Gas chromatography-mass spectrometry-based untargeted metabolomics reveals metabolic perturbations in medullary thyroid carcinoma

Determination of the geographical origin of chicken (breast and drumstick) using ICP-OES and ICP-MS: Chemometric analysis

This study aimed to develop a geographical origin discrimination analytical method for chicken breasts and drumsticks based on inductively coupled plasma (ICP). The sixty elements were set as variables, and the geographical origin discrimination analysis was conducted through chemometrics. In orthogonal partial least square discriminant analysis (OPLS-DA), twenty-three variable importance in projection (VIP) elements were selected in chicken breasts, and twenty-eight VIP elements were selected in drumsticks. The importance of the selected elements was displayed by the area under the curve (AUC) value of the receiver operating characteristic (ROC). Verification of OPLS-DA was performed through permutation test and good results were obtained. A heatmap was also used as a method for determining the geographical origin, and each top element discriminant classification was 100 % accurate, as determined through canonical discriminant analysis (CDA). This method shows potential as a food analysis tool and can accurately determine the geographic origin of chicken.

LC-MS based untargeted metabolomics studies of the metabolic response of Ginkgo biloba extract on arsenism patients

Arsenic is an environmentally ubiquitous toxic metalloid. Chronic exposure to arsenic may lead to arsenicosis, while no specific therapeutic strategies are available for the arsenism patients. And Ginkgo biloba extract (GBE) exhibited protective effect in our previous study. However, the mechanisms by which GBE protects the arsenism patients remain poorly understood. A liquid chromatography-mass spectrometry (LC-MS) based untargeted metabolomics analysis was used to study metabolic response in arsenism patients upon GBE intervention. In total, 39 coal-burning type of arsenism patients and 50 healthy residents were enrolled from Guizhou province of China. The intervention group (n = 39) were arsenism patients orally administered with GBE (three times per day) for continuous 90 days. Plasma samples from 50 healthy controls (HC) and 39 arsenism patients before and after GBE intervention were collected and analyzed by established LC-MS method. Statistical analysis was performed by MetaboAnalyst 5.0 to identify differential metabolites. Multivariate analysis revealed a separation in arsenism patients between before (BG) and after GBE intervention (AG) group. It was observed that 35 differential metabolites were identified between BG and AG group, and 30 of them were completely or partially reversed by GBE intervention, with 14 differential metabolites significantly up-regulated and 16 differential metabolites considerably down-regulated. These metabolites were involved in promoting immune response and anti-inflammatory functions, and alleviating oxidative stress. Taken together, these findings indicate that the GBE intervention could probably exert its protective effects by reversing disordered metabolites modulating these functions in arsenism patients, and provide insights into further exploration of mechanistic studies.

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.

Exploring the application value of pro-gastrin-releasing peptide in the clinical diagnosis and surgical treatment of medullary thyroid carcinoma

OBJECTIVE

To investigate the relationship between pro-gastrin-releasing peptide (ProGRP) and the clinical characteristics of patients with medullary thyroid carcinoma (MTC) and the value of ProGRP in surgical treatment monitoring.

PATIENTS AND METHODS

A total of 347 patients with MTC and non-MTC malignant and benign thyroid diseases were enrolled. The concentrations of neuron-specific enolase (NSE), carcinoembryonic antigen (CEA), calcitonin (CT), and ProGRP were determined by Elecsys® assays. The NSE, CEA, CT, and ProGRP levels in different thyroid disease groups were compared, and ProGRP levels in different clinicopathological feature groups pre and postoperatively were further compared.

RESULTS

The CT, CEA, NSE, and ProGRP levels were upregulated in the MTC group compared to those in the non-MTC malignant and benign thyroid disease groups. The area under the receiver operating characteristic curve (AUC) of ProGRP for the diagnosis of MTC was 0.832(0.787-0.871), similar to that of CT and CEA. The sensitivity and specificity were 71.4% and 92.7%, respectively, and the optimal cut-off value was 61.8 pg/mL. The AUC of ProGRP combined with CT or CEA for the diagnosis of MTC was 0.933 (0.900-0.958) and 0.922 (0.886-0.949), respectively, which were higher than those of a single index. ProGRP levels were higher in patients with lymph nodes and distant metastases than in patients without metastases. The postoperative level of ProGRP was lower than that before treatment.

