Exploring near-infrared autofluorescence properties in parathyroid tissue: an analysis of fresh and paraffin-embedded thyroidectomy specimens.

Significance: Near-infrared autofluorescence (NIRAF) utilizes the natural autofluorescence of parathyroid glands (PGs) to improve their identification during thyroid surgeries, reducing the risk of inadvertent removal and subsequent complications such as hypoparathyroidism. This study evaluates NIRAF's effectiveness in real-world surgical settings, highlighting its potential to enhance surgical outcomes and patient safety. Aim: We evaluate the effectiveness of NIRAF in detecting PGs during thyroidectomy and central neck dissection and investigate autofluorescence characteristics in both fresh and paraffin-embedded tissues. Approach: We included 101 patients diagnosed with papillary thyroid cancer who underwent surgeries in 2022 and 2023. We assessed NIRAF's ability to locate PGs, confirmed via parathyroid hormone assays, and involved both junior and senior surgeons. We measured the accuracy, speed, and agreement levels of each method and analyzed autofluorescence persistence and variation over 10 years, alongside the expression of calcium-sensing receptor (CaSR) and vitamin D. Results: NIRAF demonstrated a sensitivity of 89.5% and a negative predictive value of 89.1%. However, its specificity and positive predictive value (PPV) were 61.2% and 62.3%, respectively, which are considered lower. The kappa statistic indicated moderate to substantial agreement (kappa = 0.478; P < 0.001 ). Senior surgeons achieved high specificity (86.2%) and PPV (85.3%), with substantial agreement (kappa = 0.847; P < 0.001 ). In contrast, junior surgeons displayed the lowest kappa statistic among the groups, indicating minimal agreement (kappa = 0.381; P < 0.001 ). Common errors in NIRAF included interference from brown fat and eschar. In addition, paraffin-embedded samples retained stable autofluorescence over 10 years, showing no significant correlation with CaSR and vitamin D levels. Conclusions: NIRAF is useful for PG identification in thyroid and neck surgeries, enhancing efficiency and reducing inadvertent PG removals. The stability of autofluorescence in paraffin samples suggests its long-term viability, with false positives providing insights for further improvements in NIRAF technology.

Analysis of the Clinical Value of hsa_circ_0001955 in Papillary Thyroid Cancer Treated with 131 Iodine.

The prevalent histological variant within differentiated thyroid carcinoma is papillary thyroid carcinoma, also known as PTC. The study investigated the clinical performance of serum hsa_circ_0001955 in predicting the prognosis of PTC treated with radical thyroidectomy and iodine 131 nail clearance. The relative expression of serum circ_0001955 of PTC patients was detected before and after accepting radical thyroidectomy combined with 131I thyroid remnant ablation by RT-qPCR. Serum thyroglobulin (Tg) and thyroglobulin antibody (TgAb) levels were quantified by an automatic chemiluminescence immunoassay analyzer. Multivariate logistic regression analysis was employed to investigate the risk factors associated with the prognosis of PTC patients with postoperative 131I therapy. The serum circ_0001955 levels in 127 PTC patients were higher than that in 96 multinodular goiter patients and 110 healthy controls before treatment and had diagnostic values for PTC patients. After 131I treatment, serum circ_0001955 levels and Tg value have a correlation with potential recurrence (WBS positive). Serum circ_0001955, Tg, and TgAb value, and their combination may have diagnostic value in predicting recurrence. Serum circ_0001955 levels in patients with PTC after radical thyroidectomy and iodine 131 thyroidectomy may help predict recurrence.

New Small-Molecule SERCA Inhibitors Enhance Treatment Efficacy in Lenvatinib-Resistant Papillary Thyroid Cancer.

