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Although the incidence of some malignancy has decreased over the recent years, this is not the case of papillary thyroid microcarcinoma (PTMC), whose incidence has increased worldwide. Most PTMC are found incidentally after histological examination of specimens from surgery for benign thyroid disease. Hashimoto’s thyroiditis, whose incidence has also increased, coexists in about one in three PTMC patients. Three different mechanisms have been proposed to clarify the association between chronic lymphocytic thyroiditis and PTMC, namely tumor development/growth by: (i) TSH stimulation, (ii) expression of certain proto-oncogenes, (iii) chemokines and other molecules produced by the lymphocytic infiltrate. Whether Hashimoto’s thyroiditis protects against lymph node metastasis is debated. Overall, autommune thyroiditis seems to contribute to the favorable prognosis of PTMC. Major limitations of the studies so far performed include: (i) retrospective design, (ii) limited statistical power, (iii) high risk of selection bias, (iv) and predominant Asian ethnicity of patients. Full genetic profiling of both diseases and identification of environmental factors capable to trigger them, as well as well-powered prospective studies on different ethnical groups, may help understand their causal association and why their frequencies are continuing raising.

The latest World Health Organization Classification of Tumors, Fifth Edition, recognizes the invasive encapsulated follicular variant of papillary thyroid carcinoma (IEFVPTC) as a distinct malignant entity rather than a subtype of papillary thyroid carcinoma (PTC). This reclassification highlights the need to explore potential prognostic differences between IEFVPTC and classic PTC. This study utilized the Surveillance, Epidemiology, and End Results (SEER) database to compare prognoses of patients diagnosed with IEFVPTC and classic PTC between 2004 and 2019. Propensity score matching (PSM) was employed to adjust for confounding variables and reduce selection bias. Kaplan-Meier survival curves and Cox regression models were used to evaluate overall survival (OS) between the two groups. A total of 1,530 IEFVPTC and 81,508 classic PTC patients were analyzed. Before PSM, significant differences were noted in race, T-stage, N-stage, M-stage, laterality, radiotherapy, surgical modality, tumor size, and income. Post-PSM, these differences were not statistically significant ( p  > 0.05). Kaplan-Meier curves and Cox regression models showed no significant differences in OS between IEFVPTC and classic PTC both before and after PSM. This PSM analysis revealed no significant differences in overall survival between patients with IEFVPTC and classic PTC, suggesting that the reclassification of IEFVPTC does not translate into distinct prognostic outcomes.

The introduction of noninvasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP) was initiated and promoted by pathologists. Recent Asian studies added new knowledge to the existing literature to aid a better understanding of NIFTP. Our original data and the results of a meta-analysis suggest that the initial rate of NIFTP has been overestimated, averaging 9.1% (95% confidence interval [CI] 6.0–12.7%) of all papillary thyroid cancers worldwide. The incidence of NIFTP in the Asian population (1.6%, 95% CI 0.9–2.5%; 7 studies) is significantly lower than that reported in the non-Asian series (13.3%, 95% CI 9.0–18.3%; 18 studies). Such difference could be attributed to various perceptions of histological diagnostic thresholds, different nature of papillary thyroid carcinoma, and different approaches in the management of thyroid nodules. The active surveillance for indeterminate nodules and NIFTP, largely represented in the indeterminate cytologic categories, promoted by Japanese institutions establishes a new paradigm to reduce overtreatment of these patients. The lower prevalence of NIFTP in the Asian series indicates a low impact on the risk of malignancy in cytopathology, as it was demonstrated in our original multi-institutional cohort of thyroid nodules, and may predict a low impact on the performance of commercial molecular tests. Several Korean studies addressed the issue of BRAF mutation in NIFTP, which prompted the current refinement of the diagnostic criteria for NIFTP. Our survey of Asian pathologists found that the term NIFTP has not been universally adopted in the local practice. Endocrine pathologists must promote the new entity through provision of educational activities.

Follicular-patterned lesions of the thyroid are common; these include hyperplastic/adenomatoid nodules, follicular adenoma, follicular carcinoma and follicular variants of papillary carcinoma. Most of these lesions can be diagnosed with ease; however, there is a controversial subgroup. In this review, we present our diagnostic approach based on our experience with the histological diagnosis of these tumours, which can help in appropriate clinical management.

