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The CDK4/6 inhibitor palbociclib blocks cell cycle progression in Estrogen receptor–positive, human epidermal growth factor 2 receptor–negative (ER+/HER2−) breast tumor cells. Despite the drug’s success in improving patient outcomes, a small percentage of tumor cells continues to divide in the presence of palbociclib—a phenomenon we refer to as fractional resistance. It is critical to understand the cellular mechanisms underlying fractional resistance because the precise percentage of resistant cells in patient tissue is a strong predictor of clinical outcomes. Here, we hypothesize that fractional resistance arises from cell-to-cell differences in core cell cycle regulators that allow a subset of cells to escape CDK4/6 inhibitor therapy. We used multiplex, single-cell imaging to identify fractionally resistant cells in both cultured and primary breast tumor samples resected from patients. Resistant cells showed premature accumulation of multiple G1 regulators including E2F1, retinoblastoma protein, and CDK2, as well as enhanced sensitivity to pharmacological inhibition of CDK2 activity. Using trajectory inference approaches, we show how plasticity among cell cycle regulators gives rise to alternate cell cycle “paths” that allow individual tumor cells to escape palbociclib treatment. Understanding drivers of cell cycle plasticity, and how to eliminate resistant cell cycle paths, could lead to improved cancer therapies targeting fractionally resistant cells to improve patient outcomes. 

This study demonstrates application of convolutional neural networks (CNNs) for the analysis of a unique image analysis problem in fluorescence microscopy. We employed the U-Net CNN architecture and trained a model to segment nuclear regions in images of a translocating biosensor—which alternates between the nucleus and cytoplasm—without the need for a constant nuclear marker. The modelprovided high-quality segmentation results that allowed us to accurately quantify the extent of cyclin-dependentkinase activity in a population of cells. We envision that the development of this kind of analysis tools will enable biologists to design live-cell fluorescence imaging experiments without the need for providing a constant marker for a subcellular region of interest. As a consequence, they willbe free to increase the number of biosensors measured in single cells or reduce the phototoxicity of cellular imaging.