Papillary thyroid cancer (PTC) is one of the most treatable forms of cancer, with many cases being fully curable. However, resistance to anticancer drugs often leads to metastasis or recurrence, contributing to the failure of cancer therapy and, ultimately, patient mortality. The mechanisms underlying molecular differences in patients with metastatic or recurrent PTC, particularly those resistant to anticancer drugs through epigenetic reprogramming, remain poorly understood. Consequently, refractory PTC presents a critical challenge, and effective therapeutic strategies are urgently needed. Therefore, this study aimed to identify small-molecule inhibitors to enhance treatment efficacy in lenvatinib-resistant PTC. We observed an increase in sarco/endoplasmic reticulum calcium ATPase (SERCA) levels in patient-derived lenvatinib-resistant PTC cells compared with lenvatinib-sensitive ones, highlighting its potential as a therapeutic target. We subsequently identified two SERCA inhibitors [candidates 40 (isoflurane) and 42 (ethacrynic acid)] through in silico screening. These candidates demonstrated significant tumor shrinkage in a xenograft tumor model and reduced cell viability in patient-derived lenvatinib-resistant PTC cells when used in combination with lenvatinib. Our findings have potential clinical value for the development of new combination therapies to effectively target highly malignant, anticancer drug-resistant cancers.

HNRNPC modulates PKM alternative splicing via m6A methylation, upregulating PKM2 expression to promote aerobic glycolysis in papillary thyroid carcinoma and drive malignant progression.

The heterogeneous nuclear ribonucleoprotein C (HNRNPC) plays a crucial role in tumorigenesis, yet its role in papillary thyroid carcinoma (PTC) remains elusive. Herein, we elucidated the function and molecular mechanism of HNRNPC in PTC tumorigenesis and progression. Our study unveiled a significant upregulation of HNRNPC in PTC, and knockdown of HNRNPC markedly inhibited the proliferation, invasion, and metastasis of BCPAP cells. Furthermore, HNRNPC modulated PKM alternative splicing in BCPAP cells primarily through m6A modification. Additionally, by upregulating PKM2 expression, HNRNPC promoted aerobic glycolysis in BCPAP cells, thereby facilitating malignant progression in PTC. In summary, our findings demonstrate that HNRNPC regulates PKM alternative splicing through m6A methylation modification and promotes the proliferation, invasion and metastasis of PTC through glucose metabolism pathways mediated by PKM2. These discoveries provide new biomarkers for screening and diagnosing PTC patients and offer novel therapeutic targets for personalized treatment strategies.

Age Stratification and Prognostic Factor Analysis in Pediatric Differentiated Thyroid Cancer.

OBJECTIVES: Differentiated thyroid cancer (DTC) is rare in the pediatric population. It remains unclear whether younger children are at greater risk of more aggressive disease. We aimed to identify prognostic factors for aggressive pediatric DTC and to define an appropriate age stratification. METHODS: This retrospective cohort study included all patients aged 18 years or less who were treated for DTC between 1985 and 2021 in a tertiary medical center and were followed up for a minimum of 1.5 years after treatment. RESULTS: Seventy-eight patients were included, all diagnosed with papillary thyroid carcinoma: 30 (38.5%) low-risk, 21 (26.9%) intermediate-risk, and 27 (34.6%) high-risk according to the American Thyroid Association (ATA) risk stratification. The mean duration of follow-up was 11.8 ± 7.8 years. No evidence of disease was documented in 52 patients (66.7%) at 1-year post-treatment and 64 patients (82.1%) at the end of follow-up. On analysis by age, evidence of disease at 1-year post-treatment was found in 66.7% of children younger than 11 years, compared to 25.4% of older children (p = 0.002). There was no significant difference by age in evidence of disease at the last follow-up (p = 0.453). Patients aged <11 years at diagnosis were associated with more aggressive disease features on histopathologic examination, metastatic disease, and high ATA risk level. Patients aged <8 years were associated with more frequent bilateral disease and extrathyroidal extension. CONCLUSION: Pediatric DTC patients who are younger than 11 years at diagnosis have more aggressive disease features and a lower early remission rate than older patients. Nevertheless, their long-term outcome is satisfactory. LEVEL OF EVIDENCE: 4-retrospective cohort study Laryngoscope, 134:4818-4825, 2024.

Active surveillance of papillary thyroid carcinoma in Latin America: a scoping review.

