This study examined metabolite profile differences between serum samples of thyroid papillary carcinoma (PTC) patients and healthy controls, aiming to identify candidate biomarkers and pathogenesis pathways in this cancer type. Serum samples were collected from PTC patients (n = 80) and healthy controls (n = 80). Using principal component analysis (PCA), partial least squares discrimination analysis(PLS-DA), orthogonal partial least square discriminant analysis (OPLS-DA), t-tests, and the volcano plot, a model of abnormal metabolic pathways in PTC was constructed. PCA, PLS-DA, and OPLS-DA analysis revealed differences in serum metabolic profiles between the PTC and control group. OPLS-Loading plot analysis, combined with Variable importance in the projection (VIP)>1, Fold change (FC) > 1.5, and p < 0.05 were used to screen 64 candidate metabolites. Among them, 22 metabolites, including proline betaine, taurocholic acid, L-phenylalanine, retinyl beta-glucuronide, alpha-tocotrienol, and threonine acid were upregulated in the PTC group; meanwhile, L-tyrosine, L-tryptophan, 2-arachidonylglycerol, citric acid, and other 42 metabolites were downregulated in this group. There were eight abnormal metabolic pathways related to the differential metabolites, which may be involved in the pathophysiology of PTC. Six metabolites yielded an area under the receiver operating curve of >0.75, specifically, 3-hydroxy-cis-5-tetradecenoylcarnitine, aspartylphenylalanine, l-kynurenine, methylmalonic acid, phenylalanylphenylalanine, and l-glutamic acid. The Warburg effect was observed in PTC. The levels of 3-hydroxy-cis-5-tetradecenoylcarnitine, aspartylphenylalanine, l-kynurenine, methylmalonic acid, phenylalanine, and L-glutamic acid may help distinguish PTC patients from healthy controls. Aspartic acid metabolism, glutamic acid metabolism, urea cycle, and tricarboxylic acid cycle are involved in the mechanism of PTC.

Background: Hepatocellular carcinoma (HCC) is a particularly prevalent type of liver cancer and is one of the deadliest malignancies in Asia. Tangeretin is a biological compound extracted from traditional Chinese herbs and has been shown to have potential antitumour properties; however, its mechanism remains largely unknown. Therefore, we sought to determine the role of Tangeretin in HepG2 cells subjected to antitumour treatment. Materials and methods: Cell proliferation was quantified using CCK-8, EdU and colony formation assays, and cell migration was quantified using transwell migration and wound healing assays. Protein expression was assessed using Western blot analysis. Small interfering RNA was used to interfer protein expression. Immunoprecipitation was performed to detect the protein-protein interactions. Results: Tangeretin decreased cell proliferation and increased G2/M arrest. Tangeretin decreased cell migration. Tangeretin increased the LC3II/LC3I ratio and decreased p62 expression in HepG2 cells. Furthermore, the knockdown of BECLIN1 expression in HepG2 cells partially converted the Tangeretin-induced inhibition of proliferation, migration and autophagy. In addition, Tangeretin activated the JNK1/Bcl-2 pathway and disturbed the interaction between Bcl-2 and BECLIN1. Together, our findings demonstrate that Tangeretin inhibited the proliferation and migration of HepG2 cells through JNK/Bcl-2/BECLIN1 pathway-mediated autophagy. Conclusion: Our study contributes to the understanding of the inhibitory mechanism of Tangeretin on HCC development.

Oxidative stress is the main cause of acute myocardial infarction (AMI), which is related to the disorder of the regulation of Bmal1 on the redox state. HSPB1 form homologous‐oxidized HSPB1 (homooxidized HSPB1) to resist oxidative damage via S‐thiolated modification. However, it is still unclarified whether there is an interaction between the circadian clock and HSPB1 in myocardial injury. A total of 118 AMI patients admitted and treated in our hospital from Sep. 2019 to Sep. 2020 were selected to detect the plasma HSPB1 expression and the redox state. We divided the AMI patients into three subgroups: morning‐onset AMI (5 : 00 am to 8 : 00 am; Am‐subgroup, n = 38), noon‐onset AMI (12 : 00 pm to 15 : 00; Pm‐subgroup, n = 45), and night‐onset AMI (20 : 00 pm to 23 : 00 pm; Eve‐subgroup, n = 35) according to the circadian rhythm of onset. The Am‐subgroup had remarkably higher cardiac troponin I (cTnI), creatine kinase MB (CK‐MB), and B‐type natriuretic peptide (BNP) but lower left ventricular ejection fraction (LVEF) than the Pm‐subgroup and Eve‐subgroup. Patients complicated with cardiogenic shock were significantly higher in the Am‐subgroup than in the other two groups. The homooxidized HSPB1 in plasma markedly decreased in the Am‐subgroup. The HSPB1C141S mutant accelerated H9c2 cell apoptosis, increased reactive oxygen species (ROS), and decreased reduced‐glutathione (GSH) and the ratio of reduced‐GSH and GSSG during oxidative stress. Importantly, we found that the redox state of HSPB1 was consistent with the oscillatory rhythm of Bmal1 expression in normal C57B/L mice. The circadian rhythm disorder contributed to decrease Bmal1 and homooxidized HSPB1 in cardiomyocytes of C57BL/6 mice. In addition, Bmal1 and homooxidized HSPB1 decreased in neonatal rat cardiomyocytes exposed to H₂O₂. Knockdown of Bmal1 led to significant attenuation in homooxidized HSPB1 expression, whereas overexpression of Bmal1 increased homooxidized HSPB1 expression in response to H₂O₂. Our findings indicated that the homooxidized HSPB1 reduced probably the AMI patients’ risk of shock and target organ damage, which was associated with Bmal1 regulating the redox state of HSPB1.

Amatoxin poisoning leads to over 90% of deaths in mushroom poisoning. The objective of present study was to identify the potential metabolic biomarkers for early diagnosis of amatoxin poisoning. Serum samples were collected from 61 patients with amatoxin poisoning and 61 healthy controls. An untargeted metabolomics analysis was performed using the ultra-high-performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry (UPLC-QTOF-MS/MS). Multivariate statistical analysis revealed that the patients with amatoxin poisoning could be clearly separated from healthy controls on the basis of their metabolic fingerprints. There were 33 differential metabolites including 15 metabolites up-regulated metabolites and 18 down-regulated metabolites in patients with amatoxin poisoning compared to healthy controls. These metabolites mainly enriched in the lipid metabolism and amino acid metabolism pathways, such as Glycerophospholipid metabolism, Sphingolipid metabolism, Phenylalanine tyrosine and typtophan biosynthesis, Tyrosine metabolism, Arginine and proline metabolism, which may serve important roles in the amatoxin poisoning. Among the differential metabolites, a total of 8 significant metabolic markers were identified for discriminating patients with amatoxin poisoning from healthy controls, including Glycochenodeoxycholate-3-sulfate (GCDCA-S), 11-Oxo-androsterone glucuronide, Neomenthol-glucuronide, Dehydroisoandrosterone 3-glucuronide, Glucose 6-phosphate (G6P), Lanthionine ketimine, Glycerophosphocholine (GPC) and Nicotinamide ribotide, which achieved satisfactory diagnostic accuracy (AUC>0.8) in both discovery and validation cohorts. Strikingly, the Pearson's correlation analysis indicated that 11-Oxo-androsterone glucuronide, G6P and GCDCA-S were positively correlated with the liver injury induced by amatoxin poisoning. The findings of the current study may provide insight into the pathological mechanism of amatoxin poisoning and screened out the reliable metabolic biomarkers to contribute the clinical early diagnosis of amatoxin poisoning.

The anti-tumoral effects of metformin have been widely studied in several types of cancer, including thyroid cancer; however, the underlying molecular mechanisms remain poorly understood. As an oral hypoglycemic drug, metformin facilitates glucose catabolism and disrupts metabolic homeostasis. Metabolic reprogramming, particularly cellular glucose metabolism, is an important characteristic of malignant tumors. This study aimed to explore the therapeutic effects of metformin in thyroid cancer and the underlying metabolic mechanism. In the present study, it was shown that metformin reduced cell viability, invasion, migration, and EMT, and induced apoptosis and cell cycle G1 phase arrest in thyroid cancer. Transcriptome analysis demonstrated that the differentially expressed genes induced by metformin were involved in several signaling pathways including apoptosis singling pathways, TGF-β signaling, and cell cycle regulation in human thyroid cancer cell lines. In addition, the helicase activity of the CDC45-MCM2-7-GINS complex and DNA replication related genes such as RPA2, RAD51, and PCNA were downregulated in metformin-treated thyroid cancer cells. Moreover, metabolomics analysis showed that metformin-induced significant alterations in metabolic pathways such as glutathione metabolism and polyamine synthesis. Integrative analysis of transcriptomes and metabolomics revealed that metformin suppressed glycolysis by downregulating the key glycolytic enzymes LDHA and PKM2 and upregulating IDH1 expression in thyroid cancer. Furthermore, the anti-tumor role of metformin in thyroid cancer in vivo was shown. Together these results show that metformin plays an anti-tumor role by inhibiting glycolysis and restraining DNA replication in thyroid cancer.

Original Article Value of dissection of lymph nodes posterior to the right recurrent laryngeal nerve in patients with cN₀ papillary thyroid carcinoma Xiangyuqin Xiao, Yaqin Wu, Lianhong Zou, Yiru Chen, Chaojie Zhang