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.

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.

Objective: Papillary thyroid microcarcinoma (PTMC) comprises more than 50% of all newly detected cases of papillary thyroid carcinoma (PTC). High-volume lymph node metastasis (involving >5 lymph nodes) (hv-LNM) is associated with PTMC recurrence. In half of the clinically node-negative (cN0) PTMC patients, central lymph node metastasis (CLNM) is pathologically present. However, clinical risk factors for high-volume CLNM (hv-CLNM) in cN0 PTMC have not been defined well.Therefore, we aimed to obtain evidence for hv-CLNM risk factors in cN0 PTMC.Design: Data on patients who visited our hospital between January 2020 and December 2021 were collected; a preoperative diagnosis of cN0 and a postoperative pathological confirmation of PTMC were obtained. After filtering by inclusion versus exclusion criteria, the obtained data (N = 2268) were included in the meta-analysis. Relevant studies published as of 10 April 2022, were identified from the Web of Science, PubMed, WANFANG, and CNKI databases. These eligible studies were included in the meta-analysis and the association between clinicopathological factors and hv-CLNM in cN0 PTMC was assessed. SPSS and MetaXL were used for statistical analyses. Results:The meta-analysis included 10 previous studies (11,734 patients) and 2268 patients enroled in our hospital for a total of 14,002 subjects. The results of which suggested that younger age (<40, odds ratio [OR] = 3.28, 95% confidence interval[CI] = 2.75-3.92, p < .001 or <45 odds ratio [OR] = 2.93, 95% CI = 2.31-3.72, p < .001),