Xenotropic and polytropic retrovirus receptor 1 (XPR1) promotes progression of papillary thyroid carcinoma via the BRAF-ERK1/2-P53 signaling pathway.

BACKGROUND: Papillary thyroid carcinoma (PTC) is the most common type of thyroid cancer. Xenotropic and polytropic retrovirus receptor 1 (XPR1), identified as a cellular receptor, plays roles in many pathophysiological processes. However, the underlying function and molecular mechanisms of XPR1 in PTC remain unclear. Therefore, this study aimed to elucidate the role of XPR1 in the process of PTC and the potential mechanisms. METHODS: RNA-sequencing was performed for gene differential expression analysis in PTC patients' tissues. Immunohistochemical assay, real-time PCR, and western blotting assay were used to determine the expression of XPR1, BRAF, and P53 in PTC tissues. The function of XPR1 on the progression of PTC was explored using in vitro and in vivo experiments. The molecular mechanism of XPR1 was investigated using gene silencing, ELISA, immunofluorescence, western blotting, and real-time PCR assays. RESULTS: We found that XPR1 was markedly upregulated in PTC tissues compared to adjacent noncancerous tissues, suggesting that high expression of XPR1 could be correlated with poor patient disease-free survival in PTC. In addition, the expression of BRAF and P53 in PTC tissues was substantially higher than in adjacent noncancerous tissues. Silencing of XPR1 reduced the proliferation, migration, and invasion capacities of TPC-1 cells in vitro and effectively inhibited the tumorigenecity of PTC in vivo. More importantly, silencing of XPR1 in TPC-1 cells significantly decreased the expression of XPR1, BRAF, and P53 both in vitro and in vivo. Interestingly, we demonstrated that XPR1 may positively activate the BRAF-ERK-P53 signaling pathway, further promoting PTC progression. CONCLUSION: The findings reveal a crucial role of XPR1 in PTC progression and prognosis via the BRAF-ERK1/2-P53 signaling pathway, providing potential therapeutic targets for treating PTC.

PET/CT imaging of differentiated and medullary thyroid carcinoma using the novel SSTR-targeting peptide [18F]SiTATE - first clinical experiences.

PURPOSE: The novel 18F-labeled somatostatin receptor (SSTR)-directed radiotracer [18F]SiTATE demonstrated promising results for the imaging of various SSTR-expressing tumor types. Although thyroid carcinomas (TC) express SSTR, data on [18F]SiTATE PET/CT imaging in TC are lacking. This study explores the use of [18F]SiTATE PET/CT in a patient cohort with histologically proven TC. METHODS: As part of a prospective observational study at a single tertiary cancer center, 21 patients with TC (10 medullary (MTC) and 11 differentiated (DTC)) who underwent at least one [18F]SiTATE PET/CT were included (37 scans in total). Mean SUVmax and SUVmean of tumoral lesions, mean total-tumor-volume (TTV), and whole-body (WB)-SUVmax and WB-SUVmean on PET with their standard deviations (SDs) were determined. PET parameters were correlated to clinical parameters including tumor marker levels (thyroglobulin for DTC, calcitonin for MTC). RESULTS: 89 lesions were included in the analysis. Metastases were localized in the bone, lymph nodes, lung, soft tissue, and thyroid bed. Osseous (31 lesions; SUVmax 8.6 ± 8.0; SUVmean 5.8 ± 5.4) and nodal (37 lesions; SUVmax 8.7 ± 7.8; SUVmean 5.7 ± 5.4) metastases showed the highest uptake. The MTC disease burden on PET significantly correlated with the calcitonin tumor marker level (e.g., TTV: r = 0.771, r2 = 0.594, p = 0.002). For DTC, no such correlation was present. CONCLUSION: Our data demonstrate high feasibility of [18F]SiTATE PET/CT in a small cohort of patients with MTC and DTC. The use of [18F]SiTATE may overcome logistical disadvantages of 68Ga-based tracers and facilitate SSTR-targeted PET/CT imaging of thyroid carcinoma.

Identification of potential biomarkers of papillary thyroid carcinoma.

