Advancements in protein glycosylation biomarkers for ovarian cancer through mass spectrometry-based approaches

ABSTRACT

Introduction

Ovarian cancer, characterized by metastasis and reduced 5-year survival rates, stands as a substantial factor in the mortality of gynecological malignancies worldwide. The challenge of delayed diagnosis originates from vague early symptoms and the absence of efficient screening and diagnostic biomarkers for early cancer detection. Recent studies have explored the intricate interplay between ovarian cancer and protein glycosylation, unveiling the potential significance of glycosylation-oriented biomarkers.

Areas covered

This review examines the progress in glycosylation biomarker research, with particular emphasis on advances driven by mass spectrometry-based technologies. We document milestones achieved, discuss encountered limitations, and also highlight potential areas for future research and development of protein glycosylation biomarkers for ovarian cancer.

Expert opinion

The association of glycosylation in ovarian cancer is well known, but current research lacks desired sensitivity and specificity for early detection. Notably, investigations into protein-specific and site-specific glycoproteomics have the potential to significantly enhance our understanding of ovarian cancer and facilitate the identification of glycosylation-based biomarkers. Furthermore, the integration of advanced mass spectrometry techniques with AI-driven analysis and glycome databases holds the promise for revolutionizing biomarker discovery for ovarian cancer, ultimately transforming diagnosis and improving patient outcomes.

KEYWORDS:

• Biomarker
• glycosylation
• mass spectrometry
• ovarian cancer
• omics

Article highlights

• Ovarian cancer continues to be a leading contributor to the mortality rate of women affected by gynecological malignancies worldwide.

• The absence of efficient screening methods and early detection approaches capable of identifying ovarian cancer in its initial phases, prior to the emergence of overt symptoms, represents a crucial gap in endeavors to reduce the fatalities linked to delayed-stage diagnosis.

• Currently, clinically approved blood-based biomarkers for ovarian cancer (including CA125, HE4, and the OVA1 test) primarily consist of glycoproteins, but these markers have limited sensitivity and specificity and are not suitable for early diagnosis.

• This review focuses on MS-based analytical techniques to comprehensively assess protein glycosylation patterns in ovarian cancer, enabling the identification and quantification of compositional, structural, and linkage aspects.

• The MS techniques investigated in this study encompass MALDI-TOF, CE-MS, LC/MS, and MSI, which have been applied to the analysis of clinical specimens such as serum, plasma, ascites, and tissue, each presenting its own set of merits and limitations.

• We outline significant accomplishments attained in the continuous exploration of ovarian cancer biomarkers, delineate encountered methodological and technological obstacles, and elucidate potential forthcoming breakthroughs.

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 material discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or mending, or royalties.

Reviewer disclosures

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

Additional information

Funding

This research was supported by the Commercialization Promotion Agency for R&D Outcomes (COMPA) funded by the Ministry of Science and ICT(MSIT) [2023-23020001-11, R&D Equipment Engineer Education Program].