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

Fe(III)-quenched cysteine-capped copper nanoclusters as a selective fluorescence turn-on sensor for valine: A potential cancer biomarker candidate

This study introduces a fluorescence turn-on sensor for the selective detection of valine, an amino acid increasingly recognized as a potential biomarker in cancer diagnostics, using iron(III) (Fe3+) quenched L-cysteine capped copper nanoclusters (L-cys@CuNCs) based on the paramagnetic quenching mechanism of Fe3+. The L-cys@CuNCs, synthesized through a one-pot hydrothermal method, exhibit stable green fluorescence, high photostability and a detection limit of 3.00 µM for valine. Restoration of fluorescence upon interaction with valine enables a highly sensitive detection, with strong selectivity against other amino acids and ions. This specificity makes the sensor particularly promising for screening valine in biological samples, supporting its potential as a non-invasive cancer biomarker. To enhance practicality, a paper-based assay was developed, demonstrating its adaptability to point of care formats. Additionally, testing in human saliva and urine samples validated the probe's utility in real biological conditions, underscoring its potential in non-invasive cancer diagnostics. This biosensing platform offers a rapid, accessible tool for valine detection, contributing to early cancer detection and patient screening in clinical and resource limited settings.

Fluorescence Turn-On Sensing of Leucine Using Bimetallic Cu-Ag Nanoclusters: A Potential Non-Invasive Biomarker for Cancer Detection

This study investigates the use of bimetallic copper-silver nanoclusters (Cu-AgNCs) for fluorescence turn-on sensing of leucine, a potential biomarker for cancer detection. These nanoclusters exhibit high fluorescence tunability and specificity, with Fe3+ serving as a quencher to facilitate leucine detection. The fluorescence recovery mechanism is attributed to the interaction of leucine with Fe3+, alleviating the quenching effect on the metal nanoclusters. This bimetallic nanocluster is a promising platform for biomarker identification in cancer diagnosis. The fluorescence enhancement upon leucine binding provides a measurable signal, confirming the feasibility of these nanoclusters as noninvasive sensors for cancer biomarkers. The sensor achieves a detection limit of 0.58 μM and demonstrates a linear response within the range of 110-657 μM. This approach offers a promising method for noninvasive cancer diagnostics using saliva and urine samples. Additionally, the method's reproducibility and robustness further support its potential in clinical applications, providing a cost-effective and accessible technique for early cancer detection.

Systems biology approach delineates critical pathways associated with papillary thyroid cancer: a multi-omics data analysis

BACKGROUND

Papillary thyroid cancer (PTC) is the most prevalent follicular cell-derived subtype of thyroid cancer. A systems biology approach to PTC can elucidate the mechanism by which molecular components work and interact with one another to decipher a panoramic view of the pathophysiology.

METHODOLOGY

PTC associated genes and transcriptomic data were retrieved from DisGeNET and Gene Expression Omnibus database respectively. Published proteomic and metabolomic datasets in PTC from EMBL-EBI were used. Gene Ontology and pathway analyses were performed with SNPs, differentially expressed genes (DEGs), proteins, and metabolites linked to PTC. The effect of a nucleotide substitution on a protein's function was investigated. Additionally, significant transcription factors (TFs) and kinases were identified. An integrated strategy was used to analyse the multi-omics data to determine the key deregulated pathways in PTC carcinogenesis.

RESULTS

Pathways linked to carbohydrate, protein, and lipid metabolism, along with the immune response, signaling, apoptosis, gene expression, epithelial-mesenchymal transition (EMT), and disease onset, were identified as significant for the clinical and functional aspects of PTC. Glyoxylate and dicarboxylate metabolism and citrate cycle were the most common pathways among the PTC omics datasets. Commonality analysis deciphered five TFs and fifty-seven kinases crucial for PTC genesis and progression. Core deregulated pathways, TFs, and kinases modulate critical biological processes like proliferation, angiogenesis, immune infiltration, invasion, autophagy, EMT, and metastasis in PTC.

CONCLUSION

Identified dysregulated pathways, TFs and kinases are critical in PTC and may help in systems level understanding and device specific experiments, biomarkers, and drug targets for better management of PTC.

