Search Results (280)

Background/Objectives: To elucidate the differential transcriptional and intercellular signaling features of tumor components across various cancers, we conducted a comparative analysis using single-cell RNA sequencing (scRNA-seq). This technology enables detailed characterization of tumor ecosystems and may explain variations in tumor behavior among distinct cancer types. Methods: We analyzed publicly available scRNA-seq datasets (GEO) from seven cancer types—pancreatic ductal adenocarcinoma (PDAC), hepatocellular carcinoma (HCC), esophageal squamous cell carcinoma (ESCC), breast cancer (BC), thyroid cancer (TC), gastric cancer (GC), and colorectal cancer (CRC)—to define their unique molecular characteristics and intercellular interactions. Results: PDAC displayed a distinct tumor microenvironment (TME) dominated by myeloid cells (~42%), including abundant CXCR1/CXCR2-expressing tumor-associated neutrophils (TANs) that preferentially interacted with immune rather than cancer cells. The competitive receptor ACKR1 was minimally expressed on endothelial cells, consistent with PDAC hypo-vascularity. In HCC, tumor cells lacked EPCAM and expressed complement and stem cell markers; cancer-associated fibroblasts (CAFs) were scarce, and stellate cells expressed the pericyte marker RGS5. CAFs were abundant in ESCC and BC, with IGF1/2 expression, while in GC, these markers were uniquely found in plasma cells. Since BC and GC subtypes exhibit distinct TME patterns, it is necessary to perform subtype-specific analyses for these cancers. TC showed high expression of tumor-suppressor genes, including HOPX, in tumor cells. Differential interactions and the presence of “dominant signaling cell populations “ with dominant outgoing signals may underlie the heterogeneity in tumor aggressiveness across these cancers. Conclusions: Comparative scRNA-seq analysis of multiple cancers reveals distinct tumor phenotypes and cell–cell communication patterns, offering insights into the molecular architecture of human solid tumors. Full article

Background: Follicular thyroid carcinoma (FC) accounts for 10–15% of all thyroid cancers. FC is challenging to diagnose using fine-needle aspiration (FNA), making diagnostic thyroidectomy the standard approach. Recent studies have explored the use of circulating microRNAs for thyroid cancer diagnosis. This study evaluated the diagnostic value of circulating miRNAs in plasma for FC to potentially reduce unnecessary thyroidectomies and repeat invasive procedures. Methods: This study was a retrospective observational study, and included consecutively selected 90 patients who underwent thyroidectomy at Pusan National University Hospital between January 2013 and February 2024 and were diagnosed with FC (49 patients) or follicular thyroid adenoma (FA) (41 patients) on final histopathology. Of these, 58 patients were enrolled in the utility assessment and 32 patients were included in the validation test. Among the 58 patients included in the utility assessment, microarray analysis was conducted on 15 patients who were randomly selected to identify novel plasma miRNAs. Next, TaqMan qRT-PCR was performed to evaluate the diagnostic utility of five plasma miRNAs and to develop a predictive model capable of predicting FC from FA using logistic regression as the utility assessment on 58 patients. Finally, in the validation test, TaqMan qRT-PCR and statistical analysis were conducted again on 32 patients and the constructed predictive models, verifying the accuracy of the predictive model. Results: Using microarray analysis, a novel miRNA, miR-6085, was identified for its distinguishing capability between FC and FA. In the utility assessment, miR-6085, miR-146b-5p, miR-221, and miR-222 were significantly upregulated in the FC group. A predictive model combining these four miRNAs showed strong diagnostic value for FC, with an AUC of 0.928 (0.843, 1.000), sensitivity of 94.7% (84.2, 100), specificity of 86.4% (68.2, 100). The accuracy of this model was 76.2% (52.8, 91.8) in the validation test. Conclusions: A model combining four miRNAs (miR-6085, miR-146b-5p, miR-221, and miR-222) demonstrated high sensitivity, specificity, and accuracy, suggesting that it could be a useful tool for differentiating FC from FA. Full article