Thyroid nodules are a very common finding and have a malignancy rate of 7%-15%. Some malignant nodules have an indolent behavior and may not affect mortality if left untreated. Active surveillance (AS) is a strategy to prevent overtreatment in patients with papillary thyroid microcarcinomas (PTMCs). This review was conducted to evaluate the status of AS for low-risk PTMC in Latin America, including cultural and logistical challenges, disease progression data, and financial viability. We searched PubMed (MEDLINE), SciELO, LILACS, and Web of Science for articles published after 2014 and enrolling adult Latin American patients. Articles cited in the selected studies were also retrieved. We analyzed the AS protocols, technical or logistical challenges, patient adherence, reasons for AS interruption, surgical conversion rates, duration of AS, and disease progression during AS in our region. Three articles were included in the analysis, all of which considered AS a viable option and reported tumor progression and outcomes similar to those reported in other countries. Neck ultrasound and serum levels of thyroglobulin, thyroid-stimulating hormone (TSH), thyroxine (T4), and antithyroglobulin antibodies were included in the follow-up. No cases of new distant metastases were reported, and the outcomes were favorable when surgery was required. Anxiety was the main reason for AS interruption. We conclude that AS can be an acceptable approach and is safe and effective in Latin America, although more prospective studies are needed to consolidate this strategy in our region. Adequate infrastructure, follow-up, and patient education, as well as multidisciplinary healthcare teams trained in conducting AS must be ensured for successful results.

Papillary thyroid carcinoma with a retropharyngeal cystic goitre extending into the pharyngeal mucosal space.

Retropharyngeal goitre extending to the oropharyngeal level is rare. We present a case of papillary thyroid carcinoma (PTC) with a retropharyngeal cystic goitre extending to the uvular level. A woman in her 50s presented with swelling of the neck and dyspnoea. CT and MRI findings showed a primary tumour in the left lobe of the thyroid gland and a retropharyngeal dumbbell-shaped cystic goitre extending to the uvular level. Total thyroidectomy, central neck dissection and tracheostomy were performed. During the surgery, we opened the retropharyngeal space, and no mass was found. The pathological findings showed that the primary PTC (pT2) was surrounded by benign lesions, including the dumbbell-shaped cystic goitre. We speculated that the dumbbell-shaped cystic goitre extended from the visceral space (VS) into the pharyngeal mucosal space (PMS) and reached the uvular level because the thyroid gland is in the VS, and the VS and PMS are continuous spaces.

[Diagnosis of lymph node metastases from papillary thyroid carcinoma by measuring thyroglobulin in the puncture needle. Calculation of optimal cut-off point in our series]. / Diagnóstico de metástasis ganglionares de carcinoma papilar tiroideo midiendo tiroglobulina en la aguja de la punción. Cálculo de punto de corte optimo en nuestra serie.

Fine-needle aspiration cytology (FNAC), used in suspicious cervical lymph nodes of unknown origin is frequently inconclusive and prone to false negatives. In order to evaluate the usefulness of measuring thyroglobulin in the washing with saline solution of the puncture needle for the diagnosis of metastasis of papillary carcinoma of the thyroid, an optimal thyroglobulin cutting point has to be calculated, being positive or negative depending on whether the thyroglobulin levels are higher or lower than the cutting point. We have retrospectively studied 33 patients (19 women and 14 men) with an average age of 49.3 years, with papillary carcinoma of the thyroid and suspected lymph node metastasis. Of them 16 (47.1%) had a positive FNAC. To determine thyroglobulin predictive capacity with regards to the metastasis of papillary carcinoma of the thyroid a ROC analysis was carried out with an under curve area UCA: 0.987 (CI 95%: 0.808-1.000) obtaining, using Youden's J statistic, 0.4 ng/ml as the thyroglobulin cutting point with best predictive capacity. The study of the relationship between thyroglobulin and the preservation/non-preservation of the thyroid showed statistically significant differences (P=.023). Our results validate 0.4 ng/ml of thyroglobulin as an optimal cutting point of the presence of metastasis of papillary carcinoma of the thyroid in lymph nodes. When reviewing the bibliography, a great diversity of cutting points may be found, which is explained mainly by the great inter-observer and inter-assay variability. That is why we recommend calculating each laboratory's own optimal cutting point; and determine in subsequent studies two cutting points depending on whether or not thyroid is preserved.

