Microarray analysis refines classification of non-medullary thyroid tumours of uncertain malignancy

Follicular Thyroid Adenoma and Follicular Thyroid Carcinoma-A Common or Distinct Background? Loss of Heterozygosity in Comprehensive Microarray Study

Pre- and postsurgical differentiation between follicular thyroid adenoma (FTA) and follicular thyroid cancer (FTC) represents a significant diagnostic challenge. Furthermore, it remains unclear whether they share a common or distinct background and what the mechanisms underlying follicular thyroid lesions malignancy are. The study aimed to compare FTA and FTC by the comprehensive microarray and to identify recurrent regions of loss of heterozygosity (LOH). We analyzed formalin-fixed paraffin-embedded (FFPE) samples acquired from 32 Caucasian patients diagnosed with FTA (16) and FTC (16). We used the OncoScan™ microarray assay (Affymetrix, USA), using highly multiplexed molecular inversion probes for single nucleotide polymorphism (SNP). The total number of LOH was higher in FTC compared with FTA (18 vs. 15). The most common LOH present in 21 cases, in both FTA (10 cases) and FTC (11 cases), was 16p12.1, which encompasses many cancer-related genes, such as TP53, and was followed by 3p21.31. The only LOH present exclusively in FTA patients (56% vs. 0%) was 11p11.2-p11.12. The alteration which tended to be detected more often in FTC (6 vs. 1 in FTA) was 12q24.11-q24.13 overlapping FOXN4, MYL2, PTPN11 genes. FTA and FTC may share a common genetic background, even though differentiating rearrangements may also be detected.

Downregulation of miR‑193a‑3p via targeting cyclin D1 in thyroid cancer

Thyroid cancer (TC) is a frequently occurring malignant tumor with a rising steadily incidence. microRNA (miRNA/miR)‑193a‑3p is an miRNA that is associated with tumors, playing a crucial role in the genesis and progression of various cancers. However, the expression levels of miR‑193a‑3p and its molecular mechanisms in TC remain to be elucidated. The present study aimed to probe the expression of miR‑193a‑3p and its clinical significance in TC, including its underlying molecular mechanisms. Microarray and RNA sequencing data gathered from three major databases, specifically Gene Expression Omnibus (GEO), ArrayExpress and The Cancer Genome Atlas (TCGA) databases, and the relevant data from the literature were used to examine miR‑193a‑3p expression. Meta‑analysis was also conducted to evaluate the association between clinicopathological parameters and miR‑193a‑3p in 510 TC and 59 normal samples from the TCGA database. miRWalk 3.0, and the TCGA and GEO databases were used to predict the candidate target genes of miR‑193a‑3p. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes and protein‑protein interaction network enrichment analyses were conducted by using the predicted candidate target genes to investigate the underlying carcinogenic mechanisms. A dual luciferase assay was performed to validate the targeting regulatory association between the most important hub gene cyclin D1 (CCND1) and miR‑193a‑3p. miR‑193a‑3p expression was considerably downregulated in TC compared with in the non‑cancer controls (P<0.001). The area under the curve of the summary receiver operating characteristic was 0.80. Downregulation of miR‑193a‑3p was also significantly associated with age, sex and metastasis (P=0.020, 0.044 and 0.048, respectively). Bioinformatics analysis indicated that a low miR‑193a‑3p expression may augment CCND1 expression to affect the biological processes of TC. In addition, CCND1, as a straightforward target, was validated through a dual luciferase assay. miR‑193a‑3p and CCND1 may serve as prognostic biomarkers of TC. Finally, miR‑193a‑3p may possess a crucial role in the genesis and progression of TC by altering the CCND1 expression.

