Abstract
Inherent heterogeneity of tumors significantly limits the therapeutic efficacy of existing cancer treatment systems. This work proposes a dual-targeting theranostic system based on acid-responsive cleavage of a metal-organic framework (MOF). By functionalizing the MOF with dual aptamers that exhibit strict base complementarity to cancer cell biomarkers, the system achieves synergistic passive and active targeting, significantly improving the recognition accuracy for cancer cells. Simultaneously, leveraging the glucose-dependent metabolic features of tumor cells, the system efficiently catalyzes the generation of hydroxyl radicals (·OH) from glucose, thereby activating chemodynamic therapy. Furthermore, under infrared light irradiation, nickel (Ni) atoms doped within the MOF generate a photothermal effect, further enhancing the inactivation of cancer cells. Both in vitro and in vivo experiments confirm the high efficiency of this system for diagnosis and therapy. The photothermal effect of the MOF material is validated using density functional theory (DFT) calculations, and the therapeutic efficacy is evaluated using a machine learning-based approach, further demonstrating the system's potential for in vivo therapeutic application. This study provides a novel strategy for precise cancer diagnosis and therapy, offering promising potential to overcome the limitations of existing systems and provide new avenues for cancer theranostics.