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.

Caffeine is one of the most widely consumed psycho-stimulants. The study of the beneficial effects of caffeine consumption to decrease the risk of developing several neuropsychiatric pathologies is receiving increasing attention. Thus, accurate and sensitive methods have been developed, mainly by LC-MS/MS, in order to quantify caffeine and its metabolites. These quantifications of caffeine and its metabolites by LC-MS/MS require a considerable effort to select or find a surrogate matrix, without the compounds of interest, to be used in the calibration curves. Thus, we evaluated the possibility of using calibration curves prepared in solvent instead of calibration curves prepared in human plasma. Results show that the calibration curves prepared in solvent and in human plasma were similar by comparing their slopes and interceptions, and the accuracy and precision were within the limits of acceptance for both calibration curves. This work demonstrates that, by using internal standards, it is possible to use a calibration curve in solvent instead of a calibration curve in plasma to perform an accurate and precise quantification of caffeine and theobromine.

Coffee may protect against non-alcoholic fatty liver disease (NAFLD), but the roles of the caffeine and non-caffeine components are unclear. Coffee intake by 156 overweight subjects (87% with Type-2-Diabetes, T2D) was assessed via a questionnaire, with 98 subjects (all T2D) also providing a 24 h urine sample for quantification of coffee metabolites by LC–MS/MS. NAFLD was characterized by the fatty liver index (FLI) and by Fibroscan^® assessment of fibrosis. No associations were found between self-reported coffee intake and NAFLD parameters; however, total urine caffeine metabolites, defined as Σ_caffeine (caffeine + paraxanthine + theophylline), and adjusted for fat-free body mass, were significantly higher for subjects with no liver fibrosis than for those with fibrosis. Total non-caffeine metabolites, defined as Σ_ncm (trigonelline + caffeic acid + p-coumaric acid), showed a significant negative association with the FLI. Multiple regression analyses for overweight/obese T2D subjects (n = 89) showed that both Σ_caffeine and Σ_ncm were negatively associated with the FLI, after adjusting for age, sex, Hb_A1c, ethanol intake and glomerular filtration rate. The theophylline fraction of Σ_caffeine was significantly increased with both fibrosis and the FLI, possibly reflecting elevated CYP2E1 activity—a hallmark of NAFLD worsening. Thus, for overweight/obese T2D patients, higher intake of both caffeine and non-caffeine coffee components is associated with less severe NAFLD. Caffeine metabolites represent novel markers of NAFLD progression.

Mice deficient in adipose triglyceride lipase (ATGL^−/−) present elevated ectopic lipid levels but are paradoxically glucose-tolerant. Measurement of endogenous glucose production (EGP) and Cori cycle activity provide insights into the maintenance of glycemic control in these animals. These parameters were determined in 7 wild-type (ATGL^+/−) and 6 ATGL^−/−mice by a primed-infusion of [U-¹³C₆]glucose followed by LC-MS/MS targeted mass-isotopomer analysis of blood glucose. EGP was quantified by isotope dilution of [U-¹³C₆]glucose while Cori cycling was estimated by analysis of glucose triose¹³C-isotopomers. Fasting plasma free fatty-acids were significantly lower in ATGL^−/−versus control mice (0.43 ± 0.05 mMversus0.73 ± 0.11 mM,P<0.05). Six-hour fasting EGP rates were identical for both ATGL^−/−and control mice (79 ± 11versus71 ± 7 μmol/kg/min, resp.). Peripheral glucose metabolism was dominated by Cori cycling (80 ± 2% and 82 ± 7% of glucose disposal for ATGL^−/−and control mice, resp.) indicating that peripheral glucose oxidation was not significantly upregulated in ATGL^−/−mice under these conditions. The glucose¹³C-isotopomer distributions in both ATGL^−/−and control mice were consistent with extensive hepatic pyruvate recycling. This suggests that gluconeogenic outflow from the Krebs cycle was also well compensated in ATGL^−/−mice.

Differentiated thyroid cancer is the most common malignancy of the endocrine system. Although most thyroid nodules are benign, given the high incidence of thyroid nodules in the population, it is important to understand the differences between benign and malignant thyroid cancer and the molecular alterations associated with malignancy to improve detection and signal potential diagnostic, prognostic, and therapeutic targets. Proteomics analysis of benign and malignant human thyroid tissue largely revealed changes indicating modifications in RNA regulation, a common cancer characteristic. In addition, changes in the immune system and cell membrane/endocytic processes were also suggested to be involved. Annexin A1 was considered a potential malignancy biomarker and, similarly to other annexins, it was found to increase in the malignant group. Furthermore, a bioinformatics approach points to the transcription factor Sp1 as being potentially involved in most of the alterations seen in the malignant thyroid nodules.