Aging-associated genes TNFRSF12A and CHI3L1 contribute to thyroid cancer: An evidence for the involvement of hypoxia as a driver

The prevalence of thyroid cancer (TC) is high in the elderly. The present study was based on the hypothesis that genes, which have increased activity with aging, may play a role in the development of TC. A large-scale literature-based data analysis was conducted to explore the genes that are implicated in both TC and aging. Subsequently, a mega-analysis of 16 RNA expression datasets (1,222 samples: 439 healthy controls, and 783 patients with TC) was conducted to test a set of genes associated with aging but not TC. To uncover a possible link between these genes and TC, a functional pathway analysis was conducted, and the results were validated by analysis of gene co-expression. A multiple linear regression (MLR) model was employed to study the possible influence of sample size, population region and study age on the gene expression levels in TC. A total of 262 and 816 genes were identified to have increased activity with aging and TC, respectively; with a significant overlap of 63 genes (P<3.82×10⁻³⁵). The mega-analysis revealed two aging-associated genes (CHI3L1 and TNFRSF12A) to be significantly associated with TC (P<2.05×10⁻⁸), and identified the association with multiple hypoxia-driven pathways through functional pathway analysis, also confirmed by the co-expression analysis. The MLR analysis identified population region as a significant factor contributing to the expression levels of CHI3L1 and TNFRSF12A in TC samples (P<3.24×10⁻⁴). The determination of genes that promote aging was warranted due to their possible involvement in TC. The present study suggests CHI3L1 and TNFRSF12A as novel common risk genes associated with both aging and TC.

Clinical Significance and Potential Regulatory Mechanisms of Serum Response Factor in 1118 Cases of Thyroid Cancer Based on Gene Chip and RNA-Sequencing Data

Background

Thyroid cancer (TC) is one of the most prevalent endocrine malignancies and there may be many unclarified molecular events and gene types involved in TC. The objective of this study was to assess the clinical implications and potential mechanisms of serum response factor (SRF) in TC.

Material/Methods

RNA-sequencing and gene chip data with TC expression were collected from The Cancer Genome Atlas/Genotype-Tissue Expression, Gene Expression Omnibus, ArrayExpress, Sequence Read Archive, and Oncomine. SRF expression of all TC and adjacent non-cancerous tissue were calculated using the t test, STATA, and Meta-DiSc. The related pathways of the potential SRF target genes and target miRNAs were explored. Dual-luciferase reporter assay was performed to validate the association between SRF and its putative miRNA.

Results

One RNA-sequencing and 15 gene chips were collected, and the pooled standardized mean difference of SRF was −1.00. Furthermore, the area under the curve of sROC of SRF in TC was 0.8251, indicating a dramatic decreased expression of SRF in TC tissues based on 1118 cases. The intersection of differentially expressed genes in TC, SRF co-expressed genes, and SRF potential target genes achieved from Cistrome Cancer led to 169 overlapped genes. miR-330-5p was predicted to target SRF, which was further confirmed by dual-luciferase reporter assay.

Conclusions

The reduction of SRF appears to play a crucial role in the origin of TC. These properties are accomplished by the target genes of SRF, as a transcription factor, or by the axes with the associated miRNAs.

Genetic expression profile-based screening of genes and pathways associated with papillary thyroid carcinoma

Papillary thyroid carcinoma (PTC) is the most common subtype of thyroid cancer; however, the specific genes and signaling pathways involved in this cancer remain largely unclear. The present study analyzed three profile datasets, GSE6004, GSE29265 and GSE60542, which were comprised of 47 PTC and 41 normal thyroid tissue samples, to identify key genes and pathways associated with PTC. Initially, differentially-expressed genes (DEGs) between PTC and normal thyroid tissue were screened using R 3.4.0 (2017-04-21, R Foundation, Vienna, Austria, http://www.R-project.org/). These DEGs were then clustered by gene ontology functional terms and representative signaling pathways. Additionally, specific key gene nodes were filtered out from a constructed protein-protein interaction (PPI) network. The results identified a total of 423 shared DEGs associated with PTC, including 211 upregulated and 212 downregulated genes. These 423 genes were primarily enriched in glycosaminoglycan binding, sulfur compound binding, heparin binding, enzyme activator activity, peptidase activator activity and hsa04512: Extracellular matrix (ECM)-receptor interaction. A total of 21 central node genes were identified as key genes in the PTC disease process including complement factor D (CFD), Collagen Type I α 1 Chain (COL1A1), Extracellular Matrix Protein 1 (ECM1) and Fibronectin 1 (FN1). These genes are involved in protease binding, G-protein coupled receptor binding, extracellular matrix structural constituent and peptidase regulator activity. To conclude, using bioinformatics analysis, the present study identified candidate DEGs and critical pathways in PTC that may improve the current understanding regarding the underlying mechanisms of PTC. These genes and pathways may be used as potential therapeutic targets of PTC in the future.

