Non-invasive diagnosis of papillary thyroid microcarcinoma: a NMR-based metabolomics approach

Metabolomics and cellular altered pathways in cancer biology: A review

Cancer is a deadly disease that affects a cell's metabolism and surrounding tissues. Understanding the fundamental mechanisms of metabolic alterations in cancer cells would assist in developing cancer treatment targets and approaches. From this perspective, metabolomics is a great analytical tool to clarify the mechanisms of cancer therapy as well as a useful tool to investigate cancer from a distinct viewpoint. It is a powerful emerging technology that detects up to thousands of molecules in tissues and biofluids. Like other "-omics" technologies, metabolomics involves the comprehensive investigation of micromolecule metabolites and can reveal important details about the cancer state that is otherwise not apparent. Recent developments in metabolomics technologies have made it possible to investigate cancer metabolism in greater depth and comprehend how cancer cells utilize metabolic pathways to make the amino acids, nucleotides, and lipids required for tumorigenesis. These new technologies have made it possible to learn more about cancer metabolism. Here, we review the cellular and systemic effects of cancer and cancer treatments on metabolism. The current study provides an overview of metabolomics, emphasizing the current technologies and their use in clinical and translational research settings.

Identifying potential breath biomarkers for early diagnosis of papillary thyroid cancer based on solid-phase microextraction gas chromatography-high resolution mass spectrometry with metabolomics

INTRODUCTION

Thyroid cancer incidence rate has increased substantially worldwide in recent years. Fine needle aspiration biopsy (FNAB) is currently the golden standard of thyroid cancer diagnosis, which however, is invasive and costly. In contrast, breath analysis is a non-invasive, safe and simple sampling method combined with a promising metabolomics approach, which is suitable for early cancer diagnosis in high volume population.

OBJECTIVES

This study aims to achieve a more comprehensive and definitive exhaled breath metabolism profile in papillary thyroid cancer patients (PTCs).

METHODS

We studied both end-tidal and mixed expiratory breath, solid-phase microextraction gas chromatography coupled with high resolution mass spectrometry (SPME-GC-HRMS) was used to analyze the breath samples. Multivariate combined univariate analysis was applied to identify potential breath biomarkers.

RESULTS

The biomarkers identified in end-tidal and mixed expiratory breath mainly included alkanes, olefins, enols, enones, esters, aromatic compounds, and fluorine and chlorine containing organic compounds. The area under the curve (AUC) values of combined biomarkers were 0.974 (sensitivity: 96.1%, specificity: 90.2%) and 0.909 (sensitivity: 98.0%, specificity: 74.5%), respectively, for the end-tidal and mixed expiratory breath, indicating of reliability of the sampling and analysis method CONCLUSION: This work not only successfully established a standard metabolomic approach for early diagnosis of PTC, but also revealed the necessity of using both the two breath types for comprehensive analysis of the biomarkers.

Metabolomic screening of radioiodine refractory thyroid cancer patients and the underlying chemical mechanism of iodine resistance

Radioiodine refractory (RAIR) patients do not benefit from iodine-131 therapy. Thus, timely identification of RAIR patients is critical for avoiding ineffective radioactive iodine therapy. In addition, determining the causes of iodine resistance will facilitate the development of novel treatment strategies. This study was comprised of 20 RAIR and 14 non-radioiodine refractory (non-RAIR) thyroid cancer patients. Liquid chromatography-mass spectrometry was used to identify differences in the serum metabolites of RAIR and non-RAIR patients. In addition, chemical assays were performed to determine the effects of the differential metabolites on iodine uptake. Metabolic pathway enrichment analysis of the differential metabolites revealed significant differences in the phenylalanine and tyrosine metabolic pathways. Notably, quinate and shikimic acid, metabolites of the tyrosine pathway, were significantly increased in the RAIR group. In contrast, the phenylalanine pathway metabolites, hippuric acid and 2-phenylacetamide, were markedly decreased in the RAIR group. Thyroid peroxidase plays an important role in catalyzing the iodination of tyrosine residues, while the ionic state of iodine promotes the iodination reaction. Quinate, shikimic acid, hippuric acid, and 2-phenylacetamide were found to be involved in the iodination of tyrosine, which is a key step in thyroid hormone synthesis. Specifically, quinate and shikimic acid were found to inhibit iodination, while hippuric acid and 2-phenylacetamide promoted iodination. Abnormalities in phenylalanine and tyrosine metabolic pathways are closely associated with iodine resistance. Tyrosine is required for thyroid hormone synthesis and could be a potential cause of iodine resistance.

Plasma metabolites analysis of patients with papillary thyroid cancer: A preliminary untargeted 1H NMR-based metabolomics

Metabolomics plays a crucial role in identifying molecular biomarkers that can differentiate pathological conditions. In the case of thyroid cancer, it is essential to accurately diagnose malignancy from benignity to avoid unnecessary surgeries. The objective of this research was to apply untargeted NMR-based metabolomics in order to identify metabolic biomarkers that can distinguish between plasma samples of patients with papillary thyroid cancer (PTC) and multinodular goiter (MNG), as well as PTC and healthy individuals. The study included a cohort of 55 patients who were divided into three groups: PTC (n=20), MNG (n=16), and healthy (n=19). Plasma samples were collected from all participants and subjected to 1H NMR spectroscopy. Differential metabolites were identified using chemometric pattern recognition algorithms. The obtained metabolic profile had the potential to differentiate PTC from healthy plasma, but not from MNG. In patients diagnosed with PTC, a total of 18 compounds were discovered, revealing elevated levels of leucine, lysine, and 4-acetamidobutyric acid, while acetate, proline, acetoacetate, 3-hydroxybutyrate, glutamate, pyruvate, cystine, glutathione, asparagine, ethanolamine, histidine, tyrosine, myo-inositol, and glycerol along with a lipid compound were found to be lower in comparison to those of healthy individuals. According to the area under the curve (AUC) of the receiver operating characteristic curve, this particular profile exhibited an impressive capability of 85% to discern PTC from healthy subjects (AUC=0.853, sensitivity=78.95, specificity=84.21). The utilization of the 1H NMR-based metabolomics approach revealed considerable promise in the identification of PTC from healthy plasma specimens. The modifications noticed in the plasma metabolites have the potential to act as practical biomarkers that are non-invasive and could suggest transformations in the metabolic profile of thyroid tumors.

