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1.
Systems biomarkers for papillary thyroid cancer prognosis and treatment through multi-omics networks.
Gulfidan, G, Soylu, M, Demirel, D, Erdonmez, HBC, Beklen, H, Ozbek Sarica, P, Arga, KY, Turanli, B
Archives of biochemistry and biophysics. 2022;:109085
Abstract
The identification of biomolecules associated with papillary thyroid cancer (PTC) has upmost importance for the elucidation of the disease mechanism and the development of effective diagnostic and treatment strategies. Despite particular findings in this regard, a holistic analysis encompassing molecular data from different biological levels has been lacking. In the present study, a meta-analysis of four transcriptome datasets was performed to identify gene expression signatures in PTC, and reporter molecules were determined by mapping gene expression data onto three major cellular networks, i.e., transcriptional regulatory, protein-protein interaction, and metabolic networks. We identified 282 common genes that were differentially expressed in all PTC datasets. In addition, six proteins (FYN, JUN, LYN, PML, SIN3A, and RARA), two Erb-B2 receptors (ERBB2 and ERBB4), two cyclin-dependent receptors (CDK1 and CDK2), and three histone deacetylase receptors (HDAC1, HDAC2, and HDAC3) came into prominence as proteomic signatures in addition to several metabolites including lactaldehyde and proline at the metabolome level. Significant associations with calcium and MAPK signaling pathways and transcriptional and post-transcriptional activities of 12 TFs and 110 miRNAs were also observed at the regulatory level. Among them, six miRNAs (miR-30b-3p, miR-15b-5p, let-7a-5p, miR-130b-3p, miR-424-5p, and miR-193b-3p) were associated with PTC for the first time in the literature, and the expression levels of miR-30b-3p, miR-15b-5p, and let-7a-5p were found to be predictive of disease prognosis. Drug repositioning and molecular docking simulations revealed that 5 drugs (prochlorperazine, meclizine, rottlerin, cephaeline, and tretinoin) may be useful in the treatment of PTC. Consequently, we report here biomolecule candidates that may be considered as prognostic biomarkers or potential therapeutic targets for further experimental and clinical trials for PTC.
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2.
Skeletal health in patients with differentiated thyroid carcinoma.
Cellini, M, Rotondi, M, Tanda, ML, Piantanida, E, Chiovato, L, Beck-Peccoz, P, Lania, A, Mazziotti, G
Journal of endocrinological investigation. 2021;(3):431-442
Abstract
Osteoporosis and fractures are important comorbidities in patients with differentiated thyroid cancer (DTC), with potential negative impact on quality of life and survival. The main determinant of skeletal fragility in DTC is the thyrotropin (TSH)-suppressive therapy, which is commonly recommended to prevent disease's recurrence, especially in patients with structural incomplete response after thyroid surgery and radio-iodine therapy. TSH-suppressive therapy can stimulate bone resorption with consequent bone loss, deterioration of bone microstructure and high risk of fragility fractures. The skeletal effects of TSH-suppressive therapy may be amplified when thyroid cancer cells localize to the skeleton inducing alterations in bone remodelling, impairment of bone structure and further increase in risk of fractures. The management of skeletal fragility in DTC may be challenging, since prediction of fractures is a matter of uncertainty and data on effectiveness and safety of bone-active agents in this clinical setting are still scanty. This review deals with pathophysiological, clinical and therapeutic aspects of skeletal fragility of patients with DTC.
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3.
The Efficacy and Safety of Anlotinib in Neoadjuvant Treatment of Locally Advanced Thyroid Cancer: A Single-Arm Phase II Clinical Trial.