Computational Analysis Suggests That AsnGTT 3'-tRNA-Derived Fragments Are Potential Biomarkers in Papillary Thyroid Carcinoma.

Transfer-RNA-derived fragments (tRFs) are a novel class of small non-coding RNAs that have been implicated in oncogenesis. tRFs may act as post-transcriptional regulators by recruiting AGO proteins and binding to highly complementary regions of mRNA at seed regions, resulting in the knockdown of the transcript. Therefore, tRFs may be critical to tumorigenesis and warrant investigation as potential biomarkers. Meanwhile, the incidence of papillary thyroid carcinoma (PTC) has increased in recent decades and current diagnostic technology stands to benefit from new detection methods. Although small non-coding RNAs have been studied for their role in oncogenesis, there is currently no standard for their use as PTC biomarkers, and tRFs are especially underexplored. Accordingly, we aim to identify dysregulated tRFs in PTC that may serve as biomarker candidates. We identified dysregulated tRFs and driver genes between PTC primary tumor samples (n = 511) and adjacent normal tissue samples (n = 59). Expression data were obtained from MINTbase v2.0 and The Cancer Genome Atlas. Dysregulated tRFs and genes were analyzed in tandem to find pairs with anticorrelated expression. Significantly anticorrelated tRF-gene pairs were then tested for potential binding affinity using RNA22-if a heteroduplex can form via complementary binding, this would support the hypothesized RNA silencing mechanism. Four tRFs were significantly dysregulated in PTC tissue (p < 0.05), with only AsnGTT 3'-tRF being upregulated. Binding affinity analysis revealed that tRF-30-RY73W0K5KKOV (AsnGTT 3'-tRF) exhibits sufficient complementarity to potentially bind to and regulate transcripts of SLC26A4, SLC5A8, DIO2, and TPO, which were all found to be downregulated in PTC tissue. In the present study, we identified dysregulated tRFs in PTC and found that AsnGTT 3'-tRF is a potential post-transcriptional regulator and biomarker.

Understanding the Dosage-Dependent Role of Dicer1 in Thyroid Tumorigenesis.

Tumors originating from thyroid follicular cells are the most common endocrine tumors, with rising incidence. Despite a generally good prognosis, up to 20% of patients experience recurrence and persistence, highlighting the need to identify the underlying molecular mechanisms. Dicer1 has been found to be altered in papillary thyroid cancer (PTC). Studies suggest that Dicer1 functions as a haploinsufficient tumor suppressor gene: partial loss promotes tumorigenesis, while complete loss prevents it. To investigate the effects of partial or total Dicer1 loss in PTC in vitro, we generated stable Dicer1 (+/-) cell lines from TPC1 using CRISPR-Cas9, though no Dicer1 (-/-) lines could be produced. Therefore, siRNA against Dicer1 was transfected into Dicer1 (+/-) cell lines to further decrease its expression. Transcriptomic analysis revealed changes in proliferation and cell locomotion. BrdU staining indicated a slow-down of the cell cycle, with fewer cells in S phase and more in G0-G1-phase. Additionally, transwell assays showed decreased invasion and migration after Dicer1 knockdown by siRNA. Moreover, Dicer1 overexpression led to decreased proliferation, invasion, and increased apoptosis. Our findings deepen the understanding of Dicer1's role in thyroid cancer, demonstrating that both complete elimination and overexpression of Dicer1 inhibit thyroid oncogenesis, highlighting Dicer1 as a promising target for novel therapeutic strategies.

Descriptive Analysis of Common Fusion Mutations in Papillary Thyroid Carcinoma in Hungary.