Hypoxia expedites the progression of papillary thyroid carcinoma by promoting the CPT1A-mediated fatty acid oxidative pathway

Hypoxia has been reported to promote the proliferation and migration of thyroid cancer, while the special mechanism was still unclear. HIF-1α/carnitine palmitoyl-transferase 1A (CPT1A) was found to be associated with papillary thyroid carcinoma (PTC) but the biological role of CPT1A in PTC was not explored. The effects of hypoxia and carnitine palmitoyl-transferase 1A (CPT1A) expression on PTC cells were determined by cell counting kit-8 assay, detection of oxidative stress, inflammation response and mitochondrial membrane motential (MMP). Oil Red O staining and the detection of free fatty acids were performed to assess the status of lipid metabolism. Flow cytometric analysis was performed to assess cell apoptosis. Quantitative polymerase chain reaction (qPCR) and western blot analysis were applied to investigate the expressions of CPT1A and HIF-1α and the molecules involved cell function. The expressions of CPT1A and HIF-1α were significantly increased in PTC cells with or without hypoxia treatment. CPT1A overexpression or silencing promoted or inhibited cell viability, and hypoxia further repressed cell viability. In addition, CPT1A overexpression alleviates hypoxia-induced increased oxidative stress, inflammation response and elevated MMP. CPT1A overexpression enhanced palmitic acid-induced decreased cell growth, enhanced the metabolic capacity of free fatty acid and suppressed cell apoptosis. Animal experiments showed that CPT1A overexpression promoted PTC tumor growth, reduced lipid deposition, oxidative stress and inflammation, as well as enhancing cell function indicators. However, CPT1A silencing showed the opposite effects both in vitro and in vivo. Hypoxia induces the high expression of HIF-1α/CPT1A, thereby reprogramming the lipid metabolism of PTC cells for adapting the hypoxia environment, meanwhile inhibiting the cell damage and apoptosis caused by oxidative stress.

Metabolite signature of human malignant thyroid tissue: A systematic review and meta-analysis

BACKGROUND

Thyroid cancer (TC) is the predominant malignancy within the endocrine system. However, the standard method for TC diagnosis lacks the capability to identify the pathological condition of all thyroid lesions. The metabolomics approach has the potential to manage this problem by identifying differential metabolites.

AIMS

This study conducted a systematic review and meta-analysis of the NMR-based metabolomics studies in order to identify significant altered metabolites associated with TC.

METHODS

A systematic search of published literature in any language in three databases including Embase, PubMed, and Scopus was conducted. Out of 353 primary articles, 12 studies met the criteria for inclusion in the systematic review. Among these, five reports belonging to three articles were eligible for meta-analysis. The correlation coefficient of the orthogonal partial least squares discriminant analysis, a popular model in the multivariate statistical analysis of metabolomic data, was chosen for meta-analysis. The altered metabolites were chosen based on the fact that they had been found in at least three studies.

RESULTS

In total, 49 compounds were identified, 40 of which were metabolites. The increased metabolites in thyroid lesions compared normal samples included lactate, taurine, alanine, glutamic acid, glutamine, leucine, lysine, phenylalanine, serine, tyrosine, valine, choline, glycine, and isoleucine. Lipids were the decreased compounds in thyroid lesions. Lactate and alanine were increased in malignant versus benign thyroid lesions, while, myo-inositol, scyllo-inositol, citrate, choline, and phosphocholine were found to be decreased. The meta-analysis yielded significant results for three metabolites of lactate, alanine, and citrate in malignant versus benign specimens.

DISCUSSION

In this study, we provided a concise summary of 12 included metabolomic studies, making it easier for future researchers to compare their results with the prior findings.

CONCLUSION

It appears that the field of TC metabolomics will experience notable advancement, leading to the discovery of trustworthy diagnostic and prognostic biomarkers.

Significant dysregulation of lipid metabolism in patients with papillary thyroid carcinoma after thyroidectomy

Introduction

Thyroidectomy and thyrotropin suppressive therapy is the widely used surgical treatment for papillary thyroid carcinoma (PTC) patients. However, systematic metabolic changes of post-operative PTC patients were rarely reported.

Methods

Here, untargeted metabolomic detection of cohorts from PTC before (t0) and 1-month-after (t1) thyroidectomy, were performed to characterize circulating metabolic signatures after surgical treatment.

Results

Our results showed PTC patients exhibited lower thyroid stimulating hormone degree, higher total thyroxine, and significant lipid-related metabolic alternations after thyroidectomy, which included 97 upregulations (including 93 lipids) and 5 downregulations (including 2 lipids and 3 nucleotides). Enrichment of metabolic pathways mainly included biosynthesis of fatty acids, purine metabolism, and linoleic acid metabolism. We also demonstrated that differential surgical approaches (hemi- and total thyroidectomy) and post-operative complication phenotypes (insomnia, fatigue), might lead to characteristic metabolic signatures.

Discussion

This study revealed dynamic changes of metabolite characteristics of PTC patients after surgical treatment, which were associated with clinical thyroid function parameters, surgical approaches, and complication occurrence. It enlightened us to pay more attention on the post-operative metabolic dysregulation of PTC patients and their long-term qualities of life, so as to provide cautious clinical decisions on surgical choices, treatments, and follow-up details.

Insight of novel biomarkers for papillary thyroid carcinoma through multiomics

Introduction

The overdiagnosing of papillary thyroid carcinoma (PTC) in China necessitates the development of an evidence-based diagnosis and prognosis strategy in line with precision medicine. A landscape of PTC in Chinese cohorts is needed to provide comprehensiveness.

