Hydrogels incorporated with graphene-based nanomaterials for cancer therapy: A review
Source abstract
Abstract
Graphene-based nanomaterials (GBNs), in particular graphene oxide and reduced graphene oxide, have emerged as promising multifunctional nanomaterials for cancer therapy. The growing interest in these nanostructures lies in their exceptionally high drug-loading and photothermal capacities. Conventionally, these GBNs are administered through intravenous injection. However, this systemic route is often associated with a limited tumor uptake and off-target distribution, diminishing the therapeutic capacity of GBNs. To overcome these limitations, hydrogels are soaring as innovative local delivery systems capable of encapsulating and confining the GBNs (and other therapeutics) into the tumor site. These three-dimensional biocompatible matrices are formed by exploiting natural or synthetic polymers, which are then crosslinked by physical and/or chemical cues. The incorporation of GBNs into hydrogels matrices enhances drug loading, modulates release kinetics, and enables photoinduced hyperthermia. Therefore, several in vitro and in vivo studies have evidenced that the GBNs-incorporated hydrogels can perform a more effective chemotherapy, photothermal therapy or chemo-photothermal therapy, while at the same time, reducing the side-effects or diminishing tumor-recurrence rates. This review delves into the preclinical application of GBNs-incorporated hydrogels for cancer chemotherapy, photothermal therapy, and chemo-photothermal therapy. • GBNs stand out for their high drug-loading and photothermal capabilities. • Hydrogels incorporating GBNs enhance drug loading and modulate release kinetics. • Hydrogels can encapsulate GBNs and confine them at the tumor site. • Hydrogels incorporating GBNs can mediate a localized and improved therapy.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Graphene and Nanomaterials Applications · Cancer Research and Treatment · Carbon and Quantum Dots Applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (100+)
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