Prediction of metastasis in advanced colorectal carcinomas using CGH data

Logistic Regression Model (LRM) and artificial neural networks (ANNs) as two nonlinear models have been used to establish a novel two-stage hybrid modeling procedure for prediction of metastasis in advanced colorectal carcinomas. Two different datasets were used in training and testing procedures. For the first stage of hybrid modeling procedure, LRM was used to evaluate the contribution of DNA sequence copy number aberrations detected by Comparative Genomic Hybridization in advanced colorectal carcinoma and its metastasis. Then, the most effective parameters were selected by the LRM. Selected effective parameters among 565 detected chromosomal gains and losses were as follows: gain of 20q11.2, loss of 1q42, loss of 13q34, gain of 5q12, gain of 17p13, loss of 2q22, loss of 11q24 and gain of 2p11.2. Consequently, neural network models were constructed and fed by the parameters selected by LRM to build hybrid predictors on the two databases during self-consistency and jackknife tests, and performance of the hybrid model was verified. The results showed that our two-stage hybrid model approach is very promising for prediction of metastasis in advanced colorectal carcinomas.

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.

REGγ is associated with multiple oncogenic pathways in human cancers

Background

Recent studies suggest a role of the proteasome activator, REGγ, in cancer progression. Since there are limited numbers of known REGγ targets, it is not known which cancers and pathways are associated with REGγ.

Methods

REGγ protein expressions in four different cancers were investigated by immunohistochemistry (IHC) analysis. Following NCBI Gene Expression Omnibus (GEO) database search, microarray platform validation, differential expressions of REGγ in corresponding cancers were statistically analyzed. Genes highly correlated with REGγ were defined based on Pearson's correlation coefficient. Functional links were estimated by Ingenuity Core analysis. Finally, validation was performed by RT-PCR analysis in established cancer cell lines and IHC in human colon cancer tissues

Results

Here, we demonstrate overexpression of REGγ in four different cancer types by micro-tissue array analysis. Using meta-analysis of publicly available microarray databases and biological studies, we verified elevated REGγ gene expression in the four types of cancers and identified genes significantly correlated with REGγ expression, including genes in p53, Myc pathways, and multiple other cancer-related pathways. The predicted correlations were largely consistent with quantitative RT-PCR analysis.

Conclusions

This study provides us novel insights in REGγ gene expression profiles and its link to multiple cancer-related pathways in cancers. Our results indicate potentially important pathogenic roles of REGγ in multiple cancer types and implicate REGγ as a putative cancer marker.