Methods

6 paired PTC samples were employed for whole-exome sequencing, RNA sequencing, and data-dependent acquisition mass spectrum analysis. Weighted gene co-expression network analysis and protein-protein interactions networks were used to screen for hub genes. Moreover, we verified the hub genes' diagnostic and prognostic potential using online databases. Logistic regression was employed to construct a diagnostic model, and we evaluated its efficacy and specificity based on TCGA-THCA and GEO datasets.

Results

The basic multiomics landscape of PTC among local patients were drawn. The similarities and differences were compared between the Chinese cohort and TCGA-THCA cohorts, including the identification of PNPLA5 as a driver gene in addition to BRAF mutation. Besides, we found 572 differentially expressed genes and 79 differentially expressed proteins. Through integrative analysis, we identified 17 hub genes for prognosis and diagnosis of PTC. Four of these genes, ABR, AHNAK2, GPX1, and TPO, were used to construct a diagnostic model with high accuracy, explicitly targeting PTC (AUC=0.969/0.959 in training/test sets).

Discussion

Multiomics analysis of the Chinese cohort demonstrated significant distinctions compared to TCGA-THCA cohorts, highlighting the unique genetic characteristics of Chinese individuals with PTC. The novel biomarkers, holding potential for diagnosis and prognosis of PTC, were identified. Furthermore, these biomarkers provide a valuable tool for precise medicine, especially for immunotherapeutic or nanomedicine based cancer therapy.

Alterations in the amino acid profile in patients with papillary thyroid carcinoma with and without Hashimoto's thyroiditis

Purpose

Amino acids (AAs) play important physiological roles in living cells. Some amino acid changes in blood are specific for autoimmune disorders, and some are specific for thyroid cancer. The aims of this study were to profile AA metabolites in the serum of patients with papillary thyroid carcinoma (PTC0) without Hashimoto's thyroiditis (HT) and patients with PTC with HT (PTC1) and predict whether AA metabolites are associated with thyroid disease, thyroid hormone and thyroid autoantibodies.

Methods

A total of 95 serum samples were collected, including 28 healthy controls (HCs), 28 PTC0 patients and 39 PTC1 patients. Serum samples were analyzed by high-performance liquid chromatography-triple stage quadrupole-mass spectrometry (HPLC-TSQ-MS), and twenty-one amino acids (AAs) were detected.

Results

The serum concentration of glutamic acid was significantly elevated in PTC1 patients compared with PTC0 patients. Lysine was the second amino acid that differentiated these two groups of PTC patients. In addition, the serum concentrations of glycine, alanine and tyrosine were significantly reduced in both PTC patient groups compared to the HC group. These AAs were also correlated with thyroid hormones and antibodies. Five amino acid markers, namely, glycine, tyrosine, glutamic acid, glutamine and arginine, separated/distinguished PTC0 patients from healthy subjects, and eight AA markers, the same AAs as above without arginine but with alanine, leucine, valine and histidine, separated/distinguished PTC1 patients from healthy subjects based on ROC analysis.

Conclusion

Compared with the HCs, changes in AAs in PTC0 and PTC1 patients showed similar patterns, suggesting the possibility of a common pathophysiological basis, which confirms preliminary research that PTC is significantly associated with pathologically confirmed HT. We found two AAs, lysine and alanine, that can perform diagnostic functions in distinguishing PTC1 from PTC0.

Can ultrasound strain elastography (USE) improve management of suspicious thyroid nodules measuring <10 mm? A systematic review

INTRODUCTION

Current UK guidelines state that suspicious thyroid nodules <10 mm do not require FNA. These are often followed up with serial ultrasound scans. Ultrasound Strain Elastography (USE) could provide a more accurate alternative and preclude the need for follow-up. Can USE identify nodules at greater risk of malignancy and streamline patient management?

METHODS

Systematic review methodology used. Inclusion criteria are: - Population: patients with suspicious thyroid nodules <10 mm.- Intervention: USE.- Comparator: Ultrasound features of nodules.- Outcome measure: FNA or surgical removal of nodules. Searches performed on 6 commercial databases, along with grey literature anddissertation databases. The QUADAS-2 diagnostic study checklist used for quality assessment.

RESULTS

8 studies included and a narrative analysis performed due to heterogeneity of results. The mean USE sensitivity is 74.3%, mean specificity 80.5%. Mean overall ultrasound sensitivity is 80.4%, specificity 71.0%. Results suggest that USE is not superior to ultrasound for detecting malignancy. Some study limitations, particularly the heterogeneity of reporting the ultrasound features preclude meaningful conclusion from being drawn.

CONCLUSION

USE is more accurate at identifying benign nodules than ultrasound. Nodules appearing benign on USE could be excluded from serial ultrasound follow-up. No significant difference was found between USE and ultrasound at identifying malignant nodules.

IMPLICATIONS FOR PRACTICE

As FNA is not recommended for suspicious thyroid nodules <10 mm, these are often followed up with multiple scans and clinician reviews. This increases pressure on healthcare systems and uncertainty for the patient. This review shows that USE is more accurate at identifying benign nodules than ultrasound alone, meaning that these nodules could potentially be excluded from serial follow up. This would streamline patient management, freeing-up vital resources in ENT and ultrasound departments.

