journal article·2025-12

Ultrasensitive Detection of PD‐L1‐Expressing Extracellular Vesicles via Reflection‐Mediated Ellipsometry: From Nanoscale Optical Modeling to Immunotherapy Response Prediction

Jung Hyun Choi, Hyun Mo Cho, Jun Hyeok Lim, Wook Choi, Dongjun Shin, Chae Yeon Son, Hyun Sung Park, Sunwoo Hong, Lucia Kim, Il Doh, Jiyoon Bu, Dong Hyung Kim

Small· Volume 21· Issue 50
Publisher page

Abstract

Abstract Programmed death‐ligand 1 (PD‐L1) expression in extracellular vesicles (EVs) has emerged as a promising biomarker for predicting responses to immune checkpoint inhibitors (ICIs), but current detection methods lack the sensitivity needed for clinical translation. Here, a reflection‐mode solution‐immersed silicon (R p ‐SIS) ellipsometry sensor is adapted, originally developed for thin‐film measurements, for the ultra‐sensitive detection of PD‐L1–expressing EVs. Computational and experimental validation demonstrated that the selective use of p‐polarized light, combined with a fixed polarizer configuration, enables highly sensitive detection of nanoscale surface changes. Applied to cell‐line–derived EVs, the sensor achieved a limit of detection of 3.8 × 10 1 particles mL −1 —exceptionally high sensitivity for label‐free EV detection—with also high reproducibility and specificity. In clinical samples from patients receiving ICI therapy, PD‐L1⁺ EV levels measured by the R p ‐SIS sensor distinguished responders from non‐responders and correlated with progression‐free survival, outperforming conventional ELISA and tissue‐based PD‐L1 staining. Additionally, it is demonstrated that direct detection of intact EVs yields stronger signals than lysate‐based detection due to amplified optical responses from vesicle‐scale binding. The platform's versatility is further demonstrated by detecting alternative tumor‐derived EV biomarkers and employing diverse capture ligands. These findings establish the R p ‐SIS sensor as a clinically actionable platform for high‐sensitivity, EV‐based liquid biopsy.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Extracellular vesicles in disease · Nanoplatforms for cancer theranostics · interferon and immune responses

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

Affiliations

Department of Biological Sciences and Bioengineering Inha University Incheon 22212 Republic of Korea

Division of Biomedical Metrology Korea Research Institute of Standards and Science 267 Gajeongno Yuseong‐Gu Daejeon 34113 Republic of Korea

SIS sensor corporation 267 Gajeongno Yuseong‐Gu Daejeon 34113 Republic of Korea

Division of Pulmonology, Department of Internal Medicine, Inha University Hospital Inha University College of Medicine Incheon 22332 Republic of Korea

Institute of Advanced Machinery Design Technology Korea University 145 Anam‐Ro Seongbuk‐Gu Seoul 02841 Republic of Korea

Department of Pathology, Inha University Hospital Inha University College of Medicine Incheon 22332 Republic of Korea

Department of Applied Measurement Science University of Science and Technology (UST) 217 Gajeong‐ro Yuseong‐gu Daejeon 34113 Republic of Korea

Biohybrid Systems Research Center Inha University 100 Inha‐ro Michuhol‐gu Incheon 22212 Republic of Korea

Funding

National Research Foundation of Korea · Ministry of Science and ICT, South Korea · National Research Council of Science and Technology · Korea Research Institute of Standards and Science · Korea Health Industry Development Institute

References (54)