Background Papillary thyroid carcinoma (PTC) is the most common thyroid cancer. While many patients survive, a portion of PTC cases display high aggressiveness and even develop into refractory differentiated thyroid carcinoma. This may be alleviated by developing a novel model to predict the risk of recurrence. Ferroptosis is an iron-dependent form of regulated cell death (RCD) driven by lethal accumulation of lipid peroxides, is regulated by a set of genes and shows a variety of metabolic changes. To elucidate whether ferroptosis occurs in PTC, we analyse the gene expression profiles of the disease and established a new model for the correlation. Methods The thyroid carcinoma (THCA) datasets were downloaded from The Cancer Genome Atlas (TCGA), UCSC Xena and MisgDB, and included 502 tumour samples and 56 normal samples. A total of 60 ferroptosis related genes were summarised from MisgDB database. Gene set enrichment analysis (GSEA) and Gene set variation analysis (GSVA) were used to analyse pathways potentially involving PTC subtypes. Single sample GSEA (ssGSEA) algorithm was used to analyse the proportion of 28 types of immune cells in the tumour immune infiltration microenvironment in THCA and the hclust algorithm was used to conduct immune typing according to the proportion of immune cells. Spearman correlation analysis was performed on the ferroptosis gene expression and the correlation between immune infiltrating cells proportion. We established the WGCNA to identify genes modules that are highly correlated with the microenvironment of immune invasion. DEseq2 algorithm was further used for differential analysis of sequencing data to analyse the functions and pathways potentially involving hub genes. GO and KEGG enrichment analysis was performed using Clusterprofiler to explore the clinical efficacy of hub genes. Univariate Cox analysis was performed for hub genes combined with clinical prognostic data, and the results was included for lasso regression and constructed the risk regression model. ROC curve and survival curve were used for evaluating the model. Univariate Cox analysis and multivariate Cox analysis were performed in combination with the clinical data of THCA and the risk score value, the clinical efficacy of the model was further evaluated. Results We identify two subtypes in PTC based on the expression of ferroptosis related genes, with the proportion of cluster 1 significantly higher than cluster 2 in ferroptosis signature genes that are positively associated. The mutations of Braf and Nras are detected as the major mutations of cluster 1 and 2, respectively. Subsequent analyses of TME immune cells infiltration indicated cluster 1 is remarkably richer than cluster 2. The risk score of THCA is in good performance evaluated by ROC curve and survival curve, in conjunction with univariate Cox analysis and multivariate Cox analysis results based on the clinical data shows that the risk score of the proposed model could be used as an independent prognostic indicator to predict the prognosis of patients with papillary thyroid cancer. Conclusions Our study finds seven crucial genes, including Ac008063.2 , Apoe , Bcl3 , Acap3 , Alox5ap , Atxn2l and B2m, and regulation of apoptosis by parathyroid hormone-related proteins significantly associated with ferroptosis and immune cells in PTC, and we construct the risk score model which can be used as an independent prognostic index to predict the prognosis of patients with PTC.

The comprehensive study of the relationship between lymph node metastasis (LNM) and its associated factors in patients with concurrent papillary thyroid carcinoma (PTC) and Hashimoto’s thyroiditis (HT) remains insufficient. Building upon the initial investigation of factors associated with LNM in patients with concurrent PTC and HT, we further analyzed the complex relationships between different severity indicators of LNM and these associated factors. This study included patients confirmed PTC with HT who underwent total thyroidectomy at Xiangya Hospital, from January 2020 to December 2021. A total of 271 patients from 2020 were used as the training set, and 300 patients from 2021 as the validation set. Univariate analysis and regression modeling were used to identify key factors associated with LNM. Model reliability was assessed using the area under the receiver operating characteristic curve (AUC). Network analysis was employed to explore associations between LNM severity and its related factors. The regression model indicated that age, calcification, free triiodothyronine (FT3), and tumor maximum diameter (TMD) are independent factors for LNM. The severity model showed free thyroxine (FT4) and hemoglobin (Hb) are independent protective factors for the region and quantity of LNM, respectively, while TMD is an independent risk factor for both. Network analysis revealed TMD has a closer relationship with LNM severity compared to other associated factors. This study innovatively combined regression models and network analysis to investigate factors related to LNM in patients with PTC and HT, providing a theoretical basis for predicting preoperative LNM in future clinical practice. Highlights • Innovative Methods: First to combine regression models and network analysis for LNM study. • Risk Factor Identification:Identified 4 independent risk factors for LNM in PTC with HT. • Detailed Subgroup Analysis:Uncovered specific risk factors for LNM severity and regional spread.

