journal article·2020-05Open access

Cholesterol-functionalized carvedilol-loaded PLGA nanoparticles: anti-inflammatory, antioxidant, and antitumor effects

Ana Luiza C. de S. L. Oliveira, Alaine M. dos Santos-Silva, Arnóbio A. da Silva-Júnior, Vinícius B. Garcia, Aurigena A. de Araújo, Lioe-Fee de Geus-Oei, Alan B. Chan, Luis J. Cruz, Raimundo F. de Araújo Júnior

Journal of Nanoparticle Research· Volume 22· Issue 5

Abstract

Abstract The inflammation has been identified as factor of tumor progression, which has increased the interest and use of molecules with anti-inflammatory and antioxidant activities in the cancer treatment. In this study, the antioxidant, anti-inflammatory, and antitumor potentials of carvedilol was explored in a different approach. The cholesterol (CHO) was investigated as facilitated agent in the action of carvedilol-loaded nanoparticles. Different formulations exhibited spherical and stable nanoparticle with mean diameter size < 250 nm. The cholesterol changed the copolymer-drug interactions and the encapsulation efficiency. The in vitro cancer study was performed using murine colorectal cancer cell line (CT-26) to observe the cell viability and apoptosis on MTS assay and flow cytometry, respectively. The experiments have demonstrated that cholesterol improved the performance of drug-loaded nanoparticles, which was much better than free drug. The in vivo inflammation peritonitis model revealed that carvedilol-loaded nanoparticles increased the level of glutathione and leukocyte migration mainly when the functionalized drug-loaded nanoparticles were tested, in a lower dose than the free drug. As hypothesized, the experimental data suggest that cholesterol-functionalized carvedilol-loaded PLGA nanoparticles can be a novel and promising approach in the inflammation-induced cancer therapy since showed anti-inflammatory, antioxidant, and antitumor effects.
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Research context

OpenAlex topics: Inflammatory Biomarkers in Disease Prognosis · Nanoplatforms for cancer theranostics · Nanoparticle-Based Drug Delivery

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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