Emerging Potential of Metabolomics in Thyroid Cancer-A Comprehensive Review

Thyroid cancer is a very common endocrine system malignancy. Nevertheless, a dearth of precise markers makes it challenging to apply precision medicine to thyroid cancer. The limitations of standard diagnosis techniques (fine-needle aspiration biopsy), such as indeterminate cases and inaccuracies in distinguishing between different types of cancers, lead to unnecessary surgeries and thus warrant the development of more discriminatory biomarkers to improve the accuracy of existing diagnostic and prognostic techniques. Moreover, individualized therapies for thyroid cancer are necessary to avoid overtreatment of indolent lesions and undertreatment of high-risk progressive disease. As thyroid cancer metabolic signatures are associated with disease aggressiveness and responsiveness to therapy, metabolomics has been recently used for diagnostic and prognostic biomarker discovery. This strategy has enabled the detection of several metabolites from tissue samples or biofluids to facilitate the classification of disease aggressiveness and to potentially assist in individualized therapies. In this review, we summarize the utilization and potential of metabolomics in thyroid cancer.

Reprogramming of Thyroid Cancer Metabolism: from Mechanism to Therapeutic Strategy

Thyroid cancer as one of the most prevalent malignancies of endocrine system, has raised public concern and more research on its mechanism and treatment. And metabolism-based therapies have advanced rapidly, for the exclusive metabolic profiling of thyroid cancer. In thyroid cancer cells, plenty of metabolic pathways are reprogrammed to accommodate tumor microenvironment. In this review, we initiatively summarize recent progress in the full-scale thyroid cancer metabolic rewiring and the interconnection of various metabolites. We also discuss the efficacy and prospect of metabolic targeted detection as well as therapy. Comprehending metabolic mechanism and characteristics of thyroid cancer roundly will be highly beneficial to managing individual patients.

Salivary Tryptophan as a Metabolic Marker of HER2-Negative Molecular Subtypes of Breast Cancer

Changes in the concentration of tryptophan (Trp) indicate a serious metabolic restructuring, which is both a cause and a consequence of many diseases. This work examines the upward change in salivary Trp concentrations among patients with breast cancer. This study involved volunteers divided into three groups: breast cancer (n = 104), non-malignant breast pathologies (n = 30) and healthy controls (n = 20). In all participants, before treatment, the quantitative content of Trp in saliva was determined by capillary electrophoresis. In 20 patients with breast cancer, Trp was re-tested four weeks after surgical removal of the tumor. An increase in the Trp content in saliva in breast cancer has been shown, which statistically significantly decreases after surgical removal of the tumor. A direct correlation was found between increased Trp levels with the degree of malignancy and aggressive molecular subtypes of breast cancer, namely triple negative and luminal B-like HER2-negative. These conclusions were based on an increase in Ki-67 and an increase in Trp in HER2-negative and progesterone-negative subtypes. Factors under which an increase in Trp concentration in saliva was observed were identified: advanced stage of breast cancer, the presence of regional metastasis, low tumor differentiation, a lack of expression of HER2, estrogen and progesterone receptors and the high proliferative activity of the tumor. Thus, the determination of salivary Trp may be a valuable tool in the study of metabolic changes associated with cancer, particularly breast cancer.

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.

Metabolomic biomarkers in liquid biopsy: accurate cancer diagnosis and prognosis monitoring

Liquid biopsy, a novel detection method, has recently become an active research area in clinical cancer owing to its unique advantages. Studies on circulating free DNA, circulating tumor cells, and exosomes obtained by liquid biopsy have shown great advances and they have entered clinical practice as new cancer biomarkers. The metabolism of the body is dynamic as cancer originates and progresses. Metabolic abnormalities caused by cancer can be detected in the blood, sputum, urine, and other biological fluids via systemic or local circulation. A considerable number of recent studies have focused on the roles of metabolic molecules in cancer. The purpose of this review is to provide an overview of metabolic markers from various biological fluids in the latest clinical studies, which may contribute to cancer screening and diagnosis, differentiation of cancer typing, grading and staging, and prediction of therapeutic response and prognosis.

