Literature DB >> 17986438

A sequence-specific exopeptidase activity test (SSEAT) for "functional" biomarker discovery.

Josep Villanueva1, Arpi Nazarian, Kevin Lawlor, San San Yi, Richard J Robbins, Paul Tempst.   

Abstract

One form of functional proteomics entails profiling of genuine activities, as opposed to surrogates of activity or active "states," 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 6.3-14.3% 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 "discovery" 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.

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Year:  2007        PMID: 17986438     DOI: 10.1074/mcp.M700397-MCP200

Source DB:  PubMed          Journal:  Mol Cell Proteomics        ISSN: 1535-9476            Impact factor:   5.911


  26 in total

1.  Super-SILAC for tumors and tissues.

Authors:  Thomas A Neubert; Paul Tempst
Journal:  Nat Methods       Date:  2010-05       Impact factor: 28.547

2.  Sampling the N-terminal proteome of human blood.

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3.  Discovery proteomics and nonparametric modeling pipeline in the development of a candidate biomarker panel for dengue hemorrhagic fever.

Authors:  Allan R Brasier; Josefina Garcia; John E Wiktorowicz; Heidi M Spratt; Guillermo Comach; Hyunsu Ju; Adrian Recinos; Kizhake Soman; Brett M Forshey; Eric S Halsey; Patrick J Blair; Claudio Rocha; Isabel Bazan; Sundar S Victor; Zheng Wu; Susan Stafford; Douglas Watts; Amy C Morrison; Thomas W Scott; Tadeusz J Kochel
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4.  Robust substrate profiling method reveals striking differences in specificities of serum and lung fluid proteases.

Authors:  Douglas S Watson; Kalyani Jambunathan; David S Askew; Krishna Kodukula; Amit K Galande
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5.  Strategy for degradomic-peptidomic analysis of human blood plasma.

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Review 6.  Proteomic contributions to personalized cancer care.

Authors:  John M Koomen; Eric B Haura; Gerold Bepler; Rebecca Sutphen; Elizabeth R Remily-Wood; Kaaron Benson; Mohamad Hussein; Lori A Hazlehurst; Timothy J Yeatman; Lynne T Hildreth; Thomas A Sellers; Paul B Jacobsen; David A Fenstermacher; William S Dalton
Journal:  Mol Cell Proteomics       Date:  2008-07-29       Impact factor: 5.911

7.  Monitoring peptidase activities in complex proteomes by MALDI-TOF mass spectrometry.

Authors:  Josep Villanueva; Arpi Nazarian; Kevin Lawlor; Paul Tempst
Journal:  Nat Protoc       Date:  2009-07-23       Impact factor: 13.491

8.  Inhibition of circulating dipeptidyl peptidase 4 activity in patients with metastatic prostate cancer.

Authors:  Arpi Nazarian; Kevin Lawlor; San San Yi; John Philip; Mousumi Ghosh; Mariana Yaneva; Josep Villanueva; Alan Saghatelian; Melissa Assel; Andrew J Vickers; James A Eastham; Howard I Scher; Brett S Carver; Hans Lilja; Paul Tempst
Journal:  Mol Cell Proteomics       Date:  2014-07-23       Impact factor: 5.911

9.  Proteomic analyses of pancreatic cyst fluids.

Authors:  Eileen Ke; Bhavinkumar B Patel; Tiffany Liu; Xin-Ming Li; Oleh Haluszka; John P Hoffman; Hormoz Ehya; Nancy A Young; James C Watson; David S Weinberg; Minhhuyen T Nguyen; Steven J Cohen; Neal J Meropol; Samuel Litwin; Jeffrey L Tokar; Anthony T Yeung
Journal:  Pancreas       Date:  2009-03       Impact factor: 3.327

10.  Prediction of outcome of non-small cell lung cancer patients treated with chemotherapy and bortezomib by time-course MALDI-TOF-MS serum peptide profiling.

Authors:  Johannes Voortman; Thang V Pham; Jaco C Knol; Giuseppe Giaccone; Connie R Jimenez
Journal:  Proteome Sci       Date:  2009-09-03       Impact factor: 2.480

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