Microenvironment-responsive EGCG-functionalized nanoplatform for synergistic photothermal-chemotherapy against triple-negative breast cancer
Source abstract
Abstract
Abstract Triple-negative breast cancer (TNBC) presents significant therapeutic challenges due to its aggressive nature and lack of molecular targets. To address this challenge, we developed a pH/thermo-responsive nanoplatform based on epigallocatechin-3-gallate (EGCG) modified lipid-coated polydopamine (TEDP), capable of loading doxorubicin (DOX). EGCG, a bioactive polyphenol with high affinity for laminin receptors overexpressed in cancer cells, served both as a targeting ligand and immune microenvironment remodeling regent, enabling selective uptake and remodeling immunosuppression cells. Thermosensitive EGCG modified DOX loaded PDA (TEDP) nanoparticles exhibited spherical morphology (∼140 nm), good colloidal stability, and efficient photothermal conversion under near-infrared irradiation. Under a trigger temperature and pH 6.0, TEDP exhibited pH/temperature-triggered drug release, achieving 70% precise drug release within 4 h, thereby enabling spatiotemporally controlled drug release. Both in vitro and in vivo experiments demonstrated that TEDP nanoparticles could significantly enhance targeting, ensuring precise drug release at the tumor site while minimizing off-target toxicity of DOX. In a TNBC tumor model, the tumor suppression efficacy of TEDP treatment exceeded that of chemotherapy or photothermal therapy (PTT) monotherapy by 3.2-fold and 1.7-fold, respectively. The findings highlighted that TEDP nanoparticles generated synergistic enhancement effects through chemotherapy, PTT and anti-tumor immune responses activating. The multimodal nanoplatform would hold great promise in TNBC therapy, offering a strategy to overcome the limitations of conventional monotherapies.
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Research context
OpenAlex topics: Nanoplatforms for cancer theranostics · Nanoparticle-Based Drug Delivery · Cancer Research and Treatments
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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