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<p>Triple-negative breast cancer (TNBC) is an aggressive breast cancer subtype with limited therapeutic targets, highlighting the necessity for serum-based candidate biomarker discovery. In this study, we developed a serum small extracellular vesicle (sEV) proteomic workflow based on functionalized nanobowl enrichment and a simple on-beads lysis and in-tube digestion pretreatment for sEVs. And 107 clinical serum samples were analyzed, each requiring only 50 microliters of serum. A total of 3477 proteins were quantified, and 3152 proteins detected in &gt;50% of samples were used for statistical analysis. After quality control, 102 samples were analyzed by differential analysis, coexpression network analysis, and functional enrichment analysis. The results showed distinguishable serum sEV protein profiles among TNBC, healthy controls, benign breast diseases, and other breast cancer groups. Six candidate proteins were identified, among which thrombospondin-2 (THBS2) showed a stable increase in TNBC. This study provides a practical basis for serum sEV-based biomarker discovery in TNBC.</p>

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Serum Small Extracellular Vesicle Proteomic Analysis Based on Functionalized Nanobowl Enrichment for Screening Candidate Biomarkers of Breast Cancer

  • 期刊论文

  • 发表日期：

    2026年7月20日

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  • Jialiang Zhao,
  • Caiwei Hu,
  • Jie Feng,
  • Bokai Zhou,
  • Guangyao Wu,
  • Mingshi Jin,
  • Yu Bai

摘要

Triple-negative breast cancer (TNBC) is an aggressive breast cancer subtype with limited therapeutic targets, highlighting the necessity for serum-based candidate biomarker discovery. In this study, we developed a serum small extracellular vesicle (sEV) proteomic workflow based on functionalized nanobowl enrichment and a simple on-beads lysis and in-tube digestion pretreatment for sEVs. And 107 clinical serum samples were analyzed, each requiring only 50 microliters of serum. A total of 3477 proteins were quantified, and 3152 proteins detected in >50% of samples were used for statistical analysis. After quality control, 102 samples were analyzed by differential analysis, coexpression network analysis, and functional enrichment analysis. The results showed distinguishable serum sEV protein profiles among TNBC, healthy controls, benign breast diseases, and other breast cancer groups. Six candidate proteins were identified, among which thrombospondin-2 (THBS2) showed a stable increase in TNBC. This study provides a practical basis for serum sEV-based biomarker discovery in TNBC.