Title (eng)

Spatial Proteomics for the Molecular Characterization of Breast Cancer

Author

Klára Brožová   University of Veterinary Medicine Vienna / Medical University of Vienna

Klaus Kratochwillv   Medical University of Vienna

Brigitte Hantusch   Medical University of Vienna

Lukas Kenner   University of Veterinary Medicine Vienna / Medical University of Vienna / CBmed GmbH-Center for Biomarker Research in Medicine

Publishing

MDPI

Description (eng)

Breast cancer (BC) is a major global health issue, affecting a significant proportion of the female population and contributing to high rates of mortality. One of the primary challenges in the treatment of BC is the disease's heterogeneity, which can lead to ineffective therapies and poor patient outcomes. Spatial proteomics, which involves the study of protein localization within cells, offers a promising approach for understanding the biological processes that contribute to cellular heterogeneity within BC tissue. To fully leverage the potential of spatial proteomics, it is critical to identify early diagnostic biomarkers and therapeutic targets, and to understand protein expression levels and modifications. The subcellular localization of proteins is a key factor in their physiological function, making the study of subcellular localization a major challenge in cell biology. Achieving high resolution at the cellular and subcellular level is essential for obtaining an accurate spatial distribution of proteins, which in turn can enable the application of proteomics in clinical research. In this review, we present a comparison of current methods of spatial proteomics in BC, including untargeted and targeted strategies. Untargeted strategies enable the detection and analysis of proteins and peptides without a predetermined molecular focus, whereas targeted strategies allow the investigation of a predefined set of proteins or peptides of interest, overcoming the limitations associated with the stochastic nature of untargeted proteomics. By directly comparing these methods, we aim to provide insights into their strengths and limitations and their potential applications in BC research.

Object languages

English

Date

2023

Rights

This work is licensed under a
CC BY 4.0 - Creative Commons Attribution 4.0 International License.

CC BY 4.0 International

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

Classification

Desorption/Ionization-Mass-Spectrometry; Potential Biomarkers; Sample Preparation; Estrogen-Receptor; Cell Variability; Laser-Desorption; Tissue; Tumor; Proteins; Pathway

Member of the Collection(s) (1)