Papillary thyroid cancer (PTC) is the predominant form of malignant tumor affecting the thyroid gland. AIM: This study aimed to identify candidate biomarkers for papillary thyroid carcinoma using an integrative analysis of bioinformatics and machine learning (ML). MATERIAL AND METHOD: The PTC datasets GSE6004, GSE3467, and GSE33630 (species: Homo sapiens) were downloaded from NCBI and analyzed using the limma package to obtain DEGs. Once DEGs were identified, GO and KEGG enrichment analyses were performed as the first step in the bioinformatics process. Subsequently, a protein-protein interaction (PPI) network was constructed according to the common genes in bioinformatics and machine learning using STRING to elucidate the important genes involved in PTC pathogenesis. In machine learning, finding genes entails feature selection to identify the key genes that distinguish biological states. Hybrid feature selection will be used for this. In the second step, the original data sets were preprocessed to detect and correct missing and noisy data; after that, all data were merged. Following performing Linear and Discriminative Hybrid Feature Selection (LDHFS) on the processed dataset, machine learning algorithms such as Random Forest (RF), Naive Bayes (NB), and Support Vector Machines (SVM) are utilized. RESULTS: Bioinformatics and machine learning analyses indicate that the genes RXRG, CDH2, ETV5, QPCT, LRP4, FN1, and LPAR5 are integral to the progression of thyroid cancer. This study attained the highest accuracy utilizing the RF algorithm, achieving an accuracy rate of 94.62%, a Kappa value of 91.36%, and an AUC value of 96.13%. These results offer additional evidence and confirmation for the genetic alterations of these genes. These findings may accelerate the development of prospective therapeutic and diagnostic methods in future research. CONCLUSIONS: Bioinformatics and machine learning techniques identified the common genes "RXRG, CDH2, ETV5, QPCT, LRP4, FN1, and LPAR5" as PTC biomarkers, providing novel reference markers for the diagnosis and treatment of PTC patients. The model is anticipated to possess significant predictive value and assist in the early diagnosis and screening of clinical PTC. These insights enhance the field of PTC management and offer guidance for future research.

Radiomics and deep learning for large volume lymph node metastasis in papillary thyroid carcinoma.

Background: Thyroid cancer is prone to early lymph node metastasis (LNM), and patients with large volume LNM (LVLNM) tend to have a poorer prognosis. The aim of this study was to predict LVLNM in before surgery based on radiomics and deep learning (DL). Methods: A multicenter retrospective study was performed, including 854 papillary thyroid carcinoma (PTC) patients from three centers. Radiomics features were extracted. Logistic regression (LR), support vector machine (SVM), K-nearest neighbors (KNN), multi-layer perceptron (MLP), random forest (RF), ExtraTrees, extreme gradient boosting (XGBoost), and light gradient boosting machine (LightGBM) algorithms were used to construct radiomics models. AlexNet, DenseNet121, inception_v3, ResNet50, and transformer algorithms were used to construct DL models. The receiver operating characteristic (ROC) curve was employed to select the better-performing model. A combined model was then created by merging radiomics features and DL features. The least absolute shrinkage and selection operator (LASSO) method was utilized to identify metabolites and radiomics features with non-zero coefficients. The performance of the models was evaluated using area under the curve (AUC), accuracy (ACC), sensitivity (SEN), specificity (SPE), positive predictive value (PPV), negative predictive value (NPV), and F1-score. Results: A total of 1,357 radiomics features were extracted. Among the radiomics models, the ExtraTrees model demonstrated the optimal diagnostic capabilities with an AUC of 0.787 [95% confidence interval (CI): 0.715-0.858], and DenseNet121 DL model demonstrated the optimal diagnostic capabilities with an AUC of 0.766 (95% CI: 0.683-0.848). Furthermore, the combined model, named the Thy-DL-Radiomics model, exhibited an AUC of 0.839 (95% CI: 0.758-0.920) in the internal validation set and 0.789 (95% CI: 0.718-0.859) in the external validation set. Conclusions: A radiomics-DL features integrated model can predict LVLNM in PTC patients and provide guidance for personalized treatment.

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.

Concurrent Oral Squamous Cell Carcinoma and Incidental Papillary Thyroid Carcinoma Metastasis in Cervical Lymph Nodes: A Case Report.

