Stimuli-Sensitive Biodegradable and Amphiphilic Block Copolymer-Gemcitabine Conjugates Self-Assemble into a Nanoscale Vehicle for Cancer Therapy.
Zhenyu DuanYanhong ZhangHongyan ZhuLing SunHao CaiBijin LiQiyong GongZhongwei GuQiang LuoPublished in: ACS applied materials & interfaces (2017)
The availability and the stability of current anticancer agents, particularly water-insoluble drugs, are still far from satisfactory. A widely used anticancer drug, gemcitabine (GEM), is so poorly stable in circulation that some polymeric drug-delivery systems have been under development for some time to improve its therapeutic index. Herein, we designed, prepared, and characterized a biodegradable amphiphilic block N-(2-hydroxypropyl) methacrylamide (HPMA) copolymer-GEM conjugate-based nanoscale and stimuli-sensitive drug-delivery vehicle. An enzyme-sensitive oligopeptide sequence glycylphenylalanylleucylglycine (GFLG) was introduced to the main chain with hydrophilic and hydrophobic blocks via the reversible addition-fragmentation chain transfer (RAFT) polymerization. Likewise, GEM was conjugated to the copolymer via the enzyme-sensitive peptide GFLG, producing a high molecular weight (MW) product (90 kDa) that can be degraded into smaller MW segments (<50 kDa), and ensuring potential rapid site-specific release and stability in vivo. The amphiphilic copolymer-GEM conjugate can self-assemble into compact nanoparticles. NIR fluorescent images demonstrated that the conjugate-based nanoparticles could accumulate and be retained within tumors, resulting in significant increased antitumor efficacy compared to free GEM. The conjugate was not toxic to organs of the mice as measured by body weight reductions and histological analysis. In summary, this biodegradable amphiphilic block HPMA copolymer-gemcitabine conjugate has the potential to be a stimuli-sensitive and nanoscale drug-delivery vehicle.
Keyphrases
- cancer therapy
- drug delivery
- drug release
- body weight
- locally advanced
- atomic force microscopy
- heat shock protein
- metabolic syndrome
- deep learning
- photodynamic therapy
- emergency department
- squamous cell carcinoma
- liquid chromatography
- quantum dots
- adipose tissue
- machine learning
- type diabetes
- climate change
- rectal cancer
- human health
- convolutional neural network
- high resolution
- high fat diet induced
- adverse drug
- tandem mass spectrometry
- fluorescence imaging
- label free