Thyroid cancer is the most common type of endocrine malignancy. Papillary thyroid carcinoma (PTC) is its predominant subtype, which is responsible for the vast majority of cases. It is true that PTC is a malignant tumor with a very good prognosis due to effective primary therapeutic approaches such as thyroidectomy and radioiodine (RAI) therapy. However, we are often required to indicate second-line treatments to eradicate the tumor properly. In these scenarios, molecular therapies are promising alternatives, especially if specifically targetable mutations are present. Many of these targetable gene alterations originate from gene fusions, which can be found using molecular diagnostics like next-generation sequencing (NGS). Nonetheless, molecular profiling is far from being a routine procedure in the initial phase of PTC diagnostics. As a result, the mutation status, except for BRAF V600E mutation, is not included in risk classification algorithms either. This study aims to provide a comprehensive analysis of fusion mutations in PTC and their associations with clinicopathological variables in order to underscore certain clinical settings when molecular diagnostics should be considered earlier, and to demonstrate yet unknown molecular-clinicopathological connections. We conducted a retrospective fusion mutation screening in formalin-fixed paraffin-embedded (FFPE) PTC tissue samples of 100 patients. After quality evaluation by an expert pathologist, RNA isolation was performed, and then NGS was applied to detect 23 relevant gene fusions in the tumor samples. Clinicopathological data were collected from medical and histological records. To obtain the most associations from the multivariate dataset, we used the d-correlation method for our principal component analysis (PCA). Further statistical analyses, including Chi-square tests and logistic regressions, were performed to identify additional significant correlations within certain subsets of the data. Fusion mutations were identified in 27% of the PTC samples, involving nine distinct genes: RET, NTRK3, CCDC6, ETV6, MET, ALK, NCOA4, EML4, and SQSTM1. RET and CCDC6 fusions were associated with type of thyroidectomy, RAI therapy, smaller tumor size, and history of Hashimoto's disease. NCOA4 fusion correlated with sex, multifocality, microcarcinoma character, history of goiter, and obstructive pulmonary disease. EML4 fusion was also linked with surgical procedure type and smaller tumor size, as well as the history of hypothyroidism. SQSTM1 fusion was associated with multifocality and a medical history of thyroid/parathyroid adenoma. NTRK3 and ETV6 fusions showed significant associations with Hashimoto's disease, and ETV6, also with endometriosis. Moreover, fusion mutations were linked to younger age at the time of diagnosis, particularly the fusion of ETV6. The frequent occurrence of fusion mutations and their associations with certain clinicopathological metrics highlight the importance of integrating molecular profiling into routine PTC management. Early detection of fusion mutations can inform surgical decisions and therapeutic strategies, potentially improving clinical outcomes.

Anti-Proliferative and Anti-Migratory Activity of Licorice Extract and Glycyrrhetinic Acid on Papillary Thyroid Cancer Cell Cultures.

Papillary thyroid cancer (PTC) is the 8th most common cancer among women overall. Licorice contains over 300 active compounds, many of them with anti-cancer properties. Glycyrrhetinic acid (GA) is a major component of licorice. The aim of this study was to investigate the potential anti-proliferative effects of licorice and GA on PTC cell cultures. Licorice extract (LE) was produced from the root and tested on BCPAP and K1 cell lines, as well as GA and aldosterone. We used the MTT test to investigate the anti-proliferative activity, the wound healing test for the migratory activity, and finally, we analyzed cell cycle distribution, apoptosis, and oxidative stress after LE, GA, or aldosterone incubation. Both LE and GA reduced cell viability at 48 h and cell migration at 24 h in both PTC cultures. Aldosterone reduced cell migration only in K1 cells. LE and GA induced cell cycle arrest in the G0/G1 phase in the BCPAP cell line, while LE and aldosterone induced it in the K1 culture. GA but not LE increased the apoptosis rate in both cell lines, whereas LE but not GA increased oxidative stress in both cultures. This study presents the first evidence of the in vitro anti-proliferative and anti-migratory activity of LE and GA on PTC.

Machine learning-based diagnostics of capsular invasion in thyroid nodules with wide-field second harmonic generation microscopy.

