Defining Intercellular Heterogeneity in Cell Cycle Quiescence

TITLE: Defining Intercellular Heterogeneity in Cell Cycle Quiescence SUMMARY Cancer cells proliferate inappropriately, yet they also routinely exit the cell division cycle. Cells that exit the cell cycle to a reversible arrest are quiescent (or dormant or “slow cycling”). Quiescent cells can resist most cancer therapies, including immunotherapy, and thus are a major driver of cancer relapse. Until recently, the field has been dominated by the notion of a binary “proliferation-quiescence” decision implying that only two states exist. However, evidence indicates a spectrum of quiescent states range from shallow quiescence to deep quiescence. Deep quiescent cells re-enter the cell cycle less quickly or easily than shallow cells. Nonetheless, there is little information about the relationship between quiescence depth and tumor progression or sensitivity to treatment. Existing technological barriers prevent us from evaluating the relative quiescence depth of individual cancer cells both in culture and in tissues. Current tools can provide a snapshot of cells at the time of analysis or give information about prior cell divisions, but there are few options for measuring the history of cells in tumors or tissues and no existing tools for analyzing quiescence depth heterogeneity. In this pilot project we will test newly-generated quiescence depth biosensors. Our goal is to determine how single-cell biosensor signals correlate with true quiescence depth. We have already generated a series of genetically-encoded cell age and quiescence depth biosensors. Preliminary tests in cultured cells indicate correlation among signal, absolute time since the final cell cycle (cell age), and metrics of quiescence depth. We propose to define the accuracy and dynamic range of these biosensors in a variety of cancer cell lines. We will then deploy them in xenograft experiments to determine quiescence depth of single cells within a tumor. We will also test for correlation of biosensor signal with response to selected anti-cancer therapies. Finally, we will use the biosensors to isolate cells of varying quiescence depths for unbiased transcriptome and proteome analysis. We will determine which endogenous genes and proteins characterize quiescence depth and seek novel cancer cell vulnerabilities to exploit. Success will provide a means to evaluate quiescence heterogeneity in both normal and tumor cells. Validating the biosensors will inspire future construction of a biosensor mouse for analyzing both spontaneous tumors and the non-transformed cells in their microenvironments. The potential impacts of this work are 1) unprecedented insight into heterogeneity among non- proliferating tumor cells, 2) endogenous quiescence depth indicators, and 3) new therapeutic strategies to target quiescent cancer cells.