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Background N6-methyladenosine (m 6 A) modification is the most common chemical modification in mammalian mRNAs, and it plays important roles by regulating several cellular processes. Previous studies report that m 6 A is implicated in modulating tumorigenesis and progression. However, dysregulation of m 6 A modification and effect of m 6 A demethylase fat-mass and obesity-associated protein (FTO) on glucose metabolism has not been fully elucidated in papillary thyroid cancer (PTC). Methods Quantitative real-time PCR (qRT-PCR), western blotting and immunohistochemistry were performed to explore the expression profile of FTO in PTC tissues and adjacent non-cancerous thyroid tissues. Effects of FTO on PTC glycolysis and growth were investigated through in vitro and in vivo experiments. Mechanism of FTO-mediated m 6 A modification was explored through transcriptome-sequencing (RNA-seq), methylated RNA immunoprecipitation sequencing (MeRIP-seq), MeRIP-qPCR, luciferase reporter assays, RNA stability assay and RNA immunoprecipitation assay. Results FTO expression was significantly downregulated in PTC tissues. Functional analysis showed that FTO inhibited PTC glycolysis and growth. Further analyses were conducted to explore FTO-mediated m 6 A modification profile in PTC cells and Apolipoprotein E (APOE) was identified as the target gene for FTO-mediated m 6 A modification using RNA-seq and MeRIP-seq. FTO knockdown significantly increased APOE mRNA m 6 A modification and upregulated its expression. FTO-mediated m 6 A modification of APOE mRNA was recognized and stabilized by the m 6 A reader IGF2BP2. The findings showed that APOE also promoted tumor growth through glycolysis in PTC. Analysis showed that FTO/APOE axis inhibits PTC glycolysis by modulating IL-6/JAK2/STAT3 signaling pathway. Conclusion FTO acts as a tumor suppressor to inhibit tumor glycolysis in PTC. The findings of the current study showed that FTO inhibited expression of APOE through IGF2BP2-mediated m 6 A modification and may inhibit glycolytic metabolism in PTC by modulating IL-6/JAK2/STAT3 signaling pathway, thus abrogating tumor growth.

Emerging evidence has indicated that m5C modification plays a vital role in cancer development. However, the function of m5C-lncRNAs in PTC has never been reported. This study aims to explore the regulation mechanism of m5C RNA methylation-related long noncoding RNAs (m5C-lncRNAs) in papillary thyroid cancer (PTC). Bioinformatics analysis was used to investigate the role of m5C-lncRNAs in the prognosis and tumor immune microenvironment of PTC. Subsequently, we preliminarily verified the regulation mechanisms of m5C-lncRNAs in vivo and in vitro experiments. A total of six m5C-lncRNAs and five immune cell types were selected to construct the risk score and immune risk score (IRS) model, respectively. Patients with a high-risk score had a worse prognosis and the ROC indicated a reliable prediction performance (AUC = 0.796). As expected, the ESTIMATE and immune scores were higher ( P  < 0.001) and the tumor purity ( P  < 0.05) was significantly lower in the low-risk subgroup. CIBERSORT analysis showed Tregs, M0 macrophages, dendritic cells resting, and eosinophils were positively correlated to the risk score. Moreover, the expression levels of PD-1, PD-L1, CTLA-4, TIM-3, LAG-3, and KLRB1 were lower in the high-risk subgroup. Importantly, patients in high-risk subgroup tended to have a better response to immunotherapy than those in low-risk subgroup ( P  = 0.022). Similar to the above risk score, the IRS model also showed favorable prognosis predictive performance (AUC = 0.764). An integrated nomogram combining risk score, IRS, and age exhibited good prognostic predictive performance. Additionally, we validate the downregulation of PPP1R12A-AS1 promotes proliferation and metastasis by activating the MAPK signaling pathway. Our research confirms that m5C-lncRNAs not only contribute to evaluating the prognosis of patients with PTC but also help predict immune cell infiltration and immunotherapy response.

Background Few highly accurate tests can diagnose central lymph node metastasis (CLNM) of papillary thyroid cancer (PTC). Genetic sequencing of tumor tissue has allowed the targeting of certain genetic variants for personalized cancer therapy development. Methods This study included 488 patients diagnosed with PTC by ultrasound-guided fine-needle aspiration biopsy, collected clinicopathological data, analyzed the correlation between CLNM and clinicopathological features using univariate analysis and binary logistic regression, and constructed prediction models. Results Binary logistic regression analysis showed that age, maximum diameter of thyroid nodules, capsular invasion, and BRAF V600E gene mutation were independent risk factors for CLNM, and statistically significant indicators were included to construct a nomogram prediction model, which had an area under the curve (AUC) of 0.778. A convolutional neural network (CNN) prediction model built with an artificial intelligence (AI) deep learning algorithm achieved AUCs of 0.89 in the training set and 0.78 in the test set, which indicated a high prediction efficacy for CLNM. In addition, the prediction models were validated in the subclinical metastasis and clinical metastasis groups with high sensitivity and specificity, suggesting the broad applicability of the models. Furthermore, CNN prediction models were constructed for patients with nodule diameters less than 1 cm. The AUCs in the training set and test set were 0.87 and 0.76, respectively, indicating high prediction efficacy. Conclusions The deep learning-based multifeature integration prediction model provides a reference for the clinical diagnosis and treatment of PTC.