Critical Factors in Sample Collection and Preparation for Clinical Metabolomics of Underexplored Biological Specimens

This review article compiles critical pre-analytical factors for sample collection and extraction of eight uncommon or underexplored biological specimens (human breast milk, ocular fluids, sebum, seminal plasma, sweat, hair, saliva, and cerebrospinal fluid) under the perspective of clinical metabolomics. These samples are interesting for metabolomics studies as they reflect the status of living organisms and can be applied for diagnostic purposes and biomarker discovery. Pre-collection and collection procedures are critical, requiring protocols to be standardized to avoid contamination and bias. Such procedures must consider cleaning the collection area, sample stimulation, diet, and food and drug intake, among other factors that impact the lack of homogeneity of the sample group. Precipitation of proteins and removal of salts and cell debris are the most used sample preparation procedures. This review intends to provide a global view of the practical aspects that most impact results, serving as a starting point for the designing of metabolomic experiments.

Glutamine Production by Glul Promotes Thermogenic Adipocyte Differentiation Through Prdm9-Mediated H3K4me3 and Transcriptional Reprogramming

Thermogenic adipocytes have been extensively investigated because of their energy-dissipating property and therapeutic potential for obesity and diabetes. Besides serving as fuel sources, accumulating evidence suggests that intermediate metabolites play critical roles in multiple biological processes. However, their role in adipocyte differentiation and thermogenesis remains unexplored. Here, we report that human and mouse obesity is associated with marked downregulation of glutamine synthetase (Glul) expression and activity in thermogenic adipose tissues. Glul is robustly upregulated during brown adipocyte (BAC) differentiation and in brown adipose tissue (BAT) upon cold exposure and Cl316,243 stimulation. Further genetic, pharmacologic, or metabolic manipulations of Glul and glutamine levels reveal that glutamine cells autonomously stimulate BAC differentiation and function and BAT remodeling and improve systemic energy homeostasis in mice. Mechanistically, glutamine promotes transcriptional induction of adipogenic and thermogenic gene programs through histone modification-mediated chromatin remodeling. Among all the glutamine-regulated writer and eraser genes responsible for histone methylation and acetylation, only Prdm9, a histone lysine methyltransferase, is robustly induced during BAC differentiation. Importantly, Prdm9 inactivation by shRNA knockdown or a selective inhibitor attenuates glutamine-triggered adipogenic and thermogenic induction. Furthermore, Prdm9 gene transcription is regulated by glutamine through the recruitment of C/EBPb to its enhancer region. This work reveals glutamine as a novel activator of thermogenic adipocyte differentiation and uncovers an unexpected role of C/EBPb-Prdm9-mediated H3K4me3 and transcriptional reprogramming in adipocyte differentiation and thermogenesis.

ARTICLE HIGHLIGHTS

Combined metabolomic and lipidomic analysis uncovers metabolic profile and biomarkers for papillary thyroid carcinoma

Papillary thyroid carcinoma (PTC) is the most common endocrine malignancy with a rapidly increasing incidence. The pathogenesis of PTC is unclear, but metabolic and lipidomic reprogramming may play a role in tumor growth. We applied ultra-performance liquid chromatography-tandem mass spectrometry to perform widely targeted metabolomics and lipidomics on plasma samples from 94 patients with PTC and 100 healthy controls. We identified 113 differential metabolites and 236 differential lipids, mainly involved in branched-chain amino acid metabolism, glutamate and glutamine metabolism, tricarboxylic acid cycle, and lipid metabolism. We also screened three potential metabolite biomarkers: sebacic acid, L-glutamine, and indole-3-carboxaldehyde. These biomarkers showed excellent diagnostic performance for PTC in both discovery and validation cohorts, with areas under the receiver operating characteristic curves of 0.994 and 0.925, respectively. Our findings reveal distinct metabolic and lipidomic features of PTC and provide novel targets for diagnosis and treatment.

Diagnostic Value of Salivary Amino Acid Levels in Cancer

This review analyzed 21 scientific papers on the determination of amino acids in various types of cancer in saliva. Most of the studies are on oral cancer (8/21), breast cancer (4/21), gastric cancer (3/21), lung cancer (2/21), glioblastoma (2/21) and one study on colorectal, pancreatic, thyroid and liver cancer. The amino acids alanine, valine, phenylalanine, leucine and isoleucine play a leading role in the diagnosis of cancer via the saliva. In an independent version, amino acids are rarely used; the authors combine either amino acids with each other or with other metabolites, which makes it possible to obtain high values of sensitivity and specificity. Nevertheless, a logical and complete substantiation of the changes in saliva occurring in cancer, including changes in salivary amino acid levels, has not yet been formed, which makes it important to continue research in this direction.

