Cell cycle paths as a framework for understanding drug resistance in tumor cell subpopulations - SUMMARY / ABSTRACT Multiple clinical trials have shown that combining anti-estrogen therapy with CDK4/6 inhibitor therapy improves progression-free survival in ER+/HER2- breast cancer patients. However, many patients are resistant to CDK4/6 inhibitors or acquire resistance within the first few months of treatment. Interestingly, histological staining of treated tumors reveals a small but consistent population of cells in the proliferative phase of the cell cycle—a phenomenon we refer to as fractional resistance. It is critical to understand the mechanistic basis for fractional resistance because the precise fraction of proliferating tumor cells (e.g., 2% versus 15%) is a strong predictor of patient outcomes. Recent single-cell studies have shown that individual cells can take distinct trajectories, or “paths”, through the cell cycle that are defined by a unique combination of molecular states over time. We hypothesize that fractional resistance in breast tumors occurs because cells can take multiple paths through the cell cycle, but only some of these paths are sensitive to CDK4/6 inhibitors. To test this hypothesis, we have developed a powerful new method to profile >50 cell cycle regulator proteins in single cells. By linking single-cell states together, computationally, this approach has revealed how individual cells take alternate paths to evade cell cycle-targeted therapy. In Aim 1, we will induce fractional resistance in a panel of breast tumor models by applying increasing doses of CDK4/6 inhibitors and endocrine therapy to gradually eliminate subpopulations of proliferating tumor cells, thereby defining the range of molecular states cells can reach under drug treatment. Preliminary work suggests that resistant cells must take a particular set of paths at the G1/S transition characterized by high ratios of cyclins (e.g., cyclin D/E) to CDK inhibitors (e.g., p21/p27); altered CDT1 expression; and elevated E2F1 levels. We will validate these predictions through time-lapse microscopy. Aim 2 will take an unbiased approach to determine changes to the global protein landscape in response to increasing doses of endocrine/CDK4/6 inhibitor therapy. Using deep, quantitative proteomics that combines massive offline peptide fractionation with tandem mass tag labeling, we will determine changes to the protein landscape in response to CDK4/6 inhibition; validate these changes biochemically and by imaging; and determine the impact of the molecular state changes on sensitivity or resistance to endocrine/CDK4/6 inhibitor therapy. New preliminary results show multiple candidate regulators (e.g., CDKN3, UHRF1) that are cell cycle - dependent or expressed in fractionally resistant subpopulations. Aim 3 will identify resistant paths in resected human tumors—a technique developed by our surgical team. In addition, we will test the fractional resistance hypothesis in three ER+/HER2- PDX models to assess the extent of fractional resistance in long term, physiologically relevant model. Overall, this project will provide new knowledge in how heterogeneity in cell cycle behaviors leads to fractional drug resistance in ER+/HER2- tumors; identify novel resistance factors; and pave the way for the development of next-generation biomarkers that capture the unique cell cycle behaviors and drug sensitivities in other cancer types.
