Dataset Information

PCP39: prostate cancer proteome for 39 patients by PCT-SWATH

ABSTRACT: here we processed 105 biopsy-level tissues from 39 prostate cancer patients using pressure cycling technology (PCT) and SWATH-MS

INSTRUMENT(S): TripleTOF 5600

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Prostate Adenocarcinoma Cell, Epithelial Cell

DISEASE(S): Prostate Adenocarcinoma

SUBMITTER: Tiannan Guo

LAB HEAD: Ruedi Aebersold

PROVIDER: PXD004589 | Pride | 2018-10-17

REPOSITORIES: Pride

ACCESS DATA

Dataset's files

Source:

			Action	DRS
	20140307061249328-927290_PC-DDA91files.TraML	Other
	E1404261636_feature_alignment_requant_matrix.zip	Other
	experiment.properties	Other
	guot_L140220sw_01B.wiff	Wiff
	guot_L140220sw_01B.wiff.scan	Wiff

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Publications

Multi-region proteome analysis quantifies spatial heterogeneity of prostate tissue biomarkers.

Guo Tiannan T Li Li L Zhong Qing Q Rupp Niels J NJ Charmpi Konstantina K Wong Christine E CE Wagner Ulrich U Rueschoff Jan H JH Jochum Wolfram W Fankhauser Christian Daniel CD Saba Karim K Poyet Cedric C Wild Peter J PJ Aebersold Ruedi R Beyer Andreas A

Life science alliance 20180501 2

It remains unclear to what extent tumor heterogeneity impacts on protein biomarker discovery. Here, we quantified proteome intra-tissue heterogeneity (ITH) based on a multi-region analysis of prostate tissues using pressure cycling technology and SWATH mass spectrometry. We quantified 6,873 proteins and analyzed the ITH of 3,700 proteins. The level of ITH varied depending on proteins and tissue types. Benign tissues exhibited more complex ITH patterns than malignant tissues. Spatial variability ...[more]

PMID: 30090875

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Project description:Intra-tumor heterogeneity (ITH) has been studied at the morphologic, genomic, and transcriptomic level, but not proteomic level. Recent advances in mass spectrometric (MS) proteome quantification techniques, exemplified by SWATH-MS, a massively parallel targeting method, now also support precise quantitative proteomic comparisons across multiple samples, thus identifying molecular and implied functional differences. Here we used SWATH-MS to analyze the proteome profiles of a set of fresh-frozen prostate tissue samples derived from radical prostatectomy specimens. A high confidence set of 1,906 proteins were consistently quantified across 60 biopsy-level tissue samples from three prostatectomy patients, each consisting of 1.0 mm punch biopsies from histologically malignant (acinar and ductal adenocarcinoma) and matching benign prostatic hyperplasia tissues. The quantitative protein profiles allowed independent quantification of the degree of intra-tumor heterogeneity for each protein in benign and malignant tissues. We found that while majority of the proteins showed comparably low intra-tumor variability, 122 proteins were highly variable in malignant and/or matching benign tissues. We observed that proteins that varied between patients or tissue types also tended to be highly variable within prostate tissues, suggesting that these variability patterns will be a critical selection criterion in future protein biomarker studies. The data also permitted investigation of the heterogeneity of multiple biochemical pathways. The high variability of several of the pathways, including Glypican-1 network, alpha-linolenic acid metabolism and celecoxib pathway, explained contradictory results regarding them in the literature. In conclusion, we demonstrated a methodology for investigating proteomic intra-tumor heterogeneity from biopsy-level tissue samples, and quantified the degree of intra-tumor heterogeneity of 1,906 proteins in prostate tumors. The method and data presented here have advanced our understanding of tumor biology and offered critical insights for future biomarker development.