Background: Thyroid cancer (TC) is the most common formof endocrine system malignancy. This type of cancer may becaused by the accumulation of a variety of genetic and epigeneticchanges that lead to the activation of certain oncogenesand the inactivation of tumor suppressor genes. Having a backgroundof goiter, benign nodules, or childhood exposure toradiation are significant risk factors for developing TC. Fineneedle aspiration biopsy (FNAB) under ultrasound control followedby cytological evaluation is a commonly employed andefficient method for TC diagnosis. However, around ۱۵-۳۰%of FNABs have low accuracy and reliability due to their inabilityto differentiate between benign and malignant lesions.In contrast to FNAB,
OMICS tools are powerful and widelyconsidered effective methods in cancer research. These includegenomics, transcriptomics, proteomics, and metabolomics,which can quantify all genes mutation, genes expression, proteinslevel, and metabolites concentration in various biologicalsamples. This study provides a brief glance into the applicationof metabolomics in TC diagnosis.Materials and Methods: A literature search was carried out onGoogle Scholar and PubMed, then high quality articles (n=۲۰)in a wide time-frame from ۲۰۰۰ to ۲۰۲۳ were reviewed.Results: Among all OMICS, metabolomics is the latest emergingform that has the potential to advance a new understandingof TC phenotypic changes caused by genetic and/or environmentalinfluences. Two major methods of metabolomics approachcan be utilized for TC diagnosis are nuclear magneticresonance spectroscopy and mass spectrometry combinedwith gas chromatography or liquid chromatography. These approachesenable the measurement of metabolites in biologicalsamples of patients with TC in a quantitative manner. In thisway, metabolites can be used in the diagnosis and classificationof thyroid tumors and they can be called as new molecularbiomarkers.Conclusion:
Metabolomics of TC is expected to make significantprogress, resulting in the identification of useful diagnosticbiomarkers.