Effect of iodine on early stage thyroid autonomy

AbstractThyroid autonomy is a frequent cause of thyrotoxicosis in regions with iodine deficiency. Epidemiological data suggest that iodide may influence the course of pre-existing thyroid autonomy.Making use of FRTL-5 cells stably expressing a constitutively activating TSH receptor mutation as an in vitro model of thyroid autonomy, we investigated the impact of iodide on proliferation, function and changes in global gene expression.We demonstrate that iodine inhibits growth in TSHR WT and L629F mutant FRTL-5 cells and downregulates e.g. protocadherin cluster (Pcdha1–13) and thyroid responsive element (Thrsp). In addition functional genes e.g. iodotyrosine deiodinase (iyd) and oncogen junB are upregulated, while sodium-iodide-symporter (Nis) and thyroid peroxidase (Tpo) are downregulated by iodide.Iodide tunes down the biological activity of autonomous thyrocytes and may thus be of therapeutic benefit not only to prevent the occurrence of somatic TSHR mutations, causing thyroid autonomy, but also to slow down the development of clinically relevant disease

TERT Promoter Mutations in Papillary Thyroid Microcarcinomas

Small papillary thyroid carcinomas have contributed to the worldwide increased incidence of differentiated thyroid cancer observed over the past decades. However, the mortality rate has not changed over the same period of time, raising questions about the possibility that thyroid cancer patients, especially those with small tumors, are overdiagnosed and overtreated. Molecular prognostic marker able to discriminate aggressive thyroid cancers from those with an indolent course would be of great relevance to tailor the therapeutic approach and reduce overtreatment. Mutations in the TERT promoter were recently reported to correlate strongly with aggressiveness in advanced forms of thyroid cancer, holding promise for a possible clinical application. The occurrence and potential clinical relevance of TERT mutations in papillary thyroid microcarcinomas (mPTCs) is currently unknown. This study aimed to analyze the occurrence of two TERT promoter mutations (-124C>T and -146C>T) and their potential association with unfavorable clinical features in a large cohort of mPTCs

Recurrent EZH1 mutations are a second hit in autonomous thyroid adenomas

Autonomous thyroid adenomas (ATAs) are a frequent cause of hyperthyroidism. Mutations in the genes encoding the TSH receptor (TSHR) or the Gs protein alpha subunit (GNAS) are found in approximately 70% of ATAs. The involvement of other genes and the pathogenesis of the remaining cases are presently unknown. Here, we performed whole-exome sequencing in 19 ATAs that were paired with normal DNA samples and identified a recurrent hot-spot mutation (c.1712A>G; p.Gln571Arg) in the enhancer of zeste homolog 1 (EZH1) gene, which codes for a catalytic subunit of the polycomb complex. Targeted screening in an independent cohort confirmed that this mutation occurs with high frequency (27%) in ATAs. EZH1 mutations were strongly associated with known (TSHR, GNAS) or presumed (adenylate cyclase 9 [ADCY9]) alterations in cAMP pathway genes. Furthermore, functional studies revealed that the p.Gln571Arg EZH1 mutation caused increased histone H3 trimethylation and increased proliferation of thyroid cells. In summary, this study revealed that a hot-spot mutation in EZH1 is the second most frequent genetic alteration in ATAs. The association between EZH1 and TSHR mutations suggests a 2-hit model for the pathogenesis of these tumors, whereby constitutive activation of the cAMP pathway and EZH1 mutations cooperate to induce the hyperproliferation of thyroid cells.IZKF Wurzburg [B-281]; ERA-NET E-Rare [01GM1407B]; Deutsche KrebshilfeDeutsche Krebshilfe [109994]; Wilhelm Sander Stiftung [2013.010.1]We wish to thank Eileen Bosenberg, Bianca Klupfel, and Ines Elsner for technical support and Ulrike Zabel for DNA cloning. This study was partially supported by grants from the IZKF Wurzburg (B-281, to DC and MF); the ERA-NET E-Rare (01GM1407B, to MF and DC); the Deutsche Krebshilfe (109994, to ME); and the Wilhelm Sander Stiftung (project 2013.010.1, to RP)

A multi-gene approach to differentiate papillary thyroid carcinoma from benign lesions: gene selection using support vector machines with bootstrapping

