Supplementary material from: An Investigation on the System Dynamics ofmiR-944 Regulation in Non-Small Cell LungCancer through Mathematical Modelling

MicroRNAs (miRNAs) are key regulators of gene expression and are involved in various cancer-related processes, including tumor initiation and progression. This study presents a mathematical model to investigate the gene regulatory network associated with non-small cell lung cancer (NSCLC), focusing on the interplay between miR-944 and the tumor suppressor gene EPHA7. Using ordinary differential equations (ODEs), we modeled the mutual regulation among NSCLC, miR-944, and EPHA7, incorporating Hill functions to capture gene regulation dynamics. Our analysis shows that with a basic Hill function, the system’s equilibrium remains stable. However, incorporating higher-order Hill functions introduces complex dynamics and potential bifurcations.Through simplification and rescaling of the Jacobian matrix, we examined stability under varied conditions and identified regions of parameter space exhibiting steady states and switch-like behavior. Numerical simulations further suggest that miR-944 may act as a regulatory switch influencing NSCLC proliferation. This study demonstrates the effectiveness of mathematical modeling in understanding miRNA-driven gene networks in cancer and highlights miR-944 as a potential therapeutic target for NSCLC.