Encapsulated papillary thyroid carcinoma, follicular variant: a misnomer

Papillary thyroid carcinoma (PTC) has long been diagnosed based on its unique nuclear features (PTC-N); however, significant observer discrepancies have been reported in the diagnosis of encapsulated follicular patterned lesions (EnFPLs), because the threshold of PTC-N is subjective. An equivocal PTC-N may often occur in non-invasive EnFPLs and benign/malignant disagreements often create serious problems for patients' treatment. This review collects recent publications focusing on the so-called encapsulated follicular variant of papillary thyroid carcinoma (EnFVPTC) and tries to emphasize problems in the histopathological diagnosis of this spectrum of tumors, which covers encapsulated common-type PTC (EncPTC), EnFVPTC, well-differentiated tumor of uncertain malignant potential (WDT-UMP), follicular adenoma (FA) with equivocal PTC-N and minimally invasive follicular carcinoma (mFTC). We propose that EnFVPTC and other EnFPLs with equivocal PTC-N should be classified into a unified category of borderline malignancy, such as well-differentiated tumor of uncertain behavior (WDT-UB), based on their homogeneous excellent outcome. It is suggested that the unified nomenclature of these lesions may be helpful to reduce significant observer disagreements in diagnosis, because complete agreement in the diagnosis of an EncPTC, EnFVPTC or FA by all pathologists may be not possible for this problematic group of tumors. In conclusion, a malignant diagnosis of EnFVPTC should not be used to cover this spectrum of tumors until uncertainty about the nature of this lesion is settled, whether it is benign, precancerous or malignant.

Classification of thyroid follicular cell tumors: with special reference to borderline lesions

We propose a new classification of thyroid follicular cell tumors which is correlated with patient's prognosis. It is unique as to two new categories: borderline malignancy between benign and malignant, and moderately differentiated adenocarcinoma (MDA) as a differentiation classification to stratify tumor aggressiveness. As to diagnostic criteria, we recommend invasiveness (capsular and vascular invasion) to separate benign and malignant and it should not be based on presence or absence of papillary thyroid carcinoma (PTC) type nuclear features (PTC-N). Thus borderline malignancy in our new classification includes some of the formerly malignant tumors and they are 1) papillary microcarcinoma, 2) encapsulated conventional PTC (EncPTC), 3) encapsulated follicular variant PTC (EnFVPTC), 4) well differentiated tumor of uncertain malignant potential (WDT-UMP), 5) follicular tumors of uncertain malignant potential (FT-UMP), and 6) capsular invasion only follicular thyroid carcinoma (FTC). Review of the literature revealed that those thyroid tumors have consistently excellent outcome. Well differentiated follicular cell adenocarcinoma (WDA) in our classification includes common type PTC and low-risk follicular carcinoma (FTC). They are invasive (diffuse infiltrative) common type PTC and minimally invasive type FTC with less than 4 foci of angioinvasion. Moderately differentiated follicular cell adenocarcinoma (MDA) includes FTC with angioinvasion (more than 4), aggressive variants of PTC, such as tall cell, columnar cell, solid, loss of cellular polarity/cohesiveness (hobnail) variants and encapsulated carcinoma with high grade histology. Poorly differentiated carcinoma (PDC) includes PDC of WHO definition, insular carcinoma, tumors with minor anaplastic transformation and tumors with distant metastasis at presentation.

Can the microRNA signature distinguish between thyroid tumors of uncertain malignant potential and other well-differentiated tumors of the thyroid gland?

The term 'thyroid tumors of uncertain malignant potential' (TT-UMP) was coined by surgical pathologists to define well-differentiated tumors (WDT) showing inconclusive morphological evidence of malignancy or benignity. We have analyzed the expression of microRNA (miRNA) in a training set of 42 WDT of different histological subtypes: seven follicular tumors of UMP (FT-UMP), six WDT-UMP, seven follicular thyroid adenomas (FTA), 11 conventional papillary thyroid carcinomas (C-PTC), five follicular variants of PTC (FV-PTC), and six follicular thyroid carcinomas (FTC), which led to the identification of about 40 deregulated miRNAs. A subset of these altered miRNAs was independently validated by qRT-PCR, which included 18 supplementary TT-UMP (eight WDT-UMP and ten FT-UMP). Supervised clustering techniques were used to predict the first 42 samples. Based on the four possible outcomes (FTA, C-PTC, FV-PTC, and FTC), about 80% of FTA and C-PTC and 50% of FV-PTC and FTC samples were correctly assigned. Analysis of the independent set of 18 WDT-UMP by quantitative RT-PCR for the selection of the six most discriminating miRNAs was unable to separate FT-UMP from WDT-UMP, suggesting that the miRNA signature is insufficient in characterizing these two clinical entities. We conclude that considering FT-UMP and WDT-UMP as distinct and specific clinical entities may improve the diagnosis of WDT of the thyroid gland. In this context, a small set of miRNAs (i.e. miR-7, miR-146a, miR-146b, miR-200b, miR-221, and miR-222) appears to be useful, though not sufficient per se, in distinguishing TT-UMP from other WDT of the thyroid gland.

