preliminary data that supports these hypotheses, including functional in vitro and in vivo analyses, predictive power of BIM expression to apoptosis in cell line models, and patient data suggesting BIM expression can prospectively predict patient response to EGFR mutant targeted therapies. Lastly, we discuss potential, testable pharmaceutical strategies to overcome BIM deficiency in these cancers. If our testable hypothesis is proven correct, determining BIM expression in pre-treatment levels of oncogene- addicted cancers will change the way this growing population of cancer patients is treated.