PXD040776
PXD040776 is an original dataset announced via ProteomeXchange.
Dataset Summary
Title | Proteomic Fingerprinting of Prostate Cancer Progression Through Library-Free DIA-MS Reveals Systematic and Conserved Pathway Dysregulation |
Description | Prostate cancer is the second-most prevalent cancer in men and the cancer with the highest age-adjusted incidence overall. With rates of diagnoses positively correlating with advanced age, the aging populations in many high cancer rate countries mandate the development of facile strategies to accurately identify and stratify this disease. Protein biomarkers are used prominently in prostate cancer diagnosis and therapeutic monitoring but are often criticized for inaccuracy that leads to under or overdiagnosis, incorrect treatment, or false indication of severity. Taken together, there has never been a more pressing need to uncover biomolecular fingerprints or protein panels that enable minimally invasive cancer diagnoses and the ability to confidently stratify disease states. Research towards this goal has traditionally been limited by the lack of model organisms that mimic the unique genotypic and phenotypic characteristics associated with discrete prostate cancer severities. The recently developed benign prostate hypertrophy to prostate cancer (BCaP) cell model removes this limitation, enabling confident association of protein expression changes with cancer phenotype. Herein, we investigate three progressive prostate cancer phenotypes using library-free data-independent acquisition mass spectrometry. Identifying 91,785 peptides and quantifying 6,614 proteins, we reveal 1,242 biomolecular signatures dysregulated in accordance with cancer progression. Highlighting 7 distinct diagnostic expression patterns within this protein cohort, we reveal the progressive reorganization of critical biological processes such as kinetochore formation, cytoskeletal organization, metabolic processing, and interferon signaling. We also provide a topical comparison of transcript and protein level analyses, articulating the importance of proteomic measurements and the need for regular, multimodal analysis. Together, this study presents a primary investigation of the protein-level perturbations observed in a novel progressive cell model, pinpointing a collection of proteins that demonstrate potential for biomarker validation and utility within protein-centric prostate cancer diagnosis. |
HostingRepository | MassIVE |
AnnounceDate | 2023-03-10 |
AnnouncementXML | Submission_2023-03-10_09:28:43.061.xml |
DigitalObjectIdentifier | |
ReviewLevel | Non peer-reviewed dataset |
DatasetOrigin | Original dataset |
RepositorySupport | Unsupported dataset by repository |
PrimarySubmitter | Graham Delafield |
SpeciesList | scientific name: Homo sapiens neanderthalensis; common name: Neandertal; NCBI TaxID: 63221; |
ModificationList | Acetyl; Deamidated; Oxidation |
Instrument | Orbitrap Fusion Lumos |
Dataset History
Revision | Datetime | Status | ChangeLog Entry |
---|---|---|---|
0 | 2023-03-10 09:03:37 | ID requested | |
⏵ 1 | 2023-03-10 09:28:43 | announced |
Publication List
no publication |
Keyword List
submitter keyword: Prostate Cancer, Data-Independent Analysis, Library-Free, Proteomics, Cancer Progression |
Contact List
Lingjun Li | |
---|---|
contact affiliation | University of Wisconsin-Madison |
contact email | lingjun.li@wisc.edu |
lab head | |
Graham Delafield | |
contact affiliation | University of Wisconsin - Madison |
contact email | delafield@wisc.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/MSV000091469/ |