Mechanisms of Sensitivity to Cell Cycle Checkpoint Kinase Inhibitors
Dartmouth College, Hanover NH
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Abstract
DESCRIPTION (provided by applicant): Many anticancer drugs target DNA resulting in activation of cell cycle checkpoints, arrest of proliferation, and repair, the consequence of which is recovery and survival of the tumor cells. Current efforts to enhance tumor cell killing include combining anticancer agents with inhibitors of DNA checkpoints. Chk1 has been identified as a critical kinase for cell cycle arrest and many inhibitors are currently in preclinical and clinical development; the current studies focus on the Chk1 inhibitor MK-8776. Recent results have identified a second critical function of Chk1 whereby it prevents the collapse of stalled replication forks. Accordingly, Chk1 inhibitors can dramatically sensitize cells to antimetabolites such as hydroxyurea and gemcitabine. Recently we discovered that stalled replication forks evolve to become more Chk1 dependent with time. This is critical to the development of Chk1 inhibitors as it impacts the timing of drug delivery in clinical trials. An additional observation s that some cell lines are hypersensitive to MK-8776 alone while others are completely resistant. The hypersensitive cell lines also require much less MK-8776 to sensitize them to hydroxyurea or gemcitabine. Accordingly, we hypothesize that a subset of tumors exist that will be highly responsive to the combination of MK-8776 plus either hydroxyurea or gemcitabine. This proposal will assess the variation in response to these drugs across a panel of cell lines and dissect the underlying mechanisms. The specific aims will 1) define the mechanism(s) for differential sensitivity of human tumor cell lines to MK-8776 as a single agent; 2) define the critical step(s) that occur at stalled replication forks that render them more Chk1 dependent with time; and 3) confirm the differential response of human cell lines when grown as xenograft tumors. In addition to establishing the underlying mechanisms, this research will define the optimum schedule of drug administration and biomarkers that can identify patients whose tumors are most likely to respond. This information will be critical for the design of clinical trils and selection of appropriate patients to treat.
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