An integrative profiling of metabolome and transcriptome in the plasma and skeletal muscle following an exercise intervention in diet-induced obese mice

Exercise intervention at the early stage of type 2 diabetes mellitus (T2DM) can aid in the maintenance of blood glucose homeostasis and prevent the development of macrovascular and microvascular complications. However, the exercise-regulated pathways that prevent the development of T2DM remain largely unclear. In this study, two forms of exercise intervention, treadmill training and voluntary wheel running, were conducted for high-fat diet (HFD)-induced obese mice. We observed that both forms of exercise intervention alleviated HFD-induced insulin resistance and glucose intolerance. Skeletal muscle is recognized as the primary site for postprandial glucose uptake and for responsive alteration beyond exercise training. Metabolomic profiling of the plasma and skeletal muscle in Chow, HFD, and HFD-exercise groups revealed robust alterations in metabolic pathways by exercise intervention in both cases. Overlapping analysis identified nine metabolites, including beta-alanine, leucine, valine, and tryptophan, which were reversed by exercise treatment in both the plasma and skeletal muscle. Transcriptomic analysis of gene expression profiles in the skeletal muscle revealed several key pathways involved in the beneficial effects of exercise on metabolic homeostasis. In addition, integrative transcriptomic and metabolomic analyses uncovered strong correlations between the concentrations of bioactive metabolites and the expression levels of genes involved in energy metabolism, insulin sensitivity, and immune response in the skeletal muscle. This work established two models of exercise intervention in obese mice and provided mechanistic insights into the beneficial effects of exercise intervention on systemic energy homeostasis.

Pilot Study on the Use of Untargeted Metabolomic Fingerprinting of Liquid-Cytology Fluids as a Diagnostic Tool of Malignancy for Thyroid Nodules

Although it is the gold standard for assessing the malignancy of thyroid nodules (TNs) preoperatively, the cytological analysis of fine-needle aspiration cytology (FNAC) samples results in 20-30% of cases in indeterminate lesions (ITNs). As two-thirds of these lesions will appear benign after diagnostic surgery, improved preoperative diagnostic methods need to be developed. In this pilot study, we evaluate if the metabolomic profiles of liquid-based (CytoRich^®) FNAC samples of benign and malignant nodules can allow the molecular diagnosis of TNs. We performed untargeted metabolomic analyses with CytoRich^® FNAC in a monocentric retrospective study. The cohort was composed of cytologically benign TNs, histologically benign or papillary thyroid carcinomas (PTCs) cytologically ITNs, and suspicious/malignant TNs histologically confirmed as PTCs. The diagnostic performance of the identified metabolomic signature was assessed using several supervised classification methods. Seventy-eight patients were enrolled in the study. We identified 7690 peaks, of which 2697 ions were included for further analysis. We selected a metabolomic signature composed of the top 15 metabolites. Among all the supervised classification methods, the supervised autoencoder deep neural network exhibited the best performance, with an accuracy of 0.957 (0.842-1), an AUC of 0.945 (0.833-1), and an F1 score of 0.947 (0.842-1). Here, we report a promising new ancillary molecular technique to differentiate PTCs from benign TNs (including among ITNs) based on the metabolomic signature of FNAC sample fluids. Further studies with larger cohorts are now needed to identify a larger number of biomarkers and obtain more robust signatures.

Diazo probe-based chemical isotope labeling assisted liquid chromatography-tandem mass spectrometry analysis for sensitive determination of amino acids in biofluids

Amino acids are important biomolecules and contribute to essential biological processes. Liquid chromatography tandem mass spectrometry (LC-MS) now is a powerful tool for the analysis of amino acid metabolites; however, the structural similarity and polarity of amino acids can lead to the poor chromatographic retention and low detection sensitivities. In this study, we used a pair of light and heavy isotopomers of diazo probes, d₀/d₅-2-(diazomethyl)-N-methyl-N-phenyl-benzamide (2-DMBA/d₅ -2-DMBA) to label amino acids. The paired MS probes of 2-DMBA and d₅ -2-DMBA carry diazo groups that can efficiently and specifically react with the carboxyl group on free amino acid metabolites under mild conditions. Benefiting from the transfer of the 2-DMBA/d₅ -2-DMBA to carboxyl group on amino acids, the ionization efficiencies of amino acids presented great enhancement during LC-MS analysis. The results suggested that the detection sensitivities of 17 amino acids increased by 9-133-fold upon 2-DMBA labeling, and the obtained limits of detection (LODs) of amino acids on-column ranged from 0.011 fmol-0.057 fmol. With the application of the developed method, we successfully achieved the sensitive and accurate detection of the 17 amino acids in microliter level of serum sample. Moreover, the contents of most amino acids were different in the serum from normal and B16F10-tumour mice, demonstrating that endogenous amino acids may play important roles in the regulation of tumors development. This developed method of chemical labeling of amino acids with diazo probes assisted LC-MS analysis provides a potentially valuable tool to investigate the relationships between amino acids metabolism and diseases.