High-resolution magic angle spinning NMR for intact biological specimen analysis: Initial discovery, recent developments, and future directions

High-resolution magic angle spinning (HRMAS) NMR, an approach for intact biological material analysis discovered more than 25 years ago, has been advanced by many technical developments and applied to many biomedical uses. This article provides a history of its discovery, first by explaining the key scientific advances that paved the way for HRMAS NMR's invention, and then by turning to recent developments that have profited from applying and advancing the technique during the last 5 years. Developments aimed at directly impacting healthcare include HRMAS NMR metabolomics applications within studies of human disease states such as cancers, brain diseases, metabolic diseases, transplantation medicine, and adiposity. Here, the discussion describes recent HRMAS NMR metabolomics studies of breast cancer and prostate cancer, as well as of matching tissues with biofluids, multimodality studies, and mechanistic investigations, all conducted to better understand disease metabolic characteristics for diagnosis, opportune windows for treatment, and prognostication. In addition, HRMAS NMR metabolomics studies of plants, foods, and cell structures, along with longitudinal cell studies, are reviewed and discussed. Finally, inspired by the technique's history of discoveries and recent successes, future biomedical arenas that stand to benefit from HRMAS NMR-initiated scientific investigations are presented.

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.

Reprogramming of Cellular Metabolism and Its Therapeutic Applications in Thyroid Cancer

Metabolism is a series of life-sustaining chemical reactions in organisms, providing energy required for cellular processes and building blocks for cellular constituents of proteins, lipids, carbohydrates and nucleic acids. Cancer cells frequently reprogram their metabolic behaviors to adapt their rapid proliferation and altered tumor microenvironments. Not only aerobic glycolysis (also termed the Warburg effect) but also altered mitochondrial metabolism, amino acid metabolism and lipid metabolism play important roles for cancer growth and aggressiveness. Thus, the mechanistic elucidation of these metabolic changes is invaluable for understanding the pathogenesis of cancers and developing novel metabolism-targeted therapies. In this review article, we first provide an overview of essential metabolic mechanisms, and then summarize the recent findings of metabolic reprogramming and the recent reports of metabolism-targeted therapies for thyroid cancer.

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.

Biobanking potential for biomedical research in endocrinology

Biobanking is an actively developing scientific area that provides tools for conducting biomedical research, increasing the reliability and reproducibility of their results. In endocrinology, more and more attention is paid to the study of molecular and genetic markers of diseases for the selection of new points of influence in treatment, the development of targeted therapy and a strategy for personalized prevention. This approach is designed to solve the problems of endocrine disorders, their complications, causing significant damage to the individual and he population health, and reduce the financial burden of chronic endocrine disorders. To increase the reliability and reproducibility of research results, requirements for working with biological material should be strictly complied. The use of biobanking will increase the validity of data obtained in clinical trials in endocrinology. There are successful examples of Russian and foreign studies using the capabilities of biobanks aimed at studying diabetes, polycystic ovary syndrome, adenomas and other endocrine disorders. The article discusses the prospects for partnership with biobanks in the framework of endocrinology research. The purpose of this review is to analyze the literature to systematize knowledge for application of biobanking in biomedical research in the field of endocrinology.

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

Medullary thyroid cancer (MTC) is a rare tumor that arises from parafollicular cells within the thyroid gland. The molecular mechanism underlying MTC has not yet been fully understood. Here, we aimed to perform plasma metabolomics profiling of MTC patients to explore the perturbation of metabolic pathways contributing to MTC tumorigenesis. Plasma samples from 20 MTC patients and 20 healthy subjects were obtained to carry out an untargeted metabolomics by gas chromatography–mass spectrometry. Multivariate and univariate analyses were employed as diagnostic tools via MetaboAnalyst and SIMCA software. A total of 76 features were structurally annotated; among them, 13 metabolites were selected to be differentially expressed in MTC patients compared to controls (P < 0.05). These metabolites were mainly associated with the biosynthesis of unsaturated fatty acids and amino acid metabolisms, mostly leucine, glutamine, and glutamate, tightly responsible for tumor cells' energy production. Moreover, according to the receiver operating characteristic curve analysis, metabolites with the area under the curve (AUC) value up to 0.90, including linoleic acid (AUC = 0.935), linolenic acid (AUC = 0.92), and leucine (AUC = 0.948) could discriminate MTC from healthy individuals. This preliminary work contributes to existing knowledge of MTC metabolism by providing evidence of a distinctive metabolic profile in MTC patients relying on the metabolomics approach.

Multi-Omics Analysis of Fatty Acid Metabolism in Thyroid Carcinoma

Objective

Papillary thyroid carcinoma (PTC) accounts for the majority of thyroid cancer and affects a large number of individuals. The pathogenesis of PTC has not been completely elucidated thus far. Metabolic reprogramming is a common feature in tumours. Our previous research revealed the reprogramming of lipid metabolism in PTC. Further studies on lipid metabolism reprogramming may help elucidate the pathogenesis of PTC.

Methods

Clinical samples of PTC and para-tumour tissue were analysed using lipidomic, proteomic, and metabolomic approaches. A multi-omics integrative strategy was adopted to identify the important pathways in PTC. The findings were further confirmed using western blotting, tissue microarray, bioinformatics, and cell migration assays.

Results

Multi-omics data and the results of integrated analysis revealed that the three steps of fatty acid metabolism (hydrolysis, transportation, and oxidation) were significantly enhanced in PTC. Especially, the expression levels of LPL, FATP2, and CPT1A, three key enzymes in the respective steps, were elevated in PTC. Moreover, LPL, FATP2 and CPT1A expression was associated with the TNM stage, lymph node metastasis of PTC. Moreover, high levels of FATP2 and CPT1A contributed to poor prognosis of PTC. In addition, ectopic overexpression of LPL, FATP2 and CPT1A can each promote the migration of thyroid cancer cells.

Conclusions

Our data suggested that enhanced fatty acid metabolism supplied additional energy and substrates for PTC progression. This may help elucidating the underlying mechanism of PTC pathogenesis and identifying the potential therapeutic targets for PTC.

