Abstract
This study aimed to develop and evaluate phosphatidylserine (PS)-targeted nanoparticles for efficient delivery of methotrexate to tumor sites. Therefore, methotrexate-loaded formulations were designed and optimized by response surface methodology and validated by the genetic algorithm-artificial neural network. The optimized nanoparticles (MNP17) were further conjugated with annexin-v (ANX) using the carbodiimide coupling technique to develop the ANX-conjugated nanoparticles (ANX-MNP). These formulations were evaluated for physicochemical properties such as drug entrapment, loading, mean particle size, surface charge, morphology, and in vitro drug release. The mean particle size of formulations MNP17 and ANX-MNP were found to be 121 and 146 nm, respectively. Drug entrapment and drug loading were found to be greater than 65% and 32%, respectively. The morphology of the nanoparticles was investigated by transmission electron microscopy and atomic force microscopy. In vitro drug release from formulation was found to be approximately 90% after 120 h. The release mechanism followed the Korsmeyer Peppas model and non-Fickian diffusion (0.5 < n < 0.85). In vitro cytotoxic studies showed significantly better effects of ANX-MNP than MNP17 and native drug in MDA-MB-231 cells. Qualitative and quantitative cellular uptake studies showed higher uptake of ANX-MNP than MNP17 by MDA-MB-231 cells. The formulations showed enhanced nuclear fragmentation, generation of reactive oxygen species, alterations in mitochondrial membrane potential, and decreased colony formation and Bcl-2 expressions in ANX-MNP as compared to MNP17 and native drug. These study findings demonstrated the potential of ANX-MNP as a carrier for improved drug delivery in cancer treatment. The utilization of physiological changes of cancer cells, i.e., PS on the outer leaflet of plasma membrane serves as a ligand to achieve the site-specific drug delivery via exploiting the affinity of ANX towards exposed PS is the novelty of present research.
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