Comparative Analysis of Label-Free and 8-Plex iTRAQ Approach for Quantitative Tissue Proteomic Analysis.
High resolution proteomics approaches have been successfully utilized for the comprehensive characterization of the cell proteome. However, in the case of quantitative proteomics an open question still remains, which quantification strategy is best suited for identification of biologically relevant changes, especially in clinical specimens. In this study, a thorough comparison of a label-free approach (intensity-based) and 8-plex iTRAQ was conducted as applied to the analysis of tumor tissue samples from non-muscle invasive and muscle-invasive bladder cancer. For the latter, two acquisition strategies were tested including analysis of unfractionated and fractioned iTRAQ-labeled peptides. To reduce variability, aliquots of the same protein extract were used as starting material, whereas to obtain representative results per method further sample processing and MS analysis were conducted according to routinely applied protocols. Considering only multiple-peptide identifications, LC-MS/MS analysis resulted in the identification of 910, 1092 and 332 proteins by label-free, fractionated and unfractionated iTRAQ, respectively. The label-free strategy provided higher protein sequence coverage compared to both iTRAQ experiments. Even though pre-fraction of the iTRAQ labeled peptides allowed for a higher number of identifications, this was not accompanied by a respective increase in the number of differentially expressed changes detected. Validity of the proteomics output related to protein identification and differential expression was determined by comparison to existing data in the field (Protein Atlas and published data on the disease). All methods predicted changes which to a large extent agreed with published data, with label-free providing a higher number of significant changes than iTRAQ. Conclusively, both label-free and iTRAQ (when combined to peptide fractionation) provide high proteome coverage and apparently valid predictions in terms of differential expression, nevertheless label-free provides higher sequence coverage and ultimately detects a higher number of differentially expressed proteins. The risk for receiving false associations still exists, particularly when analyzing highly heterogeneous biological samples, raising the need for the analysis of higher sample numbers and/or application of adjustment for multiple testing.
Biotechnology Division, Biomedical Research Foundation of the Academy of Athens, Athens, Greece; Charité-Universitätsmedizin Berlin, Berlin, Germany.
Agnieszka
A
Latosinska
Biotechnology Division, Biomedical Research Foundation of the Academy of Athens, Athens, Greece.
Konstantinos
K
Vougas
Biotechnology Division, Biomedical Research Foundation of the Academy of Athens, Athens, Greece.
Manousos
M
Makridakis
Institut National de la Santé et de la Recherche Médicale (INSERM), U1048, Institute of Cardiovascular and Metabolic Diseases, Toulouse, France; Université Toulouse III Paul-Sabatier, Toulouse, France.
Julie
J
Klein
BHF Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow, United Kingdom.
William
W
Mullen
Department of Pathology, Hannover Medical School, Hannover, Germany.
Mahmoud
M
Abbas
Department of Urology, Medical School of Athens, Laikon Hospital, Athens, Greece.
Konstantinos
K
Stravodimos
Department of Urology, Medical School of Athens, Laikon Hospital, Athens, Greece.
Ioannis
I
Katafigiotis
Department of Urology, University of Lübeck, Lübeck, Germany.
Axel S
AS
Merseburger
Biotechnology Division, Biomedical Research Foundation of the Academy of Athens, Athens, Greece.
Jerome
J
Zoidakis
BHF Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow, United Kingdom; Mosaiques Diagnostics GmbH, Hannover, Germany.
Harald
H
Mischak
Biotechnology Division, Biomedical Research Foundation of the Academy of Athens, Athens, Greece.
Antonia
A
Vlahou
RWTH-Aachen, Institute for Molecular Cardiovascular Research (IMCAR), Aachen, Germany.
Vera
V
Jankowski
D002853:Chromatography, Liquid; D006801:Humans; D009363:Neoplasm Proteins / Q000378:metabolism*; D040901:Proteomics / Q000379:methods*; D053719:Tandem Mass Spectrometry / Q000379:methods; D001749:Urinary Bladder Neoplasms / Q000378:metabolism
D009363:Neoplasm Proteins