Iron oxide nanoparticles coated with bioactive materials: a viable theragnostic strategy to improve osteosarcoma treatment
Source abstract
Abstract
Abstract Osteosarcoma (OS) is distinguished as a high-grade malignant tumor, characterized by rapid systemic metastasis, particularly to the lungs, resulting in very low survival rates. Understanding the complexities of tumor development and mutation is the need of the hour for the advancement of targeted therapies in cancer care. A significant innovation in this area is the use of nanotechnology, specifically nanoparticles, to tackle various challenges in cancer treatment. Iron oxide nanoparticles stand out in both therapeutic and diagnostic applications, offering a versatile platform for targeted drug delivery, hyperthermia, magneto-thermal therapy, and combinational therapy using modulation of ferroptosis pathways. These nanoparticles are easy to synthesize, non-toxic, biocompatible, and display enhanced circulation time within the system. They can also be easily conjugated to anti-cancer drugs, targeting agents, or genetic vectors that respond to specific stimuli or pH changes. The surface functionalization of these nanoparticles using bioactive molecules unveils a promising and effective nanoparticle system for assisting osteosarcoma therapy. This review will summarize the current conventional therapies for osteosarcoma and their disadvantages, the synthesis and modification of iron oxide nanoparticles documented in the literature, cellular targeting and uptake mechanism, with focus on their functionalization using natural biomaterials and application strategies towards management of osteosarcoma. The review also compiles the translational challenges and future prospects that must be addressed for clinical advancements of iron oxide based osteosarcoma treatment in the future. Graphical abstract
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Research context
OpenAlex topics: Extracellular vesicles in disease · Nanoparticle-Based Drug Delivery · Nanoplatforms for cancer theranostics
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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