CONCLUSION

ProGRP is comparable to CEA and CT as an MTC biomarker with broad prospects. It has potential application value in the progression of MTC assessment and the evaluation of surgical intervention effects.

Experimental study on changes in metabolic mechanism of papillary thyroid carcinoma complicated with Hashimoto's thyroiditis

Background

Whether the mechanism of thyroid papillary carcinoma (PTC) is the same in patients with a Hashimoto's thyroiditis (HT) background as compared with patients with a normal background remains a highly debated and controversial issue. In this study, we aimed to analyze the differences and similarities of the metabolic mechanism of PTC in normal and HT background, and to explore the relationship between HT and PTC.

Methods

The ultra performance liquid chromatography-quadrupole-time of flight-mass spectrometry (UPLC-Q-TOF/MS) technology was used to analyze 61 PTC patient tissues (31 HT background and 30 normal tissue (NC) background). Potential biomarkers were screened from principal component analysis (PCA) to orthogonal partial least square (OPLS) discriminant analysis. HMDB was searched to identify potential differential metabolites and final metabolic pathway analysis was performed by MetaboAnalyst 5.0. We analyzed the differential metabolites diagnostic accuracy through receiver operating characteristic (ROC) curves analysis.

Results

Seven different metabolites were screened from HT group and NC group, including arginine, glutamic acid, cysteine, citric acid, malic acid, uracil and taurine. Logistic regression model combined with ROC analysis of these 7 biomarkers had good discriminability for PTC (area under operating characteristic curve of HT group and NC group were 0.867 and 0.973, respectively). The HT group had specific metabolic pathways, including aminoacyl-tRNA biosynthesis, glycine, serine and threonine metabolism.

Conclusions

The metabolic profiles of the NC and HT groups had important similarities and differences in PTC. The correlation of PTC with HT may be related to aminoacyl-tRNA biosynthesis, serine and threonine metabolism.

Faulty Metabolism: A Potential Instigator of an Aggressive Phenotype in Cdk5-dependent Medullary Thyroid Carcinoma

Mechanistic modeling of cancers such as Medullary Thyroid Carcinoma (MTC) to emulate patient-specific phenotypes is challenging. The discovery of potential diagnostic markers and druggable targets in MTC urgently requires clinically relevant animal models. Here we established orthotopic mouse models of MTC driven by aberrantly active Cdk5 using cell-specific promoters. Each of the two models elicits distinct growth differences that recapitulate the less or more aggressive forms of human tumors. The comparative mutational and transcriptomic landscape of tumors revealed significant alterations in mitotic cell cycle processes coupled with the slow-growing tumor phenotype. Conversely, perturbation in metabolic pathways emerged as critical for aggressive tumor growth. Moreover, an overlapping mutational profile was identified between mouse and human tumors. Gene prioritization revealed putative downstream effectors of Cdk5 which may contribute to the slow and aggressive growth in the mouse MTC models. In addition, Cdk5/p25 phosphorylation sites identified as biomarkers for Cdk5-driven neuroendocrine tumors (NETs) were detected in both slow and rapid onset models and were also histologically present in human MTC. Thus, this study directly relates mouse and human MTC models and uncovers vulnerable pathways potentially responsible for differential tumor growth rates. Functional validation of our findings may lead to better prediction of patient-specific personalized combinational therapies.

