Identifying potential metabolic tissue biomarkers for papillary thyroid cancer in different iodine nutrient regions

To elucidate the mechanism of "Scrophulariae Radix-Fritillaria" in goiter by integrated metabolomics and serum pharmaco-chemistry

The pharmacodynamic substances in "Scrophulariae Radix-Fritillaria" and the molecular mechanisms underlying its therapeutic effects against goiter were analyzed through metabolomics and serum pharmaco-chemistry. A rat model of goiter was established using propylthiouracil (PTU), and the animals were treated using "Scrophulariae Radix-Fritillaria." The efficacy of the drug pair was evaluated in terms of thyroid gland histopathology and blood biochemical indices. Serum and urine samples of the rats were analyzed by UPLC-Q-TOF/MS. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were performed to screen potential biomarkers in urine and the corresponding metabolic pathways. The blood components of "Scrophulariae Radix-Fritillaria" were also identified, and their correlation with urine biomarkers was analyzed in order to screen for potential bioactive compounds. "Scrophulariae Radix-Fritillaria" mitigated injury to thyroid tissues and normalized the levels of the thyroid hormones FT3, FT4, and TSH. We also identified 22 urine biomarkers related to goiter, of which 19 were regulated by "Scrophulariae Radix-Fritillaria." Moreover, urine biomarkers are involved in tryptophan metabolism, steroid hormone biosynthesis, and beta-alanine metabolism, and these pathways may be targeted by the drug pair. In addition, 47 compounds of "Scrophulariae Radix-Fritillaria" were detected by serum pharmacochemistry, of which nine components, namely, syringic acid, paeonol, cedrol, and cis-ferulic acid, fetisinine, aucubigenin, linolenic acid, ussuriedine, and 5-(methylsulfanyl)pentanenitrile, were identified as potential effective substances against goiter. To summarize, we characterized the chemical components and mechanisms of "Scrophulariae Radix-Fritillaria" involved in the treatment of goiter, and our findings provide an experimental basis for its clinical application.

Integrated proteomic and metabolomic analysis of plasma reveals regulatory pathways and key elements in thyroid cancer

Thyroid cancer (TC) is the most common endocrine malignancy with increasing incidence in recent years. Fine-needle aspiration biopsy (FNAB), as a gold standard for the initial evaluation of thyroid nodules, fails to cover all the cytopathologic conditions resulting in overdiagnosis. There is an urgent need for a better classification of thyroid cancer from benign thyroid nodules (BTNs). Here, data independent acquisition (DIA)-based proteomics and untargeted metabolomics in plasma samples of 10 patients with TC and 15 patients with BTNs were performed. Key proteins and metabolites were identified specific to TC, and an independent cohort was used to validate the potential biomarkers using enzyme-linked immunosorbent assay (ELISA). In total, 1429 proteins and 1172 metabolites were identified. Principal component analysis showed a strong overlap at the proteomic level and a significant discrimination at the metabolomic level between the two groups, indicating a more drastic disturbance in the metabolome of thyroid cancer. Integrated analysis of proteomics and metabolomics shows glycerophospholipid metabolism and arachidonic acid metabolism as key regulatory pathways. Furthermore, a multi-omics biomarker panel was developed consisting of LCAT, GPX3 and leukotriene B4. Based on the AUC value for the discovery set, the classification performance was 0.960. The AUC value of the external validation set was 0.930. Altogether, our results will contribute to the clinical application of potential biomarkers in the diagnosis of thyroid cancer.

Identifying and analyzing the key genes shared by papillary thyroid carcinoma and Hashimoto's thyroiditis using bioinformatics methods

Background

Hashimoto's thyroiditis (HT) is a chronic autoimmune disease that poses a risk factor for papillary thyroid carcinoma (PTC). The present study aimed to identify the key genes shared by HT and PTC for advancing the current understanding of their shared pathogenesis and molecular mechanisms.

Methods

HT- and PTC-related datasets (GSE138198 and GSE33630, respectively) were retrieved from the Gene Expression Omnibus (GEO) database. Genes significantly related to the PTC phenotype were identified using weighted gene co-expression network analysis (WGCNA). Differentially expressed genes (DEGs) were identified between PTC and healthy samples from GSE33630, and between HT and normal samples from GSE138198. Subsequently, functional enrichment analysis was performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Transcription factors and miRNAs regulating the common genes in PTC and HT were forecasted using the Harmonizome and miRWalk databases, respectively, and drugs targeting these genes were investigated using the Drug-Gene Interaction Database (DGIdb). The key genes in both GSE138198 and GSE33630 were further identified via Receiver Operating Characteristic (ROC) analysis. The expression of key genes was verified in external validation set and clinical samples using quantitative real-time polymerase chain reaction (qRT-PCR) and immunohistochemistry (IHC).

