Magnetically switchable mechano-chemotherapy for enhancing the death of tumour cells by overcoming drug-resistance
Source abstract
Abstract
Abstract The emergence of drug-resistant tumour cells significantly interferes with the effectiveness of chemotherapeutic treatment plans and represents a major obstacle in the ongoing quest to overcome cancers. Therefore, exploring in detail new therapeutic strategies that can obviate this important challenge is regarded as a very important topic at the time being. Herein, we propose a non-invasive and remotely controllable mechano-chemotherapeutic approach that relies on the use of a rotating magnetic field (RMF) of low intensity (45 m T) in combination with a therapeutic agent consisting of a composite nanomaterial comprised of a poly(lactic-co-glycolic acid) (PLGA) shell co-loaded with Zn0.2Fe2.8O4 magnetic nanoparticles (mNPs) and Doxorubicin (DOX). We show that RMF exposure induces a mechanical movement to this nanomaterial, which can be exploited for (i) controllably releasing the anti-cancer drug for chemotherapy, and (ii) promoting the death of tumour cells by means of mechanical forces exerted onto their membranes. Such dual behavior leads to combating cancer cells via different and complementary routes enabling a controllable and efficient therapy. The proposed model enables controllable tumor therapy by precisely operating the magnetic nanomaterials at the nanometer scale, and its applicability is neither restricted to the nanomaterial here demonstrated nor to solely addressing cancer. Modified variants of the proposed model, together with the corresponding therapeutic agents, can be developed to address other pathologies, enabling novel therapeutic approaches that exceed the precision and efficiency of current ones.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Nanoparticle-Based Drug Delivery · Micro and Nano Robotics · Erythrocyte Function and Pathophysiology
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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