Mesenchymal stem-cell-derived extracellular vesicles (MSC-EVs) have been increasingly investigated for cancer therapy and drug delivery, and they offer an advanced cell-free therapeutic option. However, their overall effects and efficacy depend on various factors, including the MSC source and cargo content. In this study, we isolated EVs from the conditioned medium of human immature dental pulp stem cells (hIDPSC-EVs) and investigated their effects on two papillary thyroid cancer (PTC) cell lines (BCPAP and TPC1). We observed efficient uptake of hIDPSC-EVs by both PTC cell lines, with a notable impact on gene regulation, particularly in the Wnt signaling pathway in BCPAP cells. However, no significant effects on cell proliferation were observed. Conversely, hIDPSC-EVs significantly reduced the invasive capacity of both PTC cell lines after 120 h of treatment. These in vitro findings suggest the therapeutic potential of hIDPSC-EVs in cancer management and emphasize the need for further research to develop novel and effective treatment strategies. Furthermore, the successful internalization of hIDPSC-EVs by PTC cell lines underscores their potential use as nanocarriers for anti-cancer agents.

Bisphenol A (BPA) is a prevalent environmental contaminant found in plastics and known for its endocrine-disrupting properties, posing risks to both human health and the environment. Despite its widespread presence, the impact of BPA on papillary thyroid cancer (PTC) progression, especially under realistic environmental conditions, is not well understood. This study examined the effects of BPA on PTC using a 3D thyroid papillary tumor spheroid model, which better mimicked the complex interactions within human tissues compared to traditional 2D models. Our findings demonstrated that BPA, at environmentally relevant concentrations, could induce significant changes in PTC cells, including a decrease in E-cadherin expression, an increase in vimentin expression, and reduced thyroglobulin (TG) secretion. These changes suggest that BPA exposure may promote epithelial–mesenchymal transition (EMT), enhance invasiveness, and reduce cell differentiation, potentially complicating treatment, including by increasing resistance to radioiodine therapy. This research highlights BPA’s hazardous nature as an environmental contaminant and emphasizes the need for advanced in vitro models, like 3D tumor spheroids, to better assess the risks posed by such chemicals. It provides valuable insights into the environmental implications of BPA and its role in thyroid cancer progression, enhancing our understanding of endocrine-disrupting chemicals.

AimsTo study the correlation between clinicopathological risk factors and the risk for intervention-requiring cancer recurrence in patients with small papillary thyroid cancers (sPTCs).Materials and methodsRecords for 397 patients with sPTC (T1 ≤ 20mm) were obtained from the Scandinavian Quality Register for Thyroid, Parathyroid and Adrenal Surgery (SQRTPA) between 2010 and 2016. Follow-up time was at least 5 years. Data regarding intervention-requiring cancer recurrence were obtained from patient medical records and analysed regarding lymph node (LN) status (N0, N1a and N1b) and recurrence.ResultsAge was significantly lower in the N1a and N1b groups compared to N0 (45 vs. 40.5 vs. 49 years, respectively; p = 0.002). Tumour size was smaller in the N1a group compared to N1b group (9 vs. 11.8 mm; p <0.01). The mean number of metastatic LNs at initial surgery was higher in the N1b compared to N1a group (6.6 vs. 3; p = 0.001), and in the recurrent compared to the non-recurrent group (7 versus 3.9; p <0.01). The recurrence rate was higher in the N1b group than the N1a and N0 groups (25% vs. 2.4% vs. 1.4%, respectively; p = 0.001).ConclusionsLymph node stage N1b at diagnosis, and having five or more metastatic nodes, are strong risk factors for cancer recurrence and decreased disease-free survival in sPTC. The management of patients with sPTC should include thorough lymph node mapping for optimal treatment and individual risk stratification.

BackgroundThyroid tissue has a special immune microenvironment that is not well characterized. Whether immune cells have a prognostic value in the recurrence of papillary thyroid cancer (PTC) needs further investigation.MethodsMultinodular non-toxic goiter (MNG) was taken as normal tissue for the difficulty in obtaining completely normal thyroid tissue (normal thyroid function, no thyroiditis, and no nodules). We compared the composition of mononuclear cells (MNCs) in peripheral blood and thyroid tissues from MNG and PTC patients by high-dimensional flow cytometry profiling and verified the results by multiplex immunohistochemistry. The recurrence rates of PTC patients with different CD8+T cell subset signatures were compared using TCGA database.ResultsWe observed that the immune cell composition of MNG was different from that in peripheral blood. Thyroid tissue contains higher percentages of T cells and NK cells. Moreover, the percentages of memory T cells and Treg cells were higher in thyroid than in peripheral blood and increased in PTC tumors. We further focused on the antitumoral CD8+T cells and found that the expression patterns of PD-1, CD39, and CD103 on CD8+T cells were different between MNG and PTC. Importantly, we found higher percentages of PD-1+CD39+CD103+CD8+T and PD-1+CD39+CD103-CD8+T cells in PTC tumor tissues from recurrent patients than non-recurrent patients. By analyzing PTC data from TCGA database, we found that the expression patterns of these molecules were associated with different pathologic types and genders among PTC patients. Moreover, patients with PD-1hiCD39loCD103hiCD8hi, PD-1hiCD39hiCD103loCD8hi, and PD-1loCD39hiCD103hiCD8hi expression patterns have a higher 10-year recurrence-free survival.ConclusionThe immune microenvironment in MNG tissue is distinct from that in peripheral blood and paratumor tissue. More memory CD8+T cells were detected in PTC, and expression patterns of PD-1, CD39, and CD103 on CD8+T cells were significantly different in physiology and gender and associated with the recurrence rate of PTC. These observations indicate that CD8+T cell signatures may be useful prognostic markers for PTC recurrence.