Background/Objectives: The optimal extent of lateral lymph node dissection in cN1b differentiated thyroid cancer remains controversial. This systematic review aimed to assess the frequency of lymph node involvement across neck levels I to V. Materials and Methods: A systematic review was conducted following PRISMA guidelines. PubMed was searched for studies on lateral neck dissection in differentiated thyroid cancer. Included studies reported level-specified metastatic rates. Data on patient numbers and metastatic events were extracted. A random-effects meta-analysis with Freeman–Tukey double arcsine transformation was performed for each neck level to calculate pooled prevalence proportions and 95% confidence intervals. Heterogeneity was assessed using the I² statistic. Results: Meta-analysis of 57 studies revealed that level III (68%, 95% CI: 63–73) and level IV (66%, 95% CI: 61–70) had the highest metastatic prevalence, followed by level IIA (46%, 95% CI: 37–56). Level V demonstrated an overall prevalence of 22% (95% CI: 18–26), with sublevel VB (19%, 95% CI: 11–28) significantly higher than VA (4%, 95% CI: 1–9). Level I (6%, 95% CI: 2–11) and sublevel IIB (14%, 95% CI: 9–20) showed the lowest risk. Significant heterogeneity (I² 71–94%) was observed across all levels. Conclusions: Our findings support sparing level I, and sublevels IIB and VA during lateral neck dissection. Current guidelines recommend systematic dissection of IIA, III, IV, and VB, although VB involvement was found to be only 19% in our study. Future personalization of the extent of neck dissection, based on individual risk factors, may be key to optimizing oncologic and functional outcomes. Full article

Background: Obesity has been proposed as a risk factor for differentiated thyroid carcinoma (DTC), though findings in the literature remain conflicting. While some studies suggest an association between elevated body mass index (BMI) and thyroid malignancy, others attribute this link to diagnostic bias. The Calabria region in Southern Italy, historically affected by iodine deficiency and endemic goiter, offers a valuable population for investigating this relationship. Objective: This study aimed to evaluate the association between obesity and clinical, sonographic, and cytological characteristics of thyroid nodules in a Calabrian cohort undergoing fine-needle aspiration biopsy (FNAB). Methods: This retrospective observational study included 1192 patients evaluated at a single endocrine referral center between 2015 and 2024. Patients were stratified by BMI (<30 vs. ≥30 kg/m²). Demographic, biochemical, ultrasound, and cytological data were collected and analyzed. Cytological results were classified according to the SIAPEC 2014 system. Results: Obese patients had significantly larger thyroid nodules in terms of anteroposterior and transverse diameters, as well as overall volume (p < 0.05). However, the distribution of high-risk cytological categories (TIR 3B, TIR 4, and TIR 5) did not differ significantly between obese and non-obese patients (9.4% in both groups). Multivariate analysis confirmed that BMI was not an independent predictor of malignancy risk (OR 0.988; p = 0.723), whereas younger age was inversely associated with malignancy. Conclusions: Obesity appears to influence thyroid nodule size but does not constitute an independent risk factor for cytological malignancy. BMI should not influence indications for FNAB or subsequent treatment decisions. Thyroid nodule management should instead rely on ultrasound risk stratification and cytological findings. Special attention should be given to younger patients as they may carry a higher malignancy risk. Full article

Aggressive thyroid carcinomas—anaplastic (ATC) and poorly differentiated (PDTC)—are rare but highly lethal malignant entities. Their immunophenotypical characterization is still incomplete, and no standardized diagnostic algorithms have been used. Our study retrospectively analyzes 40 thyroidectomy cases as follows: 12 ATC and 28 PDTC from 2014 to 2024 by evaluating clinical data, histopathological aspects, molecular analysis for presence of BRAFV600E and TERTC228/250T mutations, as well as immunohistochemical expression of BRAF_V600E, total BRAF, K-RAS, TERT, PAX-8, TTF-1, P53, and Ki-67. BRAF_V600E was present in 70% of cases, with higher prevalence in ATC. Total BRAF correlated positively with K-RAS and TERT and negatively with BRAF_V600E. TERT abnormal expression was highly prevalent in over 90% of cases, while loss of TTF-1 and PAX-8 is associated with anaplastic transformation. Ki-67 proliferative index had significantly higher values in ATC, thus supporting its role as a marker for aggressiveness. On univariate analysis, higher Ki-67 indices and lymph node invasion are independent predictor factors for the presence of metastases. However, on multivariate analysis, they both lose significance. Upon multivariate analysis, loss of TTF-1 and tumor necrosis were significant predictors for anaplastic histotype. Specific BRAF_V600E immunohistochemistry may be a good screening tool for the BRAF_V600E mutation. Molecularly, there is a relatively frequent association of the BRAFV600E mutation and TERTC228, mainly in the PDTC subgroup. Patterns of marker expression suggest that BRAF or RAF activation with subsequent loss of TTF-1 or PAX-8, TERT upregulation, and TP53 alteration are frequent occurrences in aggressive thyroid carcinomas. The association between TTF-1 loss and anaplastic transformation, presence of necrosis alongside BRAF_V600E, underlines their diagnostic potential in subclassifying aggressive thyroid carcinomas. Full article