Real-time gas mass spectroscopy by multivariate analysis

Early and significant results for a real-time, column-free miniaturized gas mass spectrometer in detecting target species with partial overlapping spectra are reported. The achievements have been made using both nanoscale holes as a nanofluidic sampling inlet system and a robust statistical technique. Even if the presented physical implementation could be used with gas chromatography columns, the aim of high miniaturization requires investigating its detection performance with no aid. As a study case, in the first experiment, dichloromethane (CH₂Cl₂) and cyclohexane (C₆H₁₂) with concentrations in the 6-93 ppm range in single and compound mixtures were used. The nano-orifice column-free approach acquired raw spectra in 60 s with correlation coefficients of 0.525 and 0.578 to the NIST reference database, respectively. Then, we built a calibration dataset on 320 raw spectra of 10 known different blends of these two compounds using partial least square regression (PLSR) for statistical data inference. The model showed a normalized full-scale root-mean-square deviation (NRMSD) accuracy of [Formula: see text] and [Formula: see text] for each species, respectively, even in combined mixtures. A second experiment was conducted on mixes containing two other gasses, Xylene and Limonene, acting as interferents. Further 256 spectra were acquired on 8 new mixes, from which two models were developed to predict CH₂Cl₂ and C₆H₁₂, obtaining NRMSD values of 6.4% and 13.9%, respectively.

Relationship between 4-Hydroxynonenal (4-HNE) as Systemic Biomarker of Lipid Peroxidation and Metabolomic Profiling of Patients with Prostate Cancer

An oxidative degradation product of the polyunsaturated fatty acids, 4-hydroxynonenal (4-HNE), is of particular interest in cancer research due to its concentration-dependent pleiotropic activities affecting cellular antioxidants, metabolism, and growth control. Although an increase in oxidative stress and lipid peroxidation was already associated with prostate cancer progression a few decades ago, the knowledge of the involvement of 4-HNE in prostate cancer tumorigenesis is limited. This study investigated the appearance of 4-HNE-protein adducts in prostate cancer tissue by immunohistochemistry using a genuine 4-HNE monoclonal antibody. Plasma samples of the same patients and samples of the healthy controls were also analyzed for the presence of 4-HNE-protein adducts, followed by metabolic profiling using LC-ESI-QTOF-MS and GC-EI-Q-MS. Finally, the analysis of the metabolic pathways affected by 4-HNE was performed. The obtained results revealed the absence of 4-HNE-protein adducts in prostate carcinoma tissue but increased 4-HNE-protein levels in the plasma of these patients. Metabolomics revealed a positive association of different long-chain and medium-chain fatty acids with the presence of prostate cancer. Furthermore, while linoleic acid positively correlated with the levels of 4-HNE-protein adducts in the blood of healthy men, no correlation was obtained for cancer patients indicating altered lipid metabolism in this case. The metabolic pathway of unsaturated fatty acids biosynthesis emerged as significantly affected by 4-HNE. Overall, this is the first study linking 4-HNE adduction to plasma proteins with specific alterations in the plasma metabolome of prostate cancer patients. This study revealed that increased 4-HNE plasma protein adducts could modulate the unsaturated fatty acids biosynthesis pathway. It is yet to be determined if this is a direct result of 4-HNE or whether they are produced by the same underlying mechanisms. Further mechanistic studies are needed to grasp the biological significance of the observed changes in prostate cancer tumorigenesis.

Metabolomics-A Tool to Find Metabolism of Endocrine Cancer

Clinical endocrinology entails an understanding of the mechanisms involved in the regulation of tumors that occur in the endocrine system. The exact cause of endocrine cancers remains an enigma, especially when discriminating malignant lesions from benign ones and early diagnosis. In the past few years, the concepts of personalized medicine and metabolomics have gained great popularity in cancer research. In this systematic review, we discussed the clinical metabolomics studies in the diagnosis of endocrine cancers within the last 12 years. Cancer metabolomic studies were largely conducted using nuclear magnetic resonance (NMR) and mass spectrometry (MS) combined with separation techniques such as gas chromatography (GC) and liquid chromatography (LC). Our findings revealed that the majority of the metabolomics studies were conducted on tissue, serum/plasma, and urine samples. Studies most frequently emphasized thyroid cancer, adrenal cancer, and pituitary cancer. Altogether, analytical hyphenated techniques and chemometrics are promising tools in unveiling biomarkers in endocrine cancer and its metabolism disorders.