Dataset Information

Engineering Multifunctional RNAi Nanomedicine To Concurrently Target Cancer Hallmarks for Combinatorial Therapy.

ABSTRACT: Cancer hallmarks allow the complexity and heterogeneity of tumor biology to be better understood, leading to the discovery of various promising targets for cancer therapy. An amorphous iron oxide nanoparticle (NP)-based RNAi strategy is developed to co-target two cancer hallmarks. The NP technology can modulate the glycolysis pathway by silencing MCT4 to induce tumor cell acidosis, and concurrently exacerbate oxidative stress in tumor cells via the Fenton-like reaction. This strategy has the following features for systemic siRNA delivery: 1)?siRNA encapsulation within NPs for improving systemic stability; 2)?effective endosomal escape through osmotic pressure and/or endosomal membrane oxidation; 3)?small size for enhancing tumor tissue penetration; and 4)?triple functions (RNAi, Fenton-like reaction, and MRI) for combinatorial therapy and in?vivo tracking.

SUBMITTER: Liu Y

PROVIDER: S-EPMC5898800 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Engineering Multifunctional RNAi Nanomedicine To Concurrently Target Cancer Hallmarks for Combinatorial Therapy.

Liu Yanlan Y Ji Xiaoyuan X Tong Winnie W L WWL Askhatova Diana D Yang Tingyuan T Cheng Hongwei H Wang Yuzhuo Y Shi Jinjun J Shi Jinjun J

Angewandte Chemie (International ed. in English) 20180116 6

Cancer hallmarks allow the complexity and heterogeneity of tumor biology to be better understood, leading to the discovery of various promising targets for cancer therapy. An amorphous iron oxide nanoparticle (NP)-based RNAi strategy is developed to co-target two cancer hallmarks. The NP technology can modulate the glycolysis pathway by silencing MCT4 to induce tumor cell acidosis, and concurrently exacerbate oxidative stress in tumor cells via the Fenton-like reaction. This strategy has the fol ...[more]

PMID: 29276823

Similar Datasets

Project description:Engineered protein therapeutics offer advantages, including strong target affinity, selectivity and low toxicity, but like natural proteins can be susceptible to proteolytic degradation, thereby limiting their effectiveness. A compelling therapeutic target is mesotrypsin, a protease up-regulated with tumour progression, associated with poor prognosis, and implicated in tumour growth and progression of many cancers. However, with its unique capability for cleavage and inactivation of proteinaceous inhibitors, mesotrypsin presents a formidable challenge to the development of biological inhibitors. We used a powerful yeast display platform for directed evolution, employing a novel multi-modal library screening strategy, to engineer the human amyloid precursor protein Kunitz protease inhibitor domain (APPI) simultaneously for increased proteolytic stability, stronger binding affinity and improved selectivity for mesotrypsin inhibition. We identified a triple mutant APPIM17G/I18F/F34V, with a mesotrypsin inhibition constant (Ki) of 89 pM, as the strongest mesotrypsin inhibitor yet reported; this variant displays 1459-fold improved affinity, up to 350?000-fold greater specificity and 83-fold improved proteolytic stability compared with wild-type APPI. We demonstrated that APPIM17G/I18F/F34V acts as a functional inhibitor in cell-based models of mesotrypsin-dependent prostate cancer cellular invasiveness. Additionally, by solving the crystal structure of the APPIM17G/I18F/F34V-mesotrypsin complex, we obtained new insights into the structural and mechanistic basis for improved binding and proteolytic resistance. Our study identifies a promising mesotrypsin inhibitor as a starting point for development of anticancer protein therapeutics and establishes proof-of-principle for a novel library screening approach that will be widely applicable for simultaneously evolving proteolytic stability in tandem with desired functionality for diverse protein scaffolds.

Dataset Information

Engineering Multifunctional RNAi Nanomedicine To Concurrently Target Cancer Hallmarks for Combinatorial Therapy.

Publications

Engineering Multifunctional RNAi Nanomedicine To Concurrently Target Cancer Hallmarks for Combinatorial Therapy.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure