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Background Pyroptosis is a form of programmed cell death triggered by inflammasomes. However, the roles of pyroptosis-related genes in thyroid cancer (THCA) remain still unclear. Objective This study aimed to construct a pyroptosis-related signature that could effectively predict THCA prognosis and survival. Methods A LASSO Cox regression analysis was performed to build a prognostic model based on the expression profile of each pyroptosis-related gene. The predictive value of the prognostic model was validated in the internal cohort. Results A pyroptosis-related signature consisting of four genes was constructed to predict THCA prognosis and all patients were classified into high- and low-risk groups. Patients with a high-risk score had a poorer overall survival (OS) than those in the low-risk group. The area under the curve (AUC) of the receiver operator characteristic (ROC) curves assessed and verified the predictive performance of this signature. Multivariate analysis showed the risk score was an independent prognostic factor. Tumor immune cell infiltration and immune status were significantly higher in low-risk groups, which indicated a better response to immune checkpoint inhibitors (ICIs). Of the four pyroptosis-related genes in the prognostic signature, qRT-PCR detected three of them with significantly differential expression in THCA tissues. Conclusion In summary, our pyroptosis-related risk signature may have an effective predictive and prognostic capability in THCA. Our results provide a potential foundation for future studies of the relationship between pyroptosis and the immunotherapy response.

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The potential of soft-shelled turtle peptides (STP) against fatigue was evaluated. Mice orally supplemented with STP significantly increased the swimming time until tiredness by 35.4–57.1%. Although not statistically significant, STP increased muscle and thymus mass. In addition, the serum lactate, ammonia, blood urea nitrogen content and creatine kinase activity in STP-fed mice were dramatically decreased when compared to the control group. Furthermore, STP supplementation increased the reserves of liver glycogen and muscle glycogen, thus improved the energy metabolism system of mice. STP treatment contributed to increased superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) activities as well as a decrease in malondialdehyde (MDA), indicating an improvement in oxidative stress protection. The Western blot (WB) results indicated that the STP supplement effectively altered the expression of oxidative stress-related protein by modulating the NRF2/KEAP1 pathway. In summary, STP affected NRF2/KEAP1 levels in skeletal muscle, leading to antioxidant activity and a slower time to exhaustion during exercise.

Background Papillary thyroid carcinoma (PTC) is the most common type of thyroid cancer (TC), accounting for more than 80% of all cases. Ferroptosis is a novel iron-dependent and Reactive oxygen species (ROS) reliant type of cell death which is distinct from the apoptosis, necroptosis and pyroptosis. Considerable studies have demonstrated that ferroptosis is involved in the biological process of various cancers. However, the role of ferroptosis in PTC remains unclear. This study aims at exploring the expression of ferroptosis-related genes (FRG) and their prognostic values in PTC. Methods A ferroptosis-related gene signature was constructed using lasso regression analysis through the PTC datasets of the Cancer Genome Atlas (TCGA). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to investigate the bioinformatics functions of significantly different genes (SDG) of ferroptosis. Additionally, the correlations of ferroptosis and immune cells were assessed through the single-sample gene set enrichment analysis (ssGSEA) and CIBERSORT database. Finally, SDG were test in clinical PTC specimens and normal thyroid tissues. Results LASSO regression model was utilized to establish a novel FRG signature with 10 genes (ANGPTL7, CDKN2A, DPP4, DRD4, ISCU, PGD, SRXN1, TF, TFRC, TXNRD1) to predicts the prognosis of PTC, and the patients were separated into high-risk and low-risk groups by the risk score. The high-risk group had poorer survival than the low-risk group (p < 0.001). Receiver operating characteristic (ROC) curve analysis confirmed the signature's predictive capacity. Multivariate regression analysis identified the prognostic signature-based risk score was an independent prognostic indicator for PTC. The functional roles of the DEGs in the TGCA PTC cohort were explored using GO enrichment and KEGG pathway analyses. Immune related analysis demonstrated that the most types of immune cells and immunological function in the high-risk group were significant different with those in the low-risk group. Quantitative Real-Time Polymerase Chain Reaction (qRT-PCR) verified the SDG have differences in expression between tumor tissue and normal thyroid tissue. In addition, cell experiments were conducted to observe the changes in cell morphology and expression of signature’s genes with the influence of ferroptosis induced by sorafenib. Conclusions We identified differently expressed FRG that may involve in PTC. A ferroptosis-related gene signature has significant values in predicting the patients’ prognoses and targeting ferroptosis may be an alternative for PTC’s therapy.

Stromal and immune cells are major components of tumor microenvironment (TME) and affect the growth and development of thyroid carcinoma (THCA). However, data on the exact mechanisms that define the relationship between the TME and THCA remain scant. We calculated stromal and immune cells scores and the proportion of tumor-infiltrating immune cells (TICs) by CIBERSORT and ESTIMATE based on the THCA gene expression data from the Cancer Genome Atlas (TCGA). In addition, we evaluated differentially expressed genes (DEGs) from high- and low-score groups and performed functional enrichment analysis. Furthermore, our data show a significant correlation between plasma complement factor B (CFB) and PTC development and prognosis. Gene Set Enrichment Analysis (GSEA) demonstrated that the CFB was mainly enriched in immune response pathways. The expression of CFB was positively correlated with T cells CD8, Macrophages M1, Plasma cells, T cells CD4 memory activated, T cells follicular helper and T cells regulatory (Tregs), whereas negatively correlated with Eosinophils, Macrophages M0, Macrophages M2, Mast cells resting, T cells CD4 memory resting in the TME. Finally, the expression level of CFB was verified by other cohorts from Gene Expression Omnibus (GEO) database and quantitative Real-Time PCR (qRT-PCR) analyses, which was consistent with the results of bioinformatic analysis. Taken together, our data demonstrated that the CFB could be a prognostic marker for THCA and its expression influences the infiltration of immune cells.