<<< Full experiment listing

PXD001812

PXD001812 is an original dataset announced via ProteomeXchange.

Dataset Summary
TitlePhosphoproteomic analysis of tamoxifen resistant breast cancer
DescriptionTamoxifen, an antagonist to estrogen receptor (ER), is a first line drug used in breast cancer treatment. However, this therapy is complicated by the fact that a substantial number of patients exhibit either de novo or acquired resistance. To characterize the signaling mechanisms underlying the resistance to tamoxifen, we established a tamoxifen-resistant cell line by treating the MCF7 breast cancer cell line with tamoxifen for over 6 months. We showed that this cell line exhibited resistance to tamoxifen both in vitro and in vivo. In order to quantify the phosphorylation alterations associated with tamoxifen resistance, we performed SILAC-based quantitative phosphoproteomic profiling on the resistant and vehicle-treated sensitive cell lines where we identified >5,600 unique phosphopeptides. We found phosphorylation levels of 1,529 peptides were increased (>2 fold) and 409 peptides were decreased (<0.5-fold) in tamoxifen resistant cells compared to tamoxifen sensitive cells. Gene set enrichment analysis revealed that focal adhesion pathway was the top enriched signaling pathway activated in tamoxifen resistant cells. We observed hyperphosphorylation of the focal adhesion kinases FAK1 and FAK2 in the tamoxifen resistant cells. Of note, FAK2 was not only hyperphosphorylated but also transcriptionally upregulated in tamoxifen resistant cells. Suppression of FAK2 by specific siRNA knockdown could sensitize the resistant cells to the treatment of tamoxifen. We further showed that inhibiting FAK activity using the small molecule inhibitor PF562271 repressed cellular proliferation in vitro and tumor formation in vivo. More importantly, our survival analysis revealed that high expression of FAK2 significantly associated with short metastasis-free survival of ER-positive breast cancer patients treated with tamoxifen-based hormone therapy. Our studies suggest that FAK2 is a great potential target for the development of therapy for the treatment of hormone refractory breast cancers.
HostingRepositoryPRIDE
AnnounceDate2016-05-25
AnnouncementXMLSubmission_2016-05-25_08:52:12.xml
DigitalObjectIdentifier
ReviewLevelPeer-reviewed dataset
DatasetOriginOriginal dataset
RepositorySupportUnsupported dataset by repository
PrimarySubmitterMuhammad Zahari
SpeciesList scientific name: Homo sapiens (Human); NCBI TaxID: 9606;
ModificationList6x(13)C: 4x(15)N labeled L-arginine; monohydroxylated residue; iodoacetamide derivatized residue; phosphorylated residue; 6x(13)C: 2x(15)N labeled L-lysine
InstrumentLTQ Orbitrap Velos
Dataset History
RevisionDatetimeStatusChangeLog Entry
02015-02-13 01:11:48ID requested
12016-05-25 08:52:13announced
Publication List
Wu X, Zahari MS, Renuse S, Nirujogi RS, Kim MS, Manda SS, Stearns V, Gabrielson E, Sukumar S, Pandey A, Phosphoproteomic Analysis Identifies Focal Adhesion Kinase 2 (FAK2) as a Potential Therapeutic Target for Tamoxifen Resistance in Breast Cancer. Mol Cell Proteomics, 14(11):2887-900(2015) [pubmed]
Keyword List
curator keyword: Biomedical
submitter keyword: SILAC, FAK, estrogen receptor, tamoxifen
Contact List
Akhilesh Pandey
contact affiliationMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205 USA
contact emailpandey@jhmi.edu
lab head
Muhammad Zahari
contact affiliationJohns Hopkins School of Medicine
contact emailsaddiq@jhmi.edu
dataset submitter
Full Dataset Link List
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/2016/05/PXD001812
PRIDE project URI
Repository Record List
[ + ]