journal article·2025-09

Boosting Checkpoint Blockade Immunotherapy with T Cell Membrane Redox Homeostasis Regulation and Deep Learning Enhanced NIR‐II Imaging

Ranran Guo, Ruixun Chen, Zhenhang Rao, Lugui Wang, Jianing Xi, Yu Zhang, Weisheng Guo, Ye Tian

Advanced Healthcare Materials· Volume 14· Issue 24
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Abstract

Abstract Immune checkpoint blockade therapy has revolutionized clinical oncotherapy by intercepting immunosuppressive pathways in tumor tissues. Nevertheless, the therapeutic efficacy is limited by a multidimensional immunosuppressive tumor microenvironment, which impedes the activity of tumor‐infiltrating immune cells and undermines treatment outcomes. In this study, a zwitterionic polymer is designed for the conjugation and traceless release of a checkpoint inhibition antibody (Atezolizumab), while concurrently enabling the restoration of membrane redox homeostasis on T cell membranes within the oxidative tumor microenvironment. Contrast‐enhanced fluorescence imaging in the near‐infrared II spectral region with a deep learning network is employed to visualize in vivo dynamics of the antibody conjugates. The antibody conjugates demonstrate enhanced and accelerated tumor accumulation, thereby promoting T cell proliferation and augmenting the antitumor efficacy. Mechanistic investigations reveal that the conjugate‐mediated regulation of the T cell surface redox state protects against damage induced by extracellular reactive oxygen species, subsequently mitigating ferroptosis of T cells. In murine models, the antibody conjugates effectively suppressed colorectal tumor growth and recurrence, leading to a significant extension of animal survival. This work thus realizes reversing suppressive immune microenvironment from multiple dimensions with a simple checkpoint inhibitor conjugate, promising for clinical translation and next‐generation immune checkpoint blockade therapy.
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Research context

OpenAlex topics: Nanoplatforms for cancer theranostics · Cancer Immunotherapy and Biomarkers · Immunotherapy and Immune Responses

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

Affiliations

School of Biomedical Engineering Southern Medical University Guangzhou 510515 China

Guangzhou Institute of Cancer Center Research The Affiliated Cancer Hospital School of Biomedical Engineering Guangzhou Medical University Guangzhou 510182 China

State Key Laboratory of Molecular Engineering of Polymers Fudan University Shanghai 200032 China

Funding

National Key Research and Development Program of China · National Natural Science Foundation of China · State Key Laboratory of Molecular Engineering of Polymers

References (52)

Show source-provided references
1. 10.1126/science.aar406010.1126/science.aar4060 ↗
2. 10.1016/j.cell.2021.09.02010.1016/j.cell.2021.09.020 ↗
3. 10.1158/2159-8290.CD-20-168010.1158/2159-8290.CD-20-1680 ↗
4. 10.3322/caac.2176310.3322/caac.21763 ↗
5. 10.1126/science.aaz086810.1126/science.aaz0868 ↗
6. 10.1002/adma.20220979910.1002/adma.202209799 ↗
7. 10.1038/s41551-024-01178-710.1038/s41551-024-01178-7 ↗
8. 10.1038/s41578-019-0108-110.1038/s41578-019-0108-1 ↗
9. 10.1038/s41577-021-00541-y10.1038/s41577-021-00541-y ↗
10. 10.1016/j.actbio.2024.01.03710.1016/j.actbio.2024.01.037 ↗
11. 10.1038/s44222-022-00004-610.1038/s44222-022-00004-6 ↗
12. 10.1002/adma.20240272010.1002/adma.202402720 ↗
13. 10.1002/adma.20230825410.1002/adma.202308254 ↗
14. 10.1126/scitranslmed.adn090410.1126/scitranslmed.adn0904 ↗
15. 10.1126/sciadv.adn300210.1126/sciadv.adn3002 ↗
16. 10.1038/s41591-018-0136-110.1038/s41591-018-0136-1 ↗
17. 10.1021/acsnano.1c0812010.1021/acsnano.1c08120 ↗
18. 10.1021/acsnano.2c1169110.1021/acsnano.2c11691 ↗
19. 10.1038/s41568-021-00435-010.1038/s41568-021-00435-0 ↗
20. 10.1038/s41573-024-00979-410.1038/s41573-024-00979-4 ↗
21. 10.1038/s41467-020-18745-610.1038/s41467-020-18745-6 ↗
22. 10.1038/s41423-022-00902-010.1038/s41423-022-00902-0 ↗
23. 10.1038/s41590-021-00996-010.1038/s41590-021-00996-0 ↗
24. 10.1016/j.cmet.2021.02.01510.1016/j.cmet.2021.02.015 ↗
25. 10.1038/s41565-022-01261-710.1038/s41565-022-01261-7 ↗
26. 10.1002/adhm.20230428410.1002/adhm.202304284 ↗
27. 10.3390/molecules2806260510.3390/molecules28062605 ↗
28. Wong R. W. · Investigative Ophthalmology & Visual Science · 2024 · 65 · 1773
29. 10.1002/anie.20110099610.1002/anie.201100996 ↗
30. 10.1016/j.cej.2022.13643810.1016/j.cej.2022.136438 ↗
31. 10.1002/adma.20180254610.1002/adma.201802546 ↗
32. 10.1073/pnas.180615311510.1073/pnas.1806153115 ↗
33. 10.1002/adma.20170014110.1002/adma.201700141 ↗
34. 10.1002/adma.20211056010.1002/adma.202110560 ↗
35. 10.1016/j.biomaterials.2022.12179510.1016/j.biomaterials.2022.121795 ↗
36. 10.1021/ja00818a00110.1021/ja00818a001 ↗
37. 10.1016/j.ccell.2016.02.00410.1016/j.ccell.2016.02.004 ↗
38. 10.1016/0003-2697(92)90170-C10.1016/0003-2697(92)90170-C ↗
39. 10.1073/pnas.060457110310.1073/pnas.0604571103 ↗
40. 10.1158/0008-5472.CAN-14-108410.1158/0008-5472.CAN-14-1084 ↗
41. 10.1038/s41592-019-0398-710.1038/s41592-019-0398-7 ↗
42. Xiao L. · J. Clin. Invest. · 2022 · 132 · 7
43. 10.1038/s41467-021-25990-w10.1038/s41467-021-25990-w ↗
44. 10.1038/s41566-024-01391-510.1038/s41566-024-01391-5 ↗
45. 10.1073/pnas.202144611810.1073/pnas.2021446118 ↗
46. 10.1109/ACCESS.2024.342152510.1109/ACCESS.2024.3421525 ↗
47. 10.1007/s10489-022-04389-010.1007/s10489-022-04389-0 ↗
48. 10.1117/1.JMI.6.1.01400610.1117/1.JMI.6.1.014006 ↗
49. 10.1038/s41551-019-0494-010.1038/s41551-019-0494-0 ↗
50. 10.1021/acs.nanolett.0c0171310.1021/acs.nanolett.0c01713 ↗
51. 10.1016/j.cej.2022.13698810.1016/j.cej.2022.136988 ↗
52. 10.1002/adma.20231164010.1002/adma.202311640 ↗