QiSampler: evaluation of scoring schemes for high-throughput datasets using a repetitive sampling strategy on gold standards

Background

High-throughput biological experiments can produce a large amount of data showing little overlap with current knowledge. This may be a problem when evaluating alternative scoring mechanisms for such data according to a gold standard dataset because standard statistical tests may not be appropriate.

Findings

To address this problem we have implemented the QiSampler tool that uses a repetitive sampling strategy to evaluate several scoring schemes or experimental parameters for any type of high-throughput data given a gold standard. We provide two example applications of the tool: selection of the best scoring scheme for a high-throughput protein-protein interaction dataset by comparison to a dataset derived from the literature, and evaluation of functional enrichment in a set of tumour-related differentially expressed genes from a thyroid microarray dataset.

Conclusions

QiSampler is implemented as an open source R script and a web server, which can be accessed at http://cbdm.mdc-berlin.de/tools/sampler/.

Well differentiated follicular thyroid neoplasia: impact of molecular and technological advances on detection, monitoring and treatment

Our understanding of the molecular mechanisms responsible for follicular thyroid cell oncogenesis has been advanced significantly in recent years. Specific genetic alterations and the molecular pathways they affect have been associated with particular histologic subtypes of well-differentiated thyroid cancer and are now being evaluated for their utility as clinical tools with diagnostic, prognostic and even therapeutic relevance. This paper focuses on the most common and clinically relevant genetic alterations shown to be consistently associated with well-differentiated thyroid carcinoma. We review the impact of recent molecular and technological advances on thyroid cancer standard of care and the practice of clinical medicine.

Encapsulated follicular thyroid tumor with equivocal nuclear changes, so-called well-differentiated tumor of uncertain malignant potential: a morphological, immunohistochemical, and molecular appraisal

There is a continuous debate regarding the classification of thyroid follicular lesions and the term "well-differentiated tumor of uncertain malignant potential (WDT-UMP)" was recently introduced to cover this problematic spectrum of tumors. The objective of this study was to reappraise WDT-UMP using morphological, immunochemical, and molecular analysis and to shed more light on encapsulated thyroid follicular-patterned tumors. A total of 30 cases of WDT-UMP with equivocal papillary thyroid carcinoma-type nuclear changes (PTC-N) or focal unequivocal PTC-N were examined. As a control, follicular adenoma (n = 29), follicular carcinoma (n = 8), hyalinizing trabecular adenoma (n = 5), and PTC (n = 48) were included. HBME-1, cytokeratin 19, and galectin-3 were positive in 12 (40.0%), 10 (33.3%) and 11 (36.7%) cases of WDT-UMP, respectively. According to the positivity of those markers, significant differences were obtained between WDT-UMP and PTC encapsulated common type (P = 0.028, 0.010, and 0.004, respectively), infiltrative follicular variant (P = 0.020, 0.026, and 0.008, respectively), and infiltrative common type (P = 0.004, 0.001, and 0.005, respectively), but not between WDT-UMP and follicular adenoma or follicular carcinoma. BRAF(V600E) mutation was absent but RET/PTC1 rearrangement was found in only two (6.7%) cases of WDT-UMP. None of the 20 patients with WDT-UMP developed recurrence, with an average follow-up of 80 months. These findings indicate that WDT-UMP has a favorable outcome and is distinct from PTC in morphological, immunohistochemical, and molecular characteristics. We propose that WDT-UMP should be classified as "well-differentiated tumor with uncertain behavior".

