ArticleMolecular & cellular proteomics : MCP2023
Data-Independent Acquisition Phosphoproteomics of Urinary Extracellular Vesicles Enables Renal Cell Carcinoma Grade Differentiation.
Article in Molecular & cellular proteomics : MCP, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it, 22 citations in OpenAlex.
- Renal cell carcinoma detection: a systematic review in diagnostic urinary biomarkers.BMC cancer · 2025Pooled it
- Extracellular Vesicle-Based Biomarkers in Spinal Cord Injury: A State-of-the-Art Review on Diagnostic and Prognostic Advances.International journal of molecular sciences · 2026Review
- Research advances in extracellular vesicles for diagnosis and treatment of genitourinary cancers.Frontiers in cell and developmental biology · 2026Review
- Review
- Kidney Cancer and Potential Use of Urinary Extracellular Vesicles.Oncology reviews · 2024Review
- Hands-Free Proteomic Profiling of Urinary Extracellular Vesicles with a High-Throughput Automated Workflow.Journal of the American Society for Mass Spectrometry · 2023Article
- One-Pot Analytical Pipeline for Efficient and Sensitive Proteomic Analysis of Extracellular Vesicles.Journal of proteome research · 2023Article
- Quantitative proteomics and phosphoproteomics of urinary extracellular vesicles define putative diagnostic biosignatures for Parkinson's disease.Communications medicine · 2023Article
- Therapeutic potential and pharmacological significance of extracellular vesicles derived from traditional medicinal plants.Frontiers in pharmacology · 2023Review
- High Throughput Isolation and Data Independent Acquisition Mass Spectrometry (DIA-MS) of Urinary Extracellular Vesicles to Improve Prostate Cancer Diagnosis.Molecules (Basel, Switzerland) · 2022Article
Corrections and comments
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Authors and funding
10 authors at 5 institutions in 2 countries.
Funding
Abstract
Translating the research capability and knowledge in cancer signaling into clinical settings has been slow and ineffective. Recently, extracellular vesicles (EVs) have emerged as a promising source for developing disease phosphoprotein markers to monitor disease status. This study focuses on the development of a robust data-independent acquisition (DIA) using mass spectrometry to profile urinary EV phosphoproteomics for renal cell cancer (RCC) grades differentiation. We examined gas-phase fractionated library, direct DIA (library-free), forbidden zones, and several different windowing schemes. After the development of a DIA mass spectrometry method for EV phosphoproteomics, we applied the strategy to identify and quantify urinary EV phosphoproteomes from 57 individuals representing low-grade clear cell RCC, high-grade clear cell RCC, chronic kidney disease, and healthy control individuals. Urinary EVs were efficiently isolated by functional magnetic beads, and EV phosphopeptides were subsequently enriched by PolyMAC. We quantified 2584 unique phosphosites and observed that multiple prominent cancer-related pathways, such as ErbB signaling, renal cell carcinoma, and regulation of actin cytoskeleton, were only upregulated in high-grade clear cell RCC. These results show that EV phosphoproteome analysis utilizing our optimized procedure of EV isolation, phosphopeptide enrichment, and DIA method provides a powerful tool for future clinical applications.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.