PXD037506

PXD037506 is an original dataset announced via ProteomeXchange.

Title	Proteomic Profile of Urinary Extracellular Vesicles Unravelled Biomarkers for Prostate Cancer Recognition
Description	Proteomic profiling of extracellular vesicles (EVs) represents a promising approach for early detection and therapeutic monitoring of diseases such as cancer, which was aimed for identifying novel biomarkers for prostate cancer diagnosis in this study. The focus of this study was to develop a robust data independent acquisition (DIA) using mass spectrometry to analyse urinary EV proteomics for prostate cancer and prostate inflammation screening. We combined three library-based analysis (direct-DIA, GPF-DIA, and fractionated DDA) to improve the stability and comprehensiveness of biomarkers. By applying this innovative DIA strategy in conjunction with stable automatic EVs extraction technology, we assessed the levels of urinary EV-associated proteins based on 40 samples consisting of 20 cases and 20 controls, where 18 EV proteins were identified to be differentiated in prostate cancer outcome, of which 3 (i.e., SERPINA3, LRG1, SCGB3A1) were shown to be consistently up regulated. We also observed 6 out of the 18 (33%) EV proteins that had been developed as drug targets, while some of them showed interactions. Moreover, the potential mechanistic pathways of significantly different EV proteins, were enriched in metabolic, immune, and inflammatory activities. These results showed consistent in an independent cohort consist of 20 participants. Based on random forest algorithm, we found that SERPINA3, LRG1, SCGB3A1 add predictable value in addition to age, prostate size, body mass index (BMI) and prostate-specific antigen (PSA). In summary, the current study revealed the EV proteomic landscape and biomarkers for prostate cancer, which has shown to provide promising insights of urine EV proteome in clinical implication.
HostingRepository	PRIDE
AnnounceDate	2023-11-14
AnnouncementXML	Submission_2023-11-14_08:43:11.867.xml
DigitalObjectIdentifier
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Unsupported dataset by repository
PrimarySubmitter	Hao Zhang
SpeciesList	scientific name: Homo sapiens (Human); NCBI TaxID: 9606;
ModificationList	No PTMs are included in the dataset
Instrument	Q Exactive HF

Revision	Datetime	Status	ChangeLog Entry
0	2022-10-17 01:51:25	ID requested
1	2023-03-11 07:18:00	announced
⏵ 2	2023-11-14 08:43:14	announced	2023-11-14: Updated project metadata.

Zhang H, Zhang GY, Su WC, Chen YT, Liu YF, Wei D, Zhang YX, Tang QY, Liu YX, Wang SZ, Li WC, Wesselius A, Zeegers MP, Zhang ZY, Gu YH, Tao WA, Yu EY, High Throughput Isolation and Data Independent Acquisition Mass Spectrometry (DIA-MS) of Urinary Extracellular Vesicles to Improve Prostate Cancer Diagnosis. Molecules, 27(23):(2022) [pubmed]

submitter keyword: Extracellular Vesicles, Prostate Cancer, Biomarkers

W. Andy. Tao
contact affiliation	Departments of Chemistry and Biochemistry, Purdue University, West Lafayette, Indiana 47907, U.S.A.
contact email	zhanghaohao@seu.edu.cn
lab head
Hao Zhang
contact affiliation	Southeast University
contact email	zhanghaohao@seu.edu.cn
dataset submitter

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://ftp.pride.ebi.ac.uk/pride/data/archive/2023/03/PXD037506

PRIDE project URI

• PRIDE
  1. PXD037506
     1. Label: PRIDE project
     2. Name: Proteomic Profile of Urinary Extracellular Vesicles Unravelled Biomarkers for Prostate Cancer Recognition