Genomic studies have provided key insights into the molecular pathogenesis of differentiated thyroid carcinoma (DTC), including the role of genes involved in the homologous recombination (HR) related to DNA repair and genomic stability. This research aimed to investigate the genetic landscape of HR genes in thyroid pathology, associated with recurrence risk and clinical prognosis. The study involved six individuals with thyroid conditions, including two patients diagnosed with papillary thyroid carcinoma (PTC) and four individuals with benign thyroid disease. The research material consisted of tumor samples collected during surgical procedures. Protein interactions were analyzed using the STRING database (string-db.org). Homologous recombination genes were sequenced using the HRR Panel vr1.0 on the MiSeq™ Sequencing System. Bioinformatics analysis revealed a relationship between BRAF mutations and HR gene defects in PTC. Mutations in BRCA1, BRCA2, and FANCA genes, typically associated with thyroid tumors, were identified in the tissue of papillary thyroid cancer (PTC). A statistically significant correlation was found between the FANCA gene mutation (rs7195066) and the recurrent course of the PTC. The preliminary findings suggest a potential role for non-pathogenic BARD1 mutations in follicular adenoma. No significant association was found between genes involved in homologous recombination repair and the incidence of papillary thyroid carcinoma, suggesting that these genes may not play a major role in the development of this type of thyroid cancer. Full article

Differentiated thyroid carcinoma (DTC) is the most common endocrine malignancy and typically has a favorable prognosis. However, a subset of patients experience aggressive disease, recurrence, or treatment resistance, underscoring the need for more precise diagnostic and therapeutic strategies. Advances in molecular profiling have improved the management of thyroid cancer by enabling risk-adapted treatment and targeted interventions. This narrative review offers a clinically focused synthesis of the current role of molecular diagnostics and personalized therapeutics in DTC. We examine key genetic alterations and their diagnostic, prognostic, and therapeutic implications, and discuss how molecular markers enhance traditional risk stratification systems, informing surgical decisions, radioactive iodine (RAI) use, and surveillance. The growing role of targeted therapies, such as tyrosine kinase inhibitors and agents against specific oncogenic drivers, is reviewed, particularly for RAI-refractory DTC. We also address real-world challenges in implementing precision medicine, including access, cost, and standardization. Future directions, such as liquid biopsy, artificial intelligence, and multi-omic integration, are explored as tools to achieve fully personalized care. This review aims to bridge the gap between molecular discovery and clinical application, offering practical insights for endocrinologists, surgeons, oncologists, and multidisciplinary teams managing DTC. Full article

Background/Objectives: Thyroid cancer encompasses distinct histological subtypes with varying biological behavior and treatment implications. Accurate preoperative subtype differentiation remains challenging. Although ultrasound (US) is widely used for thyroid nodule evaluation, qualitative assessment alone is often insufficient to distinguish between papillary (PTC), follicular (FTC), and medullary thyroid carcinoma (MTC). Methods: A retrospective analysis was performed on patients with histologically confirmed PTC, FTC, or MTC. A total of 224 standardized B-mode ultrasound images were analyzed. A set of fully quantitative features was extracted, including morphological characteristics (aspect ratio and perimeter-to-area ratio), internal echotexture (echogenicity and local entropy), boundary sharpness (gradient measures and KL divergence), and structural components (calcifications and cystic areas). Feature extraction was conducted using semi-automatic algorithms implemented in MATLAB. Statistical differences were assessed using the Kruskal–Wallis and Dunn–Šidák tests. A Random Forest classifier was trained and evaluated to determine the discriminatory performance of individual and combined features. Results: Significant differences (p < 0.05) were found among subtypes for key features such as perimeter-to-area ratio, normalized echogenicity, and calcification pattern. The full-feature Random Forest model achieved an overall classification accuracy of 89.3%, with F1-scores of 93.4% for PTC, 85.7% for MTC, and 69.1% for FTC. A reduced model using the top 10 features yielded an even higher accuracy of 91.8%, confirming the robustness and clinical relevance of the selected parameters. Conclusions: Subtype classification of thyroid cancer was effectively performed using quantitative ultrasound features and machine learning. The results suggest that biologically interpretable image-derived metrics may assist in preoperative decision-making and potentially reduce the reliance on invasive diagnostic procedures. Full article

