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Title: | Towards Building a Quantitative Proteomics Toolbox in Precision Medicine: A Mini-Review | Authors: | CORREA ROJO, Alejandro HEYLEN, Dries AERTS, Jan THAS, Olivier HOOYBERGHS, Jef Ertaylan, Gokhan VALKENBORG, Dirk |
Issue Date: | 2021 | Publisher: | FRONTIERS MEDIA SA | Source: | FRONTIERS IN PHYSIOLOGY, 12 (Art N° 723510) | Abstract: | Precision medicine as a framework for disease diagnosis, treatment, and prevention at the molecular level has entered clinical practice. From the start, genetics has been an indispensable tool to understand and stratify the biology of chronic and complex diseases in precision medicine. However, with the advances in biomedical and omics technologies, quantitative proteomics is emerging as a powerful technology complementing genetics. Quantitative proteomics provide insight about the dynamic behaviour of proteins as they represent intermediate phenotypes. They provide direct biological insights into physiological patterns, while genetics accounting for baseline characteristics. Additionally, it opens a wide range of applications in clinical diagnostics, treatment stratification, and drug discovery. In this mini-review, we discuss the current status of quantitative proteomics in precision medicine including the available technologies and common methods to analyze quantitative proteomics data. Furthermore, we highlight the current challenges to put quantitative proteomics into clinical settings and provide a perspective to integrate proteomics data with genomics data for future applications in precision medicine.</p> | Notes: | Rojo, AC; Valkenborg, D (corresponding author), Hasselt Univ, Interuniv Inst Biostat & Stat Bioinformat I BioSt, Data Sci Inst, Diepenbeek, Belgium.; Rojo, AC; Ertaylan, G (corresponding author), Flemish Inst Technol Res VITO, Mol, Belgium. alejandro.correarojo@uhasselt.be; gokhan.ertaylan@vito.be; dirk.valkenborg@uhasselt.be |
Keywords: | precision medicine;quantitative proteomics;targeted techniques;bioinformatics;biomarker discovery;clinical diagnostics;protein quantitative trait loci | Document URI: | http://hdl.handle.net/1942/35764 | e-ISSN: | 1664-042X | DOI: | 10.3389/fphys.2021.723510 | ISI #: | WOS:000698616400001 | Rights: | open access | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2022 |
Appears in Collections: | Research publications |
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fphys-12-723510.pdf | Published version | 629.47 kB | Adobe PDF | View/Open |
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