Utilizing the circulating tumor markers in diagnosis and management of medullary thyroid cancer

Medullary thyroid cancer (MTC) is the third frequent subtype of thyroid cancer-driving from thyroid C-cells. The first-line strategy to treat MTC is surgery, but tumor recurrence and patients' mortality rate have still been demonstrated in approximately 4-10% of MTC cases. Therefore, to treat and prevent the progressive form of the disease, the early diagnosis of MTC is assumed to play a critical role. In this regard, recently, circulating biomarkers have drawn researchers' attention for their nonaggressive manners in the sample collection. In this systematic review, we aimed to focus on circulating biomarkers and their applications in MTC diagnosis, prognosis and follow-up, and we discussed their clinical application and how they can affect clinical decision making in the future. A literature search (from 2000 to 2021) was accomplished on MTC circulating biomarkers in different databases, and only English articles were evaluated. We found that calcitonin (CT) and carcinoembryonic antigen (CEA) are the most important circulating biomarkers in the MTC diagnosis. Other circulating biomarkers included pro-calcitonin (Pro-CT), pro-Gastrin releasing peptide (Pro-GRP), carbohydrate antigen 19-9 (CA 19-9) and chromogranin A (CgA). Some novel circulating biomarkers comprised vaspin and retinol-binding protein-4 (RBP4), myostatin, tumor cells (CTCs), RET M918T mutated cfDNA, circulating tumor DNA (ctDNA), miR-375 and Alu83 and Alu244 cfDNAs. Several circulating biomarkers have been identified to optimize the accuracy of diagnosis and offer new prognostic criteria, which should be verified before any clinical application. Although different circulating biomarkers contributed to MTC have been discovered, a few of them could be used in clinical diagnosis. In many cases, the application of each marker may not be useful lonely; therefore, a combination of two or more biomarkers could open a new avenue in the diagnosis, prognosis and prediction of MTC.