Background Papillary thyroid carcinoma (PTC) frequently recurs to the lymph nodes, which may not be fatal immediately but is a stressor for physicians and patients. Recurrence to the distant organs, although less frequent, is often life-threatening, and the lung and bone are organs to which PTC is likely to recur. In the present study we investigated factors predicting recurrence of PTC to the lymph nodes, lung, and bone in a large number of patients undergoing long-term follow-up. Methods A total of 5,768 PTC patients (608 males and 5,159 females) without distant metastasis at diagnosis who underwent initial surgery between 1987 and 2004 in Kuma Hospital were enrolled in this study. The postoperative follow-up ranged from 12 to 280 months, and was 129 months (10.8 years) on average. Results To date, node, lung, and bone recurrences have been detected in 389 (7%), 118 (2%), and 33 patients (0.6%), respectively, and 57 patients (1%) have died of PTC. We examined the prognostic significance of the tumor size (T), extrathyroid extension (Ex), age 55 years or older (Age), male gender (Gender), clinical node metastasis (N), and extranodal tumor extension (LN-Ex) for each outcome on multivariate analysis. Age, Gender, T > 2 cm, N, and Ex were independent predictors of lymph node recurrence. Age, Ex, T > 2 cm, and N were independent prognostic factors for lung recurrence. Ex, T > 4 cm, and N independently predicted bone recurrence. Of these, N ≥ 3 cm had the strongest prognostic value for lymph node, lung, and bone recurrences. In contrast, Age was the strongest predictor for carcinoma death. LN-Ex also had a prognostic value for carcinoma death, although it was not a predictor of carcinoma recurrence. Ex, N ≥ 3 cm, and T > 2 cm also had a prognostic impact on carcinoma death. Conclusions Large lymph node metastasis showed a strong prognostic impact on carcinoma recurrence not only to the lymph nodes but also to the lung and bone, and carcinoma death. Extrathyroid extension also independently predicted these recurrences and carcinoma death, although hazard ratios were lower than for large node metastasis. Age 55 years or older, in contrast, was the strongest predictor of carcinoma death. Extranodal tumor extension did not independently affect recurrence, but it had prognostic significance for carcinoma death. These findings suggest that recurring PTC lesions of older patients and/or extranodal tumor extensions are difficult to control and very progressive.

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.

Certain cancers exhibit unique expression profiles of small nucleolar RNAs (snoRNAs), and the aberrant expression of snoRNAs may play significant roles in tumor biology. As the most common endocrine malignancy, the expression pattern and clinical relevance of snoRNAs in papillary thyroid carcinoma (PTC) remain largely unexplored. In this study, we employed small RNA microarray analysis to profile snoRNA expression in tumor tissues and corresponding normal thyroid tissues obtained from patients undergoing thyroidectomy. Differentially expressed snoRNAs (DE-snoRNAs) were validated by quantitative real-time PCR (qRT-PCR) and analysis of The Cancer Genome Atlas (TCGA) database. Furthermore, we applied CIBERSORTx and ESTIMATE algorithms to investigate the association between DE-snoRNA expression levels and clinicopathological features as well as tumor immune microenvironment in PTC. Our results revealed that SNORA68B, SNORA70F, and SNORD88A were downregulated in PTC tissues and potentially associated with the composition and distribution of tumor-infiltrating immune cells.

Purpose To explore modified parameters of the American College of Radiology Thyroid Imaging Reporting and Data System (TI-RADS) for evaluating contralateral nodules based on preoperative ultrasound features of papillary thyroid carcinoma (PTC) in the suspected lobe, thus guiding the management of bilateral PTC. Methods We retrospectively analyzed 389 consecutive patients with PTC (272 in training set, 117 in validation set) who underwent total thyroidectomy from March 2020 to March 2022. According to their postoperative pathological data, the patients were divided into unilateral and bilateral PTC groups. The clinicopathological features and sonographic characteristics of suspected nodules were compared between the groups, and further ultrasonic characteristics of TI-RADS grade (TR grade)-underestimated nodules were analyzed. Results Patients with a body mass index of ≥25 kg/m 2 ( P  < 0.001), multifocality in the suspected lobe ( P  < 0.001), and TR > 3 isthmus nodules ( P  = 0.003) tended to have bilateral PTC. After modifying the TI-RADS classification for contralateral nodules using these three parameters, the area under the curve for diagnosing contralateral lesions increased from 0.79 (95% confidence interval, 0.74–0.84) to 0.83 (0.78–0.87) in the training set. The missed diagnosis rate of contralateral PTC decreased in both the training set [21.1% (28/133) to 4.5% (6/133)] and validation set [11.4% (8/70) to 2.9% (2/70)]. Preoperative ultrasound tended to underestimate the contralateral nodules with the presence of cystic components [100% (6/6)] and halo sign [73.3% (11/15)]. Conclusion The modified TI-RADS classification based on the suspected lobe may facilitate effective preoperative malignant risk stratification of contralateral nodules in bilateral PTC.