Theranostic Layer‐by‐Layer Nanoparticles for Simultaneous Tumor Detection and Gene Silencing
| Autor: | Joelle P. Straehla, Paula T. Hammond, Liangliang Hao, Santiago Correa, Natalie Boehnke, Sangeeta N. Bhatia, Wade Wang |
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| Rok vydání: | 2020 |
| Předmět: |
Proteases
Peptide Biosensing Techniques Gene delivery 010402 general chemistry 01 natural sciences Theranostic Nanomedicine Article Catalysis Mice Drug Delivery Systems medicine Animals Gene silencing Gene Silencing Ovarian Neoplasms chemistry.chemical_classification Tumor microenvironment 010405 organic chemistry General Medicine General Chemistry medicine.disease 0104 chemical sciences chemistry Drug delivery Cancer research Nanoparticles Female Colorectal Neoplasms Peptides Ovarian cancer Biosensor |
| Zdroj: | PMC Angew Chem Int Ed Engl |
| ISSN: | 1521-3773 1433-7851 |
| DOI: | 10.1002/anie.201911762 |
| Popis: | Layer-by-layer nanoparticles are modular drug delivery vehicles that incorporate multiple functional materials through sequential deposition of polyelectrolytes onto charged nanoparticle cores. Here, we combined the multicomponent features and tumor targeting capabilities of layer-by-layer assembly with functional biosensing peptides to create a new class of nanotheranostics. These nanoparticles encapsulate a high weight percentage of siRNA while also carrying a synthetic biosensing peptide on the surface that is cleaved into a urinary reporter upon exposure to specific proteases overexpressed in the tumor microenvironment. Importantly, this biosensor reports back on molecular signatures characteristic to metastatic tumors and associated with poor prognosis – MMP9 protease overexpression. We show this nanotheranostic mediates noninvasive urinary-based diagnostics in mouse models of three different cancers with simultaneous gene silencing in flank and metastatic mouse models of ovarian cancer. This work provides a modular nanotheranostic platform to both perturb and characterize tumors, allowing for simultaneous treatment and monitoring of disease. |
| Databáze: | OpenAIRE |
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