Small molecule metabolites: discovery of biomarkers and therapeutic targets

Metabolic abnormalities lead to the dysfunction of metabolic pathways and metabolite accumulation or deficiency which is well-recognized hallmarks of diseases. Metabolite signatures that have close proximity to subject's phenotypic informative dimension, are useful for predicting diagnosis and prognosis of diseases as well as monitoring treatments. The lack of early biomarkers could lead to poor diagnosis and serious outcomes. Therefore, noninvasive diagnosis and monitoring methods with high specificity and selectivity are desperately needed. Small molecule metabolites-based metabolomics has become a specialized tool for metabolic biomarker and pathway analysis, for revealing possible mechanisms of human various diseases and deciphering therapeutic potentials. It could help identify functional biomarkers related to phenotypic variation and delineate biochemical pathways changes as early indicators of pathological dysfunction and damage prior to disease development. Recently, scientists have established a large number of metabolic profiles to reveal the underlying mechanisms and metabolic networks for therapeutic target exploration in biomedicine. This review summarized the metabolic analysis on the potential value of small-molecule candidate metabolites as biomarkers with clinical events, which may lead to better diagnosis, prognosis, drug screening and treatment. We also discuss challenges that need to be addressed to fuel the next wave of breakthroughs.

Mapping of Fatty Aldehydes in the Diabetic Rat Brain Using On-Tissue Chemical Derivatization and Air-Flow-Assisted Desorption Electrospray Ionization-Mass Spectrometry Imaging

Fatty aldehydes (FALs) are involved in various biological processes, and their abnormal metabolism is related to the occurrence and development of neurological diseases. Because of their low ionization efficiency, methods for in situ detection and mass spectrometry imaging (MSI) analysis of FALs remain underreported. On-tissue chemical tagging of hardly ionizable target analytes with easily ionized moieties can improve ionization efficiency and detection sensitivity in MSI experiments. In this study, an on-tissue chemical derivatization-air-flow-assisted desorption electrospray ionization-MSI method was developed to visualize FALs in the rat brain. The method showed high sensitivity and specificity, allowing the use of in situ high-resolution MS³ to identify FALs. The methodology was applied to investigate the region-specific distribution of FALs in the brains of control and diabetic encephalopathy (DE) rats. In DE rats, FALs were found to be significantly enriched in various brain regions, especially in the cerebral cortex, hippocampus, and amygdala. Thus, increased FAL levels and oxidative stress occurred in a region-dependent manner, which may contribute to cognitive function deficits in DE. In summary, we provide a novel method for the in situ detection of FALs in biological tissues as well as new insights into the potential pathogenesis of DE.

Engineering At-Home Dilution and Filtration Methods to Enable Paper-Based Colorimetric Biosensing in Human Blood with Cell-Free Protein Synthesis

Diagnostic blood tests can guide the administration of healthcare to save and improve lives. Most clinical biosensing blood tests require a trained technician and specialized equipment to process samples and interpret results, which greatly limits test accessibility. Colorimetric paper-based diagnostics have an equipment-free readout, but raw blood obscures a colorimetric response which has motivated diverse efforts to develop blood sample processing techniques. This work uses inexpensive readily-available materials to engineer user-friendly dilution and filtration methods for blood sample collection and processing to enable a proof-of-concept colorimetric biosensor that is responsive to glutamine in 50 µL blood drop samples in less than 30 min. Paper-based user-friendly blood sample collection and processing combined with CFPS biosensing technology represents important progress towards the development of at-home biosensors that could be broadly applicable to personalized healthcare.