Oral squamous cell carcinoma (OSCC) is the most common of all head and neck cancers accounting for 90% of all oral malignancies. It is commonly associated with the use of tobacco smoking or quid form. The incidence of oral carcinoma is higher in males than females with a ratio of 1.4:1, though females commonly adopt tobacco quid chewing habit. OSCC metastasis to cervical lymph node at the rate of 20-42.6% according to studies reported so far. Papillary thyroid carcinoma (PTC) occurs with a higher incidence in females than males with metastasis into cervical lymph nodes though the primary lesion frequently goes undetected. Concurrent metastasis of OSCC and PTC to the cervical lymph node during neck dissection has been reported rarely in the literature. This case report presents a 48-year-old female with lymph node metastasis of carcinoma of the right mandibular posterior alveolar region concurrently with metastasis of PTC (with primary lesion clinically undetected) encountered during cervical lymph node examination.

Correlation between body mass index and lymph node metastasis in papillary thyroid carcinoma: a retrospective clinical study.

Background: Papillary thyroid carcinoma (PTC) is the most common malignant tumor of the thyroid gland, with lymph node metastasis significantly affecting patient prognosis. In recent years, body mass index (BMI) has garnered widespread attention as a potential factor influencing cancer development. This study aimed to explore the relationship between BMI and lymph node metastasis in patients with PTC, particularly focusing on the risk of metastasis in the lateral and central neck compartments. Methods: This retrospective study comprised 993 patients who underwent surgical treatment and were pathologically confirmed to have PTC. Patient BMI data were collected, and their relationship with lymph node metastasis in the lateral and central neck compartments was analyzed. Logistic regression models were employed to analyze the correlation between BMI and lymph node metastasis. Results: The study found a significant correlation between BMI and the risk of lateral neck lymph node metastasis in patients (P=0.008), along with a corresponding increase in extrathyroidal extension risk (P=0.02). While elevated BMI did not directly increase the risk of central compartment metastasis, a significant increase was observed in the number of central compartment lymph node metastases (P=0.009) and their proportion among the total central compartment lymph nodes (P=0.01) in patients with higher BMI. Additionally, multifocality, age, and gender were identified as risk factors for lateral neck lymph node metastasis, whereas Hashimoto's thyroiditis did not exhibit a similar impact. Conclusions: This study highlights that higher BMI is an important risk factor for lateral neck lymph node metastasis in patients with PTC and may exacerbate the severity of central compartment lymph node metastasis. These findings underscore the importance of considering BMI in the management of thyroid cancer and provide data support for future prevention and intervention strategies.

Clinicopathological features affecting the efficacy in 131I ablation therapy of papillary thyroid carcinoma with lymph node metastasis.

Background: Lymph node metastasis is the major cause of increased recurrence and death in patients with papillary thyroid carcinoma (PTC). We evaluate the clinicopathologic factors affecting excellent response (ER) in patients with PTC with lymph node metastasis following operation and 131I ablation therapy. Methods: A total of 423 patients with PTC with lymph node metastasis who underwent thyroidectomy and postoperative 131I ablation therapy were enrolled. The relationship between clinicopathological factors affecting ER achievement was analyzed. Results: Multivariate analysis showed that the foci diameter (≤1 cm), unifocal, combination with Hashimoto's thyroiditis (HT), lymph node metastases rate (LR) (≤40%), no postoperative lymph node metastasis, low preablative stimulated thyroglobulin (ps-Tg) level (≤3.87 ng/mL), and the time of 131I ablation therapy (one time) were positively correlated with the ER achievement [odds ratio (OR): 1.744, 3.114, 3.920, 4.018, 2.074, 9.767, and 49.491, respectively; all p < 0.05]. The receiver operating characteristic (ROC) curves showed that the cutoff values of ps-Tg and LR were 4.625 ng/mL and 50.50%, respectively. The AUC of ROC of ps-Tg and LR for predicting ER achievement was 0.821 and 0.746, respectively. The Tg and the cumulative risk of non-ER elevated with the increase of LR, especially for the high-level ps-Tg (>4.625 ng/mL) group. Conclusion: The foci diameter and number, combination with HT, LR, and ps-Tg level are independent factors for ER. Ps-Tg level and LR are valid predictive factors for the efficacy of 131I therapy in patients with PTC. The predictive value of the cumulative risk of non-ER can be improved by the combination of ps-Tg and LR.

Intraglandular dissemination: a special pathological feature.

