Dataset Information

Comparative assessment of quantification methods for tumor tissue phosphoproteomics

ABSTRACT: The choice of quantification method is critical for study design and comparison of cancer phosphoproteomes. We comparatively assessed label-free quantification (LFQ), spike-in-SILAC (stable isotope labeling of amino acids in cell culture) and tandem mass tag (TMT) labeling techniques for quantitative phosphoproteome analysis in tumor tissues. Using ovarian cancer tissue as an example, our study establishes a resource for the design and analysis of quantitative phosphoproteomics studies in cancer research and diagnosis. TMT provided the lowest accuracy and the highest precision and robustness across different phosphosite abundances and matrices (cell culture versus tumor tissue). Spike-in-SILAC offered the best compromise between these features, but was limited by low phosphosite coverage. LFQ provided the lowest precision, but the highest number of phosphosite identifications. Spike-in-SILAC and LFQ were susceptible to matrix effects arising from different sample types. Analysis based on match between run (MBR) improved phosphosite coverage across technical replicates in LFQ and spike-in-SILAC, but further reduced the precision and robustness of quantification.

INSTRUMENT(S): Orbitrap Fusion

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Ovarian Serous Carcinoma Cell

DISEASE(S): Malignant Neoplasm Of Ovary

SUBMITTER: yang zhang

LAB HEAD: Peter L. Horvatovich

PROVIDER: PXD030450 | Pride | 2022-08-09

REPOSITORIES: Pride

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Dataset's files

Source:

			Action	DRS
	190417_ID_1_YZ_cellline_TMT_pair1_total.raw	Raw
	190417_ID_2_YZ_cellline_TMT_pair2_total.raw	Raw
	190417_ID_3_YZ_cellline_TMT_pair1_enriched.raw	Raw
	190417_ID_4_YZ_cellline_TMT_pair2_enriched.raw	Raw
	190417_ID_77_YZ_tissue_TMT_pair1_total.raw	Raw

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Publications

Comparative Assessment of Quantification Methods for Tumor Tissue Phosphoproteomics.

Zhang Yang Y Dreyer Benjamin B Govorukhina Natalia N Heberle Alexander M AM Končarević Saša S Krisp Christoph C Opitz Christiane A CA Pfänder Pauline P Bischoff Rainer R Schlüter Hartmut H Kwiatkowski Marcel M Thedieck Kathrin K Horvatovich Peter L PL

Analytical chemistry 20220726 31

With increasing sensitivity and accuracy in mass spectrometry, the tumor phosphoproteome is getting into reach. However, the selection of quantitation techniques best-suited to the biomedical question and diagnostic requirements remains a trial and error decision as no study has directly compared their performance for tumor tissue phosphoproteomics. We compared label-free quantification (LFQ), spike-in-SILAC (stable isotope labeling by amino acids in cell culture), and tandem mass tag (TMT) isob ...[more]

PMID: 35880733

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Project description:Measuring the properties of endogenous cell proteins, such as expression level, subcellular localization and turnover rates, on a whole proteome level remains a major challenge in the post-genome era. Quantitative methods for measuring mRNA expression do not reliably predict corresponding protein levels and provide little or no information on other protein properties. Here we describe a combined pulse-labelling, spatial proteomics and data analysis strategy to characterize the expression, localization, synthesis, degradation and turnover rates of endogenously expressed, untagged human proteins in different subcellular compartments. Using quantitative mass spectrometry and SILAC, a total of 80,098 peptides from 8,041 HeLa proteins were quantified, and their spatial distribution between the cytoplasm, nucleus and nucleolus determined and visualised using specialised software tools developed in PepTracker. Using information from ion intensities and rates of change in isotope ratios, protein abundance levels and protein synthesis, degradation and turnover rates were calculated for the whole cell and for the respective cytoplasmic, nuclear and nucleolar compartments. Expression levels of endogenous HeLa proteins varied by up to seven orders of magnitude. The average turnover rate for HeLa proteins was approximately 20 hours. Turnover rate did not correlate with either molecular weight or net charge, but did correlate with abundance, with highly abundant proteins showing longer than average half-lives. Fast turnover proteins had overall a higher frequency of PEST motifs than slow turnover proteins but no general correlation was observed between amino or carboxy terminal amino acid identities and turnover rates. A subset of proteins was identified that exist in pools with different turnover rates depending on their subcellular localization. This strongly correlated with subunits of large, multi-protein complexes, suggesting a general mechanism whereby their assembly is controlled in a different subcellular location to their main site of function.