Selection of novel molecular markers is an important goal of cancer genomics studies. The aim of our analysis was to apply the multivariate bioinformatical tools to rank the genes – potential markers of papillary thyroid cancer (PTC) according to their diagnostic usefulness. We also assessed the accuracy of benign/malignant classification, based on gene expression profiling, for PTC. We analyzed a 180-array dataset (90 HG-U95A and 90 HG-U133A oligonucleotide arrays), which included a collection of 57 PTCs, 61 benign thyroid tumors, and 62 apparently normal tissues. Gene selection was carried out by the support vector machines method with bootstrapping, which allowed us 1) ranking the genes that were most important for classification quality and appeared most frequently in the classifiers (bootstrap-based feature ranking, BBFR); 2) ranking the samples, and thus detecting cases that were most difficult to classify (bootstrap-based outlier detection). The accuracy of PTC diagnosis was 98.5% for a 20-gene classifier, its 95% confidence interval (CI) was 95.9–100%, with the lower limit of CI exceeding 95% already for five genes. Only 5 of 180 samples (2.8%) were misclassified in more than 10% of bootstrap iterations. We specified 43 genes which are most suitable as molecular markers of PTC, among them some well-known PTC markers (MET, fibronectin 1, dipeptidylpeptidase 4, or adenosine A1 receptor) and potential new ones (UDP-galactose-4-epimerase, cadherin 16, gap junction protein 3, sushi, nidogen, and EGF-like domains 1, inhibitor of DNA binding 3, RUNX1, leiomodin 1, F-box protein 9, and tripartite motif-containing 58). The highest ranking gene, metallophosphoesterase domain-containing protein 2, achieved 96.7% of the maximum BBFR score

Analysis options for high-throughput sequencing in miRNA expression profiling

Background: Recently high-throughput sequencing (HTS) using next generation sequencing techniques became useful in digital gene expression profiling. Our study introduces analysis options for HTS data based on mapping to miRBase or counting and grouping of identical sequence reads. Those approaches allow a hypothesis free detection of miRNA differential expression. Methods: We compare our results to microarray and qPCR data from one set of RNA samples. We use Illumina platforms for microarray analysis and miRNA sequencing of 20 samples from benign follicular thyroid adenoma and malignant follicular thyroid carcinoma. Furthermore, we use three strategies for HTS data analysis to evaluate miRNA biomarkers for malignant versus benign follicular thyroid tumors. Results: High correlation of qPCR and HTS data was observed for the proposed analysis methods. However, qPCR is limited in the differential detection of miRNA isoforms. Moreover, we illustrate a much broader dynamic range of HTS compared to microarrays for small RNA studies. Finally, our data confirm hsa-miR-197-3p, hsa-miR-221-3p, hsa-miR-222-3p and both hsa-miR-144-3p and hsa-miR-144-5p as potential follicular thyroid cancer biomarkers. Conclusions: Compared to microarrays HTS provides a global profile of miRNA expression with higher specificity and in more detail. Summarizing of HTS reads as isoform groups (analysis pipeline B) or according to functional criteria (seed analysis pipeline C), which better correlates to results of qPCR are promising new options for HTS analysis. Finally, data opens future miRNA research perspectives for HTS and indicates that qPCR might be limited in validating HTS data in detail.:Background; Methods; Results; Discussion; Conclusion

Activation of mitogen-activated protein kinase signaling and development of papillary thyroid carcinoma in thyroid-stimulating hormone receptor D633H knockin mice

Objective: Nonautoimmune hyperthyroidism (NAH) is rare and occurs due to a constitutively activating thyroid stimulating hormone receptor (TSHR) mutation. In contrast to other thyroid nodules, no further evaluation for malignancy is recommended for hot thyroid nodules. In the first model for NAH in mice nearly all homozygous mice had developed papillary thyroid cancer by 12 months of age. Methods: To further evaluate these mice, whole exome sequencing and phosphoproteome analysis were employed in a further generation of mice to identify any other mutations potentially responsible and to identify the pathways involved in thyroid carcinoma development. Results: Only three genes (Nrg1, Rrs1, Rasal2) were mutated in all mice examined, none of which were known primary drivers of papillary thyroid cancer development. Wild-type and homozygous TSHR D633H knockin mice showed distinct phosphoproteome profiles with an enrichment of altered phosphosites found in ERK/mitogen-activated protein kinase (MAPK) signaling. Most importantly, phosphosites with known downstream effects included BRAF p.S766, which forms an inhibitory site: a decrease of phosphorylation at this site suggests an increase in MEK/ERK pathway activation. The decreased phosphorylation at BRAF p.S766 would suggest decreased AMP-activated protein kinase (AMPK) signaling, which is supported by the decreased phosphorylation of STIM1 p.S257, a downstream AMPK target. Conclusion: The modified phosphoproteome profile of the homozygous mice in combination with human literature suggests a potential signaling pathway from constitutive TSHR signaling and cAMP activation to the activation of ERK/MAPK signaling. This is the first time that a specific mechanism has been identified for a possible involvement of TSH signaling in thyroid carcinoma development