Intraglandular dissemination is an important pathological feature of thyroid cancer, yet the biological characteristics of this phenomenon remain relatively underexplored. This paper aims to provide a comprehensive overview of its biological behaviors, protein expressions, and identification methods. Several retrospective studies have found that thyroid cancers with intraglandular dissemination have higher rates of lymph node metastasis, capsule invasion, and vascular invasion, exhibiting more aggressive biological behavior. Immunohistochemistry results show abnormal expression of proteins such as FKBP5, CENPF, CX26, KIF11, PTK7, which are associated with poor prognosis in thyroid cancers with intraglandular dissemination, offering potential guidance for specific targeted therapy in the future. Moreover, adjunctive techniques including ultrasound, fine-needle aspiration, and genetic testing offer valuable support in accurately identifying these cases, facilitating moreproactive treatment and closer follow-up.

Association between blood inflammatory indicators and prognosis of papillary thyroid carcinoma: a narrative review.

Background and Objective: Papillary thyroid carcinoma (PTC) is the most common subtype of thyroid cancer, accounting for up to 85-90% of cases, with the best overall prognosis and mostly inert tumors. However, some tumors are aggressive, causing metastasis, recurrence, and other bad outcomes. Preoperative inflammation indices, such as lymphocyte-to-monocyte ratio (LMR), neutrophil-to-lymphocyte ratio (NLR), and systemic immune inflammation index (SII) in peripheral blood, have recently gained attention as nonspecific markers of inflammatory response in thyroid. In this study, we reviewed the interactions between preoperative inflammatory factors and outcomes in patients with PTC. Methods: This is a narrative review. We searched for English articles published between January 2014 and December 2023 on PubMed and Web of Science to identify how do these blood indicators affect the prognosis of patients with papillary thyroid cancer. Key Content and Findings: All retrievable indicators that have predictive significance for the prognosis of PTC were included, and the prognosis mainly included tumor-node-metastasis (TNM) staging, survival rate, recurrence, clinical and pathological risk factors such as lymph node metastasis (LNM), etc. From the general evidence, the prognostic predictive value of cell count alone was unknown, and low LMR was usually associated with poor prognosis, high NLR and high platelet-to-lymphocyte ratio (PLR) usually indicated poor prognosis. Conclusions: These minimally invasive, low-cost, and easily obtainable blood indicators provide convenience for precise prognosis management of PTC patients, but many of the findings are conflicting and need to be validated by prospective studies that are more multi-sample, multi-centre and incorporate factors such as age that affect the immune response.

TLE4 downregulation identified by WGCNA and machine learning algorithm promotes papillary thyroid carcinoma progression via activating JAK/STAT pathway.

Background: Papillary Thyroid Carcinoma (PTC), a common type of thyroid cancer, has a pathogenesis that is not fully understood. This study utilizes a range of public databases, sophisticated bioinformatics tools, and empirical approaches to explore the key genetic components and pathways implicated in PTC, particularly concentrating on the Transducin-Like Enhancer of Split 4 (TLE4) gene. Methods: Public databases such as TCGA and GEO were utilized to conduct differential gene expression analysis in PTC. Hub genes were identified using Weighted Gene Co-expression Network Analysis (WGCNA), and machine learning techniques, including Random Forest, LASSO regression, and SVM-RFE, were employed for biomarker identification. The clinical impact of the TLE4 gene was assessed in terms of diagnostic accuracy, prognostic value, and its functional enrichment analysis in PTC. Additionally, the study focused on understanding the role of TLE4 in the dynamics of immune cell infiltration, gene function enhancement, and behaviors of PTC cells like growth, migration, and invasion. To complement these analyses, in vivo studies were performed using a xenograft mouse model. Results: 244 genes with significant differential expression across various databases were identified. WGCNA indicated a strong link between specific gene modules and PTC. Machine learning analysis brought the TLE4 gene into focus as a key biomarker. Bioinformatics studies verified that TLE4 expression is lower in PTC, linking it to immune cell infiltration and the JAK-STAT signaling pathways. Experimental data revealed that decreased TLE4 expression in PTC cell lines leads to enhanced cell growth, migration, invasion, and activates the JAK/STAT pathway. In contrast, TLE4 overexpression in these cells inhibited tumor growth and metastasis. Conclusions: This study sheds light on TLE4's crucial role in PTC pathogenesis, positioning it as a potential biomarker and target for therapy. The integration of multi-omics data and advanced analytical methods provides a robust framework for understanding PTC at a molecular level, potentially guiding personalized treatment strategies.

