Aptamer‐Engineered Ellipsometry for Clinical Detection of BALF‐Derived Exosomes: Multi‐Level Engineering for Prognostic Evaluation of Immunotherapy Responses
Exosomes emerges as indicators of the tumor microenvironment, yet their predictive utility for immunotherapy responses is limited by the insufficient sensitivity and specificity of currently available assays. Here, a multi-level engineering strategy is presented that enables accurate exosome-based prediction of immunotherapy responses by integrating systematic aptamer ligand tailoring, ultrasensitive ellipsometry-based sensing, and clinically relevant tumor-proximal fluid sampling. Aptamers specifically targeting PD-L1 are identified through systematic evolution of ligands by exponential enrichment (SELEX), followed by truncation and computational sequence refinement to enhance binding specificity. The optimized aptamer sequence (Tr-Apt13) is validated from molecular interaction analyses to in vitro assays, demonstrating superior target binding efficacy over conventional antibodies, attributed to dense surface immobilization and multivalent binding capability. When incorporated into an ellipsometry-based dual-prism solution-immersed silicon sensor, Tr-Apt13 enabled ultrasensitive detection of PD-L1-expressing exosomes with a detection limit of ≈9.8 particles mL<sup>-1</sup>, exhibiting high linearity and stability. Clinical validation using bronchoalveolar lavage fluid (BALF) from lung cancer patients revealed precise discrimination between responders and non-responders at exosome concentrations as low as 10<sup>3</sup> particles mL<sup>-1</sup>, outperforming serum-based analysis, conventional ELISA, and tissue immunohistochemistry. Collectively, this multi-level strategy offers a new perspective on exosome-based diagnostics, enabling precise prediction of immunotherapy efficacy in lung cancer patients.
Authors
- Euna Jeong (ORCID: https://orcid.org/0000-0002-8802-4140)
- Jiyoon Bu (ORCID: https://orcid.org/0000-0002-0153-5109)
- Jung Hyun Choi
- Won Chegal (ORCID: https://orcid.org/0000-0001-8774-8318)
- Lucia Kim (ORCID: https://orcid.org/0000-0002-4100-6607)
- Chulhwan Park (ORCID: https://orcid.org/0000-0003-1148-7881)
- Sung Pil Jung (ORCID: https://orcid.org/0000-0002-6192-6718)
- Yeeun Woo
- Woo‐Jin Jeong (ORCID: https://orcid.org/0000-0001-8577-6964)
- Jun Hyeok Lim (ORCID: https://orcid.org/0000-0001-5515-737X)
- Minyoung Lee (ORCID: https://orcid.org/0000-0003-3862-8760)
- Taek Lee (ORCID: https://orcid.org/0000-0003-4158-130X)
- J.H. Ok
- Dong Hyung Kim (ORCID: https://orcid.org/0000-0001-8939-0532)
- Jooyoung Kim (ORCID: https://orcid.org/0009-0009-5189-3148)
- Hyun Mo Cho
Institutions
- Kwangwoon University (KR)
- Inha University (KR)
- Korea Research Institute of Standards and Science (KR)
- Sensor Electronics (United States) (US)
- Inha University Hospital (KR)
- Korea University of Science and Technology (KR)
Publication Details
- Journal
- Advanced Science
- Published
- 2025-10-31
- DOI
- https://doi.org/10.1002/advs.202515247
- Citations
- 1
- Primary Topic
- Extracellular vesicles in disease
- Type
- article
- Field-Weighted Citation Impact
- 0.81
Funders
- National Research Foundation
- Ministry of Trade, Industry and Energy
- Korea Research Institute of Standards and Science
- Korea Health Industry Development Institute
- National Research Foundation of Korea
- National Research Council of Science and Technology
- Ministry of Science and ICT, South Korea