A Sequence-specific Exopeptidase Activity Test (SSEAT) for âFunctionalâ Biomarker Discovery
One form of functional proteomics entails profiling of genuine activities, as opposed to surrogates of activity or active âstates,â in a complex biological matrix: for example, tracking enzyme-catalyzed changes, in real time, ranging from simple modifications to complex anabolic or catabolic rea...
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Veröffentlicht in: | Molecular & cellular proteomics 2008-03, Vol.7 (3), p.509 |
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container_title | Molecular & cellular proteomics |
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creator | Josep Villanueva Arpi Nazarian Kevin Lawlor San San Yi Richard J. Robbins Paul Tempst |
description | One form of functional proteomics entails profiling of genuine activities, as opposed to surrogates of activity or active
âstates,â in a complex biological matrix: for example, tracking enzyme-catalyzed changes, in real time, ranging from simple
modifications to complex anabolic or catabolic reactions. Here we present a test to compare defined exoprotease activities
within individual proteomes of two or more groups of biological samples. It tracks degradation of artificial substrates, under
strictly controlled conditions, using semiautomated MALDI-TOF mass spectrometric analysis of the resulting patterns. Each
fragment is quantitated by comparison with double labeled, non-degradable internal standards (all- d -amino acid peptides) spiked into the samples at the same time as the substrates to reflect adsorptive and processing-related
losses. The full array of metabolites is then quantitated (coefficients of variation of 6.3â14.3% over five replicates) and
subjected to multivariate statistical analysis. Using this approach, we tested serum samples of 48 metastatic thyroid cancer
patients and 48 healthy controls, with selected peptide substrates taken from earlier standard peptidomics screens ( i.e. the âdiscoveryâ phase), and obtained class predictions with 94% sensitivity and 90% specificity without prior feature selection
(24 features). The test all but eliminates reproducibility problems related to sample collection, storage, and handling as
well as to possible variability in endogenous peptide precursor levels because of hemostatic alterations in cancer patients. |
doi_str_mv | 10.1074/mcp.M700397-MCP200 |
format | Article |
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âstates,â in a complex biological matrix: for example, tracking enzyme-catalyzed changes, in real time, ranging from simple
modifications to complex anabolic or catabolic reactions. Here we present a test to compare defined exoprotease activities
within individual proteomes of two or more groups of biological samples. It tracks degradation of artificial substrates, under
strictly controlled conditions, using semiautomated MALDI-TOF mass spectrometric analysis of the resulting patterns. Each
fragment is quantitated by comparison with double labeled, non-degradable internal standards (all- d -amino acid peptides) spiked into the samples at the same time as the substrates to reflect adsorptive and processing-related
losses. The full array of metabolites is then quantitated (coefficients of variation of 6.3â14.3% over five replicates) and
subjected to multivariate statistical analysis. Using this approach, we tested serum samples of 48 metastatic thyroid cancer
patients and 48 healthy controls, with selected peptide substrates taken from earlier standard peptidomics screens ( i.e. the âdiscoveryâ phase), and obtained class predictions with 94% sensitivity and 90% specificity without prior feature selection
(24 features). The test all but eliminates reproducibility problems related to sample collection, storage, and handling as
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âstates,â in a complex biological matrix: for example, tracking enzyme-catalyzed changes, in real time, ranging from simple
modifications to complex anabolic or catabolic reactions. Here we present a test to compare defined exoprotease activities
within individual proteomes of two or more groups of biological samples. It tracks degradation of artificial substrates, under
strictly controlled conditions, using semiautomated MALDI-TOF mass spectrometric analysis of the resulting patterns. Each
fragment is quantitated by comparison with double labeled, non-degradable internal standards (all- d -amino acid peptides) spiked into the samples at the same time as the substrates to reflect adsorptive and processing-related
losses. The full array of metabolites is then quantitated (coefficients of variation of 6.3â14.3% over five replicates) and
subjected to multivariate statistical analysis. Using this approach, we tested serum samples of 48 metastatic thyroid cancer
patients and 48 healthy controls, with selected peptide substrates taken from earlier standard peptidomics screens ( i.e. the âdiscoveryâ phase), and obtained class predictions with 94% sensitivity and 90% specificity without prior feature selection
(24 features). The test all but eliminates reproducibility problems related to sample collection, storage, and handling as
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âstates,â in a complex biological matrix: for example, tracking enzyme-catalyzed changes, in real time, ranging from simple
modifications to complex anabolic or catabolic reactions. Here we present a test to compare defined exoprotease activities
within individual proteomes of two or more groups of biological samples. It tracks degradation of artificial substrates, under
strictly controlled conditions, using semiautomated MALDI-TOF mass spectrometric analysis of the resulting patterns. Each
fragment is quantitated by comparison with double labeled, non-degradable internal standards (all- d -amino acid peptides) spiked into the samples at the same time as the substrates to reflect adsorptive and processing-related
losses. The full array of metabolites is then quantitated (coefficients of variation of 6.3â14.3% over five replicates) and
subjected to multivariate statistical analysis. Using this approach, we tested serum samples of 48 metastatic thyroid cancer
patients and 48 healthy controls, with selected peptide substrates taken from earlier standard peptidomics screens ( i.e. the âdiscoveryâ phase), and obtained class predictions with 94% sensitivity and 90% specificity without prior feature selection
(24 features). The test all but eliminates reproducibility problems related to sample collection, storage, and handling as
well as to possible variability in endogenous peptide precursor levels because of hemostatic alterations in cancer patients.</abstract><pub>American Society for Biochemistry and Molecular Biology</pub><pmid>17986438</pmid><doi>10.1074/mcp.M700397-MCP200</doi></addata></record> |
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source | EZB-FREE-00999 freely available EZB journals; PubMed Central; Alma/SFX Local Collection; Free Full-Text Journals in Chemistry |
title | A Sequence-specific Exopeptidase Activity Test (SSEAT) for âFunctionalâ Biomarker Discovery |
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