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Current strategies and findings in clinically relevant post-translational modification-specific proteomics.

Pagel O, Loroch S, Sickmann A, Zahedi RP - Expert Rev Proteomics (2015)

Bottom Line: Thus, quantitative proteomics holds a great potential to discover, validate and accurately quantify biomarkers in body fluids and primary tissues.A major effort will be to improve the complete integration of robust but sensitive proteomics technology to clinical environments.Here, we discuss PTMs that are relevant for clinical research, with a focus on phosphorylation, glycosylation and proteolytic cleavage; furthermore, we give an overview on the current developments and novel findings in mass spectrometry-based PTM research.

View Article: PubMed Central - PubMed

Affiliation: Leibniz-Institut für Analytische Wissenschaften - ISAS - e.V., Otto-Hahn-Straße 6b, 44227 Dortmund, Germany.

ABSTRACT
Mass spectrometry-based proteomics has considerably extended our knowledge about the occurrence and dynamics of protein post-translational modifications (PTMs). So far, quantitative proteomics has been mainly used to study PTM regulation in cell culture models, providing new insights into the role of aberrant PTM patterns in human disease. However, continuous technological and methodical developments have paved the way for an increasing number of PTM-specific proteomic studies using clinical samples, often limited in sample amount. Thus, quantitative proteomics holds a great potential to discover, validate and accurately quantify biomarkers in body fluids and primary tissues. A major effort will be to improve the complete integration of robust but sensitive proteomics technology to clinical environments. Here, we discuss PTMs that are relevant for clinical research, with a focus on phosphorylation, glycosylation and proteolytic cleavage; furthermore, we give an overview on the current developments and novel findings in mass spectrometry-based PTM research.

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Using the classical t-test for biomarker research. Two simulated markers 1 and 2 (A) in a background of an iTRAQ-based phosphoproteomics experiment (B, C). Using the two-sample t-test, the not-promising marker 2 would be defined as significant, whereas marker 1 would not be considered. Using the moderated t-test provided in the Limma package [92,89,93], only the promising marker 1 remains significant. A detailed description for the use of this package was recently published by Kammers et al.[86].
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Figure 0003: Using the classical t-test for biomarker research. Two simulated markers 1 and 2 (A) in a background of an iTRAQ-based phosphoproteomics experiment (B, C). Using the two-sample t-test, the not-promising marker 2 would be defined as significant, whereas marker 1 would not be considered. Using the moderated t-test provided in the Limma package [92,89,93], only the promising marker 1 remains significant. A detailed description for the use of this package was recently published by Kammers et al.[86].

Mentions: Therefore, choosing appropriate normalization methods and statistical tests is a major concern directly affecting the final selection of candidates. The often used two-sample t-test to estimate whether a regulation can be considered as significant or not has some inherent drawbacks, since it takes into account both the fold-change and the estimated variance of each potential candidate. If the sample size is small (n ≤ 5), estimation of the variance is quite uncertain. Consequently, the t-test often declares strongly regulated hits with a high variance as ‘not significant’ [86]. Figure 3 demonstrates how decisions for potentially regulated candidates would be made on the basis of a two-sample t-test (two-sided, unequal variance) for two simulated markers in an experiment with n = 3 (3 patients vs 3 controls). Marker 1 exhibits a clear fold-change (3.2-fold), but also a high variance, and thus would be rejected at a 5% confidence level. In contrast, marker 2 does not exhibit a biologically significant regulation (1.1-fold), but the low variance would render it ‘significant’ at a 5% confidence level. Thus, decisions should not be made merely based on p-values resulting from a two-sample t-test.


Current strategies and findings in clinically relevant post-translational modification-specific proteomics.

Pagel O, Loroch S, Sickmann A, Zahedi RP - Expert Rev Proteomics (2015)

Using the classical t-test for biomarker research. Two simulated markers 1 and 2 (A) in a background of an iTRAQ-based phosphoproteomics experiment (B, C). Using the two-sample t-test, the not-promising marker 2 would be defined as significant, whereas marker 1 would not be considered. Using the moderated t-test provided in the Limma package [92,89,93], only the promising marker 1 remains significant. A detailed description for the use of this package was recently published by Kammers et al.[86].
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4487610&req=5

Figure 0003: Using the classical t-test for biomarker research. Two simulated markers 1 and 2 (A) in a background of an iTRAQ-based phosphoproteomics experiment (B, C). Using the two-sample t-test, the not-promising marker 2 would be defined as significant, whereas marker 1 would not be considered. Using the moderated t-test provided in the Limma package [92,89,93], only the promising marker 1 remains significant. A detailed description for the use of this package was recently published by Kammers et al.[86].
Mentions: Therefore, choosing appropriate normalization methods and statistical tests is a major concern directly affecting the final selection of candidates. The often used two-sample t-test to estimate whether a regulation can be considered as significant or not has some inherent drawbacks, since it takes into account both the fold-change and the estimated variance of each potential candidate. If the sample size is small (n ≤ 5), estimation of the variance is quite uncertain. Consequently, the t-test often declares strongly regulated hits with a high variance as ‘not significant’ [86]. Figure 3 demonstrates how decisions for potentially regulated candidates would be made on the basis of a two-sample t-test (two-sided, unequal variance) for two simulated markers in an experiment with n = 3 (3 patients vs 3 controls). Marker 1 exhibits a clear fold-change (3.2-fold), but also a high variance, and thus would be rejected at a 5% confidence level. In contrast, marker 2 does not exhibit a biologically significant regulation (1.1-fold), but the low variance would render it ‘significant’ at a 5% confidence level. Thus, decisions should not be made merely based on p-values resulting from a two-sample t-test.

Bottom Line: Thus, quantitative proteomics holds a great potential to discover, validate and accurately quantify biomarkers in body fluids and primary tissues.A major effort will be to improve the complete integration of robust but sensitive proteomics technology to clinical environments.Here, we discuss PTMs that are relevant for clinical research, with a focus on phosphorylation, glycosylation and proteolytic cleavage; furthermore, we give an overview on the current developments and novel findings in mass spectrometry-based PTM research.

View Article: PubMed Central - PubMed

Affiliation: Leibniz-Institut für Analytische Wissenschaften - ISAS - e.V., Otto-Hahn-Straße 6b, 44227 Dortmund, Germany.

ABSTRACT
Mass spectrometry-based proteomics has considerably extended our knowledge about the occurrence and dynamics of protein post-translational modifications (PTMs). So far, quantitative proteomics has been mainly used to study PTM regulation in cell culture models, providing new insights into the role of aberrant PTM patterns in human disease. However, continuous technological and methodical developments have paved the way for an increasing number of PTM-specific proteomic studies using clinical samples, often limited in sample amount. Thus, quantitative proteomics holds a great potential to discover, validate and accurately quantify biomarkers in body fluids and primary tissues. A major effort will be to improve the complete integration of robust but sensitive proteomics technology to clinical environments. Here, we discuss PTMs that are relevant for clinical research, with a focus on phosphorylation, glycosylation and proteolytic cleavage; furthermore, we give an overview on the current developments and novel findings in mass spectrometry-based PTM research.

Show MeSH