MassIVE MSV000092139

Partial Public PXD042867

Unraveling the Global Proteome and Phosphoproteome of Prostate Cancer Patient-Derived Xenografts

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Description

Resistance to androgen deprivation therapies leads to metastatic castration-resistant prostate cancer (mCRPC) of adenocarcinoma (AdCa) origin that can transform to emergent aggressive variant prostate cancer (AVPC) which has neuroendocrine (NE)-like features. To this end, we used LuCaP patient-derived xenograft (PDX) tumors, clinically relevant models that reflects and retains key features of the tumor from advanced prostate cancer patients. Here we performed proteome and phosphoproteome characterization of 48 LuCaP PDX tumors and identified over 94,000 peptides and 9,700 phosphopeptides corresponding to 7,738 proteins. When we compared 15 NE versus 33 AdCa PDX samples, we identified 309 unique proteins and 476 unique phosphopeptides that were significantly altered and corresponded to proteins that are known to distinguish these two phenotypes. Assessment of protein and RNA concordance from these tumors revealed increased dissonance in transcriptionally regulated proteins in NE and metabolite interconversion enzymes in AdCa. Keywords: Proteomics, phosphoproteomics, Neuroendocrine, Adenocarcinoma, biomarkers, surfaceome, secretome, blood proteins, prostate cancer, patient-derived xenograft [doi:10.25345/C51N7XX66] [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: Proteomics, phosphoproteomics, Neuroendocrine, Adenocarcinoma, biomarkers, surfaceome, secretome, blood proteins, prostate cancer, patient-derived xenograft

Contact

Principal Investigators:
(in alphabetical order) 		Justin M. Drake PhD, University Minnesota, United States
Submitting User: DrakeLab

Publications

Sychev ZE, Day A, Bergom HE, Larson G, Ali A, Ludwig M, Boytim E, Coleman I, Corey E, Plymate SR, Nelson PS, Hwang JH, Drake JM.
Unraveling the Global Proteome and Phosphoproteome of Prostate Cancer Patient-Derived Xenografts.
Mol Cancer Res. Epub 2024 Feb 12.

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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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