Show source-provided references
1. 10.1038/nrc.2017.710.1038/nrc.2017.7 ↗
2. 10.1002/adma.20180534410.1002/adma.201805344 ↗
3. 10.1016/j.trac.2022.11691210.1016/j.trac.2022.116912 ↗
4. 10.1002/advs.20210278910.1002/advs.202102789 ↗
5. 10.1002/smtd.20240205810.1002/smtd.202402058 ↗
6. 10.1038/s41586-018-0392-810.1038/s41586-018-0392-8 ↗
7. 10.3389/fonc.2020.0076010.3389/fonc.2020.00760 ↗
8. 10.1016/j.cej.2025.16744710.1016/j.cej.2025.167447 ↗
9. 10.1021/acs.nanolett.0c0095310.1021/acs.nanolett.0c00953 ↗
10. 10.1016/j.bios.2022.11444510.1016/j.bios.2022.114445 ↗
11. 10.3389/fmolb.2024.137982210.3389/fmolb.2024.1379822 ↗
12. 10.1016/j.ccr.2025.21676710.1016/j.ccr.2025.216767 ↗
13. 10.1002/advs.20250927010.1002/advs.202509270 ↗
14. 10.1007/s11418-017-1144-z10.1007/s11418-017-1144-z ↗
15. 10.1038/s41598-020-75011-x10.1038/s41598-020-75011-x ↗
16. 10.1016/j.bios.2020.11222210.1016/j.bios.2020.112222 ↗
17. 10.1021/acssensors.1c0110110.1021/acssensors.1c01101 ↗
18. 10.1016/j.bios.2019.11180010.1016/j.bios.2019.111800 ↗
19. 10.1016/j.bios.2014.06.03910.1016/j.bios.2014.06.039 ↗
20. 10.1016/j.bios.2019.11146910.1016/j.bios.2019.111469 ↗
21. 10.1039/D0SC00809E10.1039/D0SC00809E ↗
22. 10.1039/D4NA00387J10.1039/D4NA00387J ↗
23. 10.1093/clinchem/44.9.203110.1093/clinchem/44.9.2031 ↗
24. 10.1016/S0040-6090(97)00858-410.1016/S0040-6090(97)00858-4 ↗
25. 10.1039/C4AN01584C10.1039/C4AN01584C ↗
26. 10.1016/j.bios.2020.11252510.1016/j.bios.2020.112525 ↗
27. 10.3390/s2317740010.3390/s23177400 ↗
28. 10.1016/j.snb.2023.13458810.1016/j.snb.2023.134588 ↗
29. 10.1039/D1NA00114K10.1039/D1NA00114K ↗
30. 10.1021/acs.jpcc.4c0093710.1021/acs.jpcc.4c00937 ↗
31. 10.1364/AO.46.00496310.1364/AO.46.004963 ↗
32. 10.1364/OE.25.02707710.1364/OE.25.027077 ↗
33. Ambruster D. · Clin. Biochem. Rev. · 2008 · 29 · S49
34. 10.4103/2229-5186.7934510.4103/2229-5186.79345 ↗
35. 10.3390/biom1006082410.3390/biom10060824 ↗
36. 10.5772/6414810.5772/64148 ↗
37. 10.1016/j.bbrc.2018.05.10710.1016/j.bbrc.2018.05.107 ↗
38. 10.1016/j.mcpro.2022.10047610.1016/j.mcpro.2022.100476 ↗
39. 10.1016/j.bios.2023.11584110.1016/j.bios.2023.115841 ↗
40. 10.1016/j.bios.2023.11549310.1016/j.bios.2023.115493 ↗
41. 10.1186/s12951-021-01210-x10.1186/s12951-021-01210-x ↗
42. 10.1007/s00216-019-01608-510.1007/s00216-019-01608-5 ↗
43. 10.1016/j.talanta.2024.12618210.1016/j.talanta.2024.126182 ↗
44. 10.1016/j.aca.2020.12.01810.1016/j.aca.2020.12.018 ↗
45. 10.1016/j.jelechem.2022.11659010.1016/j.jelechem.2022.116590 ↗
46. 10.1038/s41378-022-00387-x10.1038/s41378-022-00387-x ↗
47. 10.1038/s41598-018-27203-910.1038/s41598-018-27203-9 ↗
48. 10.1021/acs.biomac.2c0101810.1021/acs.biomac.2c01018 ↗
49. 10.1021/acs.analchem.0c0138710.1021/acs.analchem.0c01387 ↗
50. 10.1016/j.bios.2022.11463610.1016/j.bios.2022.114636 ↗
51. 10.1021/acsnano.4c1635310.1021/acsnano.4c16353 ↗
52. 10.1038/mtna.2016.10210.1038/mtna.2016.102 ↗
53. 10.1038/s41598-020-57497-710.1038/s41598-020-57497-7 ↗
54. 10.4070/kcj.1996.26.2.51410.4070/kcj.1996.26.2.514 ↗