Recent Metabolomics Analysis in Tumor Metabolism Reprogramming

Metabolic reprogramming has been suggested as a hallmark of cancer progression. Metabolomic analysis of various metabolic profiles represents a powerful and technically feasible method to monitor dynamic changes in tumor metabolism and response to treatment over the course of the disease. To date, numerous original studies have highlighted the application of metabolomics to various aspects of tumor metabolic reprogramming research. In this review, we summarize how metabolomics techniques can help understand the effects that changes in the metabolic profile of the tumor microenvironment on the three major metabolic pathways of tumors. Various non-invasive biofluids are available that produce accurate and useful clinical information on tumor metabolism to identify early biomarkers of tumor development. Similarly, metabolomics can predict individual metabolic differences in response to tumor drugs, assess drug efficacy, and monitor drug resistance. On this basis, we also discuss the application of stable isotope tracer technology as a method for the study of tumor metabolism, which enables the tracking of metabolite activity in the body and deep metabolic pathways. We summarize the multifaceted application of metabolomics in cancer metabolic reprogramming to reveal its important role in cancer development and treatment.

Diagnostic approach to thyroid cancer based on amino acid metabolomics in saliva by ultra-performance liquid chromatography with high resolution mass spectrometry

Thyroid cancer is a malignant disease with dramatically low advanced-stage 10-year survival. Meanwhile, the metabolites in saliva are becoming a wealthy source of disease biomarkers. However, there is a lack of non-invasive analytical methods for the identification of biomarkers in saliva for the preoperative diagnosis of thyroid cancer. Therefore, we developed an ultra-high performance liquid chromatography-high resolution mass spectrometry (UPLC-HRMS) method to simultaneously determine the metabolic levels of 10 amino acids in saliva, aiming to study the amino acid metabolism profile to promote early diagnosis of thyroid cancer. We tested unstimulated whole saliva from patients with papillary thyroid carcinoma (PTC; n = 61) and healthy controls (HC; n = 61), and used receiver operating characteristic (ROC) curves to establish the diagnostic value of potential markers. The method validation results showed good precision, linearity (R² > 0.99), recovery (92.2 %-110.3 %), intra- and inter-day precision (RSD < 7 % and RSD < 9 %, respectively). The concentration of 10 amino acids was significantly different between PTC and HC in human salivary analysis (P < 0.05), the area under the curve (AUC) values of a single marker for the diagnosis of PTC were ranging from 0.678 to 0.833. A panel of alanine, valine, proline, phenylalanine was selected in combination yielded the AUC of 0.936, which will improve the accuracy of early diagnosis of thyroid cancer (sensitivity: 91.2 %; specificity: 85.2 %). This study proved the possibility of salivary amino acid biomarkers for PTC early diagnosis, providing a simple auxiliary way for the non-invasive diagnosis of thyroid cancer.

A glance at the actual role of glutamine metabolism in thyroid tumorigenesis

Thyroid cancers (TCs) are the most prevalent malignancy of the endocrine system and the seventh most common cancer in women. According to estimates from the Global Cancer Observatory (GCO) in 2020, the incidence of thyroid cancer globally was 586,000 cases. As thyroid cancer incidences have dramatically increased, identifying the most important metabolic pathways and biochemical markers involved in thyroid tumorigenesis can be critical strategies for controlling the prevalence and ultimately treatment of this disease. Cancer cells undergo cellular metabolism and energy alteration in order to promote cell proliferation and invasion. Glutamine is one of the most abundant free amino acids in the human body that contributes to cancer metabolic remodeling as a carbon and nitrogen source to sustain cell growth and proliferation. In the present review, glutamine metabolism and its regulation in cancer cells are highlighted. Thereafter, emphasis is given to the perturbation of glutamine metabolism in thyroid cancer, focusing on metabolomics studies.

Shared and unique metabolic features of the malignant and benign thyroid lesions determined with use of 1H HR MAS NMR spectroscopy

The purpose of this work was to investigate the distinct and common metabolic features of the malignant and benign thyroid lesions in reference to the non-transformed tissue from the contralateral gland (chronic thyroiditis and colloid goiter). 1H HR MAS NMR spectra of 38 malignant lesions, 32 benign lesions and 112 samples from the non-tumoral tissue (32 from chronic thyroiditis and 80 samples from colloid goiter) were subjected both to multivariate and univariate analysis. The increased succinate, glutamine, glutathione, serine/cysteine, ascorbate, lactate, taurine, threonine, glycine, phosphocholine/glycerophosphocholine and decreased lipids were found in both lesion types in comparison to either colloid goiter or chronic thyroiditis. The elevated glutamate and choline, and reduced citrate and glucose were additionally evident in these lesions in reference to goiter, while the increased myo-inositol-in comparison to thyroiditis. The malignant lesions were characterized by the higher alanine and lysine levels than colloid goiter and thyroiditis, while scyllo-inositol was uniquely increased in the benign lesions (not in cancer) in comparison to both non-tumoral tissue types. Moreover, the benign lesions presented with the unique increase of choline in reference to thyroiditis (not observed in the cancerous tissue). The metabolic heterogeneity of the non-tumoral tissue should be considered in the analysis of metabolic reprogramming in the thyroid lesions.

The Potential of Metabolomics in the Diagnosis of Thyroid Cancer

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.

Characteristics of fecal metabolic profiles in patients with irritable bowel syndrome with predominant diarrhea investigated using 1 H-NMR coupled with multivariate statistical analysis

BACKGROUND

Gut microbiota are known to be closely related to irritable bowel syndrome (IBS). However, not much is known about characteristic fecal metabolic profiles of IBS. We aimed to characterize fecal metabolites in patients with IBS with predominant diarrhea (IBS-D) using ¹ H-nuclear magnetic resonance (¹ H-NMR) spectroscopy.

METHODS

In this study, we enrolled 29 patients diagnosed with IBS-D according to the Rome IV criteria, 22 healthy controls (HC) and 11 HC administered laxatives (HC-L) in the age group of 20-69 year. The usual diet of the patients and HC was maintained, their fecal samples were collected and investigated by NMR-based global metabolic profiling coupled with multivariate statistical analysis.

