journal article·2022-09-07

Apoptosis-Sensing Xenograft Zebrafish Tumor Model for Anticancer Evaluation of Redox-Responsive Cross-Linked Pluronic Micelles

Jinsong Tao, Zhengjie Wei, Yaxin Cheng, Meng Xu, Qiuxia Li, Simon Ming-Yuen Lee, Wei Ge, Kathy Qian Luo, Xueqing Wang, Ying Zheng

ACS Applied Materials & Interfaces· Volume 14· Issue 35
Publisher page

Abstract

A suitable animal model for preclinical screening and evaluation in vivo could vastly increase the efficiency and success rate of nanomedicine development. Compared with rodents, the transparency of the zebrafish model offers unique advantages of real-time and high-resolution imaging of the whole body and cellular levels in vivo. In this research, we established an apoptosis-sensing xenograft zebrafish tumor model to evaluate the anti-cancer effects of redox-responsive cross-linked Pluronic polymeric micelles (CPPMs) visually and accurately. First, doxorubicin (Dox)-loaded CPPMs were fabricated and characterized with glutathione (GSH)-responsive drug release. Then, the B16F10 xenograft zebrafish tumor model was established to mimic the tumor microenvironment with angiogenesis and high GSH generation for redox-responsive tumor-targeting evaluation in vivo. The high GSH generation was first verified in the xenograft zebrafish tumor model. Compared with ordinary Pluronic polymeric micelles, Dox CPPMs had a much higher accumulation in zebrafish tumor sites. Finally, the apoptosis-sensing B16F10-C3 xenograft zebrafish tumor model was established for visual, rapid, effective, and noninvasive assessment of anti-cancer effects at the cellular level in vivo. The Dox CPPMs significantly inhibited the proliferation of cancer cells and induced apoptosis in the B16F10-C3 xenograft zebrafish tumor model. Therefore, the redox-responsive cross-linked Pluronic micelles showed effective anti-cancer therapy in the xenograft zebrafish tumor model. This xenograft zebrafish tumor model is available for rapid screening and assessment of anti-cancer effects in preclinical studies.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Zebrafish Biomedical Research Applications · Immune cells in cancer · Phagocytosis and Immune Regulation

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

Affiliations

State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau 999078, China

Institute of Applied Physics and Materials Engineering, University of Macau, Macau 999078, China

Faculty of Health Sciences, University of Macau, Macau 999078, China

MOE Frontier Science Centre for Precision Oncology, University of Macau, Macau 999078, China

Beijing Key Laboratory of Molecular Pharmaceutics and New Drug Delivery System, School of Pharmaceutical Sciences, Peking University, Beijing 100191, China

Funding

Fundo para o Desenvolvimento das Ci?ncias e da Tecnologia

References (41)

Show source-provided references
1. 10.1016/j.progpolymsci.2007.09.00310.1016/j.progpolymsci.2007.09.003 ↗
2. 10.1016/j.ijpharm.2017.09.00510.1016/j.ijpharm.2017.09.005 ↗
3. 10.3390/molecules2304090710.3390/molecules23040907 ↗
4. 10.1007/s11095-006-9662-510.1007/s11095-006-9662-5 ↗
5. 10.1016/j.addr.2019.01.00210.1016/j.addr.2019.01.002 ↗
6. 10.1016/j.apsb.2022.02.00210.1016/j.apsb.2022.02.002 ↗
7. 10.3389/fphar.2020.0077010.3389/fphar.2020.00770 ↗
8. 10.1016/j.cclet.2020.05.03410.1016/j.cclet.2020.05.034 ↗
9. 10.1016/j.addr.2019.04.00910.1016/j.addr.2019.04.009 ↗
10. 10.1021/acsnano.7b0699510.1021/acsnano.7b06995 ↗
11. 10.1021/acsnano.9b0723310.1021/acsnano.9b07233 ↗
12. 10.1016/j.jconrel.2021.01.00610.1016/j.jconrel.2021.01.006 ↗
13. 10.1016/j.addr.2019.01.00110.1016/j.addr.2019.01.001 ↗
14. 10.1016/j.jconrel.2019.08.02210.1016/j.jconrel.2019.08.022 ↗
15. 10.1016/j.jconrel.2017.09.03710.1016/j.jconrel.2017.09.037 ↗
16. 10.1021/acsami.7b1280910.1021/acsami.7b12809 ↗
17. 10.1016/j.colsurfb.2017.05.02210.1016/j.colsurfb.2017.05.022 ↗
18. 10.1021/acsami.7b0117110.1021/acsami.7b01171 ↗
19. 10.1016/j.biomaterials.2020.12018010.1016/j.biomaterials.2020.120180 ↗
20. 10.1016/j.phrs.2017.08.01710.1016/j.phrs.2017.08.017 ↗
21. 10.1002/smll.20210358410.1002/smll.202103584 ↗
22. 10.1021/acsami.6b0168010.1021/acsami.6b01680 ↗
23. 10.1038/sj.cdd.440047610.1038/sj.cdd.4400476 ↗
24. 10.1002/bit.2557210.1002/bit.25572 ↗
25. 10.1016/j.apsb.2018.11.00110.1016/j.apsb.2018.11.001 ↗
26. 10.1006/bbrc.2001.489610.1006/bbrc.2001.4896 ↗
27. 10.1002/bit.2681610.1002/bit.26816 ↗
28. 10.1002/ppap.20200018810.1002/ppap.202000188 ↗
29. 10.1016/j.stemcr.2017.12.00710.1016/j.stemcr.2017.12.007 ↗
30. 10.1039/c4nr07641a10.1039/c4nr07641a ↗
31. 10.1016/s0145-305x(03)00103-410.1016/s0145-305x(03)00103-4 ↗
32. 10.1038/nature1211110.1038/nature12111 ↗
33. 10.1177/019262331140959710.1177/0192623311409597 ↗
34. 10.1006/dbio.2000.999510.1006/dbio.2000.9995 ↗
35. 10.1016/s1074-7613(04)00084-610.1016/s1074-7613(04)00084-6 ↗
36. 10.1242/dev.14575510.1242/dev.145755 ↗
37. 10.1038/nrg209110.1038/nrg2091 ↗
38. 10.1007/978-3-030-34025-4_2210.1007/978-3-030-34025-4_22 ↗
39. 10.3390/cells909197810.3390/cells9091978 ↗
40. 10.1016/j.ajps.2019.08.00310.1016/j.ajps.2019.08.003 ↗
41. 10.3389/fonc.2017.0018610.3389/fonc.2017.00186 ↗