Papillary thyroid carcinoma (PTC) is one of the most common, well-differentiated carcinomas of the thyroid gland. PTC nodules are often surrounded by a collagen capsule that prevents the spread of cancer cells. However, as the malignant tumor progresses, the integrity of this protective barrier is compromised, and cancer cells invade the surroundings. The detection of capsular invasion is, therefore, crucial for the diagnosis and the choice of treatment and the development of new approaches aimed at the increase of diagnostic performance are of great importance. In the present study, we exploited the wide-field second harmonic generation (SHG) microscopy in combination with texture analysis and unsupervised machine learning (ML) to explore the possibility of quantitative characterization of collagen structure in the capsule and designation of different capsule areas as either intact, disrupted by invasion, or apt to invasion. Two-step k-means clustering showed that the collagen capsules in all analyzed tissue sections were highly heterogeneous and exhibited distinct segments described by characteristic ML parameter sets. The latter allowed a structural interpretation of the collagen fibers at the sites of overt invasion as fragmented and curled fibers with rarely formed distributed networks. Clustering analysis also distinguished areas in the PTC capsule that were not categorized as invasion sites by the initial histopathological analysis but could be recognized as prospective micro-invasions after additional inspection. The characteristic features of suspicious and invasive sites identified by the proposed unsupervised ML approach can become a reliable complement to existing methods for diagnosing encapsulated PTC, increase the reliability of diagnosis, simplify decision making, and prevent human-related diagnostic errors. In addition, the proposed automated ML-based selection of collagen capsule images and exclusion of non-informative regions can greatly accelerate and simplify the development of reliable methods for fully automated ML diagnosis that can be integrated into clinical practice.

Meta-analysis of prediction models for predicting lymph node metastasis in thyroid cancer.

BACKGROUND: The purpose of this systematic review and meta-analysis is to assess the efficacy of various machine learning (ML) techniques in predicting preoperative lymph node metastasis (LNM) in patients diagnosed with papillary thyroid carcinoma (PTC). Although prior studies have investigated the potential of ML in this context, the current evidence is not sufficiently strong. Hence, we undertook a thorough analysis to ascertain the predictive accuracy of different ML models and their practical relevance in predicting preoperative LNM in PTC patients. MATERIALS AND METHODS: In our search, we thoroughly examined PubMed, Cochrane Library, Embase, and Web of Science, encompassing their complete database history until December 3rd, 2022. To evaluate the potential bias in the machine learning models documented in the included studies, we employed the Prediction Model Risk of Bias Assessment Tool (PROBAST). RESULTS: A total of 107 studies, involving 136,245 patients, were included. Among them, 21,231 patients showed central LNM (CLNM) and 4,637 had lateral LNM (LLNM). The meta-analysis results revealed that the c-index for predicting LNM, CLNM, and LLNM were 0.762 (95% CI: 0.747-0.777), 0.762 (95% CI: 0.747-0.777), and 0.803 (95% CI: 0.773-0.834) in the training set, and 0.773 (95% CI: 0.754-0.791), 0.762 (95% CI: 0.747-0.777), and 0.829 (95% CI: 0.779-0.879) in the validation set, respectively. A total of 134 machine learning-based prediction models were included, covering 10 different types. Logistic Regression (LR) was the most commonly used model, accounting for 81.34% (109/134) of the included models. CONCLUSIONS: Machine learning methods have shown a certain level of accuracy in predicting preoperative LNM in PTC patients, indicating their potential as a predictive tool. Their use in the clinical management of PTC holds great promise. Among the various ML models investigated, the performance of logistic regression-based nomograms was deemed satisfactory.

Prediction Model of Cervical Lymph Node Metastasis in Papillary Thyroid Carcinoma.