RESULTS

We detected 55 metabolites in ¹ H-NMR spectra of fecal samples: four amines, 16 amino acids, six fatty acids, eight organic acids, three sugars, and 18 other compounds. Orthogonal partial least square-discriminant analysis derived score plots showed clear separation between the IBS-D group and the HC and HC-L groups. Among the 55 metabolites identified, we found five disease-relevant potential biomarkers distinguishing the IBS-D from the HC, namely, cadaverine, putrescine, threonine, tryptophan, and phenylalanine.

CONCLUSIONS

The patients with IBS-D were clearly differentiated from the HC and HC-L by fecal metabolite analysis using ¹ H-NMR spectroscopy, and five fecal metabolites characteristic of IBS-D were found. The findings of this study could be used to develop alternative and complementary diagnostic methods and as a source of fundamental information for developing novel therapies for IBS-D.

Correlations between the metabolic profile and 18F-FDG-Positron Emission Tomography-Computed Tomography parameters reveal the complexity of the metabolic reprogramming within lung cancer patients

Several studies have demonstrated that the metabolite composition of plasma may indicate the presence of lung cancer. The metabolism of cancer is characterized by an enhanced glucose uptake and glycolysis which is exploited by ¹⁸F-FDG positron emission tomography (PET) in the work-up and management of cancer. This study aims to explore relationships between ¹H-NMR spectroscopy derived plasma metabolite concentrations and the uptake of labeled glucose (¹⁸F-FDG) in lung cancer tissue. PET parameters of interest are standard maximal uptake values (SUV_max), total body metabolic active tumor volumes (MATV_WTB) and total body total lesion glycolysis (TLG_WTB) values. Patients with high values of these parameters have higher plasma concentrations of N-acetylated glycoproteins which suggest an upregulation of the hexosamines biosynthesis. High MATV_WTB and TLG_WTB values are associated with higher concentrations of glucose, glycerol, N-acetylated glycoproteins, threonine, aspartate and valine and lower levels of sphingomyelins and phosphatidylcholines appearing at the surface of lipoproteins. These higher concentrations of glucose and non-carbohydrate glucose precursors such as amino acids and glycerol suggests involvement of the gluconeogenesis pathway. The lower plasma concentration of those phospholipids points to a higher need for membrane synthesis. Our results indicate that the metabolic reprogramming in cancer is more complex than the initially described Warburg effect.

Advances in metabolomics of thyroid cancer diagnosis and metabolic regulation

Thyroid cancers (TCs) are the most frequent endocrine malignancy with an unpredictable fast-growing incidence, especially in females all over the world. Fine-needle aspiration biopsy (FNAB) analysis is an accurate diagnostic method for detecting thyroid nodules and classification of TC. Though simplicity, safety, and accuracy of FNAB, 15-30% of cases are indeterminate, and it is not possible to determine the exact cytology of the specimen. This demands the need for innovative methods capable to find crucial biomarkers with adequate sensitivity for diagnosis and prediction in TC researches. Cancer-based metabolomics is a vast emerging field focused on the detection of a large set of metabolites extracted from biofluids or tissues. Using analytical chemistry procedures allows for the potential recognition of cancer-based metabolites for the purposes of advancing the era of personalized medicine. Nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) coupled with separation techniques e.g., gas chromatography (GC) and liquid chromatography (LC) are the main approaches for metabolic studies in cancers. The immense metabolite profiling has provided a chance to discover novel biomarkers for early detection of thyroid cancer and reduce unnecessary aggressive surgery. In this review, we recapitulate the recent advances and developed methods of diverse metabolomics tools and metabolic phenotypes of thyroid cancer, following a brief discussion of recent challenges in the thyroid cancer diagnosis.

Identification of β-hydroxybutyrate as a potential biomarker for female papillary thyroid cancer

Aim: β-Hydroxybutyrate (BHB) was proved to be a differential metabolite of papillary thyroid cancer (PTC) by semiquantitative analysis, while whether BHB could be used as a potential biomarker for female PTC still needed to be validated. Materials & methods: An LC-MS/MS method with surrogate matrix was established to validate serum BHB in specified PTC patients. Conclusion: Serum BHB levels in PTCs were significantly higher than those in HCs. For both serum BHB with a cut-off value of 312.5 ng/ml and serum BHB/creatinine of 33.5 μmol/mmol, a promising prediction rate to distinguish low-grade PTCs from HCs with satisfactory sensitivity and specificity was achieved, indicating that serum BHB might be proved as a useful biomarker for low-grade female PTC.

Oncometabolites as biomarkers in thyroid cancer: a systematic review

INTRODUCTION

Thyroid cancer (TC) is an important common endocrine malignancy, and its incidence has increased in the past decades. The current TC diagnosis and classification tools are fine-needle aspiration (FNA) and histological examination following thyroidectomy. The metabolite profile alterations of thyroid cells (oncometabolites) can be considered for current TC diagnosis and management protocols.

METHODS

This systematic review focuses on metabolite alterations within the plasma, FNA specimens, and tissue of malignant TC contrary to benign, goiter, or healthy TC samples. A systematic search of MEDLINE (PubMed), Scopus, Embase, and Web of Science databases was conducted, and the final 31 studies investigating metabolite biomarkers of TC were included.

RESULTS

A total of 15 targeted studies and 16 untargeted studies revealed several potential metabolite signatures of TC such as glucose, fructose, galactose, mannose, 2-keto-d-gluconic acid and rhamnose, malonic acid and inosine, cholesterol and arachidonic acid, glycosylation (immunoglobulin G [IgG] Fc-glycosylation), outer mitochondrial membrane 20 (TOMM20), monocarboxylate transporter 4 (MCT4), choline, choline derivatives, myo-/scyllo-inositol, lactate, fatty acids, several amino acids, cell membrane phospholipids, estrogen metabolites such as 16 alpha-OH E1/2-OH E1 and catechol estrogens (2-OH E1), and purine and pyrimidine metabolites, which were suggested as the TC oncometabolite.