Huang, NS, Wei, WJ, Xiang, J, Chen, JY, Guan, Q, Lu, ZW, Ma, B, Sun, GH, Wang, YL, Ji, QH, et al
Thyroid : official journal of the American Thyroid Association. 2021;(12):1808-1813
Abstract
Background: Surgery is the primary treatment for locally advanced thyroid cancer. For some cases, R0/R1 resection could not be achieved at initial diagnosis and neoadjuvant treatment would be an option. Anlotinib is a multitarget tyrosine kinase inhibitor, which demonstrated antitumor activity in radioiodine-refractory differentiated thyroid cancer and medullary thyroid cancer. We aimed to evaluate the efficacy and safety of anlotinib in locally advanced thyroid cancer in the neoadjuvant setting. Methods: This single-arm phase II study investigated the efficacy and safety of anlotinib (12 mg orally daily, 2 weeks on/1 week off) for 2-6 cycles in patients with locally advanced thyroid cancer in the neoadjuvant setting. The key eligibility criteria included age 14-80 years old; locally advanced thyroid cancer that would benefit from surgery, and at least one measurable lesion. Operable patients received surgery after neoadjuvant treatment. The primary endpoint was objective response rate (ORR). Results: A total of 13 patients were enrolled and received an average of 3.5 cycles of anlotinib treatment. The ORR of anlotinib was 76.9% (95% confidence interval: 46.2-95.0%). The R0/R1 resection rate in the intent-to-treat population was 61.5% and in the per-protocol population was 72.7%. The median time to response was 61.5 days, and the disease control rate at 18 weeks was 92.3%. No patients had blood transfusion or tracheotomy. Most adverse events (AEs) were grade 1 or 2 and tended to discontinue when neoadjuvant treatment ceased. Common AEs of all grades were hypertension (76.9%), hypertriglyceridemia (69.2%), proteinuria (53.8%), thyrotropin increase (53.8%), cholesterol elevation (53.8%), and hand-foot syndrome (38.5%). Conclusions: Anlotinib demonstrated antitumor activity in the neoadjuvant treatment and the majority of patients achieved R0/R1 resection. AEs were consistent with the known anlotinib AE profile. These results suggest that anlotinib neoadjuvant treatment represents a new option for locally advanced thyroid cancer. Clinical Trial Registration Number: NCT04309136.
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Association between programmed cell death ligand 1 expression and thyroid cancer: A meta-analysis.
Wan, B, Deng, P, Dai, W, Wang, P, Dong, Z, Yang, C, Tian, J, Hu, T, Yan, K
Medicine. 2021;(14):e25315
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Abstract
BACKGROUND Programmed cell death ligand 1 (PD-L1), which is highly expressed in a variety of malignant tumors, is closely related to clinicopathological features and prognosis. However, there are few studies on the potential effects of PD-L1 on thyroid carcinoma, the incidence of which has shown an upward trend worldwide. This study aimed to explore the association between PD-L1 expression and clinicopathological features and prognosis of thyroid cancer. METHODS An elaborate retrieval was performed using Medline, PubMed, Cochrane Library, EMBASE, Web of Science, WanFang databases, and China National Knowledge Infrastructure to determine the association between PD-L1 expression and disease-free survival (DFS), overall survival (OS), and clinicopathological features in patients with thyroid cancer. Study selection, data extraction, risk assessment, and data synthesis were performed independently by 2 reviewers. In this meta-analysis, RevMan 5.3 and Stata 15.1 were used for bias risk assessment and data synthesis. RESULTS After a detailed search, 2546 cases reported in 13 articles were included in this meta-analysis. The outcomes revealed that high expression of PD-L1 in patients with thyroid cancer was associated with poor DFS (hazard ratio [HR] = 3.37, 95% confidence interval [CI] 2.54-4.48, P < .00001) and OS (HR = 2.52, 95% CI: 1.20-5.32, P = .01). High PD-L1 expression was associated with tumor size ≥2 cm, tumor recurrence, extrathyroidal extension, concurrent thyroiditis, unifocal tumor, and absence of psammoma body (P < .05). Subgroup analysis showed that positive expression of PD-L1 was related to poor prognosis for DFS of non-medullary thyroid carcinoma, and the overexpression of PD-L1 in differentiated thyroid carcinoma (DTC) was related to tumor recurrence, concurrent thyroiditis, extrathyroidal extension, unifocal DTC, late stage DTC, and BRAFV600E mutation in DTC. CONCLUSION PD-L1 is a significant predictor of prognosis and malignancy of thyroid cancer (especially DTC), and PD-L1 inhibitors may be a promising therapeutic option for refractory thyroid cancer in the future.
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Central lymph node dissection and permanent hypoparathyroidism after total thyroidectomy for papillary thyroid cancer: population-based study.
