fig6

Figure 6. Development of personalized treatment strategies for drug resistance. (A) High-resolution single-cell and spatial multi-omics analyses of patient samples to intratumoral heterogeneity characterization; (B) Computational analysis and bioinformatics tools to accurately identify drug-resistant subclones, decode subclone-specific characteristics, cell-cell interactions, and bypass signaling pathways, thereby computationally identifying potential drug resistance mechanisms and therapeutic targets; (C) Sequential use of cell models, 3D in vitro models, and animal models for identification of resistance mechanisms related targets, selection and validation of the most appropriate and effective drug types and personalized treatment strategies, and ultimately validation of their efficacy in clinical trials. The main challenges currently lie in reproducing in vivo the therapeutic effects of in vitro models and the low efficiency of constructing these models. Created in BioRender. Da, E. (2026) https://BioRender.com/ys10nrf.