Mechanism of DAPK1 for Regulating Cancer Stem Cells in Thyroid Cancer.

Death-associated protein kinase 1 (DAPK1) is a calcium/calmodulin (Ca2+/CaM)-dependent serine/threonine (Ser/Thr) protein kinase and is characteristically downregulated in metastatic cancer. Several studies showed that DAPK1 is involved in both the early and late stages of cancer. DAPK1 downregulation is elaborately controlled by epigenetic, transcriptional, posttranscriptional, and posttranslational processes. DAPK1 is known to regulate not only cancer cells but also stromal cells. Recent studies showed that DAPK1 was involved not only in tumor suppression but also in epithelial-mesenchymal transition (EMT) and cancer stem cell (CSC) formation in colon and thyroid cancers. CSCs are major factors in determining cancer aggressiveness in cancer metastasis and treatment prognosis by influencing EMT. However, the molecular mechanism involved in the regulation of cancer cells by DAPK1 remains unclear. In particular, little is known about the existence of CSCs and how they are regulated in papillary thyroid carcinoma (PTC) among thyroid cancers. In this review, we describe the molecular mechanism of CSC regulation by DAPK1 in PTC progression.

A nomogram for risk stratification of central cervical lymph node metastasis in patients with papillary thyroid carcinoma.

Background: Whether to perform prophylactic central lymph node dissection for cN0 papillary thyroid carcinoma (PTC) patients is still controversial. This retrospective study aimed to develop and validate a nomogram based on ultrasound and dual-energy computed tomography (DECT) for the risk stratification of central lymph node metastasis (CLNM) in patients with PTC. Methods: A total of 525 patients from 2017 to 2019 [Tianjin First Central Hospital (Hospital A)] were retrospectively analyzed to form the training cohort and to conduct internal validation. Another group of 204 patients in 2020 (Hospital A) formed the temporal validation cohort. A total of 107 patients in 2020 [Binzhou Medical University Hospital (Hospital B)] formed the geographic validation cohort, which was a retrospective cohort study. The area under the curve (AUC), calibration curve, and decision curve were used to evaluate the performance of the nomogram. The locally weighted regression curve was used for risk stratification. Results: Diameter, taller-than-wide, calcification, capsular invasion, and iodine concentration in the arterial and venous phases were independent risk predictors of CLNM. The AUC of the nomogram was 0.922 (95% confidence interval: 0.895-0.943) in the training cohort. Two external validation cohorts demonstrated the good performance of the nomogram in predicting CLNM, with AUCs of 0.912 and 0.861. The significantly improved net reclassification index and integrated discriminatory improvement index indicated that DECT was a powerful supplement to ultrasound for predicting CLNM. The risk stratification system divided all patients into low-risk (0-50 points), intermediate-risk (51-100 points), and high-risk groups (>100 points). Conclusions: The nomogram and risk stratification system estimated the utility of CLNM to guide individualized treatment of patients with PTC.

Polymorphism Pro64His within galectin-3 has functional consequences at proteome level in thyroid cells.

Introduction: The single nucleotide polymorphism (SNP) rs4644 at codon 64 of galectin-3 (gal-3, gene name: LGALS3), specifying the variant proline (P64) to histidine (H64), is known to affect the protein's functions and has been associated with the risk of several types of cancer, including differentiated thyroid carcinoma (DTC). Materials and methods: To deepen our understanding of the biological effects of this SNP, we analyzed the proteome of two isogenic cell lines (NC-P64 vs. NA-H64) derived from the immortalized non-malignant thyrocyte cell line Nthy-Ori, generated through the CRISPR-Cas9 technique to differ by rs4644 genotype. We compared the proteome of these cells to detect differentially expressed proteins and studied their proteome in relation to their transcriptome. Results: Firstly, we found, consistently with previous studies, that gal-3-H64 could be detected as a monomer, homodimer, and heterodimer composed of one cleaved and one uncleaved monomer, whereas gal-3-P64 could be found only as a monomer or uncleaved homodimer. Moreover, results indicate that rs4644 influences the expression of several proteins, predominantly upregulated in NA-H64 cells. Overall, the differential protein expression could be attributed to the altered mRNA expression, suggesting that rs4644 shapes the function of gal-3 as a transcriptional co-regulator. However, this SNP also appeared to affect post-transcriptional regulatory mechanisms for proteins whose expression was oppositely regulated compared to mRNA expression. It is conceivable that the rs4644-dependent activities of gal-3 could be ascribed to the different modalities of self-dimerization. Conclusion: Our study provided further evidence that rs4644 could affect the gal-3 functions through several routes, which could be at the base of differential susceptibility to diseases, as reported in case-control association studies.

