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.

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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

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article

Extracellular Vesicle Protein Panel Enables Early Lung Cancer Detection in a Large Clinical Cohort

Xiaoju Zhang, Yuanlin Song, Zuoren Wu, Chunxue Bai et al.
3 citations
Journal of Extracellular Vesicles
Extracellular vesicles in disease
2.42
article

Extracellular Vesicle Protein Panel Enables Early Lung Cancer Detection in a Large Clinical Cohort

Xiaoju Zhang, Yuanlin Song, Zuoren Wu, Chunxue Bai, Yencheng Chao, Yuanyuan Ji, Xiaocen Wang, Wensi Zhu, Linxiao Han, Lei Gao, Jiayuan Sun, Ge Zhang, Ying Li, Ziqi Wang, Jie Liu, Jian Zhou, Qin Wang, Lin Tong, Ludan He, Qiaoliang Zhu, Shujing Chen, Xiuzhen Lv
article en
3 citations

Abstract

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.

Journal of Extracellular VesiclesVol. 14(8)
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)
National Natural Science Foundation of China, Science and Technology Commission of Shanghai Municipality, National Key Research and Development Program of China
Good health and well-being
Openalex Percentile: Top 11%
Extracellular vesicles in disease
2.42
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