Death-associated protein 3 is overexpressed in human thyroid oncocytic tumours

Background: The human death-associated protein 3 (hDAP3) is a GTP-binding constituent of the small subunit of the mitochondrial ribosome with a pro-apoptotic function.Methods: A search through publicly available microarray data sets showed 337 genes potentially coregulated with the DAP3 gene. The promoter sequences of these 337 genes and 70 out of 85 mitochondrial ribosome genes were analysed in silico with the DAP3 gene promoter sequence. The mitochondrial role of DAP3 was also investigated in the thyroid tumours presenting various mitochondrial contents. Results: The study revealed nine transcription factors presenting enriched motifs for these gene promoters, five of which are implicated in cellular growth (ELK1, ELK4, RUNX1, HOX11-CTF1, TAL1-ternary complex factor 3) and four in mitochondrial biogenesis (nuclear respiratory factor-1 (NRF-1), GABPA, PPARG-RXRA and estrogen-related receptor alpha (ESRRA)). An independent microarray data set showed the overexpression of ELK1, RUNX1 and ESRRA in the thyroid oncocytic tumours. Exploring the thyroid tumours, we found that DAP3 mRNA and protein expression is upregulated in tumours presenting a mitochondrial biogenesis compared with the normal tissue. ELK1 and ESRRA were also showed upregulated with DAP3. Conclusion: ELK1 and ESRRA may be considered as potential regulators of the DAP3 gene expression. DAP3 may participate in mitochondrial maintenance and play a role in the balance between mitochondrial homoeostasis and tumourigenesis

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

DNA microarray and miRNA analyses reinforce the classification of follicular thyroid tumors

Context: Focusing on mitochondrial function and thyroid tumorigenesis, we used an integrative approach to identify relevant biomarkers for borderline thyroid lesions. Design: Using cDNA and microRNA (miRNA) microarrays and quantitative RT-PCR analysis (qPCR), we explored samples of various types of thyroid tumors including 25 benign follicular adenomas represented by macrofollicular variants of thyroid adenomas, 38 oncocytic variants of follicular thyroid tumors, 19 papillary thyroid carcinomas, and 10 tumors of uncertain malignant potential, together with 53 normal thyroid tissue samples. Results: Our transcriptomic analysis, which highlighted discrepancies between controls and tumor tissues, as well as between various tumor types, led to the identification of 13 genes, allowing discrimination between the thyroid adenomas, oncocytic variants of follicular thyroid tumors, and papillary thyroid carcinomas, whereas the tumors of uncertain malignant potential were found to overlap these classes. Five of these genes (TP53, HOXA9, RUNX1, MYD88, and CITED1), with a differential expression confirmed by qPCR analysis, are implicated in tumorigenesis, 4 in mitochondrial metabolism (MRPL14, MRPS2, MRPS28, and COX6A1), and 2 in thyroid metabolic pathways (CaMKIINalpha and TPO). The global miRNA analysis revealed 62 differential miRNAs, the expression level for 10 of these being confirmed by qPCR. The differential expression of the miRNAs was in accordance with the modulation of gene expression and the ontologies revealed by our transcriptomic analysis. Conclusions: These findings reinforce the classification of follicular thyroid tumors established by the World Health Organization, and our technique offers a novel molecular approach to refine the classification of thyroid tumors of uncertain malignant potential

Decreased expression of thyrotropin receptor gene suggests a high-risk subgroup for oncocytic adenoma

International audienceOBJECTIVE: The malignancy of thyroid oncocytic tumours, or oncocytomas, is higher than that of follicular tumours. The aim of this study was to investigate the role of thyroid-specific genes in oncocytic tumours and papillary carcinomas. DESIGN AND METHODS: We compared 29 oncocytic tumours with 12 papillary carcinomas. Real-time quantitative PCR was used to measure the expression of thyroid-specific differentiation markers (thyrotrophin-stimulation hormone receptor (TSHR), thyroglobulin (TG) and Na(+)/I(-) symporter (NIS)), transcription factors (thyroid transcription factor-1 (TTF-1) and paired box gene-8 (PAX8)) and nuclear receptors (peroxisome proliferator-activated receptor (PPARgamma1) and thyroid hormone receptor (TRbeta1)) involved in thyroid carcinogenesis. RESULTS: TSHR, TTF-1 and TRbeta1 levels were significantly lower in oncocytic tumours than in papillary carcinomas, as a result of specific biological changes in oncocytic tumours. However, PAX8 and PPARgamma1 did not seem to be involved in the process. Applying the criterion of the underexpression of the thyroid-specific differentiation markers, TSHR, TG and NIS, we classified the oncocytic tumours and papillary carcinomas into three groups. In the first, all three markers were underexpressed; in the second, TSHR was normal while TG and NIS were underexpressed; and in the third, only NIS was underexpressed. The expression patterns revealed that 13 of the 24 oncocytic adenomas underexpressing TSHR in our study, as did four of the five oncocytic carcinomas. CONCLUSION: Cases of oncocytic adenoma associated with low levels of TSHR could be putative oncocytic carcinomas and should therefore receive adequate follow-up [corrected]