Results

In total, 690 and 1945 DEGs were associated with PTC and HT, respectively; of these, 56 were shared and exhibited excellent predictive accuracy in the GSE138198 and GSE33630 cohorts. Notably, four genes, Alcohol Dehydrogenase 1B (ADH1B), Active BCR-related (ABR), alpha-1 antitrypsin (SERPINA1), and lysophosphatidic acid receptor 5 (LPAR5) were recognized as key genes shared by HT and PTC. Subsequently, EGR1 was identified as a common transcription factor regulating ABR, SERPINA1, and LPAR5 expression. These findings were confirmed using qRT-PCR and immunohistochemical analysis.

Conclusion

Four (ADH1B, ABR, SERPINA1, and LPAR5) out of 56 common genes exhibited diagnostic potential in HT and PTC. Notably, this study, for the first time, defined the close relationship between ABR and HT/PTC progression. Overall, this study provides a basis for understanding the shared pathogenesis and underlying molecular mechanisms of HT and PTC, which might help improve patient diagnosis and prognosis.

Comprehensive serum metabolomics and network analysis to reveal the mechanism of gypenosides in treating lung cancer and enhancing the pharmacological effects of cisplatin

Gypenosides (GYP) exerted anticancer activity against various cancers. However, the mechanism of GYP against lung cancer (LC) in vivo remains unclear. This study aims to reveal the potential mechanism of GYP against LC and enhancing cisplatin efficacy using a comprehensive analysis of metabolomics, network analysis. Pharmacodynamic results showed that GYP inhibited tumor growth, reduced tumor volume and tumor weight, and alleviated pathological symptoms in Lewis tumor-bearing mice, and GYP could enhance the anti-LC effects of cisplatin. Using serum metabolomics methods, 53 metabolites were found to be significantly altered in the model group, and the levels of 23 biomarkers were significantly restored after GYP treatment. GYP-related metabolic pathways involved six pathways, including alpha-linolenic acid metabolism, glutathione metabolism, sphingolipid metabolism, glycerophospholipid metabolism, tryptophan metabolism, and primary bile acid biosynthesis. 57 genes associated with differential metabolites of GYP recovery and 7 genes of 11 saponins of GYP against LC were screened by network analysis, the STRING database was used to find the association between 57 genes and 7 genes, and a compound-intersection gene-metabolite related gene-metabolite-pathway network was constructed, and STAT3, MAPK14, EGFR and TYMS might be the crucial targets of GYP against LC. Western blot results showed that GYP restored the levels of STA3, MAPK14, EGFR, and TYMS in the model group, and GYP also restored the levels of STAT3 and MAPK14 in the cisplatin group, indicating that GYP might exert anti-LC effects and enhance the pharmacological effects of cisplatin through MAPK14/STAT3 signaling pathway. Our method revealed the effect and mechanism of GYP on LC and the pharmacological effects of GYP-enhanced chemotherapeutic agent cisplatin, which provided some reference for the development of anti-cancer drugs.

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.

Applications of spatially resolved omics in the field of endocrine tumors

Endocrine tumors derive from endocrine cells with high heterogeneity in function, structure and embryology, and are characteristic of a marked diversity and tissue heterogeneity. There are still challenges in analyzing the molecular alternations within the heterogeneous microenvironment for endocrine tumors. Recently, several proteomic, lipidomic and metabolomic platforms have been applied to the analysis of endocrine tumors to explore the cellular and molecular mechanisms of tumor genesis, progression and metastasis. In this review, we provide a comprehensive overview of spatially resolved proteomics, lipidomics and metabolomics guided by mass spectrometry imaging and spatially resolved microproteomics directed by microextraction and tandem mass spectrometry. In this regard, we will discuss different mass spectrometry imaging techniques, including secondary ion mass spectrometry, matrix-assisted laser desorption/ionization and desorption electrospray ionization. Additionally, we will highlight microextraction approaches such as laser capture microdissection and liquid microjunction extraction. With these methods, proteins can be extracted precisely from specific regions of the endocrine tumor. Finally, we compare applications of proteomic, lipidomic and metabolomic platforms in the field of endocrine tumors and outline their potentials in elucidating cellular and molecular processes involved in endocrine tumors.

Comprehensive Analysis of Metabolic Genes in Breast Cancer Based on Multi-Omics Data

Background: Reprogramming of cell metabolism is one of the most important hallmarks of breast cancer. This study aimed to comprehensively analyze metabolic genes in the initiation, progression, and prognosis of breast cancer.

Materials and Methods: Data from The Cancer Genome Atlas (TCGA) in breast cancer were downloaded including RNA-seq, copy number variation, mutation, and DNA methylation. A gene co-expression network was constructed by the weighted correlation network analysis (WGCNA) package in R. Association of metabolic genes with tumor-related immune cells and clinical parameters were also investigated.

