Exploring oncology treatment strategies with tyrosine kinase inhibitors through advanced 3D models (Review).

Abstract

The limitations of two-dimensional (2D) models in cancer research have hindered progress in fully understanding the complexities of drug resistance and therapeutic failures. However, three-dimensional (3D) models provide a more accurate representation of in vivo environments, capturing critical cellular interactions and dynamics that are essential in evaluating the efficacy and toxicity of tyrosine kinase inhibitors (TKIs). These advanced models enable researchers to explore drug resistance mechanisms with greater precision, optimizing treatment strategies and improving the predictive accuracy of clinical outcomes. By leveraging 3D models, it will be possible to deepen the current understanding of TKIs and drive forward innovations in cancer treatment. The present review discusses the limitations of 2D models and the transformative impact of 3D models on oncology research, highlighting their roles in addressing the challenges of 2D systems and advancing TKI studies.