BACKGROUND: The objective of this study is to develop a predictive model for the assessment of cervical lymph node metastasis risk in papillary thyroid carcinoma (PTC). METHODS: A retrospective study was conducted on 212 patients with PTC who underwent initial surgical treatment from August 2022 to April 2023 in 2 hospitals. Data were randomly split into 7:3 training-validation sets. Logistic regression was used for feature selection and predictive model creation. Model performance was assessed using receiver operating characteristic (ROC) and calibration curves. Clinical utility was determined using decision curves. RESULTS: Among the 212 patients with PTC, 104 cases (49.1%) exhibited cervical lymph node metastasis, while 108 cases (50.9%) did not. Multivariate logistic regression analysis revealed that age (OR = 0.95), FT3 (OR = 0.41), tumor maximum diameter ≥0.9 cm (OR = 1.85), intratumoral microcalcifications (OR = 1.84), and suspicious lymph node on ultrasound (OR = 2.96) were independent risk factors for lymph node metastasis in PTC patients (P < 0.05). The constructed model for predicting the risk of cervical lymph node metastasis demonstrated a training set ROC curve area under the curve (AUC) of 0.742 (95% CI: 0.664 - 0.821), with a cut-off value of 0.615, specificity of 87.8%, and sensitivity of 51.4%. The validation set exhibited an AUC of 0.648 (95% CI: 0.501 - 0.788), with a cut-off value of 0.644, specificity of 91.2%, and sensitivity of 43.3%. Including the BRAF V600 E mutation did not improve the model's diagnostic performance significantly. Decision curve analysis indicated clinical feasibility of the model. CONCLUSION: The predictive model developed in this study effectively predicts lymph node metastasis risk in PTC patients by incorporating ultrasound features, demographic characteristics, and serum parameters. However, including the BRAF V600 E mutation does not significantly improve the model's diagnostic performance.

BackgroundThe objective of this study is to develop a predictive model for the assessment of cervical lymph node metastasis risk in papillary thyroid carcinoma.MethodsA retrospective study was conducted on 212 patients with papillary thyroid carcinoma who underwent initial surgical treatment at the First Affiliated Hospital of Fujian Medical University from August 2022 to April 2023. Data randomly split into 7:3 training-validation sets. Logistic regression used for feature selection and predictive model creation. Model performance assessed using ROC and calibration curves. Clinical utility determined using decision curves.ResultsAmong the 212 patients with PTC, 104 cases (49.1%) exhibited cervical lymph node metastasis, while 108 cases (50.9%) did not. Multivariate logistic regression analysis revealed that age (OR = 0.95), FT3 (OR = 0.41), tumor maximum diameter ≠¥ 0.9cm(OR = 1.85), intratumoral microcalcifications (OR = 1.84), and suspicious lymph node on ultrasound (OR = 2.96) were independent risk factors for LNM in PTC patients (P < 0.05). The constructed model for predicting the risk of cervical lymph node metastasis demonstrated a training set ROC curve area under the curve (AUC) of 0.742 (95% CI: 0.664 - 0.821), with a cut-off value of 0.615, specificity of 87.8%, and sensitivity of 51.4%. The validation set exhibited an AUC of 0.648 (95% CI: 0.501 - 0.788), with a cut-off value of 0.644, specificity of 91.2%, and sensitivity of 43.3%. Including BRAF V600E gene did not improve model's diagnostic performance significantly. Decision curve analysis indicated clinical feasibility of the model.ConclusionThe predictive model developed in this study effectively predicts lymph node metastasis risk in PTC patients by incorporating ultrasound features, demographic characteristics, and serum parameters.However, Including the BRAF V600E mutation does not significantly improve diagnosis performance.

Impact of Hashimoto's thyroiditis on the tumor microenvironment in papillary thyroid cancer: insights from single-cell analysis.

This study investigates the impact of Hashimoto's thyroiditis (HT), an autoimmune disorder, on the papillary thyroid cancer (PTC) microenvironment using a dataset of 140,456 cells from 11 patients. By comparing PTC cases with and without HT, we identify HT-specific cell populations (HASCs) and their role in creating a TSH-suppressive environment via mTE3, nTE0, and nTE2 thyroid cells. These cells facilitate intricate immune-stromal communication through the MIF-(CD74+CXCR4) axis, emphasizing immune regulation in the TSH context. In the realm of personalized medicine, our HASC-focused analysis within the TCGA-THCA dataset validates the utility of HASC profiling for guiding tailored therapies. Moreover, we introduce a novel, objective method to determine K-means clustering coefficients in copy number variation inference from bulk RNA-seq data, mitigating the arbitrariness in conventional coefficient selection. Collectively, our research presents a detailed single-cell atlas illustrating HT-PTC interactions, deepening our understanding of HT's modulatory effects on PTC microenvironments. It contributes to our understanding of autoimmunity-carcinogenesis dynamics and charts a course for discovering new therapeutic targets in PTC, advancing cancer genomics and immunotherapy research.

