PXD039504-1
PXD039504 is an original dataset announced via ProteomeXchange.
Dataset Summary
Title | Data-independent acquisition phosphoproteomics of urinary extracellular vesicles enables renal cell carcinoma grade differentiation |
Description | 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 (GPF) 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 (CKD), and healthy control (HC) individuals. Urinary EVs were efficiently isolated by functional magnetic beads, and EV phosphopeptides were subsequently enriched by PolyMAC. We quantified 2,584 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. |
HostingRepository | MassIVE |
AnnounceDate | 2023-03-25 |
AnnouncementXML | Submission_2023-03-25_08:11:27.688.xml |
DigitalObjectIdentifier | |
ReviewLevel | Non peer-reviewed dataset |
DatasetOrigin | Original dataset |
RepositorySupport | Unsupported dataset by repository |
PrimarySubmitter | Marco Hadisurya |
SpeciesList | scientific name: Homo sapiens; common name: human; NCBI TaxID: 9606; |
ModificationList | Phospho |
Instrument | Q Exactive HF-X |
Dataset History
Revision | Datetime | Status | ChangeLog Entry |
---|---|---|---|
0 | 2023-01-16 19:49:49 | ID requested | |
⏵ 1 | 2023-03-25 08:11:28 | announced |
Publication List
no publication |
Keyword List
submitter keyword: Renal cell carcinoma, Extracellular vesicles, Phosphorylation, Cancer Grades |
Contact List
W. Andy Tao | |
---|---|
contact affiliation | Purdue University |
contact email | taow@purdue.edu |
lab head | |
Marco Hadisurya | |
contact affiliation | Purdue University |
contact email | mhadisur@purdue.edu |
dataset submitter |
Full Dataset Link List
MassIVE dataset URI |
Dataset FTP location NOTE: Most web browsers have now discontinued native support for FTP access within the browser window. But you can usually install another FTP app (we recommend FileZilla) and configure your browser to launch the external application when you click on this FTP link. Or otherwise, launch an app that supports FTP (like FileZilla) and use this address: ftp://massive.ucsd.edu/MSV000091069/ |