MassIVE MSV000082926

Imported Reanalysis Dataset Public PXD004476

Human Bile LC-MS/MS

Description

The proteome analysis of bile fluid represents a promising strategy to identify biomarker candidates for various diseases of the hepatobiliary system. However, to obtain substantive results in biomarker discovery studies large patient cohorts necessarily need to be analyzed. Consequently, this would lead to an unmanageable number samples to be measured if sample preparation protocols with extensive fractionation methods are applied. Hence, the performance of simple workflows allowing for "one sample, one shot" experiments have been evaluated in this study. In detail, sixteen different protocols implying modifications at the stages of desalting, delipidation, deglycosylation and tryptic digestion have been tested. Each method has been individually evaluated regarding various performance criteria and comparative analyses have been conducted to uncover possible complementarities. Here, the best performance in terms of proteome coverage has been assessed for a combination of acetone precipitation with in-gel digestion. Finally, a mapping of all obtained protein identifications with putative biomarkers for hepatocellular carcinoma (HCC) and cholangiocellular carcinoma (CCC) revealed several proteins easily detectable in bile fluid. These results can build the basis for future studies with large and well-defined patient cohorts in a more disease-related context, instead of a technical one as reported here. [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: Bile fluid ; proteomics ; method comparison ; biomarkers ; hepatocellular carcinoma ; cholangiocellular carcinoma

Contact

Principal Investigators:
(in alphabetical order)
Dominik Andre Megger, Medizinisches Proteom-Center (MPC) Ruhr-Universit?�t Bochum Clinical Proteomics - Infection Research Universitaetsstrasse 150, D-44801 Bochum, N/A
Submitting User: ccms

Publications

Megger DA, Padden J, Rosowski K, Uszkoreit J, Bracht T, Eisenacher M, Gerges C, Neuhaus H, Schumacher B, Schlaak JF, Sitek B.
One Sample, One Shot - Evaluation of sample preparation protocols for the mass spectrometric proteome analysis of human bile fluid without extensive fractionation.
J Proteomics. Epub 2016 Dec 5.

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Number of distinct conditions across all analyses (original submission and reanalyses) associated with this dataset.

Distinct condition labels are counted across all files submitted in the "Metadata" category having a "Condition" column in this dataset.

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Number of distinct biological replicates across all analyses (original submission and reanalyses) associated with this dataset.

Distinct replicate labels are counted across all files submitted in the "Metadata" category having a "BioReplicate" or "Replicate" column in this dataset.

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Number of distinct technical replicates across all analyses (original submission and reanalyses) associated with this dataset.

The technical replicate count is defined as the maximum number of times any one distinct combination of condition and biological replicate was analyzed across all files submitted in the "Metadata" category. In the case of fractionated experiments, only the first fraction is considered.

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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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Number of distinct protein accessions reported across all analyses (original submission and reanalyses) associated with this dataset.

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Number of distinct unmodified peptide sequences reported across all analyses (original submission and reanalyses) associated with this dataset.

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Number of distinct peptide sequences (including modified variants or peptidoforms) reported across all analyses (original submission and reanalyses) associated with this dataset.

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Total number of peptide-spectrum matches (i.e. spectrum identifications) reported across all analyses (original submission and reanalyses) associated with this dataset.

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Number of distinct proteins quantified across all analyses (original submission and reanalyses) associated with this dataset.

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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Number of distinct proteins found to be differentially abundant in at least one comparison across all analyses (original submission and reanalyses) associated with this dataset.

A protein is differentially abundant if its change in abundance across conditions is found to be statistically significant with an adjusted p-value <= 0.05 and lists no issues associated with statistical tests for differential abundance.

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

"N/A" means no results of this type were submitted.
This dataset may not contain all raw spectra data as originally deposited in PRIDE. It has been imported to MassIVE for reanalysis purposes, so its spectra data here may consist solely of processed peak lists suitable for reanalysis with most software.