Literature DB >> 29785737

Clinical Proteomics: Closing the Gap from Discovery to Implementation.

Maria Frantzi1, Agnieszka Latosinska1, Georgia Kontostathi2, Harald Mischak1.   

Abstract

Clinical proteomics, the application of proteome analysis to serve a clinical purpose, represents a major field in the area of proteome research. Over 1000 manuscripts on this topic are published each year, with numbers continuously increasing. However, the anticipated outcome, the transformation of the reported findings into improvements in patient management, is not immediately evident. In this article, the value and validity of selected clinical proteomics findings are investigated, and it is assessed how far implementation has progressed. A main conclusion from this assessment is that to achieve implementation, well-powered clinical studies are required in the appropriate population, addressing a specific clinical need and with a clear context-of-use. Efforts toward implementation, to be feasible, must be supported by the key players in science: publishers and funders. The authors propose a change on objectives, from additional discovery studies toward studies aiming at validation of the plethora of potential biomarkers that have been described, to demonstrate practical value of clinical proteomics. All elements required, potential biomarkers, technologies, and bio-banked samples are available (based on today's literature), hence a change in focus from discovery toward validation and application is not only urgently necessary, but also possible based on resources available today.
© 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Entities:  

Keywords:  biomarkers; drug targets; mass spectrometry; personalized medicine; proteomics

Mesh:

Substances:

Year:  2018        PMID: 29785737     DOI: 10.1002/pmic.201700463

Source DB:  PubMed          Journal:  Proteomics        ISSN: 1615-9853            Impact factor:   3.984


  2 in total

Review 1.  Promise and Implementation of Proteomic Prostate Cancer Biomarkers.

Authors:  Agnieszka Latosinska; Maria Frantzi; Axel S Merseburger; Harald Mischak
Journal:  Diagnostics (Basel)       Date:  2018-08-29

2.  ProtRank: bypassing the imputation of missing values in differential expression analysis of proteomic data.

Authors:  Matúš Medo; Daniel M Aebersold; Michaela Medová
Journal:  BMC Bioinformatics       Date:  2019-11-09       Impact factor: 3.169

  2 in total

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