MassIVE MSV000080776

Imported Reanalysis Dataset Public PXD002286

Phospo-proteomic profiling of Castration Resistant Prostate Cancer

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Description

The integration of diverse ‘omic’ datasets will increase our understanding of the key signaling pathways that drive disease. Here, we used clinical tissue cohorts corresponding to lethal metastatic castration resistant prostate cancer (CRPC) obtained at rapid autopsy to integrate mutational, transcriptomic, and phosphoproteomic datasets for pathway analysis. Using Tied Diffusion through Interacting Events (TieDIE), we integrated differentially expressed transcriptional master regulators, functionally mutated genes, and differentially ‘activated’ kinases in CRPC tissues to synthesize a robust signaling network consisting of pathways with known and novel gene interactions. For 6 individual CRPC patients for which we had transcriptomic and phosphoproteomic data we observed distinct pathway activation states for each patient profile. In one patient, the activated pathways were strikingly similar to a prostate cancer cell line, 22Rv1, providing us with a good pre-clinical model to test targeted, combination therapies. In all, synthesis of multiple ‘omic’ datasets revealed a plethora of pathway information suitable for targeted therapies in lethal prostate cancer. [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: phosphorylation ; prostate cancer ; human

Contact

Principal Investigators:
(in alphabetical order) 		Thomas Graeber, David Geffen School of Medicine, University of California, Los Angeles, CA 90095 Department of Molecular and Medical Pharmacology, Jonsson Comprehensive Cancer Center, Institute for Molecular Medicine, California NanoSystems Institute, N/A
Submitting User: ccms

Publications

Drake JM, Paull EO, Graham NA, Lee JK, Smith BA, Titz B, Stoyanova T, Faltermeier CM, Uzunangelov V, Carlin DE, Fleming DT, Wong CK, Newton Y, Sudha S, Vashisht AA, Huang J, Wohlschlegel JA, Graeber TG, Witte ON, Stuart JM.
Phosphoproteome Integration Reveals Patient-Specific Networks in Prostate Cancer.
Cell. 2016 Aug 11;166(4):1041-54. Epub 2016 Aug 4.

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Originally identified proteins that were automatically remapped by MassIVE to proteins in the SwissProt human reference database.

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Distinct protein accessions are counted across all files submitted in the "Statistical Analysis of Quantified Analytes" category having a "Protein" column in this dataset.

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