Deep convolutional neural network model ResNeSt for discrimination of papillary thyroid carcinomas and benign nodules in thyroid nodules diagnosed as atypia of undetermined significance.

Background: A deep convolutional neural network (DCNN) model was employed for the differentiation of thyroid nodules diagnosed as atypia of undetermined significance (AUS) according to the 2023 Bethesda System for Reporting Thyroid Cytopathology (TBSRTC). The aim of this study was to investigate the efficiency of ResNeSt in improving the diagnostic accuracy of fine-needle aspiration (FNA) biopsy. Methods: Fragmented images were used to train and test DCNN models. A training dataset was built from 1,330 samples diagnosed as papillary thyroid carcinoma (PTC) or benign nodules, and a test dataset was built from 173 samples diagnosed as AUS. ResNeSt was trained and tested to provide a differentiation. With regard to AUS samples, the characteristics of the cell nuclei were compared using the Wilcoxon test. Results: The ResNeSt model achieved an accuracy of 92.49% (160/173) on fragmented images and 84.78% (39/46) from a patient wise viewpoint in discrimination of PTC and benign nodules in AUS nodules. The sensitivity and specificity of ResNeSt model were 95.79% and 88.46%. The κ value between ResNeSt and the pathological results was 0.847 (P<0.001). With regard to the cell nuclei of AUS nodules, both area and perimeter of malignant nodules were larger than those of benign ones, which were 2,340.00 (1,769.00, 2,807.00) vs. 1,941.00 (1,567.50, 2,455.75), P<0.001 and 190.46 (167.64, 208.46) vs. 171.71 (154.95, 193.65), P<0.001, respectively. The grayscale (0 for black, 255 for white) of malignant lesions was lower than that of benign ones, which was 37.52 (31.41, 46.67) vs. 45.84 (31.88, 57.36), P <0.001, indicating nuclear staining of malignant lesions were deeper than benign ones. Conclusions: In summary, the DCNN model ResNeSt showed great potential in discriminating thyroid nodules diagnosed as AUS. Among those nodules, malignant nodules showed larger and more deeply stained nuclei than benign nodules.

Synchronous papillary and follicular thyroid carcinomas: the first retrospective cohort study and literature review.

Background: Papillary thyroid carcinoma (PTC) and follicular thyroid carcinoma (FTC) contribute to more than 95% of thyroid malignancies. However, synchronous PTC and FTC are less common; it is most commonly discovered incidentally as synchronous malignancies during operation, which adds difficulties to intraoperative decision-making and postoperative treatment. Therefore, we analyzed the clinicopathological characteristics and prognosis of patients with PTC and FTC in our center. Methods: We conducted a search of single PTC, single FTC, and synchronous PTC/FTC patients who received initial surgery treatment at Fudan University Shanghai Cancer Center from 2006 to 2018 and collected paraffin-embedded samples of synchronous patients. Clinicopathological characteristics were collected from the electronic medical record system. Follow-up was performed through telephone contact or medical records. Exome sequencing was performed by ThyroLead panel. Results: Total of 42 synchronous PTC/FTC patients, 244 single FTC patients, and 2,959 single PTC patients were included. It showed a similarity between the clinicopathological features of synchronous thyroid cancer patients and single PTC patients, with a greater proportion of females, higher probabilities of lymph node metastasis, and higher rate of concurrence of Hashimoto's disease. The disease-free survival (DFS) curve indicated a worse prognosis of the synchronous group and single PTC group compared to the single FTC group, who had a propensity for neck lymph node recurrence; however, logistic multivariate regression analysis did not find any factor related to recurrence in the synchronous group. After re-checking pathology, DNA extraction, and quality control, genetic alteration information of 62 samples including primary tumors and metastatic lymph nodes from 35 synchronous cancer patients was displayed. In total, 81 mutations and 1 fusion gene were identified, including mutations related to outcomes and targeted therapy. Besides, some rare mutations in thyroid cancer were found in these patients. Conclusions: To conclude, synchronous PTC/FTC tend to be incidentally discovered during or after operation, behaving more like single PTC. The prognosis of synchronous patients is worse than that of single FTC patients and supplemental cervical lymph node dissection, total thyroidectomy, and postoperative radioiodine therapy should be taken into consideration after diagnosis. The next-generation sequencing (NGS) showed a unique molecular feature of synchronous patients with some rare mutations.

