abstract
Thyroid cancer is the most common endocrine system malignancy. However, there is still a lack of reliable and specific markers for the detection and staging of this disease. Fine needle aspiration biopsy is the current gold standard for diagnosis of thyroid cancer, but drawbacks to this technique include indeterminate results or an inability to discriminate different carcinomas, thereby requiring additional surgical procedures to obtain a final diagnosis. It is, therefore, necessary to seek more reliable markers to complement and improve current methods. Omics approaches have gained much attention in the last decade in the field of biomarker discovery for diagnostic and prognostic characterisation of various pathophysiological conditions. Metabolomics, in particular, has the potential to identify molecular markers of thyroid cancer and identify novel metabolic profiles of the disease, which can, in turn, help in the classification of pathological conditions and lead to a more personalised therapy, assisting in the diagnosis and in the prediction of cancer behaviour. This review considers the current results in thyroid cancer biomarker research with a focus on metabolomics.
keywords
MAGNETIC-RESONANCE-SPECTROSCOPY; CARCINOMA; HSP90; BIOMARKERS; TARGET; TUMORS; DISCRIMINATION; METABOLISM; PROFILES; PATHWAYS
subject category
Biochemistry & Molecular Biology; Chemistry
authors
Coelho, M; Raposo, L; Goodfellow, BJ; Atzori, L; Jones, J; Manadas, B
our authors
acknowledgements
This work was supported by the European Regional Development Fund (ERDF) through the COMPETE 2020-Operational Programme for Competitiveness and Internationalisation and Portuguese national funds via FCT-Fundacao para a Ciencia e a Tecnologia, I.P., under projects: POCI-01-0145-FEDER-007440 (Ref. UIDB/04539/2020), POCI-01-0145-FEDER-016428 (Ref. SAICTPAC/0010/2015), POCI-01-0145-FEDER-029311 (Ref. PTDC/BTM-TEC/29311/2017), POCI-01-0145-FEDER-30943 (Ref. PTDC/MEC-PSQ/30943/2017) and PTDC/MED-NEU/27946/2017; and by The National Mass Spectrometry Network (RNEM) under the contract POCI-01-0145-FEDER-402-022125 (Ref. ROTEIRO/0028/2013). MC was supported by PhD fellowship PD/BD/135178/2017, co-financed by the European Social Fund (ESF) through the POCH (Programa Operacional do Capital Humano) and national funds via FCT.