Salivary Metabolomics for Systemic Cancer Diagnosis: A Systematic Review

Cancers are the leading cause of death worldwide. The most common cancers include breast, lung, and colorectum. Salivary metabolome profiling is a novel non-invasive method in oncological diagnosis. This systematic review was designed to answer the question "Are salivary metabolites reliable for the diagnosis of systemic cancers?". Following the inclusion and exclusion criteria, nineteen studies were included (according to PRISMA statement guidelines). Changes in salivary metabolome were most commonly determined in patients with breast cancer, gastrointestinal cancers, and lung cancer. Most studies involved unstimulated whole saliva as the diagnostic material, evaluated by different spectroscopic methods. Among the found saliva metabolites, the alterations in the metabolic pathways of amino acids and polyamines were most frequently observed, which showed significant predictive values in oncological diagnostics. The most frequently encountered risks of bias were the absence of data regarding blinding, sample size justification, and randomisation. In conclusion, salivary metabolites seem to be potentially reliable for detecting the most common systemic cancers. However, further research is desirable to confirm these outcomes and to detect new potential metabolic biomarkers in saliva.

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.

Metabolomics as a valid analytical technique in environmental exposure research: application and progress

BACKGROUND

In recent years, studies have shown that exposure to environmental pollutants (e.g., radiation, heavy metal substances, air pollutants, organic pollutants) is a leading cause of human non-communicable diseases. The key to disease prevention is to clarify the harmful mechanisms and toxic effects of environmental pollutants on the body. Metabolomics is a high-sensitivity, high-throughput omics technology that can obtain detailed metabolite information of an organism. It is a crucial tool for gaining a comprehensive understanding of the pathway network regulation mechanism of the organism. Its application is widespread in many research fields such as environmental exposure assessment, medicine, systems biology, and biomarker discovery.

AIM OF REVIEW

Recent findings show that metabolomics can be used to obtain molecular snapshots of organisms after environmental exposure, to help understand the interaction between environmental exposure and organisms, and to identify potential biomarkers and biological mechanisms.

KEY SCIENTIFIC CONCEPTS OF REVIEW

This review focuses on the application of metabolomics to understand the biological effects of radiation, heavy metals, air pollution, and persistent organic pollutants exposure, and examines some potential biomarkers and toxicity mechanisms.

Screening and validation of lymph node metastasis risk-factor genes in papillary thyroid carcinoma

BACKGROUND

Although most papillary thyroid carcinoma (PTC) cases have a good prognosis, some PTCs are more aggressive and are often accompanied by lymph node (LN) metastasis, a high recurrence rate, and poor prognosis. Distinguishing highly invasive metastatic PTC is an urgent problem that needs to be addressed clinically. We analyzed a microarray of metastasized PTC and validated it using quantitative reverse transcription PCR (RT-qPCR) and immunohistochemistry to identify biomarkers that can be used to assess the risk of PTC metastasis.

METHODS

The microarray of metastasized PTC was screened using the Gene Expression Omnibus (GEO) database. The differences between cancer and normal tissues were analyzed using the official GEO tool: GEO2R. Gene expression profile data (GEPIA) were used to verify the expression of differential genes in large samples and to analyze their correlation. The Kaplan-Meier plotter (KM-plotter) database was used for the analysis of genes potentially related to survival. RT-qPCR was used to check the expression of risk factor genes in pathological sections from PTC patients with clinical LN metastasis. Immunohistochemistry was used to verify the expression of core risk-associated genes.

RESULTS

Fourteen PTC metastasis-associated genes were identified. In metastasized PTC, CLDN1, LRP4, LRRK2, and TENM1 were highly expressed, whereas DIO1, DPP6, HGD, IPCEF1, MT1F, SLC26A4, SLC26A7, SPX, TFF3, and TPO were expressed at low levels, compared to expression in normal tissues. DIO1, HGD, SLC26A4, and TPO were found to be the core risk genes in the PTC metastatic risk set. Results based on clinical samples showed that the expression differences for metastasis risk-associated genes were consistent with the bioinformatics analysis results.

CONCLUSIONS

Fourteen differentially expressed genes (CLDN1, LRP4, LRRK2, TENM1, DIO1, DPP6, HGD, IPCEF1, MT1F, SLC26A4, SLC26A7, SPX, TFF3, TPO) are associated with an increased risk of PTC metastasis, and DIO1, HGD, SLC26A4, and TPO are the key risk-associated genes in this set that might affect the occurrence and development of PTC through iodine metabolism. These genes could provide a reference for clinical metastatic PTC risk evaluation and treatment.