Extracellular Vesicles from Thyroid Carcinoma: The New Frontier of Liquid Biopsy

Int J Mol Sci. 2019 Mar 5;20(5):1114. doi: 10.3390/ijms20051114.

Abstract

The diagnostic approach to thyroid cancer is one of the most challenging issues in oncology of the endocrine system because of its high incidence (3.8% of all new cancer cases in the US) and the difficulty to distinguish benign from malignant non-functional thyroid nodules and establish the cervical lymph node involvement during staging. Routine diagnosis of thyroid nodules usually relies on a fine-needle aspirate biopsy, which is invasive and often inaccurate. Therefore, there is an urgent need to identify novel, accurate, and non-invasive diagnostic procedures. Liquid biopsy, as a non-invasive approach for the detection of diagnostic biomarkers for early tumor diagnosis, prognosis, and disease monitoring, may be of particular benefit in this context. Extracellular vesicles (EVs) are a consistent source of tumor-derived RNA due to their prevalence in circulating bodily fluids, the well-established isolation protocols, and the fact that RNA in phospholipid bilayer-enclosed vesicles is protected from blood-borne RNases. Recent results in other types of cancer, including our recent study on plasma EVs from glioblastoma patients suggest that information derived from analysis of EVs from peripheral blood plasma can be integrated in the routine diagnostic tumor approach. In this review, we will examine the diagnostic and prognostic potential of liquid biopsy to detect tumor-derived nucleic acids in circulating EVs from patients with thyroid carcinoma.

Keywords: cancer; diagnostic biomarkers; exosomes; extracellular vesicles; liquid biopsy; miRNA; papillary thyroid carcinoma; thyroid carcinoma.

Publication types

  • Review

MeSH terms

  • Biomarkers, Tumor / metabolism*
  • Extracellular Vesicles / metabolism
  • Extracellular Vesicles / pathology*
  • Humans
  • Thyroid Neoplasms / metabolism
  • Thyroid Neoplasms / pathology*

Substances

  • Biomarkers, Tumor