journal article·2023-11-08

Enhanced NIR-II Fluorescent Lateral Flow Biosensing Platform Based on Supramolecular Host–Guest Self-Assembly for Point-of-Care Testing of Tumor Biomarkers

Zhaorui Song, Hong Guo, Yongkuan Suo, Yongde Zhang, Shanshan Zhang, Peng Qiu, Lifu Liu, Botong Chen, Zhen Cheng

ACS Applied Materials & Interfaces· Volume 15· Issue 44
Publisher page

Abstract

Point-of-care detection of tumor biomarkers with high sensitivity remains an enormous challenge in the early diagnosis and mass screening of cancer. Fluorescent lateral flow immunoassay (LFA) is an attractive platform for point-of-care testing due to its inherent advantages. Particularly, a fluorescent probe is crucial to improving the analytical performance of the LFA platform. Herein, we developed an enhanced second near-infrared (NIR-II) LFA (ENIR-II LFA) platform based on supramolecular host–guest self-assembly for detection of the prostate-specific antigen (PSA) as a model analyte. In this platform, depending on the effective supramolecular surface modification strategy, cucurbit[7]uril (CB[7])-covered rare-earth nanoparticles (RENPs) emitting in the NIR-II (1000–1700 nm) window were prepared and employed as an efficient fluorescent probe (RENPs-CB[7]). Benefiting from its superior optical properties, such as low autofluorescence, excellent photostability, enhanced fluorescence intensity, and increased antibody-conjugation efficiency, the ENIR-II LFA platform displayed a wide linear detection range from 0.65 to 120 ng mL –1, and the limit of detection was down to 0.22 ng mL –1 for PSA, which was 18.2 times lower than the clinical cutoff value. Moreover, the testing time was also shortened to 6 min. Compared with the commercial visible fluorescence LFA kit (VIS LFA) and the previously reported NIR-II LFA based on a RENPs-PAA probe, this ENIR-II LFA demonstrated more competitive advantages in analytical sensitivity, detection range, testing time, and production cost. Overall, the ENIR-II LFA platform offers great potential for the highly sensitive, rapid, and convenient detection of tumor biomarkers and is expected to serve as a useful technique in the general population screening of the high-incidence cancer region.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Nanoplatforms for cancer theranostics · Advanced biosensing and bioanalysis techniques · Biosensors and Analytical Detection

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

Affiliations

Shandong Laboratory of Yantai Drug Discovery, Bohai Rim Advanced Research Institute for Drug Discovery, Yantai 264117, Shandong, China

Clinical Laboratory, Qingdao Women and Children’s Hospital Affiliated, Qingdao University, Qingdao 266034, China

State Key Laboratory of Drug Research, Molecular Imaging Center, Shanghai Institute of Materia Medica Chinese Academy of Sciences, Shanghai 201203, China

Funding

National Natural Science Foundation of China · Natural Science Foundation of Shandong Province · Bohai Rim Advanced Research Institute for Drug Discovery

References (51)

Show source-provided references
1. 10.1038/s41575-022-00620-y10.1038/s41575-022-00620-y ↗
2. 10.1039/C6CS00908E10.1039/C6CS00908E ↗
3. 10.1002/anie.20190685610.1002/anie.201906856 ↗
4. 10.1186/s12967-020-02281-410.1186/s12967-020-02281-4 ↗
5. 10.1016/j.bios.2019.11197810.1016/j.bios.2019.111978 ↗
6. 10.1016/j.snb.2020.12881210.1016/j.snb.2020.128812 ↗
7. 10.1038/nbt.164110.1038/nbt.1641 ↗
8. 10.1021/acs.analchem.1c0334410.1021/acs.analchem.1c03344 ↗
9. 10.1016/j.bios.2023.11519310.1016/j.bios.2023.115193 ↗
10. 10.1002/anie.20210345810.1002/anie.202103458 ↗
11. 10.1021/acsnano.1c0193210.1021/acsnano.1c01932 ↗
12. 10.1021/acs.analchem.2c0294510.1021/acs.analchem.2c02945 ↗
13. 10.1126/scitranslmed.abj412410.1126/scitranslmed.abj4124 ↗
14. 10.3390/molecules2719659610.3390/molecules27196596 ↗
15. 10.1016/j.jhazmat.2021.12720410.1016/j.jhazmat.2021.127204 ↗
16. 10.1038/s41551-020-00655-z10.1038/s41551-020-00655-z ↗
17. 10.1007/s12274-022-4351-110.1007/s12274-022-4351-1 ↗
18. 10.1016/j.cej.2022.13520410.1016/j.cej.2022.135204 ↗
19. 10.1016/j.bios.2023.11506310.1016/j.bios.2023.115063 ↗
20. 10.1016/j.addr.2023.11482110.1016/j.addr.2023.114821 ↗
21. 10.1021/acsnano.2c1206810.1021/acsnano.2c12068 ↗
22. 10.1002/ird3.1010.1002/ird3.10 ↗
23. 10.1016/j.foodchem.2020.12771810.1016/j.foodchem.2020.127718 ↗
24. 10.1016/j.ab.2022.11484710.1016/j.ab.2022.114847 ↗
25. 10.1016/j.snb.2020.12905010.1016/j.snb.2020.129050 ↗
26. 10.1038/nmat447610.1038/nmat4476 ↗
27. 10.1002/adma.20190032110.1002/adma.201900321 ↗
28. 10.1002/anie.20200704010.1002/anie.202007040 ↗
29. 10.1021/acsnano.7b0246610.1021/acsnano.7b02466 ↗
30. 10.1016/j.snb.2020.12823310.1016/j.snb.2020.128233 ↗
31. 10.1021/acs.chemrev.1c0055310.1021/acs.chemrev.1c00553 ↗
32. 10.1002/anie.20221037010.1002/anie.202210370 ↗
33. 10.1021/acsnano.0c0600010.1021/acsnano.0c06000 ↗
34. 10.1016/j.snb.2021.13038010.1016/j.snb.2021.130380 ↗
35. 10.1016/j.bios.2023.11535310.1016/j.bios.2023.115353 ↗
36. 10.1039/C8CC00708J10.1039/C8CC00708J ↗
37. 10.1021/acs.jpcc.6b0930110.1021/acs.jpcc.6b09301 ↗
38. 10.1016/j.nantod.2020.10090510.1016/j.nantod.2020.100905 ↗
39. 10.1039/C4CS00186A10.1039/C4CS00186A ↗
40. 10.1039/C7CS00185A10.1039/C7CS00185A ↗
41. 10.1016/j.trac.2020.11608610.1016/j.trac.2020.116086 ↗
42. 10.1039/C5CS00631G10.1039/C5CS00631G ↗
43. 10.1016/j.jhazmat.2022.12960310.1016/j.jhazmat.2022.129603 ↗
44. 10.1016/j.snb.2020.12881210.1016/j.snb.2020.128812 ↗
45. 10.3390/s2112409910.3390/s21124099 ↗
46. 10.1186/s12951-021-00817-410.1186/s12951-021-00817-4 ↗
47. 10.2116/analsci.27.23710.2116/analsci.27.237 ↗
48. 10.1016/j.cca.2009.04.01310.1016/j.cca.2009.04.013 ↗
49. 10.1039/C9CC08501G10.1039/C9CC08501G ↗
50. 10.1002/advs.20190204210.1002/advs.201902042 ↗
51. 10.1002/anie.20190760510.1002/anie.201907605 ↗