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Proteomic Analysis of Urinary Extracellular Vesicles Reveals Estrogen/Progesterone Status-Associated Biomarkers of Breast Cancer Patients: Potential Roles in Diagnosis and Prognosis

IMPACT SIGNAL77/100
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Information from the abstract

Objective: This study aimed to identify potential diagnostic and prognostic biomarkers in urinary extracellular vesicles (uEVs). Material and Methods: Urine samples (n=30) from patients representing four breast cancer (BC) subtypes—Luminal A, Luminal B, human epidermal growth factor receptor 2 (HER2)-enriched, and triple-negative breast cancer (TNBC)—were collected. uEVs were isolated using differential ultracentrifugation and characterized by transmission electron microscopy and western blotting, confirming a round morphology, size range of 50–150 nanometer (nm), and presence of extracellular vesicle (EV) markers.Results: Proteomic profiling via liquid chromatography-tandem mass spectrometry identified 70 upregulated and 10 downregulated differentially expressed proteins (DEPs) between pre- and post-surgical samples. Upregulated DEPs were enriched in pathways related to chromosome segregation, inhibition of cell differentiation, and inflammation. Six BC-associated proteins were identified in uEVs: CTIP, ATAD2, TSP50, SCRIB, LRRC3, and POTEF. Notably, CTIP (fold change (FC)=9.54, adj-p-value=0.04) and ATAD2 (FC=8.02, adj-p-value=0.03) were significantly elevated in estrogen/progesterone receptor (ER/PR)-positive patients. Additionally, high expression of RANBP2 and LRRC16A/CARMIL1 correlated with poor overall survival (OS), while RRP9 and KIAA1967 were linked to favorable OS. One post-surgical sample from a patient with brain metastasis showed a unique protein profile.Conclusion: This study highlights that uEVs contain BC-specific protein markers associated with molecular subtypes and survival outcomes. These findings support the potential of uEV-based proteomics as a noninvasive tool for BC diagnosis and prognosis prediction.

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Why this record is monitored

This record has an Impact Signal of 77/100 based on recency, source, collaboration, and bibliographic signals. It prioritizes monitoring and is not a judgment of research quality.

Related topics: Extracellular vesicles in disease · Ferroptosis and cancer prognosis · Retinoids in leukemia and cellular processes

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Thai researcher and institutional participation

Rassanee Bissanum · Nilobon Jeanmard · Hutcha Sriplung · Sawanya Charoenlappanit · Sittiruk Roytrakul · Raphatphorn Navakanitworakul · Prince of Songkla University · National Science and Technology Development Agency

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Data limitations

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