Comparative Cell Cycle Phosphoproteomics Reveals Conserved Phosphorylation Events Across Cancer Cell Types

Protein phosphorylation functions as a fundamental regulatory switch in cell cycle progression. Despite multiple global phosphoproteomic studies profiling cell cycle-dependent phosphorylation events, a systematic comparison across different cell types to identify conserved phosphorylation sites has not yet been performed within a unified experimental framework. Here, we present a multi-cell-line cell cycle-dependent phosphoproteomic analysis across diverse cancer cells to characterize the conserved phosphoproteomic profile and assess dynamic indicators of cancer cell proliferation. By combining cell cycle synchronization with dimethyl labeling-based quantitative mass spectrometry, we generated a comprehensive dataset of cell cycle-dependent phosphorylation events across interphase, mitosis, and mitotic exit. In contrast to previous large-scale studies that relied on a single cellular model, our dataset captures both conserved and cell line-selective features of regulatory cell cycle phosphorylation. Comparison of the phosphorylation profiles across cell types revealed that cytokinesis displays a more heterogeneous and context-dependent pattern than mitosis. Focusing on a highly conserved mitotic exit phosphorylation site on keratin 8, we generated an ectopic keratin expression model in HEK 293 cells and validated our findings using targeted proteomics and high-resolution microscopy, demonstrating its essential role in maintaining cell division fidelity. Furthermore, this comparative analysis reveals that cells lacking native keratins can rapidly adapt to and reorganize an ectopic network through the conserved Aurora B-dependent pathway, highlighting the remarkable plasticity of the cell division machinery across different cellular contexts. This study provides a comprehensive characterization of phosphorylation dynamics across mitosis and mitotic exit, establishing a robust reference for comparative cell cycle signaling analyses.