Positional proteomics: is the technology ready to study clinical cohorts?

ABSTRACT

Introduction

Positional proteomics provides proteome-wide information on protein termini and their modifications, uniquely enabling unambiguous identification of site-specific, limited proteolysis. Such proteolytic cleavage irreversibly modifies protein sequences resulting in new proteoforms with distinct protease-generated neo-N and C-termini and altered localization and activity. Misregulated proteolysis is implicated in a wide variety of human diseases. Protein termini, therefore, constitute a huge, largely unexplored source of specific analytes that provides a deep view into the functional proteome and a treasure trove for biomarkers.

Areas covered

We briefly review principal approaches to define protein termini and discuss recent advances in method development. We further highlight the potential of positional proteomics to identify and trace specific proteoforms, with a focus on proteolytic processes altered in disease. Lastly, we discuss current challenges and potential for applying positional proteomics in biomarker and pre-clinical research.

Expert opinion

Recent developments in positional proteomics have provided significant advances in sensitivity and throughput. In-depth analysis of proteolytic processes in clinical cohorts thus appears feasible in the near future. We argue that this will provide insights into the functional state of the proteome and offer new opportunities to utilize proteolytic processes altered or targeted in disease as specific diagnostic, prognostic and companion biomarkers.

KEYWORDS:

• Positional proteomics
• proteoform
• HUNTER
• degradomics
• terminomics
• biomarker
• proteolysis

Article highlights

• Positional proteomics enables proteome-wide analysis of protein termini and their modifications

• Protein termini reveal unique information on proteolytic proteoforms

• This provides unique information on the functional state of the proteome

• Recent advances in positional proteomics tremendously increased sensitivity and throughput

• Termini-centric analysis of clinical cohorts is now feasible and valuable

Declaration of interest

O Schilling has received research grants from Hoffman La-Roche and Bayer and is co-applicant of two relevant patent filings (PCT/EP2022/060059; PCT/EP2022/081262). The authors have no other 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 apart from those disclosed.

Reviewer disclosures

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

Author contributions

PF Lange and PF Huesgen conceived the review and wrote the initial draft; all authors contributed content and edited the final version.

Additional information

Funding

This paper was funded by the Deutsche Forschungsgemeinschaft (DFG, project 517812866 to P.F.H. and projects 441891347 - SFB 1479 “OncoEscape”, 423813989 - GRK 2606 “ProtPath”, 322977937 - GRK 2344 “MeInBio” to O.S.), the Canadian Institutes for Health Research (PJT-169190 to P.F.L.), the Canada Research Chairs Program (CRC-RS 950-230867 to P.F.L.), the Michael Smith Foundation for Health Research Scholar Program (MSFHR-SA-16442 to P.F.L.), the Michael Cuccione Foundation (MCF to P.F.L.) and the BC Children’s Hospital Foundation through the Better Responses through Avatars and Evidence (BRAVE) Initiative (to P.F.L.)