Highly Adaptable Dendrimer Gel Nanoparticles with Dual Targeting of uPAR and Ribonucleotide Reductase R2 for Better Retention and Improved Therapeutic Outcomes in Triple-Negative Breast Cancer
Triple-negative breast cancer (TNBC) accounts for approximately 15% of breast cancers and lacks estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2), rendering it unresponsive to hormonal or anti-HER2 therapies. Due to its poor prognosis and limited treatment options, there is an urgent need for targeted therapies. In this study, we developed highly adaptable polyamidoamine (PAMAM) dendrimer-based gel nanoparticles with dual-targeting capabilities against urokinase-type plasminogen activator receptor (uPAR) and ribonucleotide reductase R2 (R2). These nanoparticles were designed to target both TNBC cells and cancer-associated stromal cells by leveraging uPA-uPAR interactions and delivering the antisense oligonucleotide GTI-2040 (GTI) against R2. The resulting dual-functional dendrimer gel nanoparticles, GDP-uPA/GTI, demonstrated good biocompatibility, with an average size of ∼16.45 nm. GDP-uPA/GTI enhanced GTI delivery by 3.4-fold in TNBC cells (MDA-MB-231) and by 4.8-fold in stromal cells (HCC2218) compared to GTI alone. It reduced R2 expression by 83.1% and induced ∼30% TNBC cell death. In a TNBC xenograft model, GDP-uPA/GTI significantly inhibited tumor growth by 50.5%. These findings highlight the unique design of the dual-functional dendrimer gel nanoparticles and their dual-targeting efficacy, demonstrating their potential as a promising therapeutic strategy for TNBC.
Authors
- Da Huang (ORCID: https://orcid.org/0000-0003-3621-5233)
- Anna Chernatynskaya (ORCID: https://orcid.org/0000-0002-8179-0010)
- Yue‐Wern Huang (ORCID: https://orcid.org/0000-0003-1957-6459)
- Vidit Singh
- Hsin-Yin Chuang
- Hu Yang (ORCID: https://orcid.org/0000-0003-3030-004X)
- Lin Qi
Institutions
- Missouri University of Science and Technology (US)
- Fuzhou University (CN)
Publication Details
- Journal
- ACS Applied Materials & Interfaces
- Published
- 2025-06-02
- DOI
- https://doi.org/10.1021/acsami.5c03560
- Citations
- 2
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 3.01