A comprehensive prediction model for central lymph node metastasis in papillary thyroid carcinoma with Hashimoto's thyroiditis: BRAF may not be a valuable predictor.

Purpose: Papillary thyroid carcinoma (PTC) frequently coexists with Hashimoto's thyroiditis (HT), which poses challenges in detecting central lymph node metastasis (CLNM) and determining optimal surgical management. Our study aimed to identify the independent predictors for CLNM in PTC patients with HT and develop a comprehensive prediction model for individualized clinical decision-making. Patients and methods: In this retrospective study, a total of 242 consecutive PTC patients who underwent thyroid surgery and central lymph node dissection between February 2019 and December 2021 were included. 129 patients with HT were enrolled as the case group and 113 patients without HT as control. The results of patients' general information, laboratory examination, ultrasound features, pathological evaluation, and BRAF mutation were collected. Multivariate logistic regression analysis was used to identify independent predictors, and the prediction model and nomogram were developed for PTC patients with HT. The performance of the model was assessed using the receiver operating characteristic curve, calibration curve, decision curve analysis, and clinical impact curve. In addition, the impact of the factor BRAF mutation was further evaluated. Results: Multivariate analysis revealed that gender (OR = 8.341, P = 0.013, 95% CI: 1.572, 44.266), maximum diameter (OR = 0.316, P = 0.029, 95% CI: 0.113, 0.888), multifocality (OR = 3.238, P = 0.010, 95% CI: 1.319, 7.948), margin (OR = 2.750, P = 0.046, 95% CI: 1.020, 7.416), and thyrotropin receptor antibody (TR-Ab) (OR = 0.054, P = 0.003, 95% CI: 0.008, 0.374) were identified as independent predictors for CLNM in PTC patients with HT. The area under the curve of the model was 0.82, with accuracy, sensitivity, and specificity of 77.5%, 80.3% and 75.0%, respectively. Meanwhile, the model showed satisfactory performance in the internal validation. Moreover, the results revealed that BRAF mutation cannot further improve the efficacy of the prediction model. Conclusion: Male, maximum diameter > 10mm, multifocal tumors, irregular margin, and lower TR-Ab level have significant predictive value for CLNM in PTC patients with HT. Meanwhile, BRAF mutation may not have a valuable predictive role for CLNM in these cases. The nomogram constructed offers a convenient and valuable tool for clinicians to determine surgical decision and prognostication for patients.

Comprehensive transcriptome and scRNA-seq analyses uncover the expression and underlying mechanism of SYNJ2 in papillary thyroid carcinoma.

Synaptojanin 2 (SYNJ2) has crucial role in various tumors, but its role in papillary thyroid carcinoma (PTC) remains unexplored. This study first detected SYNJ2 protein expression in PTC using immunohistochemistry method and further assessed SYNJ2 mRNA expression through mRNA chip and RNA sequencing data and its association with clinical characteristics. Additionally, KEGG, GSVA, and GSEA analyses were conducted to investigate potential biological functions, while single-cell RNA sequencing data were used to explore SYNJ2's underlying mechanisms in PTC. Meanwhile, immune infiltration status in different SYNJ2 expression groups were analyzed. Besides, we investigated the immune checkpoint gene expression and implemented drug sensitivity analysis. Results indicated that SYNJ2 is highly expressed in PTC (SMD = 0.66 [95% CI: 0.17-1.15]) and could distinguish between PTC and non-PTC tissues (AUC = 0.74 [0.70-0.78]). Furthermore, the study identified 134 intersecting genes of DEGs and CEGs, mainly enriched in the angiogenesis and epithelial-mesenchymal transition (EMT) pathways. Subsequent analysis showed the above pathways were activated in PTC epithelial cells. PTC patients with high SYNJ2 expression showed higher sensitivity to the six common drugs. Summarily, SYNJ2 may promote PTC progression through angiogenesis and EMT pathways. High SYNJ2 expression is associated with better response to immunotherapy and chemotherapy.