The coexistence of papillary thyroid carcinoma, anaplastic thyroid carcinoma (squamous cell carcinoma subtype) and poorly differentiated thyroid carcinoma: a case report.

Background: Papillary thyroid carcinoma (PTC) accounts for about 60% of adult thyroid carcinoma and generally has an excellent prognosis. Primary squamous cell carcinoma of thyroid (PSCCT) is a rare thyroid tumor with high malignancy and poor prognosis. In 2022, the 5th edition of World Health Organization (WHO) has classified it as a subtype of anaplastic thyroid carcinoma (ATC), abbreviated as ATC-squamous cell carcinoma (SCC) subtype. Poorly differentiated thyroid carcinoma (PDTC) is a kind of follicular-derived malignancy, which is prone to recurrence and distant metastasis. Here, we report a rare case of the coexistence of PTC, ATC-SCC subtype and PDTC. Case Description: We herein report a case of 69-year-old female who initially presented with a history of left neck mass for one month. Comprehensive auxiliary examinations and postoperative pathology confirmed the diagnosis of PTC combined with ATC-SCC subtype, and PDTC. Total thyroidectomy with radical left cervical lymph node dissection was performed, followed by thyroid-stimulating hormone (TSH) suppressive therapy, 131I, radiotherapy and chemotherapy. The patient showed no tumor recurrence or metastasis after a 5-month postoperative follow-up. Conclusions: The simultaneous occurrence of PTC, ATC-SCC subtype, and PDTC is extremely rare in clinical terms or literature reports. The treatment has not been standardized, and early radical surgery is the first choice. In addition, the combination of adjuvant therapies such as TSH suppressive therapy, radiotherapy, chemotherapy and 131I may further improve the prognosis of the patient.

Analysis of risk factors for lateral lymph node metastasis in T1 stage papillary thyroid carcinoma: a retrospective cohort study.

Background: The occurrence of cervical lymph node metastasis in T1 stage papillary thyroid carcinoma (PTC) is frequently observed. Notably, lateral lymph node metastasis (LLNM) emerges as a critical risk factor adversely affecting prognostic outcomes in PTC. The primary aim of this investigation was to delineate the risk factors associated with LLNM in the initial stages of PTC. Methods: This retrospective analysis encompassed 3,332 patients diagnosed with T1 stage PTC without evident LLNM at the time of diagnosis. These individuals underwent primary surgical intervention at West China Hospital, Sichuan University between June 2017 and February 2023. The cohort was divided into two groups: patients manifesting LLNM and those without metastasis at the time of surgery. Additionally, T1 stage PTC patients were subdivided into T1a and T1b categories. Factors influencing LLNM were scrutinized through both univariate and multivariate analyses. Results: The incidence of LLNM was observed in 6.2% of the cohort (206 out of 3,332 patients). Univariate analysis revealed significant correlations between LLNM and male gender (P<0.001), tumor localization in the upper lobe (P<0.001), maximal volume of the primary tumor (P<0.001), largest tumor diameter (P<0.001), multifocality (P<0.001), and bilaterality (P<0.001), with the exception of age (P=0.788) and duration of active surveillance (AS) (P=0.978). Multivariate logistic regression analysis identified male gender (P<0.001), upper lobe tumor location (P<0.001), maximal primary tumor volume (P<0.001), and multifocality (P<0.001) as independent predictors of LLNM. However, age categories (≤55, >55 years), maximum tumor diameter, bilaterality, and surveillance duration did not exhibit a significant impact. Comparative analyses between T1a and T1b subgroups showed congruent univariate results but revealed differences in multivariate outcomes. In the T1a subgroup, gender, tumor location, and multifocality (all P<0.05) were associated with elevated LLNM risk. Conversely, in the T1b subgroup, tumor location, dimensions, and multifocality (all P<0.05) were significant predictors of LLNM risk, whereas gender (P=0.097) exerted a marginal influence. Conclusions: The investigation highlights several key risk factors for LLNM in T1 stage PTC patients, including gender, upper lobe tumor location, larger tumor size, and multifocality. Conversely, prolonged AS and younger age did not significantly elevate LLNM risk, suggesting the viability of AS as a strategic option in selected cases.

