Size-variable self-feedback nanomotors for glioblastoma therapy via mitochondrial mineralization
Developing targeted treatment for glioblastoma is crucial but challenging. Herein, we propose a size-variable self-feedback nanomotor system, utilizing the unique high-calcium microenvironment of glioblastoma to prevent its progression through mitochondrial mineralization. It comprises three components: a self-feedback degradable lipid shell (containing nitric oxide-releasing lipid and nitric oxide-responsive degradable lipid), a motion nanomotor core (containing L-arginine derivatives and carboxyl-rich zwitterionic monomers for Ca<sup>2+</sup> recruitment), and curcumin (inhibiting Ca<sup>2+</sup> efflux). Nitric oxide-releasing lipid can be catalyzed by inducible nitric oxide synthase to release nitric oxide, triggering nitric oxide-responsive degradable lipid degradation. Initially, the larger nanomotors (~ 500 nm) penetrate the blood-brain barrier via chemotaxis towards glioblastoma microenvironment. During chemotaxis, the lipid shell gradually degrades, releasing smaller nanomotor core (~50 nm), which can target mitochondria and recruit Ca<sup>2+</sup> to induce mitochondrial mineralization together with curcumin, inhibiting glioblastoma progression. This work may provide a glioblastoma-specific treatment strategy.
Authors
- Mimi Wan (ORCID: https://orcid.org/0000-0002-8686-7961)
- shifa liu (ORCID: https://orcid.org/0009-0003-6570-2812)
- Chun Mao (ORCID: https://orcid.org/0000-0003-4085-3414)
- Yingjie Wang (ORCID: https://orcid.org/0000-0002-6393-763X)
- Xue Xia (ORCID: https://orcid.org/0000-0002-2872-7151)
- Tiantian Chen (ORCID: https://orcid.org/0000-0001-6090-099X)
- Tiantian Liang (ORCID: https://orcid.org/0000-0001-8331-2066)
- Yu Duan (ORCID: https://orcid.org/0000-0002-2155-7188)
Institutions
- Nanjing Normal University (CN)
Publication Details
- Journal
- Nature Communications
- Published
- 2025-10-09
- DOI
- https://doi.org/10.1038/s41467-025-64020-x
- Citations
- 3
- Primary Topic
- Micro and Nano Robotics
- Type
- article
- Field-Weighted Citation Impact
- 3.77
Funders
- National Natural Science Foundation of China