Background/Objectives: Differentiating between benign and malignant cervical lymph nodes (LNs) is a critical challenge in the clinical setting. We assessed the ability of shear wave elastography (SWE) to distinguish between lymphomas and solid tumor metastases presenting as cervical adenopathy. Methods: We performed a single-center, prospective, observational study in adults with clinically suspicious cervical lymph nodes. The ultrasound examination included conventional ultrasound and SWE with quantitative assessment (tissue stiffness in kPa). Pathology examination was the definitive confirmation method. Simple univariate binary logistic regression and multiple univariate binary logistic regression were used. Results: The maximum shear wave velocity (SWV) in patients with benign pathologies was 35 kPa, lower than the minimal values for lymphoma (40 kPa) and metastases (50 kPa). Furthermore, squamous cell carcinoma and distant metastases were more prevalent among men. Independent from other factors used in the statistical model, we found a positive association between sex and the presence of metastatic lymph nodes. Finally, each 1 kPa from SWE measurement was associated with a 3% increase in the risk for LNs to present metastatic adenopathy. Conclusions: This study highlights the potential of SWE for the preoperative assessment of nodal status in patients with various malignancies affecting the head and neck region, thyroid, and other areas. Full article

Poorly differentiated thyroid malignancy, a rare histological type of aggressive thyroid malignancy with associated difficulties and gaps in its histological and molecular characterization, might lead to challenging clinical presentations that require a prompt multimodal approach. This case study involved a 56-year-old, non-smoking male with a rapidly developing goiter (within 2–3 months) in association with mild, non-specific neck compressive symptoms. His medical history was irrelevant. A voluminous goiter with substernal and posterior extension up to the vertebral bodies was detected using an ultrasound and computed tomography (CT) scan and required emergency thyroidectomy. He had normal thyroid function, as well as negative thyroid autoimmunity and serum calcitonin. The surgery was successful upon “Y” incision, which was used to give better access to the retrosternal component in order to avoid a sternotomy. Post-operatively, the subject developed hypoparathyroidism-related hypocalcemia and showed a very high serum thyroglobulin level (>550 ng/mL). The pathological report confirmed poorly differentiated, multifocal thyroid carcinoma (with an insular, solid, and trabecular pattern) against a background of papillary carcinoma (pT3b, pN0, and pM1; L1; V2; Pn0; R1; and stage IVB). The subject received 200 mCi of radioiodine therapy for 6 weeks following the thoracic surgery. Whole-body scintigraphy was performed before radioiodine therapy and showed increased radiotracer uptake at the thyroid remnants and pre-tracheal levels. Additionally, single-photon emission computed tomography combined with CT (SPECT/CT) was performed, and confirmed the areas of intense uptake, in addition to a moderate uptake in the right and left pulmonary parenchyma, suggesting lung metastasis. To conclude, an overall low level of statistical evidence exists regarding poorly differentiated malignancy in substernal goiters, and the data also remains scarce regarding the impact of genetic and molecular configurations, such as the BRAF-positive profile, in this specific instance. Furthermore, multimodal management includes additional diagnosis methods such as SPECT/CT, while long-term multilayered therapy includes tyrosine kinase inhibitors if the outcome shows an iodine-resistant profile with a poor prognosis. Awareness remains a key factor in cases of a poorly differentiated carcinoma presenting as a rapidly growing goiter with substernal extension in an apparently healthy adult. A surgical approach, while varying with the surgeon’s skills, represents a mandatory step to ensure a better prognosis. In addition to a meticulous histological characterization, genetic/molecular features provide valuable information regarding the outcome and can further help with the decision to use new anti-cancer drugs if tumor response upon radioiodine therapy is no longer achieved; such a development is expected in this disease stage in association with a BRAF-positive configuration. Full article

