Novel Bioengineering Strategies to Improve Bioavailability and In Vivo Circulation of H-Ferritin Nanocages by Surface Functionalization

Abstract

Due to its unique architecture and innate capability to specifically target cancer cells, ferritin has emerged as an attractive class of biomaterials for drug delivery. In many studies, various chemotherapeutics have been loaded into ferritin nanocages constituted by H-chains of ferritin (HFn), and their related anti-tumor efficacy has been explored by employing different strategies. Despite the multiple advantages and the versatility of HFn-based nanocages, there are still many challenges to face for their reliable implementation as drug nanocarriers in the process of clinical translation. This review aims at providing an overview of the significant efforts expended during recent years to maximize the features of HFn in terms of increased stability and in vivo circulation. The most considerable modification strategies explored to improve bioavailability and pharmacokinetics profiles of HFn-based nanosystems will be discussed herein.

Figure 1

Scheme of chemical and genetical modifications of HFn aimed at improving stability and in vivo circulation.

Figure 2

Fabrication and characterization of a biomineralized ferritin nanoplatform and evaluation of its in vivo distribution. (A) Schematic illustration of the preparation of the Fn@CaP nanoplatform. (B) Comparative analysis of blood half-life of Fn and Fn@CaP in HeLa tumor-bearing mice. (C) CLSM images of Fn and Fn@CaP accumulated in tumor tissues. (D) Comparative analysis of dynamic tumor versus liver fluorescence intensity of Cy7-labeled Fn and Fn@CaP in mice given the indicated treatments. (E) Comparative analysis of the fluorescence intensity of Cy7-labeled Fn and Fn@CaP at 24 h. Data represent the mean ± s.d. Statistical significance was calculated via a two-tailed Student’s t test (D, E). ***p < 0.001, ****p < 0.0001. Reproduced with permission from ref (23). Copyright 2021 Wiley-VCH GmbH.

Figure 3

Scheme of HFn-PASE loading strategy. Reproduced with permission from ref (28). Copyright 2022 Elsevier B.V.