Thyroid cancer remains the most common endocrine malignancy worldwide, and its incidence has steadily increased over the past four years. Papillary Thyroid Cancer (PTC) is the most common differentiated thyroid cancer, accounting for 80–85% of all thyroid cancers. Mitochondrial proteins (MRPs) are an important part of the structural and functional integrity of the mitochondrial ribosomal complex. It has been reported that MRPL9 is highly expressed in liver cancer and promotes cell proliferation and migration, but it has not been reported in PTC. In the present study we found that MRPL9 was highly expressed in PTC tissues and cell lines, and lentivirus-mediated overexpression of MRPL9 promoted the proliferation and migration ability of PTC cells, whereas knockdown of MRPL9 had the opposite effect. The interaction between MRPL9 and GGCT (γ-glutamylcyclotransferase) was found by immunofluorescence and co-immunoprecipitation experiments (Co-IP). In addition, GGCT is highly expressed in PTC tissues and cell lines, and knockdown of GGCT/MRPL9 in vivo inhibited the growth of subcutaneous xenografts in nude mice and inhibited the formation of lung metastases. Mechanistically, we found that knockdown of GGCT/MRPL9 inhibited the MAPK/ERK signaling pathway. In conclusion, our study found that the interaction of GGCT and MRPL9 modulates the MAPK/ERK pathway, affecting the proliferation and migration of PTC cells. Therefore, GGCT/MRPL9 may serve as a potential biomarker for PTC monitoring and PTC treatment.

Background Thyroid cancer is the most common malignancy of endocrine system, and papillary thyroid cancer (PTC) is the most common subtype. E2F8, a novel identified E2F family member, was reported to associate with progression of several human cancers, however, its clinical significance and biological role in PTC remain unknown. Methods E2F8 or miR-144 expression profiles in PTC tissues were obtained from The Cancer Genome Atlas (TCGA) datasets, and the correlation of E2F8 expression with clinicopathological features was analyzed in a cohort PTC patients. The effects of E2F8 and miR-144 on proliferation were evaluated both in vitro and in vivo. Luciferase reporter assay was used to determine E2F8 was a direct target of miR-144. Results E2F8 was widely upregulated in PTC tissues, and overexpression of E2F8 was correlated with more aggressive clinicopathological features. In contrast, we found that silence of E2F8 significantly suppressed proliferation of PTC cells by inducing G1-phase arrest via downregulating Cyclin D1 (CCND1) both in vitro and in vivo. We also identified miR-144 as a tumor-suppressive microRNA that directly targeted E2F8 to inhibit proliferation of PTC cells in vitro and in vivo. Moreover, miR-144 was widely downregulated in PTC, where its expression correlated inversely with E2F8 expression. Conclusions Our results demonstrate a new miR-144/E2F8/CCND1 regulatory axis controlling PTC development, which may offer a potential prognostic and therapeutic strategy. Trial registration No applicable.

Background Tall cell variant (TCV) of papillary thyroid cancer (PTC) is the most common aggressive subtype of PTC. The factors that affect survival of patients with TCV remain unclear. We aimed to develop a model to predict the cancer-specific survival (CSS). Methods A total of 1615 patients diagnosed with TCV between 2004 and 2016 were identified from the Surveillance, Epidemiology, and End Results (SEER) database and randomized into training and validation cohorts (7:3). A predictive nomogram for predicting CSS was constructed by Cox proportional hazards regression and validated by concordance index (C-index), calibration curve, and decision curve analyses (DCA). A risk classification system was built based on the total nomogram scores of each case. Results A nomogram was constructed including five independent prognostic factors (age, tumor size, T stage, M stage, and extent of surgery) associated with CSS in TCV patients. Various validations proved that the nomogram model had good consistency and discrimination for TCV prognosis. The risk classification system could perfectly classify TCV patients into three risk groups with significantly different CSS. Compared with traditional AJCC TNM staging system, the nomogram could better predict CSS in TCV patients. Conclusions A nomogram and corresponding risk classification system were developed for predicting CSS in TCV patients. The model has excellent performance and can be used to help clinicians make accurate prognostic assessment and individualized treatment.