The plk1 Gene Regulatory Network Modeling Identifies Three Circuits for plk1-mediated Genomic Instability Leading to Neoplastic Transformation

Genomic instability has been increasingly recognized over the past decade as a fundamental driver of cancer initiation and progression, largely owing to its association with specific genes and cellular mechanisms that offer therapeutic potential. However, a comprehensive molecular framework that captures the interconnected processes underlying this phenomenon remains elusive. In this study, we focused on polo-like kinase 1 (PLK1), a key cell cycle regulator frequently overexpressed in diverse human tumors, to reconstruct a regulatory network that consolidates pre-existing biological knowledge exclusively related to pathways involved in genome stability maintenance and cancer. The resulting model integrates nine biological processes, 1030 reactions, and 716 molecular species to form a literature-supported network in which PLK1 serves as a central regulatory node. However, rather than depicting an isolated PLK1-centric system, this network reflects a broader and more complex architecture of interrelated genomic instability mechanisms. As expected, the simulations reproduced known behaviors associated with PLK1 dysregulation, reinforcing the well-established role of the kinase in genome destabilization. Importantly, this model also enables the exploration of additional, less-characterized dynamics, including the potential involvement of genes such as kif2c, incenp, and other regulators of chromosomal segregation and DNA repair, which appear to contribute to instability events downstream of PLK1. While these findings are grounded in mechanistic simulations and require further experimental validation, gene expression and survival analyses across tumor types support their clinical relevance by linking them to poor prognosis in specific cancers. Overall, the model provides a systemic and adaptable foundation for studying PLK1-related genomic instability, enabling both the reinforcement of known mechanisms and discovery of candidate genes and circuits that may drive tumorigenesis through compromised genome integrity across distinct cancer contexts.