Proteomic Profiling of Serum Extracellular Vesicles Identifies Diagnostic Signatures and Therapeutic Targets in Breast Cancer.
Ganfei XuRui HuangReziya WumaierJiacheng LyuMinjing HuangYaya ZhangQingjian ChenWenting LiuMengyu TaoJunjian LiZhong-Hua TaoBo YuErxiang XuLingfeng WangGuoying YuOlivier GiresLei ZhouWei ZhuChen DingHongxia WangPublished in: Cancer research (2024)
Analysis of extracellular vesicles (EVs) is a promising noninvasive liquid biopsy approach for breast cancer (BC) detection, prognosis, and therapeutic monitoring. A comprehensive understanding of the characteristics and proteomic composition of BC-specific EVs from human samples is required to realize the potential of this strategy. In this study, we applied a mass spectrometry-based, data-independent acquisition (DIA) proteomic approach to characterize human serum EVs derived from patients with BC (n = 126) and healthy donors (HDs, n = 70) in a discovery cohort and validated the findings in five independent cohorts. Examination of the EV proteomes enabled construction of specific EV protein classifiers for diagnosing BC and distinguishing patients with metastatic disease. Of note, TALDO1 was found to be an EV biomarker of distant metastasis of BC. In vitro and in vivo analysis confirmed the role of TALDO1 in stimulating BC invasion and metastasis. Finally, high-throughput molecular docking and virtual screening of a library consisting of 271,380 small molecules identified a potent TALDO1 allosteric inhibitor, AO-022, which could inhibit BC migration in vitro and tumor progression in vivo. Together, this work elucidates the proteomic alterations in the serum EVs of BC patients to guide development of improved diagnosis, monitoring, and treatment strategies.
Keyphrases
- molecular docking
- high throughput
- label free
- mass spectrometry
- end stage renal disease
- small molecule
- chronic kidney disease
- ejection fraction
- gene expression
- newly diagnosed
- poor prognosis
- lymph node
- prognostic factors
- machine learning
- young adults
- risk assessment
- big data
- deep learning
- peritoneal dialysis
- high performance liquid chromatography
- liquid chromatography
- kidney transplantation
- human health
- amino acid
- patient reported
- capillary electrophoresis
- fine needle aspiration
- data analysis
- long non coding rna