PXD023904-2

PXD023904 is an original dataset announced via ProteomeXchange.

Title	Deep Visual Proteomics defines single-cell identity and heterogeneity
Description	Despite the availabilty of imaging-based and mass-spectrometry-based methods for spatial proteomics, a key challenge remains connecting images with single-cell-resolution protein abundance measurements. Here we introduce Deep Visual Proteomics (DVP), which combines artificial-intelligence-driven image analysis of cellular phenotypes with automated single-cell or single-nucleus laser microdissection and ultra-high-sensitivity mass spectrometry. DVP links protein abundance to complex cellular or subcellular phenotypes while preserving spatial context. By individually excising nuclei from cell culture, we classified distinct cell states with proteomic profiles defined by known and uncharacterized proteins. In an archived primary melanoma tissue, DVP identified spatially resolved proteome changes as normal melanocytes transition to fully invasive melanoma, revealing pathways that change in a spatial manner as cancer progresses, such as mRNA splicing dysregulation in metastatic vertical growth that coincides with reduced interferon signaling and antigen presentation. The ability of DVP to retain precise spatial proteomic information in the tissue context has implications for the molecular profiling of clinical samples.
HostingRepository	PRIDE
AnnounceDate	2023-06-16
AnnouncementXML	Submission_2023-06-16_02:42:22.103.xml
DigitalObjectIdentifier
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Unsupported dataset by repository
PrimarySubmitter	FabianCoscia
SpeciesList	scientific name: Homo sapiens (Human); NCBI TaxID: 9606;
ModificationList	No PTMs are included in the dataset
Instrument	timsTOF Pro

Revision	Datetime	Status	ChangeLog Entry
0	2021-01-31 22:59:28	ID requested
1	2022-04-27 12:00:59	announced
⏵ 2	2023-06-16 02:42:22	announced	2023-06-16: Updated project metadata.
3	2023-11-14 09:01:08	announced	2023-11-14: Updated project metadata.

Mund A, Coscia F, Kriston A, Hollandi R, Kov, á, cs F, Brunner AD, Migh E, Schweizer L, Santos A, Bzorek M, Naimy S, Rahbek-Gjerdrum LM, Dyring-Andersen B, Bulkescher J, Lukas C, Eckert MA, Lengyel E, Gnann C, Lundberg E, Horvath P, Mann M, Deep Visual Proteomics defines single-cell identity and heterogeneity. Nat Biotechnol, 40(8):1231-1240(2022) [pubmed]

submitter keyword: Microscopy, Digital Pathology,Proteomics, Laser Microdissection

MatthiasMann
contact affiliation	Prof. Dr. Matthias Mann Max Planck Institute of Biochemistry Am Klopferspitz 18 82152 Martinsried +49 89 8578-2557
contact email	mmann@biochem.mpg.de
lab head
FabianCoscia
contact affiliation	Max Delbrueck Center for Molecular Medicine
contact email	fabian.coscia@cpr.ku.dk
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/2022/04/PXD023904

PRIDE project URI

• PRIDE
  1. PXD023904
     1. Label: PRIDE project
     2. Name: Deep Visual Proteomics defines single-cell identity and heterogeneity