journal article·2022-12Open access

Macrophage Reprogramming with Anti‐miR223‐Loaded Artificial Protocells Enhances In Vivo Cancer Therapeutic Potential

Paco López‐Cuevas, Can Xu, Charlotte E. Severn, Tiah C. L. Oates, Stephen J. Cross, Ashley M. Toye, Stephen Mann, Paul Martin

Advanced Science· Volume 9· Issue 35

Abstract

Abstract Several immune cell‐expressed miRNAs (miRs) are associated with altered prognostic outcome in cancer patients, suggesting that they may be potential targets for development of cancer therapies. Here, translucent zebrafish (Danio rerio) is utilized to demonstrate that genetic knockout or knockdown of one such miR, microRNA‐223 (miR223), globally or specifically in leukocytes, does indeed lead to reduced cancer progression. As a first step toward potential translation to a clinical therapy, a novel strategy is described for reprogramming neutrophils and macrophages utilizing miniature artificial protocells (PCs) to deliver anti‐miRs against the anti‐inflammatory miR223. Using genetic and live imaging approaches, it is shown that phagocytic uptake of anti‐miR223‐loaded PCs by leukocytes in zebrafish (and by human macrophages in vitro) effectively prolongs their pro‐inflammatory state by blocking the suppression of pro‐inflammatory cytokines, which, in turn, drives altered immune cell‐cancer cell interactions and ultimately leads to a reduced cancer burden by driving reduced proliferation and increased cell death of tumor cells. This PC cargo delivery strategy for reprogramming leukocytes toward beneficial phenotypes has implications also for treating other systemic or local immune‐mediated pathologies.
Source: crossref · Quality: baseline

Research context

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

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

Affiliations

School of Biochemistry Biomedical Sciences Building University Walk University of Bristol Bristol BS8 1TD UK

Centre for Protolife Research School of Chemistry University of Bristol Bristol BS8 1TS UK

National Institute for Health Research Blood and Transplant Research Unit (NIHR BTRU) in Red Blood Cell Products University of Bristol Bristol BS34 7QH UK

Wolfson Bioimaging Facility Biomedical Sciences Building University Walk University of Bristol Bristol BS8 1TD UK

Max Planck Bristol Centre for Minimal Biology School of Chemistry University of Bristol Bristol BS8 1TS UK

School of Materials Science and Engineering Shanghai Jiao Tong University Shanghai 200240 P. R. China

References (75)

