BSCI-13 DEVELOPMENT OF NOVEL ANTI-BRAIN METASTASIS INHIBITORS

Abstract The current standard of care (surgery and radiation) for brain metastases (BM) is inadequate as BM have a 90% mortality rate within one year of diagnosis, posing a large unmet clinical need. The Singh lab has generated a large in-house biobank of patient-derived BM cell lines that are established from BM patient tumor samples. We use these BM cell lines to generate murine orthotopic xenograft models of BM and interrogate the biological processes that lead to BM. These models have successfully recapitulated all the stages of their respective BM cascades and additionally captured a “pre-metastatic” population of BM cells that have just seeded the brains of mice before forming mature, clinically detectable tumors. Pre-metastatic cell populations are impossible to detect in human patients but represent a therapeutic window wherein metastasizing cells can be targeted and eradicated before establishing clinically detectable and difficult to treat brain tumors. RNA sequencing of pre-metastatic BM cells revealed a unique deregulated transcriptomic profile that is specific to pre-metastatic cells despite the tumor of origin. Connectivity Map analysis was applied to the gene expression signatures of pre-metastatic BM cells to identity a compound (Drug A) which selectively inhibits BM cell proliferation but is not blood-brain barrier (BBB) penetrant and has not been previously considered in the context of brain metastasis. We synthesized a BBB-penetrant analogue of Drug A and found, using our patient-derived xenograft (PDX) models, that it increased survival benefit relative to both placebo and Drug A. Beginning with this promising scaffold, we will conduct structure-activity hypothesis-driven medicinal chemistry campaigns to optimize this scaffold for brain permeation while maintaining selective anti-BM activity. Development of novel small molecules that target pre-metastatic BM cells could slow or prevent the formation of BM and dramatically improve the prognosis of at-risk cancer patients.