PXD006616

PXD006616 is an original dataset announced via ProteomeXchange.

Title	INKA, an integrative analysis pipeline for inference of hyperactive phosphokinases in mass spectrometry-based phosphoproteomics data
Description	As a large proportion of current targeted cancer therapies is based on specific (tyrosine) kinase inhibitors, uncovering the identity of hyperactive kinases at work in tumors is crucial for proper treatment selection. A major challenge in phosphoproteomic data analysis is to relate kinases to the extent and magnitude of their phosphorylation 'footprint', and to rank them accordingly in order to single out kinases that are crucial for tumor growth in individual patients. Previous approaches have either zeroed in on phosphorylation of kinases themselves as a read-out of kinase activity, or focused on inferring kinase activities from the phosphorylation of their (supposed) substrates. Here, we combine both kinase-centric and substrate-centric analyses. We present a computational pipeline called Integrative Inferred Kinase Activity (INKA) scoring that integrates the observed abundance of phosphopeptides derived from (i) kinases as a whole, (ii) their kinase activation loop segments, (iii) proteins deduced to be kinase substrates based on prior experimental knowledge of kinase-substrate relationships, and/or (iv) kinase substrates predicted by the sequence motif- and network-based NetworKIN algorithm. As a proof of concept, applying this pipeline to the analysis of phosphoproteomic data on seven different oncogene-driven cancer cell lines highlighted the high, top ranking inferred activity of known driver kinases in these cells. This demonstrates the potential of label-free MS-based phosphoproteomics combined with dedicated data analysis for identifying (hyper)active kinases that, in potential future applications to tumors, may be selected for targeted inhibition in a personalized treatment setting.
HostingRepository	PRIDE
AnnounceDate	2024-10-22
AnnouncementXML	Submission_2024-10-22_04:38:21.534.xml
DigitalObjectIdentifier
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Unsupported dataset by repository
PrimarySubmitter	Sander Piersma
SpeciesList	scientific name: Homo sapiens (Human); NCBI TaxID: 9606;
ModificationList	phosphorylated residue; monohydroxylated residue; acetylated residue; iodoacetamide derivatized residue
Instrument	Q Exactive

Revision	Datetime	Status	ChangeLog Entry
0	2017-05-29 05:07:44	ID requested
1	2019-04-18 04:54:17	announced
⏵ 2	2024-10-22 04:38:27	announced	2024-10-22: Updated project metadata.

Beekhof R, van Alphen C, Henneman AA, Knol JC, Pham TV, Rolfs F, Labots M, Henneberry E, Le Large TY, de Haas RR, Piersma SR, Vurchio V, Bertotti A, Trusolino L, Verheul HM, Jimenez CR, INKA, an integrative data analysis pipeline for phosphoproteomic inference of active kinases. Mol Syst Biol, 15(4):e8250(2019) [pubmed]

10.15252/msb.20188250;

curator keyword: Technical, Biomedical

submitter keyword: Human, single-shot, Tyrosine kinase, phosphokinase ranking, label-free, phosphoproteomics

Connie Ramona Jimenez
contact affiliation	OncoProteomics Laboratory, Dept of Medical Oncology, VU University Medical Center, Amsterdam, The Netherlands
contact email	c.jimenez@vumc.nl
lab head
Sander Piersma
contact affiliation	OncoProteomics Laboratory, dept of Medical Oncology, VUmc Medical Center, Amsterdam, The Netherlands
contact email	s.piersma@vumc.nl
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/2019/04/PXD006616

PRIDE project URI

• PRIDE
  1. PXD006616
     1. Label: PRIDE project
     2. Name: INKA, an integrative analysis pipeline for inference of hyperactive phosphokinases in mass spectrometry-based phosphoproteomics data