Metabolomics-A Tool to Find Metabolism of Endocrine Cancer

Expression of TSPAN1 and its link to thyroid nodules: one step forward on the path to thyroid tumorigenesis biomarkers

BACKGROUND

Thyroid cancer is ranked as the most common malignancy within the endocrine system and the seventh most prevalent cancer in women globally. Thyroid malignancies require evaluating biomarkers capable of distinguishing between them for accurate diagnosis. We examined both mRNA and protein levels of TSPAN1 in plasma and tissue samples from individuals with thyroid nodules to aid this endeavour.

METHODS

In this case-control study, TSPAN1 was assessed at both protein and mRNA levels in 90 subjects, including papillary thyroid cancer (PTC; N = 60), benign (N = 30), and healthy subjects (N = 26) using enzyme-linked immunosorbent assay (ELISA) and SYBR-Green Real-Time PCR, respectively.

RESULTS

TSPAN1 plasma levels were decreased in PTC and benign compared to healthy subjects (P = 0.002). TSPAN1 mRNA levels were also decremented in the tumoral compared to the paired normal tissues (P = 0.012); this drop was also observed in PTC patients compared to benign patients (P = 0.001). Further, TSPAN1 had an appropriate diagnostic value for detecting PTC patients from healthy plasma samples with a sensitivity of 76.7% and specificity of 65.4% at the cutoff value < 2.7 (ng/ml).

CONCLUSION

TSPAN1 levels are significantly reduced in patients with benign and PTC, demonstrating its potential value as a diagnostic biomarker. Additionally, the significant reduction in TSPAN1 mRNA expression within PTC tumor tissues may suggest its involvement in tumor progression and development. Further studies, including larger-scale validation studies and mechanistic investigations, are imperative to clarify the molecular mechanisms behind TSPAN1 and, ultimately, its clinical utility for treating thyroid disorders.

In Search of Relevant Urinary Biomarkers for Thyroid Papillary Carcinoma and Benign Thyroid Nodule Differentiation, Targeting Metabolic Profiles and Pathways via UHPLC-QTOF-ESI+-MS Analysis

BACKGROUND

Identification of specific urine metabolic profiles for patients diagnosed with papillary thyroid carcinoma (TC) vs. benign nodules (B) to identify specific biomarkers and altered pathways compared to those of healthy controls (C).

METHODS

Patient urine samples were collected, before surgery and after a histological confirmation of TC (n = 30) and B (n = 30), in parallel with sample collection from healthy controls (n = 20). The untargeted and semi-targeted metabolomic protocols were applied using UPLC-QTOF-ESI+-MS analysis, and the statistical analysis was performed using the Metaboanalyst 6.0 platform. The results for the blood biomarkers, previously published, were compared with the data obtained from urine sampling using the Venny algorithm and multivariate statistics.

RESULTS

Partial least squares discrimination, including VIP values, random forest graphs, and heatmaps (p < 0.05), together with biomarker analysis (AUROC ranking) and pathway analysis, suggested a specific model for the urinary metabolic profile and pathway alterations in TC and B vs. C, based on 190 identified metabolites in urine that were compared with the serum metabolites. By semi-targeted metabolomics, 10 classes of metabolites, considered putative biomarkers, were found to be responsible for specific alterations in the metabolic pathways, from polar molecules to lipids. Specific biomarkers for discrimination were identified in each class of metabolites that were either upregulated or downregulated when compared to those of the controls.

CONCLUSIONS

The lipidomic window was the most relevant for identifying biomarkers related to thyroid cancer and benign conditions, since this study detected a stronger involvement of lipids and selenium-related molecules for metabolic discrimination.

Identification of serum metabolites associated with polybrominated diphenyl ethers (PBDEs) exposure in papillary thyroid carcinoma: a case-control study

As the most common endocrine cancer, thyroid cancer (TC) has sharply increased globally over the past three decades. The growing incidence of TC might be counted by genetics, radiation, iodine, autoimmune disease, and exposure to environmental endocrine-disrupting chemicals (EDCs). Polybrominated diphenyl ethers (PBDEs), being typical EDCs, have been widely utilized in plastics, electronics, furniture, and textiles as flame retardants since the 1980s, and research has indicated a significant correlation between their exposure and the risk of TC. Even so, PBDEs exposure impact on the metabolic signature for TC remains unexplored. In this study, eight congeners of PBDEs were determined in serum from 111 patents with papillary thyroid cancer (PTC) and 111 healthy participants based on case-control epidemiology using gas chromatography-atmospheric pressure chemical ionization-tandem mass spectrometry (GC-APCI-MS/MS). Based on the tertile distribution of total PBDEs concentrations in 59 participants, metabolomics analysis was further performed by ultra-high performance liquid chromatography coupled to hybrid quadrupole-Orbitrap MS. In the partial correlation analysis, the 29 identified metabolites were correlated with PBDEs exposure (P < 0.05). In addition, PBDEs disrupted the metabolism of glycerophospholipids, sphingolipids, taurine, and hypotaurine, indicating that neurotransmitters, oxidative stress, and inflammation are the vulnerable pathways affected in PTC. Furthermore, (±)-octopamine and 5-hydroxyindole, both of which modulate the actions of neurotransmitters, emerged as potential disturbed metabolite markers for TC following exposure to PBDEs. This study analyzed the impact of PBDEs on PTC in terms of the metabolic changes and further explored possible biomarkers, which helped us have a deep understanding of the possible mechanism of the effects of PBDEs on TC.