Detection of thyroglobulin for diagnosis of metastatic lateral cervical lymph nodes in papillary thyroid carcinoma: accuracy and application in clinical practice.

Background: Accurate assessment of lateral cervical lymph node metastasis (LLNM) involvement is important for treating papillary thyroid carcinoma (PTC). Thyroglobulin is associated with LLNM, but there may be differences in the diagnostic value of serum thyroglobulin (sTg) and fine needle aspiration washout fluid thyroglobulin (FNA-Tg). Herein, we investigated the optimal cutoff value (OCV) of sTg and FNA-Tg and their diagnostic performance. Methods: We enrolled 116 PTC patients who underwent radical resection of thyroid carcinoma with lateral cervical lymph node dissection at the Affiliated Hospital of Zunyi Medical University from June 2018 to July 2022. We used the receiver operating characteristic (ROC) curve analysis to determine the OCV for sTg and FNA-Tg to diagnose LLNM in PTC patients. We also evaluated the performance of FNA-Tg, sTg, fine needle aspiration cytology (FNAC), and their combinations for diagnosis. Pathological results were the gold standard. Results: We performed 125 lymph node dissections, 106 had metastasis, and 19 did not. The OCV for sTg was 17.31 ng/mL [area under the curve (AUC) =0.760, sensitivity =78.30%, specificity =73.68%, and accuracy =77.60%]. Meanwhile, the OCV for FNA-Tg was 4.565 ng/mL (AUC =0.948, sensitivity =89.62%, specificity =100%, and accuracy =91.20%). The combination of FNAC and FNA-Tg presented the greatest diagnostic performance for LLNM detection in PTC patients. Moreover, serum antithyroglobulin antibody (TgAb) was not correlated with sTg or FNA-Tg levels. Conclusions: The cutoff value for the diagnosis of LLNM in PTC are sTg >17.31 ng/mL or FNA-Tg >4.565 ng/mL. The combination method of FNA-Tg and FNAC is the most optimal choice for the diagnosis of LLNM and is highly recommended for further clinical application.

Prediction of bilateral thyroid carcinoma and lateral cervical lymph node metastasis in PTC patients with suspicious thyroid nodules.

PURPOSE: This study aimed to evaluate the factors associated with bilateral papillary thyroid carcinoma (PTC) and lateral cervical lymph node metastasis (LLNM) in patients with suspicious unilateral PTC. METHODS: This study analyzed patients with suspicious unilateral PTC who were enrolled in a university hospital between 2016 and 2019 in Zhejiang, China. Using logistic regression, the study examined the factors associated with bilateral PTC and LLNM in demographic data, anthropometric measurements, lifestyle factors, medical history, preoperative diagnostic tests, and histopathological factors. RESULTS: A total of 256 patients, with a mean age of 49 years, were enrolled. Bilateral PTC was associated with multifocality (aOR: 5.069, 95% CI: 2.440-10.529, P < 0.001), and contralateral nodule in the upper (aOR: 9.073, 95% CI: 2.111-38.985, P = 0.003) and middle (aOR: 9.926, 95% CI: 2.683-36.717, P < 0.001). LLNM was positively associated with bilateral PTC (aOR, 4.283, 95% CI: 1.378-13.308, p = 0.012), male (aOR, 3.377, 95% CI: 1.205-9.461, P = 0.021), upper location of carcinoma (aOR, 3.311, 95% CI: 1.091-10.053, p = 0.035), and punctate echogenic foci (aOR, 3.309, 95% CI: 1.165-9.394, P = 0.025). Contralateral maximal nodule in the upper (aOR: 0.098, 95% CI: 0.015-0.628, p = 0.014), middle (aOR: 0.114, 95% CI: 0.033-0.522, p < 0.001), and lower (aOR, 0.028, 95% CI: 0.003-0.276, P = 0.002) location were inversely associated with LLNM. CONCLUSION: Upper and middle location of contralateral nodule and tumor multifocality predicted the risk bilateral PTC. Bilateral PTC, male, upper tumor location, punctate echogenic foci and contralateral nodule location in the entire lobes were independent predictors for LLNM.