Cancer is one of the major causes of mortality, globally. Cancerous cells invade normal cells and metastasize to distant sites with the help of the lymphatic system. There are several mechanisms involved in the development and progression of cancer. Several treatment strategies including the use of phytoconstituents have evolved and been practiced for better therapeutic outcomes against cancer. Fisetin is one such naturally derived flavone that offers numerous pharmacological benefits, i.e., antioxidant, anti-inflammatory, antiangiogenic, and anticancer properties. It inhibits the rapid growth, invasiveness, and metastasis of tumors by hindering the multiplication of cancer cells, and prompts apoptosis by avoiding cell division related to actuation of caspase-9 and caspase-8. However, its poor bioavailability associated with its extreme hydrophobicity hampers its clinical utility. The issues related to fisetin delivery can be addressed by adapting to the developmental aspects of nanomedicines, such as formulating it into lipid or polymer-based systems, including nanocochleates and liposomes. This review aims to provide in-depth information regarding fisetin as a potential candidate for anticancer therapy, its properties and various formulation strategies.
Nanoconstructs are made up of nanoparticles and ligands, which can deliver the loaded cargo at the desired site of action. Various nanoparticulate platforms have been utilized for the preparation of nanoconstructs, which may serve both diagnostic as well as therapeutic purposes. Nanoconstructs are mostly used to overcome the limitations of cancer therapies, such as toxicity, nonspecific distribution of the drug, and uncontrolled release rate. The strategies employed during the design of nanoconstructs help improve the efficiency and specificity of loaded theranostic agents and make them a successful approach for cancer therapy. Nanoconstructs are designed with a sole purpose of targeting the requisite site, overcoming the barriers which hinders its right placement for desired benefit. Therefore, instead of classifying modes for delivery of nanoconstructs as actively or passively targeted systems, they are suitably classified as autonomous and nonautonomous types. At large, nanoconstructs offer numerous benefits, however they suffer from multiple challenges, too. Hence, to overcome such challenges computational modelling methods and artificial intelligence/machine learning processes are being explored. The current review provides an overview on attributes and applications offered by nanoconstructs as theranostic agent in cancer.
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