Thyroid cancer cell metabolism: A glance into cell culture system-based metabolomics approaches

Thyroid cancer is the most common malignancy of the endocrine system and the seventh most prevalent cancer in women worldwide. It is a complex and diverse disease characterized by heterogeneity, underscoring the importance of understanding the underlying metabolic alterations within tumor cells. Metabolomics technologies offer a powerful toolset to explore and identify endogenous and exogenous biochemical reaction products, providing crucial insights into the intricate metabolic pathways and processes within living cells. Metabolism plays a central role in cell function, making metabolomics a valuable reflection of a cell's phenotype. In the OMICs era, metabolomics analysis of cells brings numerous advantages over existing methods, propelling cell metabolomics as an emerging field with vast potential for investigating metabolic pathways and their perturbation in pathophysiological conditions. This review article aims to look into recent developments in applying metabolomics for characterizing and interpreting the cellular metabolome in thyroid cancer cell lines, exploring their unique metabolic characteristics. Understanding the metabolic alterations in tumor cells can lead to the identification of critical nodes in the metabolic network that could be targeted for therapeutic intervention.

Metabolic regulation of tumor cells exposed to different oxygenated polycyclic aromatic hydrocarbons

Oxygenated polycyclic aromatic hydrocarbons (OPAHs) are a class of polycyclic aromatic derivatives with oxygen-containing functional groups that induce oxidative stress and mutations. However, studies of the carcinogenic and metabolic effects of OPAHs are limited. In this study, we analyzed the carcinogenic effects of four different OPAHs and found that 9-fluorenone (FLO), 9,10-anthraquinone (AQ), and 7,12-benz(a)anthraquinone (BAQ) promoted cell invasion and metastasis via epithelial-mesenchymal transition (EMT) and induced endothelial cell angiogenesis by affecting the expression of vascular endothelial growth factor (VEGF), angiopoietin (ANG), and platelet-derived growth factor (PDGF), whereas 1,8-naphthalic anhydride (NAD) did not show significant carcinogenic effects. In addition, combined with metabolomic analysis, we found that the tumor-promoting effects of different OPAHs were related to their effects on the metabolome, especially the metabolism of glutathione related to oxidative stress. These results provide an experimental basis for studying the carcinogenic and metabolic effects of OPAHs, and an important reference for comprehensively assessing the ecological and health risks of this compounds.

Cancer metabolites: promising biomarkers for cancer liquid biopsy

Cancer exerts a multitude of effects on metabolism, including the reprogramming of cellular metabolic pathways and alterations in metabolites that facilitate inappropriate proliferation of cancer cells and adaptation to the tumor microenvironment. There is a growing body of evidence suggesting that aberrant metabolites play pivotal roles in tumorigenesis and metastasis, and have the potential to serve as biomarkers for personalized cancer therapy. Importantly, high-throughput metabolomics detection techniques and machine learning approaches offer tremendous potential for clinical oncology by enabling the identification of cancer-specific metabolites. Emerging research indicates that circulating metabolites have great promise as noninvasive biomarkers for cancer detection. Therefore, this review summarizes reported abnormal cancer-related metabolites in the last decade and highlights the application of metabolomics in liquid biopsy, including detection specimens, technologies, methods, and challenges. The review provides insights into cancer metabolites as a promising tool for clinical applications.

Metabolomics in oncology

BACKGROUND

Oncogenic transformation alters intracellular metabolism and contributes to the growth of malignant cells. Metabolomics, or the study of small molecules, can reveal insight about cancer progression that other biomarker studies cannot. Number of metabolites involved in this process have been in spotlight for cancer detection, monitoring, and therapy.

RECENT FINDINGS

In this review, the "Metabolomics" is defined in terms of current technology having both clinical and translational applications. Researchers have shown metabolomics can be used to discern metabolic indicators non-invasively using different analytical methods like positron emission tomography, magnetic resonance spectroscopic imaging etc. Metabolomic profiling is a powerful and technically feasible way to track changes in tumor metabolism and gauge treatment response across time. Recent studies have shown metabolomics can also predict individual metabolic changes in response to cancer treatment, measure medication efficacy, and monitor drug resistance. Its significance in cancer development and treatment is summarized in this review.

CONCLUSION

Although in infancy, metabolomics can be used to identify treatment options and/or predict responsiveness to cancer treatments. Technical challenges like database management, cost and methodical knowhow still persist. Overcoming these challenges in near further can help in designing new treatment régimes with increased sensitivity and specificity.