CONCLUSION

Citrate was suggested as the first most significant biomarker and lactate as the second one. Further research is needed to confirm these biomarkers as the TC diagnostic oncometabolite.

Serum-plasma matched metabolomics for comprehensive characterization of benign thyroid nodule and papillary thyroid carcinoma

Metabolomics offers a noninvasive methodology to identify metabolic markers for pathogenesis and diagnosis of diseases. This work aimed to characterize circulating metabolic signatures of benign thyroid nodule (BTN) and papillary thyroid carcinoma (PTC) via serum-plasma matched metabolomics. A cohort of 1,540 serum-plasma matched samples and 114 tissues were obtained from healthy volunteers, BTN and PTC patients enrolled from 6 independent centers. Untargeted metabolomics was determined by liquid chromatography-quadrupole time-of-flight mass spectrometric and multivariate statistical analyses. The use of serum-plasma matched samples afforded a broad-scope detection of 1,570 metabolic features. Metabolic phenotypes revealed significant pattern differences for healthy versus BTN and healthy versus PTC. Perturbed metabolic pathways related mainly to amino acid and lipid metabolism. It is worth noting that, BTN and PTC showed no significant differences but rather overlap in circulating metabolic signatures, and this observation was replicated in all study centers. For differential diagnosis of healthy versus thyroid nodules (BTN + PTC), a panel of 6 metabolic markers, namely myo-inositol, α-N-phenylacetyl-L-glutamine, proline betaine, L-glutamic acid, LysoPC(18:0) and LysoPC(18:1) provided area under the curve of 97.68% in the discovery phase and predictive accuracies of 84.78-98.18% in the 4 validation centers. Taken together, serum-plasma matched metabolomics showed significant differences in circulating metabolites for healthy versus nodules but not for BTN versus PTC. Our results highlight the true metabolic nature of thyroid nodules, and potentially decrease overtreatment that exposes patients to unnecessary risks.

Comparison of the prevalence of incidental and non-incidental papillary thyroid microcarcinoma during 2008-2016: a single-center experience

Background

The incidence of papillary thyroid microcarcinoma (PTMC) is increasing; however, it is not clear whether this reflects an increase in the incidence of incidental or in that of non-incidentally (presurgically) discovered PTMC (IPTMC vs. NIPTMC). We assessed the incidence of IPTMC and NIPTMC over the past 9 years, to discern whether the increase in PTMC incidence is due to improved diagnostics or to a real increase in the incidence.

Methods

We performed a retrospective chart review of 4327 patients who were consecutively admitted to and surgically treated for thyroid pathology at a single institution. As a main presurgical diagnostic test, all patients underwent ultrasound-guided fine-needle aspiration biopsy (UG-FNAB). The analyzed time frame was divided into three equal periods (I: 2008–2010, II: 2011–2013, III: 2014–2016), and IPTMCs and NIPTMCs were assessed and compared in each period.

Results

We evaluated 393 (9.08%) patients with thyroid malignancy, of which 156 (3.60% of all thyroid tumors [TTs]; 39.69% of all thyroid cancers [TCs]) were diagnosed as PTMC. The prevalence of NIPTMC among all TCs increased from 16.66% in 2008 to 33.75% in 2016, while that of IPTMC decreased from 20.83% in 2008 to 13.75% in 2016. The incidence rates of NIPTMC and IPTMC in period III differed statistically significantly (p < 0.0001). The prevalence rate of NIPTMC in period III was higher than that in period II, yet comparable to that in period I (p = 0.0014; p = 0.2804, respectively).

Conclusions

The prevalence of NIPTMC, rather than that of IPTMC, is escalating; this may be due to better presurgical diagnosis.

Diagnosis of post-surgical fine-needle aspiration biopsies of thyroid lesions with indeterminate cytology using HRMAS NMR-based metabolomics

INTRODUCTION

Ultrasound examination coupled with fine-needle aspiration (FNA) cytology is the gold standard for the diagnosis of thyroid cancer. However, about 10-40% of these analyses cannot be conclusive on the malignancy of the lesions and lead to surgery. The cytological indeterminate FNA biopsies are mainly constituted of follicular-patterned lesions, which are benign in 80% of the cases.

OBJECTIVES

The development of a FNAB classification approach based on the metabolic phenotype of the lesions, complementary to cytology and other molecular tests in order to limit the number of patients undergoing unnecessary thyroidectomy.

METHODS

We explored the potential of a NMR-based metabolomics approach to improve the quality of the diagnosis from FNABs, using thyroid tissues collected post-surgically.

RESULTS

The NMR-detected metabolites were used to produce a robust OPLSDA model to discriminate between benign and malignant tumours. Malignancy was correlated with amino acids such as tyrosine, serine, alanine, leucine and phenylalanine and anti-correlated with myo-inositol, scyllo-inositol and citrate. Diagnosis accuracy was of 84.8% when only indeterminate lesions were considered.

CONCLUSION

These results on model FNAB indicate that there is a clear interest in exploring the possibility to export NMR metabolomics to pre-surgical diagnostics.

Diagnostic Accuracy of Preoperative Neutrophil-to-Lymphocyte and Platelet-to-Lymphocyte Ratios in Detecting Occult Papillary Thyroid Microcarcinomas in Benign Multinodular Goitres

Objective

To investigate the diagnostic accuracy of neutrophil-to-lymphocyte (NLR) and platelet-to-lymphocyte (PLR) ratios in detecting occult papillary thyroid microcarcinomas in benign, multinodular goitres.

Methods

397 total thyroidectomy patients were identified from the institutional thyroid surgery database between 2007 and 2016 (94 males, 303 females, mean age 53 ± 14.5 years). NLR and PLR were calculated as the absolute neutrophil and absolute platelet counts divided by the absolute lymphocyte count, respectively, based on the preoperative complete blood cell count.