Organoid and spheroid technologies have rapidly become pivotal in thyroid cancer research, offering models that are more physiologically relevant than traditional two-dimensional culture. In the study of papillary and anaplastic thyroid carcinomas, two subtypes that differ both histologically and clinically, three-dimensional (3D) models offer unparalleled insights into tumor biology, therapeutic vulnerabilities, and resistance mechanisms. These models maintain essential tumor characteristics such as cellular diversity, spatial structure, and interactions with the microenvironment, making them extremely valuable for disease modeling and drug testing. This review emphasizes recent progress in the development and use of thyroid cancer organoids and spheroids, focusing on their role in replicating disease features, evaluating targeted therapies, and investigating epithelial–mesenchymal transition (EMT), cancer stem cell behavior, and treatment resistance. Patient-derived organoids have shown potential in capturing individualized drug responses, supporting precision oncology strategies for both differentiated and aggressive subtypes. Additionally, new platforms, such as thyroid organoid-on-a-chip systems, provide dynamic, high-fidelity models for functional studies and assessments of endocrine disruption. Despite ongoing challenges, such as standardization, limited inclusion of immune and stromal components, and culture reproducibility, advancements in microfluidics, biomaterials, and machine learning have enhanced the clinical and translational potential of these systems. Organoids and spheroids are expected to become essential in the future of thyroid cancer research, particularly in bridging the gap between laboratory discoveries and patient-focused therapies. Full article

Thyroid cancer, the most frequently occurring endocrine neoplasm, comprises a heterogeneous group of histological subtypes, spanning from the indolent papillary thyroid carcinoma (PTC) to the rapidly progressive and lethal anaplastic thyroid carcinoma (ATC). Although conventional therapies, such as surgery and radioactive iodine (RAI), are effective for differentiated thyroid cancers, treatment resistance and poor prognosis remain major challenges in advanced and undifferentiated forms. In current times, growing attention has been directed toward the potential of Natural Killer (NK) cells as a promising immunotherapeutic avenue. These innate immune cells are capable of direct cytotoxicity against tumor cells, but their efficiency is frequently compromised by the immunosuppressive tumor microenvironment (TME), which inhibits NK cell activation, infiltration, and persistence. This review explores the dynamic interaction between NK cells and the TME in thyroid cancer, detailing key mechanisms of immune evasion, including the impact of suppressive cytokines, altered chemokine landscapes, and inhibitory ligand expression. We further discuss latest advancements in NK cell-based immunotherapies, including strategies for ex vivo expansion, genetic modification, and combinatorial approaches with checkpoint inhibitors or cytokines. Additionally, emerging modalities, such as NK cell-derived extracellular vesicles, are addressed. By combining mechanistic insights with advancing therapeutic techniques, this review provides a comprehensive perspective on NK cell-based interventions and their future potential in improving outcomes for patients with thyroid cancer. Full article

