Salivary metabolomics for cancer detection

ABSTRACT

Introduction: Saliva is an ideal biofluid that can be collected in a noninvasive manner, enabling safe and frequent screening of various diseases. Recent studies have revealed that salivary metabolomics analysis has the potential to detect both oral and systemic cancers.

Area covered: We reviewed the technical aspects, as well as applications, of salivary metabolomics for cancer detection. The topics include the effects of preconditioning and the method of sample collection, sample storage, processing, measurement, data analysis, and validation of the results. We also examined the rational relationship between salivary biomarkers and tumors distant from the oral cavity. A strategy to establish standard operating protocols for obtaining reproducible quantification data is also discussed

Expert opinion: Salivary metabolomics reflects oral and systematic health status, which potently enables cancer detection. The sensitivity and specificity of each marker and their combinations have been well evaluated, but a validation study is required. Further, the standard operating protocol for each procedure should be established to obtain reproducible data before clinical usage.

KEYWORDS:

• Biomarker
• cancer
• mass spectrometry
• metabolomics
• saliva

Article highlights

• The applications of salivary metabolomics to detect cancers are reviewed.

• The rational relationship between salivary biomarkers and tumors is reviewed.

• The technical aspects that need addressing to obtain the reproducible data are reviewed.

Declaration of interest

The author has 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, 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 paper was funded by A grant from the Program on Open Innovation Platform with Enterprises, Research Institutes and Academia (OPERA): JPMJOP1842; and Grants from Tsuruoka City and Yamagata Prefecture.