Results

NLR was significantly higher in carcinomas and microcarcinomas compared to benign pathology (p = 0.026), whereas a direct association could not be established for PLR. Both NLR and PLR scored low in all parameters of diagnostic accuracy, with overall accuracy ranging between 45 and 50%.

Conclusions

As surrogate indices of the systemic inflammatory response, NLR and PLR are inexpensive and universally available from routine blood tests. Although we found higher NLR values in cases of malignancy, NLR and PLR cannot effectively predict the presence of occult papillary microcarcinomas in otherwise benign, multinodular goitres.

Metabolomics-A Promising Approach to Pituitary Adenomas

Background: Metabolomics-the novel science that evaluates the multitude of low-molecular-weight metabolites in a biological system, provides new data on pathogenic mechanisms of diseases, including endocrine tumors. Although development of metabolomic profiling in pituitary disorders is at an early stage, it seems to be a promising approach in the near future in identifying specific disease biomarkers and understanding cellular signaling networks. Objectives: To review the metabolomic profile and the contributions of metabolomics in pituitary adenomas (PA). Methods: A systematic review was conducted via PubMed, Web of Science Core Collection and Scopus databases, summarizing studies that have described metabolomic aspects of PA. Results: Liquid chromatography tandem mass spectrometry (LC-MS/MS) and nuclear magnetic resonance (NMR) spectrometry, which are traditional techniques employed in metabolomics, suggest amino acids metabolism appears to be primarily altered in PA. N-acetyl aspartate, choline-containing compounds and creatine appear as highly effective in differentiating PA from healthy tissue. Deoxycholic and 4-pyridoxic acids, 3-methyladipate, short chain fatty acids and glucose-6-phosphate unveil metabolite biomarkers in patients with Cushing's disease. Phosphoethanolamine, N-acetyl aspartate and myo-inositol are down regulated in prolactinoma, whereas aspartate, glutamate and glutamine are up regulated. Phosphoethanolamine, taurine, alanine, choline-containing compounds, homocysteine, and methionine were up regulated in unclassified PA across studies. Intraoperative use of ultra high mass resolution matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI), which allows localization and delineation between functional PA and healthy pituitary tissue, may contribute to achievement of complete tumor resection in addition to preservation of pituitary cell lines and vasopressin secretory cells, thus avoiding postoperative diabetes insipidus. Conclusion: Implementation of ultra high performance metabolomics analysis techniques in the study of PA will significantly improve diagnosis and, potentially, the therapeutic approach, by identifying highly specific disease biomarkers in addition to novel molecular pathogenic mechanisms. Ultra high mass resolution MALDI-MSI emerges as a helpful clinical tool in the neurosurgical treatment of pituitary tumors. Therefore, metabolomics appears to be a science with a promising prospect in the sphere of PA, and a starting point in pituitary care.

The Synergistic Effects of Celecoxib and Sodium Valproate on Apoptosis and Invasiveness Behavior of Papillary Thyroid Cancer Cell Line In-vitro

Metastasis to lymph nodes and distant organs is the main challenge in the treatment of papillary thyroid cancer. In the current investigation, we aimed to evaluate the synergistic effects of celecoxib (CX) and sodium valproate (VPA) against cell survival, invasiveness properties, and expression of metalloproteinase-2 and -9 (MMP-2 and MMP-9) in papillary thyroid cancer cell line, B-CPAP cells. The effect of CX and VPA on B-CPAP cells viability and apoptosis were investigated using MTT assay and annexin V/7-AAD flowcytometry, respectively. The effects of the drugs on invasiveness properties of B-CPAP cells and expression of MMP-2 and MMP-9 were evaluated using transwell assay and real time PCR, respectively. MTT assay showed that CX and VPA decreased viability of B-CPAP cells dose dependently (IC₅₀ 32.4µM and 6.8 mM, respectively). Combination of CX (5 μM) and VPA (2.5 and 5 mM) increased apoptosis, and reduced cell migration and invasion of B-CPAP cell, synergistically. Real time PCR results showed that both CX (5 µM) and VPA (2.5 and 5 mM) reduced MMP-2 expression (P < 0.05) but had no significant effects on the expression of MMP-9. Our findings suggest that CX and VPA synergistically increase apoptosis and suppress migration and invasion of B-CPAP cells through inhibition of MMP-2 expression.

Serum and urine 1H NMR-based metabolomics in the diagnosis of selected thyroid diseases

Early detection of nodular thyroid diseases including thyroid cancer is still primarily based on invasive procedures such as fine-needle aspiration biopsy. Therefore, there is a strong need for development of new diagnostic methods that could provide clinically useful information regarding thyroid nodular lesions in a non-invasive way. In this study we investigated ¹H NMR based metabolic profiles of paired urine and blood serum samples, that were obtained from healthy individuals and patients with nodular thyroid diseases. Estimation of predictive potential of metabolites was evaluated using chemometric methods and revealed that both urine and serum carry information sufficient to distinguish between patients with nodular lesions and healthy individuals. Data fusion allowed to further improve prediction quality of the models. However, stratification of tumor types and their differentiation in relation to each other was not possible.

Integrative metabolomics as emerging tool to study autophagy regulation

Recent technological developments in metabolomics research have enabled in-depth characterization of complex metabolite mixtures in a wide range of biological, biomedical, environmental, agricultural, and nutritional research fields. Nuclear magnetic resonance spectroscopy and mass spectrometry are the two main platforms for performing metabolomics studies. Given their broad applicability and the systemic insight into metabolism that can be obtained it is not surprising that metabolomics becomes increasingly popular in basic biological research. In this review, we provide an overview on key metabolites, recent studies, and future opportunities for metabolomics in studying autophagy regulation. Metabolites play a pivotal role in autophagy regulation and are therefore key targets for autophagy research. Given the recent success of metabolomics, it can be expected that metabolomics approaches will contribute significantly to deciphering the complex regulatory mechanisms involved in autophagy in the near future and promote understanding of autophagy and autophagy-related diseases in living cells and organisms.