Results: We summarized 3,620 metabolic genes and observed mutations in 2,964 genes, of which the most frequently mutated were PIK3CA (51%), TNN (26%), and KMT2C (15%). Four genes (AKT1, ERBB2, KMT2C, and USP34) were associated with survival of breast cancer. Significant association was detected in the tumor mutation burden (TMB) of metabolic genes with T stage (p = 0.045) and N stage (p = 0.004). Copy number variations were significantly associated with recurrence and prognosis of breast cancer. The co-expression network for differentially expressed metabolic genes by WGCNA suggested that the modules were associated with glycerophospholipid, arachidonic acid, carbon, glycolysis/gluconeogenesis, and pyrimidine/purine metabolism. Glycerophospholipid metabolism correlated with most of the immune cells, while arachidonic acid metabolism demonstrated a significant correlation with endothelial cells. Methylation and miRNA jointly regulated 14 metabolic genes while mutation and methylation jointly regulated PIK3R1.

Conclusion: Based on multi-omics data of somatic mutation, copy number variation, mRNA expression, miRNA expression, and DNA methylation, we identified a series of differentially expressed metabolic genes. Metabolic genes are associated with tumor-related immune cells and clinical parameters, which might be therapy targets in future clinical application.

Increased Epoxyeicosatrienoic Acids and Hydroxyeicosatetraenoic Acids After Treatment of Iodide Intake Adjustment and 1,25-Dihydroxy-Vitamin D3 Supplementation in High Iodide Intake-Induced Hypothyroid Offspring Rats

Aim: This study aimed to investigate the potential role of fatty acids in high iodide intake-induced hypothyroidism and its complications and also in the intervention of iodide intake adjustment and 1,25-dihydroxy-vitamin D3 [1,25(OH)2D3] supplementation. Methods: Pregnant rats were allocated to two groups, namely, normal iodide (NI, 7.5 μg/day) intake and 100 times higher-than-normal iodide (100 HI, 750 μg/day) intake. The offspring were continuously administered potassium iodide from weaning [i.e., postnatal day 21 (PN21)] to PN90. After PN90, the offspring were either administered iodide intake adjustment (7.5 μg/day) or 1,25(OH)2D3 supplementation (5 μg·kg-1·day-1), or both, for 4 weeks. Thyroid function tests (free triiodothyronine, free thyroxine, thyrotropin, thyroid peroxidase antibody, and thyroglobulin antibody), blood lipids (triglyceride, total cholesterol, free fatty acid, and low-density lipoprotein cholesterol), and vitamin D3 (VD3) levels were detected by ELISA. Cardiac function was measured by echocardiography. Blood pressure was measured using a non-invasive tail-cuff system. The serum fatty acids profile was analyzed by liquid chromatography-mass spectrometry. Results: In the offspring rats with continued 100 HI administration, the levels of 8,9-dihydroxyeicosatrienoic acid (8,9-DHET) and thromboxane B2 (TXB2) were decreased, while those of prostaglandin J2 (PGJ2), prostaglandin B2 (PGB2), 4-hydroxydocosahexaenoic acid (4-HDoHE), 7-HDoHE, 8-HDoHE, and 20-HDoHE were increased. Significant correlations were found between PGB2, 8,9-DHET, 7-HDoHE levels and thyroid dysfunction, between PGJ2, 20-HDoHE, PGB2, 8,9-DHET levels and cardiac dysfunction, between PGJ2, 20-HDoHE levels and hypertension, between 4-HDoHE, 8-HDoHE, TXB2 levels and dyslipidemia, and between PGB2 and decreased VD3 level. After the treatment of iodide intake adjustment and 1,25(OH)2D3 supplementation, the levels of 16-hydroxyeicosatetraenoic acids (16-HETE), 18-HETE, 5,6-epoxyeicosatrienoic acid (5,6-EET), 8,9-EET, 11,12-EET, 14,15-EET, PGE2, 5-oxo-ETE, and 15-oxo-ETE were increased. The significant associations between PGE2, 16-HETE, 18-HETE and improved thyroid function and also between 5,6-EET, 11,12-EET, 14,15-EET, 16-HETE, 15-oxo-ETE and attenuated dyslipidemia were detected. Conclusion: Increased levels of prostaglandins (PGs) and HDoHEs and decreased levels of 8,9-DHET and TXB2 might occur in the progression of cardiac dysfunction, hypertension, and dyslipidemia in high iodide intake-induced hypothyroidism. The increased levels of EETs and HETEs might help to ameliorate these complications after iodide intake adjustment and 1,25(OH)2D3 supplementation.