Show source-provided references
1. 10.1371/journal.pbio.100056210.1371/journal.pbio.1000562 ↗
2. 10.1371/journal.pone.011218310.1371/journal.pone.0112183 ↗
3. 10.1016/S0065-2776(06)90001-710.1016/S0065-2776(06)90001-7 ↗
4. 10.1007/s12307-014-0147-510.1007/s12307-014-0147-5 ↗
5. 10.1189/jlb.060938510.1189/jlb.0609385 ↗
6. 10.3390/cells904101810.3390/cells9041018 ↗
7. 10.1016/j.cub.2012.05.01010.1016/j.cub.2012.05.010 ↗
8. 10.1038/nrc397910.1038/nrc3979 ↗
9. 10.1155/2016/845172810.1155/2016/8451728 ↗
10. 10.1177/00359157100030160110.1177/003591571000301601 ↗
11. 10.3389/fcell.2021.67619310.3389/fcell.2021.676193 ↗
12. 10.1038/nature1067310.1038/nature10673 ↗
13. 10.1016/j.molimm.2013.11.01810.1016/j.molimm.2013.11.018 ↗
14. 10.1515/med-2020-014610.1515/med-2020-0146 ↗
15. 10.1186/s13148-016-0243-010.1186/s13148-016-0243-0 ↗
16. 10.1007/s00441-012-1514-510.1007/s00441-012-1514-5 ↗
17. 10.1158/1541-7786.MCR-10-052910.1158/1541-7786.MCR-10-0529 ↗
18. 10.15252/emmm.20180902410.15252/emmm.201809024 ↗
19. 10.1016/j.celrep.2018.01.05810.1016/j.celrep.2018.01.058 ↗
20. 10.1016/j.gene.2015.04.02210.1016/j.gene.2015.04.022 ↗
21. 10.1021/ja504213m10.1021/ja504213m ↗
22. 10.1016/j.cbpa.2014.05.01810.1016/j.cbpa.2014.05.018 ↗
23. 10.1038/ncomms323910.1038/ncomms3239 ↗
24. 10.1038/s41557-020-00585-y10.1038/s41557-020-00585-y ↗
25. 10.1038/s41565-019-0399-910.1038/s41565-019-0399-9 ↗
26. 10.1016/j.canlet.2019.02.05110.1016/j.canlet.2019.02.051 ↗
27. 10.1038/onc.2014.29410.1038/onc.2014.294 ↗
28. 10.1371/journal.pone.001517010.1371/journal.pone.0015170 ↗
29. 10.15252/embj.20149014710.15252/embj.201490147 ↗
30. 10.1111/joim.1209910.1111/joim.12099 ↗
31. 10.1002/JLB.3MR0218-079R10.1002/JLB.3MR0218-079R ↗
32. 10.1021/acscentsci.8b0055510.1021/acscentsci.8b00555 ↗
33. 10.1038/nmat491610.1038/nmat4916 ↗
34. 10.1038/nchem.261710.1038/nchem.2617 ↗
35. 10.1038/s42004-021-00597-w10.1038/s42004-021-00597-w ↗
36. 10.1021/acssynbio.7b0030610.1021/acssynbio.7b00306 ↗
37. 10.1039/c1sc00183c10.1039/c1sc00183c ↗
38. 10.1038/s41467-020-19308-510.1038/s41467-020-19308-5 ↗
39. 10.1182/blood-2010-10-31412010.1182/blood-2010-10-314120 ↗
40. 10.1186/1471-213X-7-4210.1186/1471-213X-7-42 ↗
41. 10.1038/srep3685310.1038/srep36853 ↗
42. 10.1089/zeb.2018.168110.1089/zeb.2018.1681 ↗
43. 10.4049/jimmunol.180113910.4049/jimmunol.1801139 ↗
44. 10.15252/embj.20179778610.15252/embj.201797786 ↗
45. 10.3389/fimmu.2017.0109710.3389/fimmu.2017.01097 ↗
46. 10.1371/journal.pone.004297110.1371/journal.pone.0042971 ↗
47. 10.1111/pcmr.1216110.1111/pcmr.12161 ↗
48. 10.1016/j.jconrel.2017.08.02310.1016/j.jconrel.2017.08.023 ↗
49. 10.1016/j.xcrp.2020.10029110.1016/j.xcrp.2020.100291 ↗
50. 10.1021/acsnano.0c0212710.1021/acsnano.0c02127 ↗
51. 10.1021/acsnano.0c0753710.1021/acsnano.0c07537 ↗
52. 10.1172/JCI12712510.1172/JCI127125 ↗
53. 10.1172/JCI7905210.1172/JCI79052 ↗
54. 10.1038/s41467-017-00972-z10.1038/s41467-017-00972-z ↗
55. 10.1038/nrd.2018.16910.1038/nrd.2018.169 ↗
56. 10.1038/s41551-018-0236-810.1038/s41551-018-0236-8 ↗
57. 10.1038/nm158910.1038/nm1589 ↗
58. 10.1371/journal.pone.006030010.1371/journal.pone.0060300 ↗
59. 10.3324/haematol.2009.01982810.3324/haematol.2009.019828 ↗
60. 10.3324/haematol.2017.17934110.3324/haematol.2017.179341 ↗
61. Westerfield M. · 2007
62. 10.1016/j.stem.2007.11.00210.1016/j.stem.2007.11.002 ↗
63. 10.1002/dvdy.2134310.1002/dvdy.21343 ↗
64. 10.1007/978-1-4939-7665-2_1810.1007/978-1-4939-7665-2_18 ↗
65. 10.1038/nprot.2013.06810.1038/nprot.2013.068 ↗
66. Benard E. L. · J. Visualized Exp. · 2012 · 15 · e3781
67. 10.1186/1471-2105-15-2910.1186/1471-2105-15-29 ↗
68. 10.4049/jimmunol.150172910.4049/jimmunol.1501729 ↗
69. 10.1038/nmeth.201910.1038/nmeth.2019 ↗
70. Modular Image Analysis (MIA) plugin for Fiji developed by S. Cross and used in this study (mianalysis/mia: Version 0.21.12) https://zenodo.org/record/6079178(accessed: September 2022).
71. 10.1016/j.ymeth.2016.09.01610.1016/j.ymeth.2016.09.016 ↗
72. 10.1109/TSMC.1979.431007610.1109/TSMC.1979.4310076 ↗
73. 10.1093/bioinformatics/btw41310.1093/bioinformatics/btw413 ↗
74. 10.1006/cgip.1993.104010.1006/cgip.1993.1040 ↗
75. 10.1309/82U1089XLQGKMMN110.1309/82U1089XLQGKMMN1 ↗