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

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 mem...

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Main Authors: Linxiao Han, Yuanlin Song, Lin Tong, Jiayuan Sun, Xiaoju Zhang, Shujing Chen, Ying Li, Ziqi Wang, Lei Gao, Qiaoliang Zhu, Yencheng Chao, Xiaocen Wang, Ge Zhang, Wensi Zhu, Ludan He, Jie Liu, Qin Wang, Zuoren Wu, Yuanyuan Ji, Chunxue Bai, Xiuzhen Lv, Jian Zhou
Format: Article
Language:English
Published: Wiley 2025-08-01
Series:Journal of Extracellular Vesicles
Online Access:https://doi.org/10.1002/jev2.70129
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Summary: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, EVELC‐M5) 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. EVELC‐M5 could accurately differentiate patients with early lung cancer from the control group. The area under the curve (AUC) of EVELC‐M5 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 EVELC‐M5 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
ISSN:2001-3078