Salem, FA, Bergenfelz, A, Nordenström, E, Almquist, M
The British journal of surgery. 2021;(6):684-690
Abstract
BACKGROUND Papillary thyroid cancer is treated with total/near-total thyroidectomy (TT) with or without central lymph node dissection (CLND), depending on risk factors and tumour size. Balancing the risk of disease recurrence and surgical morbidity remains a challenge. A population-based nationwide study was undertaken to evaluate the risk of permanent hypoparathyroidism associated with CLND. METHOD Data on patients with stage pT1-3 papillary thyroid cancer, who underwent TT with or without CLND between 1 July 2004 and 30 June 2014 were retrieved from the Scandinavian Quality Register for Thyroid, Parathyroid and Adrenal Surgery. Drug use was ascertained by cross-linking with the Swedish Prescribed Drug Register. Permanent hypoparathyroidism was defined as treatment with active D vitamin or oral calcium drugs for more than 6 months after surgery. Data were analysed separately for all patients and those who underwent TT + CLND. Univariable and multivariable logistic regression analyses were done, yielding odds ratios (ORs) with 95 per cent confidence intervals. RESULTS A total of 722 patients were included in the study. Permanent hypoparathyroidism was more common in the TT + CLND group than the TT group: 30 of 265 patients (6·6 per cent) versus six of 457 (2·3 per cent) (P = 0·011). In multivariable logistic regression analysis, CLND was a risk factor for permanent hypoparathyroidism (OR 3·74, 95 per cent c.i. 1·46 to 9·59, based on use of combined therapy 6 months after surgery). In patients who had TT + CLND, node negativity was associated with a risk of permanent hypoparathyroidism (OR 3·08, 1·31 to 7·25). CONCLUSION CLND is an independent risk factor for permanent hypoparathyroidism. Node negativity is associated with a higher risk of permanent hypoparathyroidism.
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Shared and unique metabolic features of the malignant and benign thyroid lesions determined with use of 1H HR MAS NMR spectroscopy.
Skorupa, A, Ciszek, M, Chmielik, E, Boguszewicz, Ł, Oczko-Wojciechowska, M, Kowalska, M, Rusinek, D, Tyszkiewicz, T, Kluczewska-Gałka, A, Czarniecka, A, et al
Scientific reports. 2021;(1):1344
Abstract
The purpose of this work was to investigate the distinct and common metabolic features of the malignant and benign thyroid lesions in reference to the non-transformed tissue from the contralateral gland (chronic thyroiditis and colloid goiter). 1H HR MAS NMR spectra of 38 malignant lesions, 32 benign lesions and 112 samples from the non-tumoral tissue (32 from chronic thyroiditis and 80 samples from colloid goiter) were subjected both to multivariate and univariate analysis. The increased succinate, glutamine, glutathione, serine/cysteine, ascorbate, lactate, taurine, threonine, glycine, phosphocholine/glycerophosphocholine and decreased lipids were found in both lesion types in comparison to either colloid goiter or chronic thyroiditis. The elevated glutamate and choline, and reduced citrate and glucose were additionally evident in these lesions in reference to goiter, while the increased myo-inositol-in comparison to thyroiditis. The malignant lesions were characterized by the higher alanine and lysine levels than colloid goiter and thyroiditis, while scyllo-inositol was uniquely increased in the benign lesions (not in cancer) in comparison to both non-tumoral tissue types. Moreover, the benign lesions presented with the unique increase of choline in reference to thyroiditis (not observed in the cancerous tissue). The metabolic heterogeneity of the non-tumoral tissue should be considered in the analysis of metabolic reprogramming in the thyroid lesions.
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A Review of the Role of the S-Detect Computer-Aided Diagnostic Ultrasound System in the Evaluation of Benign and Malignant Breast and Thyroid Masses.
Zhang, D, Jiang, F, Yin, R, Wu, GG, Wei, Q, Cui, XW, Zeng, SE, Ni, XJ, Dietrich, CF
Medical science monitor : international medical journal of experimental and clinical research. 2021;:e931957
Abstract
Computer-aided diagnosis (CAD) systems have attracted extensive attention owing to their performance in the field of image diagnosis and are rapidly becoming a promising auxiliary tool in medical imaging tasks. These systems can quantitatively evaluate complex medical imaging features and achieve efficient and high-diagnostic accuracy. Deep learning is a representation learning method. As a major branch of artificial intelligence technology, it can directly process original image data by simulating the structure of the human brain neural network, thus independently completing the task of image recognition. S-Detect is a novel and interactive CAD system based on a deep learning algorithm, which has been integrated into ultrasound equipment and can help radiologists identify benign and malignant nodules, reduce physician workload, and optimize the ultrasound clinical workflow. S-Detect is becoming one of the most commonly used CAD systems for ultrasound evaluation of breast and thyroid nodules. In this review, we describe the S-Detect workflow and outline its application in breast and thyroid nodule detection. Finally, we discuss the difficulties and challenges faced by S-Detect as a precision medical tool in clinical practice and its prospects.
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Gene network and biological pathways associated with susceptibility to differentiated thyroid carcinoma.
