Mass spectrometry-based methods for investigating the dynamics and organization of the surfaceome: exploring potential clinical implications

ABSTRACT

Introduction

Cell-surface proteins are extremely important for many cellular events, such as regulating cell-cell communication and cell-matrix interactions. Aberrant alterations in surface protein expression, modification (especially glycosylation), and interactions are directly related to human diseases. Systematic investigation of surface proteins advances our understanding of protein functions, cellular activities, and disease mechanisms, which will lead to identifying surface proteins as disease biomarkers and drug targets.

Areas covered

In this review, we summarize mass spectrometry (MS)-based proteomics methods for global analysis of cell-surface proteins. Then, investigations of the dynamics of surface proteins are discussed. Furthermore, we summarize the studies for the surfaceome interaction networks. Additionally, biological applications of MS-based surfaceome analysis are included, particularly highlighting the significance in biomarker identification, drug development, and immunotherapies.

Expert opinion

Modern MS-based proteomics provides an opportunity to systematically characterize proteins. However, due to the complexity of cell-surface proteins, the labor-intensive workflow, and the limit of clinical samples, comprehensive characterization of the surfaceome remains extraordinarily challenging, especially in clinical studies. Developing and optimizing surfaceome enrichment methods and utilizing automated sample preparation workflow can expand the applications of surfaceome analysis and deepen our understanding of the functions of cell-surface proteins.

Plain Language Summary

The cell surface contains many important proteins such as receptors and transporters. These proteins are responsible for cells to communicate with each other, take nutrients from outside, and interact with their surroundings. Aberrant changes in surface protein expression, modifications, and interactions with other molecules directly result in various diseases, including infections, immune disorders, and cancer. Currently, mass spectrometry (MS)-based proteomics is very powerful to study proteins on a large scale, and there has been a strong interest in employing MS to investigate cell-surface proteins. In this review, we discuss different methods combining mass spectrometry with other approaches to systematically characterize protein abundance, dynamics, modification, and interaction on the cell surface. These methods help uncover protein functions and specific cell-surface proteins related to human diseases. A better understanding of the functions and properties of cell-surface proteins can facilitate the discovery of surface proteins as effective biomarkers for disease early detection and the identification of drug targets for disease treatment.

KEYWORDS:

• Biomarker discovery
• cell-surface proteins
• enrichment methods
• protein dynamics
• protein glycosylation
• protein interactions
• MS-based proteomics

Article highlights

• Advancement of cell-surface protein enrichment methods allows for their systematic identification and quantification using MS-based proteomics.

• Profiling surface protein glycosylation is critical to understand protein functions and properties.

• Studying surface protein interaction networks uncovers receptors for orphan ligands, drug off-targets, signaling pathways, and protein complexes, shedding light on signal transduction mechanisms, and aiding in drug development.

• Promoting surfaceome studies in clinical practice requires further advancement in methodologies, instrumentation, bioinformatic tools, and the cultivation of interdisciplinary collaborations.

Declaration of interest

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Additional information

Funding

This work was supported by the National Institute of General Medical Sciences of the National Institutes of Health [R01GM118803 and R01GM127711].