Extracellular Vesicle Protein Panel Enables Early Lung Cancer Detection in a Large Clinical Cohort
The early detection and diagnosis of lung cancer through extracellular vesicle (EV)-based liquid biopsy show substantial promise for enhancing clinical outcomes. Nonetheless, there is a scarcity of large-scale clinical investigations validating EV-based liquid biopsy. To evaluate the EV membrane protein panel as a diagnostic tool for early-stage cancer detection and validate its efficacy and clinical applicability, a cohort comprised of 302 individuals without cancer and 645 with lung cancer was recruited. Participants were randomly divided into training and validation cohorts at a 1:1 ratio while maintaining the proportion of different subtypes. A diagnostic panel (EV early lung cancer membrane protein 5, EV<sup>ELC-M5</sup>) consisting of five EV membrane proteins (CD81, PDL1, GLIPR1, LBR and SFTPA1) was developed using a High-throughput Nano-biochip Integrated System for Liquid Biopsy (HNCIB) to realize rapid analysis of a large cohort of patient samples at a single EV level. EV<sup>ELC-M5</sup> could accurately differentiate patients with early lung cancer from the control group. The area under the curve (AUC) of EV<sup>ELC-M5</sup> for distinguishing patients with early lung cancer from the control group in the validation cohort was 0.926, and the AUC for diagnosing patients with early lung cancer with lung nodules ≤ 8 mm was 0.931. EV-SFTPA1 proved to be the most effective marker, exhibiting a sensitivity of 89.4% in patients with early lung cancer. To our knowledge, this is the first study to use EV-SFTPA1 for early lung cancer detection, elucidating its robust tissue specificity. Collectively, the findings highlight that EV<sup>ELC-M5</sup> in conjunction with HNCIB is an effective diagnostic toolset for detecting early lung cancer and substantially promotes its diagnosis. Trial Registration: ClinicalTrials.gov identifier: ChiCTR2300072317.
Authors
- Xiaoju Zhang (ORCID: https://orcid.org/0000-0001-7040-5490)
- Yuanlin Song (ORCID: https://orcid.org/0000-0003-3373-6631)
- Zuoren Wu (ORCID: https://orcid.org/0000-0002-1825-491X)
- Chunxue Bai (ORCID: https://orcid.org/0000-0001-5798-3130)
- Yencheng Chao (ORCID: https://orcid.org/0000-0002-0636-6252)
- Yuanyuan Ji (ORCID: https://orcid.org/0000-0001-5805-0404)
- Xiaocen Wang (ORCID: https://orcid.org/0000-0002-6196-7739)
- Wensi Zhu (ORCID: https://orcid.org/0009-0001-9504-6794)
- Linxiao Han
- Lei Gao (ORCID: https://orcid.org/0000-0002-7005-8924)
- Jiayuan Sun (ORCID: https://orcid.org/0000-0003-3158-3256)
- Ge Zhang (ORCID: https://orcid.org/0000-0002-3116-3246)
- Ying Li (ORCID: https://orcid.org/0000-0001-5062-0230)
- Ziqi Wang (ORCID: https://orcid.org/0000-0003-3067-5167)
- Jie Liu (ORCID: https://orcid.org/0000-0001-6988-5773)
- Jian Zhou (ORCID: https://orcid.org/0000-0003-4736-9457)
- Qin Wang (ORCID: https://orcid.org/0000-0001-7081-6580)
- Lin Tong (ORCID: https://orcid.org/0000-0002-8855-9487)
- Ludan He
- Qiaoliang Zhu
- Shujing Chen
- Xiuzhen Lv
Institutions
- Sun Yat-sen University (CN)
- Fudan University (CN)
- Shanghai Chest Hospital (CN)
- Jinshan Hospital of Fudan University (CN)
- Zhongshan Hospital (CN)
- The First Affiliated Hospital, Sun Yat-sen University (CN)
- Henan Provincial People's Hospital (CN)
Publication Details
- Journal
- Journal of Extracellular Vesicles
- Published
- 2025-08-01
- DOI
- https://doi.org/10.1002/jev2.70129
- Citations
- 3
- Primary Topic
- Extracellular vesicles in disease
- Type
- article
- Field-Weighted Citation Impact
- 2.42
Funders
- National Natural Science Foundation of China
- Science and Technology Commission of Shanghai Municipality
- National Key Research and Development Program of China