Chemical Affinity Capture of Plasma Extracellular Vesicles Enables Efficient and Large-Scale Proteomic Identification of Prostate Cancer Biomarkers

The serum prostate-specific antigen (PSA) testing is widely used for prostate cancer (PCa) screening but suffers from poor specificity, leading to unnecessary biopsies and overtreatment. The significant potential of extracellular vesicles (EVs) in cancer diagnosis has driven the development of efficient methods to isolate and identify EV biomarkers from large-scale clinical samples. Here, we systematically evaluate five commonly used EV isolation techniques through proteomic profiling of plasma-derived EVs, endorsing TiO<sub>2</sub>-based chemical affinity capture as a superior approach for analyzing EVs from complex clinical samples. This method demonstrates exceptional advantages in speed, throughput, reproducibility, and protein coverage. Using this optimized workflow, we analyzed plasma EVs from 80 patients with PCa and benign prostatic hyperplasia (BPH), identifying growth differentiation factor 15 (GDF15) as a compelling biomarker with a predictive power (AUC) of 0.908 for PCa. Extensive validation across independent cohorts comprising 457 samples, including plasma EVs and prostate tissues, confirmed GDF15's ability to distinguish PCa from BPH and stratify PCa stages. Notably, the combination of GDF15 with PSA further enhanced diagnostic efficiency, particularly for patients in the PSA diagnostic gray zone. This study establishes a robust workflow for EV protein analysis in large clinical cohorts and highlights EV-GDF15 as a promising biomarker for noninvasive PCa diagnosis.

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Publication Details

Journal
ACS Nano
Published
2025-04-18
DOI
https://doi.org/10.1021/acsnano.5c01564
Citations
12
Primary Topic
Extracellular vesicles in disease
Type
article
Field-Weighted Citation Impact
9.67

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article

Chemical Affinity Capture of Plasma Extracellular Vesicles Enables Efficient and Large-Scale Proteomic Identification of Prostate Cancer Biomarkers

Tao Su, Shisheng Wang, Mengqi Luo, Dingkun Zhang et al.
12 citations
ACS Nano
Extracellular vesicles in disease
9.67
article

Chemical Affinity Capture of Plasma Extracellular Vesicles Enables Efficient and Large-Scale Proteomic Identification of Prostate Cancer Biomarkers

Tao Su, Shisheng Wang, Mengqi Luo, Dingkun Zhang, Xinyuan Wang, Meng Gong, Lu Yang, Youmei Jin, Tianhai Lin, Hao Yang, Li Li, Yong Zhang, Jingqiu Cheng, Jingping Liu, Shan Liu, Yujia Yuan, Wenjuan Zeng, Yi Zhong, Weiya Wang
article en
12 citations

Abstract

The serum prostate-specific antigen (PSA) testing is widely used for prostate cancer (PCa) screening but suffers from poor specificity, leading to unnecessary biopsies and overtreatment. The significant potential of extracellular vesicles (EVs) in cancer diagnosis has driven the development of efficient methods to isolate and identify EV biomarkers from large-scale clinical samples. Here, we systematically evaluate five commonly used EV isolation techniques through proteomic profiling of plasma-derived EVs, endorsing TiO<sub>2</sub>-based chemical affinity capture as a superior approach for analyzing EVs from complex clinical samples. This method demonstrates exceptional advantages in speed, throughput, reproducibility, and protein coverage. Using this optimized workflow, we analyzed plasma EVs from 80 patients with PCa and benign prostatic hyperplasia (BPH), identifying growth differentiation factor 15 (GDF15) as a compelling biomarker with a predictive power (AUC) of 0.908 for PCa. Extensive validation across independent cohorts comprising 457 samples, including plasma EVs and prostate tissues, confirmed GDF15's ability to distinguish PCa from BPH and stratify PCa stages. Notably, the combination of GDF15 with PSA further enhanced diagnostic efficiency, particularly for patients in the PSA diagnostic gray zone. This study establishes a robust workflow for EV protein analysis in large clinical cohorts and highlights EV-GDF15 as a promising biomarker for noninvasive PCa diagnosis.

ACS NanoVol. 19(16)
University of Electronic Science and Technology of China (CN), Sichuan University (CN), West China Hospital of Sichuan University (CN), Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital (CN)
National Natural Science Foundation of China, Natural Science Foundation of Sichuan Province, West China Hospital, Sichuan University
Zero hunger
Openalex Percentile: Top 2%
Extracellular vesicles in disease
9.67
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