PXD012073-1

PXD012073 is an original dataset announced via ProteomeXchange.

Title	Kinome-centric pharmacoproteomics identifies signaling pathways underlying cellular responses to targeted cancer drugs
Description	Kinase-dependent signaling networks are frequently dysregulated in cancer, driving disease progression. While kinase inhibition has become an important therapeutic approach many cancers resist drug treatment. Therefore, we need both reliable biomarkers that predict drug responses and new targets to overcome drug resistance. Determining the kinase(s) that control cancer progression in individual cancers can pose a significant challenge. Genomics has identified important, yet limited numbers of kinase driver mutations. Transcriptomics can quantify aberrant gene expression, but it cannot measure the protein phosphorylation that regulates kinase-dependent signaling network activity. Proteomics measures protein expression and phosphorylation and, therefore, quantifies aberrant signaling network activity directly. We developed a kinome-centric pharmacoproteomics platform to study signaling pathways that determine cancer drug response. Using hepatocellular carcinoma (HCC) as our model, we determined kinome activity with kinobead/LC-MS profiling, and screened 299 kinase inhibitors for growth inhibition. Integrating kinome activity with drug responses, we obtained a comprehensive database of predictive biomarkers, and kinase targets that promote drug sensitivity and resistance. Our dataset specified pathway-based biomarkers for the clinical HCC drugs sorafenib, regorafenib and lenvatinib, and we found these biomarkers enriched in human HCC specimens. Strikingly, our database also revealed signaling pathways that promote HCC cell epithelialmesenchymal transition (EMT) and drug resistance, and that NUAK1 and NUAK2 regulate these pathways. Inhibition of these kinases reversed the EMT and sensitized HCC cells to kinase inhibition. These results2 demonstrate that our kinome pharmacoproteomics platform discovers both predictive biomarkers for personalized oncology and novel cancer drug targets.
HostingRepository	MassIVE
AnnounceDate	2019-11-29
AnnouncementXML	Submission_2019-11-29_21:43:22.xml
DigitalObjectIdentifier
ReviewLevel	Non peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Unsupported dataset by repository
PrimarySubmitter	Martin Golkowski
SpeciesList	scientific name: Homo sapiens; common name: human; NCBI TaxID: 9606;
ModificationList	Phospho
Instrument	LTQ Orbitrap Elite; Orbitrap Fusion ETD

Revision	Datetime	Status	ChangeLog Entry
0	2018-12-15 10:54:36	ID requested
⏵ 1	2019-11-29 21:43:23	announced

no publication

submitter keyword: hepatocellular carcinoma, kinase inhibitor, kinobeads, epithelial-mesenchymal transition, drug resistance

Shao-En Ong
contact affiliation	University of Washington
contact email	shaoen@uw.edu
lab head
Martin Golkowski
contact affiliation	University of Washington
contact email	golkom@uw.edu
dataset submitter

MassIVE dataset URI

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