ABSTRACT
Introduction: Diagnosis of hepatocellular carcinoma (HCC) is important for improving the survival rate and selecting the optimum therapeutic option. However, some patients with HCC are not diagnosed until after symptoms appear, when the tumor is already advanced. Thus, biomarkers associated with HCC and novel diagnostic methods are required to improve the diagnosis of HCC. Mass spectrometry (MS) is one of the most widely used analytical tools in proteomic research. Furthermore, tandem MS (MS/MS) has been applied for the discovery and verification of protein biomarkers for clinical use.
Areas covered: We review candidate glycoprotein biomarkers, including their aberrant glycosylation discovered by MS-based proteomics techniques and their diagnostic strategies using human blood samples. Finally, we discuss the limitations and prospects of MS-based approaches for clinical applications.
Expert commentary: The development of biomarkers with high sensitivity and specificity is essential for optimizing the management of HCC. Various glycoprotein biomarkers of HCC have been identified using MS-based techniques. MS-based assays will continue to play an important role in clinical applications for discovery and verification of biomarkers. Furthermore, combination of multibiomarker, improvements in sample enrichment and the development of highly sensitive MS methods will facilitate more rapid adoption of MS for the diagnosis of HCC.
Article highlights
Diagnosis of hepatocellular carcinoma (HCC) is essential for selection of the optimum therapeutic strategy, and to increase the survival rate.
Proteomics has been applied to the discovery of protein biomarkers of HCC.
MS-based analysis has potential for the discovery and verification of biomarkers of HCC.
Targeted MS methods, such as MRM and PRM, have been used to quantify protein biomarkers with high sensitively and selectivity.
Altered fucosylation of serum and plasma proteins is closely related to HCC and has potential as a biomarker of HCC.
MS-based protein assays with improved analytical sensitivity and advanced sample preparation techniques will be useful for clinical applications.
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.