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

Area of Science:

• Oncology
• Biomedical Engineering
• Pharmacology

Background:

• Traditional two-dimensional (2D) cell culture models present significant limitations in recapitulating the complex tumor microenvironment.
• These limitations hinder the accurate assessment of drug resistance and therapeutic efficacy, particularly for targeted therapies like tyrosine kinase inhibitors (TKIs).

Purpose of the Study:

• To review the limitations of 2D cancer models in evaluating drug efficacy and toxicity.
• To highlight the advantages and transformative impact of three-dimensional (3D) models in oncology research.
• To emphasize the role of 3D models in advancing the study of TKIs and overcoming challenges in cancer treatment.

Main Methods:

• Comparative analysis of 2D versus 3D cell culture models in cancer research.
• Review of literature focusing on the application of 3D models for evaluating tyrosine kinase inhibitors (TKIs).
• Discussion of how 3D models improve the understanding of drug resistance and predict clinical outcomes.

Main Results:

• 3D models provide a more physiologically relevant environment, capturing cell-cell and cell-matrix interactions crucial for drug response.
• Advanced 3D models enhance the precision in studying drug resistance mechanisms and evaluating TKI efficacy and toxicity.
• These models improve the predictive accuracy of treatment outcomes compared to traditional 2D systems.

Conclusions:

• Three-dimensional models represent a significant advancement over 2D models for cancer research, particularly for TKI studies.
• Leveraging 3D models is essential for optimizing cancer treatment strategies and improving therapeutic success rates.
• Further adoption of 3D modeling will accelerate innovation in targeted cancer therapy.