On-Demand Generation of Peroxynitrite from an Integrated Two-Dimensional System for Enhanced Tumor Therapy

Nanosystem-mediated tumor radiosensitization strategy combining the features of X-ray with infinite penetration depth and high atomic number elements shows considerable application potential in clinical cancer therapy. However, it is difficult to achieve satisfactory anticancer efficacy using clinical radiotherapy for the majority of solid tumors due to the restrictions brought about by the tumor hypoxia, insufficient DNA damage, and rapid DNA repair during and after treatment. Inspired by the complementary advantages of nitric oxide (NO) and X-ray-induced photodynamic therapy, we herein report a two-dimensional nanoplatform by the integration of the NO donor-modified LiYF4:Ce scintillator and graphitic carbon nitride nanosheets for on-demand generation of highly cytotoxic peroxynitrite (ONOO–). By simply adjusting the Ce3+ doping content, the obtained nanoscintillator can realize high radioluminescence, activating photosensitive materials to simultaneously generate NO and superoxide radical for the formation of ONOO– in the tumor. Obtained ONOO– effectively amplifies therapeutic efficacy of radiotherapy by directly inducing mitochondrial and DNA damage, overcoming hypoxia-associated radiation resistance. The level of glutamine synthetase (GS) is downregulated by ONOO–, and the inhibition of GS delays DNA damage repair, further enhancing radiosensitivity. This work establishes a combinatorial strategy of ONOO– to overcome the major limitations of radiotherapy and provides insightful guidance to clinical radiotherapy. Agency for Science, Technology and Research (A*STAR) Submitted/Accepted version Financial support from the National Natural Science Foundation of China (51972075, 51972076, and 51772059), the Natural Science Foundation of Shandong Province (ZR2019ZD29), the Natural Science Foundation of Heilongjiang Province (YQ2019E014), the Postdoctoral Scientific Research Developmental Fund (LBH-Q18034), and the Ph.D. Student Research and Innovation Fund of the Fundamental Research Funds for the Central Universities (3072020GIP1016) are greatly acknowledged. This research is also supported by the Singapore Agency for Science, Technology and Research (A*STAR) AME IRG grant (A20E5c0081).