Mass Spectrometry-Based Proteomics Workflows in Cancer Research: The Relevance of Choosing the Right Steps

Other authors

Institut Català de la Salut

[Carrillo-Rodriguez P] Proteomics Unit of University of Bergen (PROBE), University of Bergen, Bergen, Norway. Vall d’Hebron Institute of Oncology (VHIO), Barcelona, Spain. [Selheim F] Proteomics Unit of University of Bergen (PROBE), University of Bergen, Bergen, Norway. [Hernandez-Valladares M] Proteomics Unit of University of Bergen (PROBE), University of Bergen, Bergen, Norway. Department of Physical Chemistry, University of Granada, Granada, Spain. Instituto de Investigación Biosanitaria ibs.GRANADA, Granada, Spain

Vall d'Hebron Barcelona Hospital Campus

Publication date

2023-03-01T11:48:36Z

2023-03-01T11:48:36Z

2023-01-16



Abstract

Mass spectrometry; Proteomics; Workflows


Espectrometría de masas; Proteómica; Flujos de trabajo


Espectrometria de masses; Proteòmica; Fluxos de treball


The qualitative and quantitative evaluation of proteome changes that condition cancer development can be achieved with liquid chromatography–mass spectrometry (LC-MS). LC-MS-based proteomics strategies are carried out according to predesigned workflows that comprise several steps such as sample selection, sample processing including labeling, MS acquisition methods, statistical treatment, and bioinformatics to understand the biological meaning of the findings and set predictive classifiers. As the choice of best options might not be straightforward, we herein review and assess past and current proteomics approaches for the discovery of new cancer biomarkers. Moreover, we review major bioinformatics tools for interpreting and visualizing proteomics results and suggest the most popular machine learning techniques for the selection of predictive biomarkers. Finally, we consider the approximation of proteomics strategies for clinical diagnosis and prognosis by discussing current barriers and proposals to circumvent them.


This research was funded by the Research Council of Norway INFRASTRUKTUR-program (project number: 295910).

Document Type

Article


Published version

Language

English

Publisher

MDPI

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Rights

Attribution 4.0 International

http://creativecommons.org/licenses/by/4.0/

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