Kulkarni, O, Sugier, PE, Guibon, J, Boland-Augé, A, Lonjou, C, Bacq-Daian, D, Olaso, R, Rubino, C, Souchard, V, Rachedi, F, et al
Scientific reports. 2021;(1):8932
Abstract
Variants identified in earlier genome-wide association studies (GWAS) on differentiated thyroid carcinoma (DTC) explain about 10% of the overall estimated genetic contribution and could not provide complete insights into biological mechanisms involved in DTC susceptibility. Integrating systems biology information from model organisms, genome-wide expression data from tumor and matched normal tissue and GWAS data could help identifying DTC-associated genes, and pathways or functional networks in which they are involved. We performed data mining of GWAS data of the EPITHYR consortium (1551 cases and 1957 controls) using various pathways and protein-protein interaction (PPI) annotation databases and gene expression data from The Cancer Genome Atlas. We identified eight DTC-associated genes at known loci 2q35 (DIRC3), 8p12 (NRG1), 9q22 (FOXE1, TRMO, HEMGN, ANP32B, NANS) and 14q13 (MBIP). Using the EW_dmGWAS approach we found that gene networks related to glycogenolysis, glycogen metabolism, insulin metabolism and signal transduction pathways associated with muscle contraction were overrepresented with association signals (false discovery rate adjusted p-value < 0.05). Additionally, suggestive association of 21 KEGG and 75 REACTOME pathways with DTC indicate a link between DTC susceptibility and functions related to metabolism of cholesterol, amino sugar and nucleotide sugar metabolism, steroid biosynthesis, and downregulation of ERBB2 signaling pathways. Together, our results provide novel insights into biological mechanisms contributing to DTC risk.
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Long-Term Results of a Phase II Trial of Apatinib for Progressive Radioiodine Refractory Differentiated Thyroid Cancer.
Lin, YS, Zhang, X, Wang, C, Liu, YQ, Guan, WM, Liang, J
The Journal of clinical endocrinology and metabolism. 2021;(8):e3027-e3036
Abstract
CONTEXT Radioiodine refractory differentiated thyroid cancer (RAIR-DTC) has been a global challenge due to its poor prognosis and limited treatment options. OBJECTIVE We report here the long-term results of the phase II clinical trial of apatinib, an anti-angiogenic tyrosine kinase inhibitor, for RAIR-DTC. METHODS This was an open-label, exploratory phase II clinical trial among progressive RAIR-DTC patients. Apatinib treatment was given once daily until disease progression, unmanageable toxicity, withdrawal, or death. The primary end points were objective response rate (ORR) and disease control rate (DCR). Progression-free survival (PFS), overall survival (OS), duration of response, long-term safety, and the association between patients with different tumor genotype (BRAFV600E and TERT promotor mutation) and their PFS rates were also assessed. RESULTS The ORR was 80%, and the DCR was 95%. The overall median PFS was 18.4 months (95% CI, 9.2-36.8 months) and the median OS was 51.6 months (95% CI, 29.2-not reached [NR]). Patients with BRAFV600E mutation (10 of 18 evaluated) had a longer median PFS compared with patients with BRAF wild-type (NR vs 9.2 months; P = 0.002). The most common adverse events included palmar-plantar erythrodysesthesia syndrome (19/20), proteinuria (18/20), and hypertension (16/20). CONCLUSION In this long-term evaluation, apatinib displayed sustainable efficacy and tolerable safety profile, warranting it as a promising treatment option for progressive RAIR-DTC.
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High prevalence of thyroid carcinoma in patients with insulin resistance: a meta-analysis of case-control studies.
Zhao, J, Zhang, Q, Yang, Y, Yao, J, Liao, L, Dong, J
Aging. 2021;(18):22232-22241
Abstract
The association between insulin resistance and thyroid carcinoma is controversial. We conducted this meta-analysis of association between insulin resistance and thyroid carcinoma. There were 14 studies included in this meta-analysis. Random-effect model was used to merge the weighted mean difference value of fasting serum insulin level and the pooled effect shows that the level of fasting serum insulin is higher in patients with thyroid carcinoma than those of controls (1.88, 95% CI 0.87 to 2.90, P=0.0003). Random-effect model was used to estimate the pooled weighted mean difference and it shows that thyroid carcinoma patients have a higher level of homeostasis model assessment of insulin resistance (HOMA-IR) than patients without thyroid carcinoma (0.54, 95% CI 0.29 to 0.78, P<0.0001). Fixed-effect model with the odds ratio of insulin resistance shows that insulin resistance could increase the risk of thyroid carcinoma 216% compared with participants without insulin resistance (3.16, 95% CI 2.09 to 4.77, P<0.0001). In conclusion, insulin resistance might be a risk factor for thyroid carcinoma.