Comparative analysis of diagnostic performance, feasibility and cost of different test-methods for thyroid nodules with indeterminate cytology

Since it is impossible to recognize malignancy at fine needle aspiration (FNA) cytology in indeterminate thyroid nodules, surgery is recommended for all of them. However, cancer rate at final histology is < 30%. Many different test-methods have been proposed to increase diagnostic accuracy in such lesions, including Galectin-3-ICC (GAL-3-ICC), BRAF mutation analysis (BRAF), Gene Expression Classifier (GEC) alone and GEC+BRAF, mutation/fusion (M/F) panel, alone, M/F panel+miRNA GEC, and M/F panel by next generation sequencing (NGS), FDG-PET/CT, MIBI-Scan and TSHR mRNA blood assay. We performed systematic reviews and meta-analyses to compare their features, feasibility, diagnostic performance and cost. GEC, GEC+BRAF, M/F panel+miRNA GEC and M/F panel by NGS were the best in ruling-out malignancy (sensitivity = 90%, 89%, 89% and 90% respectively). BRAF and M/F panel alone and by NGS were the best in ruling-in malignancy (specificity = 100%, 93% and 93%). The M/F by NGS showed the highest accuracy (92%) and BRAF the highest diagnostic odds ratio (DOR) (247). GAL-3-ICC performed well as rule-out (sensitivity = 83%) and rule-in test (specificity = 85%), with good accuracy (84%) and high DOR (27) and is one of the cheapest (113 USD) and easiest one to be performed in different clinical settings. In conclusion, the more accurate molecular-based test-methods are still expensive and restricted to few, highly specialized and centralized laboratories. GAL-3-ICC, although limited by some false negatives, represents the most suitable screening test-method to be applied on a large-scale basis in the diagnostic algorithm of indeterminate thyroid lesions

Increasing the Number of Thyroid Lesions Classes in Microarray Analysis Improves the Relevance of Diagnostic Markers

BackgroundGenetic markers for thyroid cancers identified by microarray analysis have offered limited predictive accuracy so far because of the few classes of thyroid lesions usually taken into account. To improve diagnostic relevance, we have simultaneously analyzed microarray data from six public datasets covering a total of 347 thyroid tissue samples representing 12 histological classes of follicular lesions and normal thyroid tissue. Our own dataset, containing about half the thyroid tissue samples, included all categories of thyroid lesions. Methodology/Principal Findings Classifier predictions were strongly affected by similarities between classes and by the number of classes in the training sets. In each dataset, sample prediction was improved by separating the samples into three groups according to class similarities. The cross-validation of differential genes revealed four clusters with functional enrichments. The analysis of six of these genes (APOD, APOE, CLGN, CRABP1, SDHA and TIMP1) in 49 new samples showed consistent gene and protein profiles with the class similarities observed. Focusing on four subclasses of follicular tumor, we explored the diagnostic potential of 12 selected markers (CASP10, CDH16, CLGN, CRABP1, HMGB2, ALPL2, ADAMTS2, CABIN1, ALDH1A3, USP13, NR2F2, KRTHB5) by real-time quantitative RT-PCR on 32 other new samples. The gene expression profiles of follicular tumors were examined with reference to the mutational status of the Pax8-PPARγ, TSHR, GNAS and NRAS genes. Conclusion/Significance We show that diagnostic tools defined on the basis of microarray data are more relevant when a large number of samples and tissue classes are used. Taking into account the relationships between the thyroid tumor pathologies, together with the main biological functions and pathways involved, improved the diagnostic accuracy of the samples. Our approach was particularly relevant for the classification of microfollicular adenomas