PXD021398

PXD021398 is an original dataset announced via ProteomeXchange.

Title	Deep learning boosts immunopeptidomics one mass spectrum at a time
Description	Characterizing the human leukocyte antigen (HLA) bound ligandome by mass spectrometry (MS) holds great promise for developing vaccines and drugs for immune oncology. Still, the identification of such non-tryptic peptides presents substantial computational challenges. To address these, we synthesized >300,000 peptides within the ProteomeTools project representing HLA class I & II ligands and products of the proteases AspN and LysN and analyzed these by multi-modal LC-MS/MS. The resulting data enabled training of a single model using the deep learning framework Prosit that shows outstanding prediction accuracy of fragment ion spectra for tryptic and non-tryptic peptides. Applying Prosit demonstrates that the identification of HLA peptides can be improved by 50-300% on average, that proteasomal HLA peptide splicing may not exist and that additional neo-epitopes that elicit an immune response can be identified from patient tumors. Together, the provided peptides, spectra and computational tools substantially expand the scope of immunopeptidomics workflows.
HostingRepository	PRIDE
AnnounceDate	2022-02-14
AnnouncementXML	Submission_2022-02-14_02:18:25.947.xml
DigitalObjectIdentifier
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Unsupported dataset by repository
PrimarySubmitter	Daniel Zolg
SpeciesList	scientific name: Homo sapiens (Human); NCBI TaxID: 9606;
ModificationList	No PTMs are included in the dataset
Instrument	Orbitrap Fusion Lumos; Q Exactive HF

Revision	Datetime	Status	ChangeLog Entry
0	2020-09-10 05:11:14	ID requested
1	2021-04-26 09:47:35	announced
⏵ 2	2022-02-14 02:18:26	announced	2022-02-14: Updated project metadata.

Dataset with its publication pending

ProteomeXchange project tag: EPIC-XS

submitter keyword: HLA peptide, Rescoring, fragmentation prediction, spectra prediction, ligand, HLA Class I, ProteomeTools, spliced peptide, proteasomal splicing, deep learning,Prosit

Bernhard Kuster
contact affiliation	Chair of Proteomics and Bioanalytics, Technical University of Munich, Germany
contact email	kuster@tum.de
lab head
Daniel Zolg
contact affiliation	Technical University of Munich
contact email	daniel.zolg@tum.de
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/2021/04/PXD021398

PRIDE project URI

• PRIDE
  1. PXD021398
     1. Label: PRIDE project
     2. Name: Deep learning boosts immunopeptidomics one mass spectrum at a time