Literature DB >> 16901203

Studying multiple protein profiles over time to assess biomarker validity.

Raj S Kasthuri1, Michael R Verneris, Hassan N Ibrahim, Bernd Jilma, Gary L Nelsestuen.   

Abstract

Protein profile analysis is increasingly used for identification of disease biomarkers. The approaches vary from surface-enhanced laser desorption/ionization to protein arrays. Newer platforms are constantly being developed. Almost all are based on matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and are often coupled with sophisticated software tools. Protein profiling has been applied to a variety of samples including plasma, urine, cerebrospinal fluid, saliva and solid tissue. This article focuses on those instances where it is possible to obtain sequential samples from the same individual. In the authors use of a profile method, many protein changes with highly significant correlations to disease have been found. The main challenge lies in the validation of the marker to demonstrate its adequacy for use in the clinical setting. The latter requires a methodology that is robust and amenable to high-throughput. One problem is that interindividual variability among the healthy population can mask major changes that occur on an intraindividual basis. Often, a large change for an individual may remain within the range of healthy individuals. Thus, one strategy to optimize biomarker discovery is to examine serial samples from a given individual, where a disease biomarker is established by comparison with the individual's own baseline sample. The focus of this review is to illustrate the principle and value of serial protein profiling using a rapid protein extraction method.

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Year:  2006        PMID: 16901203     DOI: 10.1586/14789450.3.4.455

Source DB:  PubMed          Journal:  Expert Rev Proteomics        ISSN: 1478-9450            Impact factor:   3.940


  5 in total

Review 1.  Personalized medicine beyond genomics: alternative futures in big data-proteomics, environtome and the social proteome.

Authors:  Vural Özdemir; Edward S Dove; Ulvi K Gürsoy; Semra Şardaş; Arif Yıldırım; Şenay Görücü Yılmaz; I Ömer Barlas; Kıvanç Güngör; Alper Mete; Sanjeeva Srivastava
Journal:  J Neural Transm (Vienna)       Date:  2015-12-08       Impact factor: 3.575

2.  Temporal stability of the urinary proteome after kidney transplant: more sensitive than protein composition?

Authors:  Sanjeev K Akkina; Yan Zhang; Gary L Nelsestuen; William S Oetting; Hassan N Ibrahlm
Journal:  J Proteome Res       Date:  2009-01       Impact factor: 4.466

3.  Urinary Peptide patterns in native kidneys and kidney allografts.

Authors:  Yan Zhang; William S Oetting; Stephen B Harvey; Matthew D Stone; Teresa Monkkonen; Arthur J Matas; Fernando G Cosio; Gary L Nelsestuen
Journal:  Transplantation       Date:  2009-06-27       Impact factor: 4.939

Review 4.  An odyssey of islet transplantation for therapy of type 1 diabetes.

Authors:  Garth L Warnock; Yu Huan Theresa Liao; Xiaojie Wang; Dawei Ou; Ziliang Ao; James D Johnson; C B Verchere; David Thompson
Journal:  World J Surg       Date:  2007-06-12       Impact factor: 3.282

5.  Monitoring of Serial Presurgical and Postsurgical Changes in the Serum Proteome in a Series of Patients with Calcific Aortic Stenosis.

Authors:  Kazumi Satoh; Kazuo Yamada; Tomoko Maniwa; Teiji Oda; Ken-ichi Matsumoto
Journal:  Dis Markers       Date:  2015-05-20       Impact factor: 3.434

  5 in total

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