Background and Objectives: Thyroid nodules are a common endocrine disorder, with 10–15% exhibiting malignancy. Accurate differentiation of malignant and benign nodules is crucial for optimizing treatment outcomes. Current diagnostic tools, such as the Bethesda classification and fine-needle aspiration biopsy (FNAB), are limited in sensitivity and specificity, particularly in indeterminate cases. Tumor-infiltrating immune cells (TIICs) in the tumor microenvironment (TME) play a significant role in thyroid cancer progression. CD66b⁺ neutrophil-like monocytes constitute a novel subset of myeloid cells that are implicated in the modulation of anti-tumor immune responses, but their role in thyroid cancer remains unclear. Materials and Methods: Peripheral blood and thyroid nodule tissue samples were obtained from 24 patients with papillary thyroid carcinoma, and from 10 patients who underwent surgery for symptoms of tracheal compression due to benign thyroid nodules. Myeloid cell populations were assayed by flow cytometric immunophenotyping with CD45, HLA-DR, CD14, and CD66b. The data were statistically analyzed with the clinical properties of the patients. Results: The neutrophil-like monocytes, which were determined as HLA-DR⁺CD14⁺CD66b⁺ cells, found in the circulation (11.9 ± 2.4% of total mononuclear immune cells) of the patients with papillary thyroid carcinoma, were significantly elevated (p < 0.001). Accordingly, these cells were more frequently detected in tumor tissues (21.1 ± 2.1% of total tumor-infiltrating immune cells) compared to non-tumor thyroid tissues (p = 0.0231). The infiltration levels of neutrophil-like monocytes were significantly higher in malignant nodules as well as in the peripheral blood of the papillary thyroid carcinoma patients compared to the samples obtained from the patients with benign nodules. The tumor tissues exhibited increased immune cell infiltration and harbored CD66b-expressing neutrophil-like HLA-DR⁺CD14⁺ monocytic cells, which indicates an inflammatory milieu in malignant thyroid cancer. Conclusions: This study identifies neutrophil-like monocytes as a potential biomarker for differentiating malignant and benign thyroid nodules. Elevated levels of this novel subtype of immune cells in malignant tissues suggest their role in tumor progression and their utility in enhancing diagnostic accuracy. Incorporating these findings into clinical practice may refine surgical decision-making and improve outcomes through personalized diagnostic and therapeutic strategies, particularly for radioiodine-refractory thyroid cancer. Full article

Background/Objectives: Differentiated Thyroid Cancer (DTC), comprising papillary and follicular carcinomas, is the most common type of thyroid cancer. This is highly infectious and increasing at a higher rate. Some patients experience recurrence even after undergoing successful treatment. Early signs of recurrence can be hard to identify, and the existing health care system cannot always identify it on time. Therefore, predicting its recurrence accurately and in its early stage is a significant clinical challenge. Numerous advanced technologies, such as machine learning, are being used to overcome this clinical challenge. Thus, this study presents a novel approach for predicting the recurrence of DTC. The key objective is to improve the prediction accuracy through hyperparameter optimization. Methods: In order to achieve this, we have used a metaheuristic algorithm, the whale optimization algorithm (WOA) and its modified version. The modifications that we introduced in the original WOA algorithm are a piecewise linear chaotic map for population initialization and inertia weight. Both of our algorithms optimize the hyperparameters of the Extreme Gradient Boosting (XGBoost) model to increase the overall performance. The proposed algorithms were applied to the dataset collected from the University of California, Irvine (UCI), Machine Learning Repository to predict the chances of recurrence for DTC. This dataset consists of 383 samples with a total of 16 features. Each feature captures the critical medical and demographic information. Results: The model has shown an accuracy of 99% when optimized with WOA and 97% accuracy when optimized with the modified WOA. Conclusions: Furthermore, we have compared our work with other innovative works and validated the performance of our model for the prediction of DTC recurrence. Full article

Background and Objectives: Thyroid cancer is the prevailing endocrine malignancy, with incidence growing over the last decades in the world. The current diagnostic techniques often yield inconclusive results, emphasizing the need for more effective diagnostic approaches. Molecular profiling emerges as a promising avenue for carcinoma differentiation, offering precise insights to guide patient selection for surgical intervention. This study aimed to identify molecular markers in thyroid cancer through the expression analysis of genes within the MAPK pathway, aiming to enhance the sensitivity and specificity of carcinoma diagnosis. Methods: Through a comparative analysis of malignant and benign thyroid samples, we identified 46 genes of the MAPK pathway that exhibited differential expression by PCR array analysis. Results: Validation through RT-qPCR and in silico analysis using TCGA confirmed significant results for CCNA1, CDKN1C, CREB1, FOS, HSPA5, JUN, MAP2K6, and SFN genes identified in our cohort, reinforcing the relevance of these biomarkers. Specifically, noteworthy are our findings regarding the potential diagnostic value of CCNA1 and SFN genes in papillary thyroid carcinoma, while the reduced expression of CDKN1C, FOS, and JUN genes in follicular carcinoma suggests their value in distinguishing the thyroid pathologies. Conclusions: This study identifies promising diagnostic markers, namely CCNA1, CDKN1C, FOS, JUN, and SFN genes, which have the potential to enhance clinical decision-making in thyroid cancer. Full article