Copy number and gene expression alterations in radiation-induced papillary thyroid carcinoma from chernobyl pediatric patients

BACKGROUND

Following exposure to radiation during the Chernobyl fallout tragedy, papillary thyroid carcinoma (PTC) increased significantly in individuals who were children at the time of the accident. We have used two high-throughput, whole genome platforms to analyze radiation-induced PTCs from pediatric patients from the Chernobyl region.

METHODS

We performed comparative genomic hybridization using Affymetrix 50K Mapping arrays and gene expression profiling on 10 pediatric post-Chernobyl PTCs obtained from patients living in the region. We performed an overlay analysis of these two data sets.

RESULTS

Many regions of copy number alterations (CNAs) were detected including novel regions that had never been associated with PTCs. Increases in copy numbers were consistently found on chromosomes 1p, 5p, 9q, 12q, 13q, 16p, 21q, and 22q. Deletions were observed less frequently and were mapped to 1q, 6q, 9q, 10q, 13q, 14q, 21q, and 22q. Gene expression analysis revealed that most of the altered genes were also perturbed in sporadic adult PTC; however, 141 gene expression changes were found to be unique to the post-Chernobyl tumors. The genes with the highest increases in expression that were novel to the pediatric post-Chernobyl tumors were TESC, PDZRN4, TRAa/TRDa, GABBR2, and CA12. The genes showing the largest expression decreases included PAPSS2, PDLIM3, BEXI, ANK2, SORBS2, and PPARGCIA. An overlay analysis of the gene expression and CNA profiles was then performed. This analysis identified genes showing both CNAs and concurrent gene expression alterations. Many of these are commonly seen in sporadic PTC such as SERPINA, COL8A, and PDX, while others were unique to the radiation-induced profiles including CAMK2N1, AK1, DHRS3, and PDE9A.

CONCLUSIONS

This type of analysis allows an assessment of gene expression changes that are associated with a physical mechanism. These genes and chromosomal regions are potential markers for radiation-induced PTC.

Identification of borderline thyroid tumors by gene expression array analysis

BACKGROUND

A subset of follicular lesions of the thyroid is encapsulated similar to follicular adenomas but with partial nuclear features suggestive of papillary thyroid carcinoma (PTC), raising the possibility of biologically borderline tumors.

METHODS

Gene expression profiling and advanced significance analyses were performed on 50 histologically unequivocal benign and malignant tumors, and a list of 61 differentially expressed genes was generated. By using this 61-gene list, unsupervised hierarchical and K-means cluster analyses were performed on 40 additional tumors, including 15 histologically borderline tumors, 11 benign tumors, and 14 PTCs.

RESULTS

Analysis revealed 3 distinct tumor groups-benign, malignant, and intermediate. Tumors in the intermediate group (n = 15) were mostly histologic borderline tumors and had an expression profile overlapping with the benign and malignant groups. Twenty-seven genes were expressed differentially between the benign and intermediate groups, including the cyclic AMP response element-binding protein/p300-interactivator with glutamic acid/aspartic acid-rich carboxy-terminal domain 1 or CITED1 gene and the fibroblast growth factor receptor 2 or FGFR2 gene. Fourteen genes were expressed differentially between the intermediate group and malignant tumors, notably overexpression of the met proto-oncogene and of the high-mobility group adenine/thymine-hook 2 or HMGA2 gene in malignancies. Mutations of the v-raf murine sarcoma viral oncogene homolog B1 or BRAF gene were identified in 4 of 14 malignant tumors but not in benign or intermediate tumors. Patients who had either histologically or molecularly borderline tumors did not have metastasis or recurrences.

CONCLUSIONS

Gene expression profiling supported the finding that encapsulated thyroid follicular lesions with partial nuclear features of PTC are biologically borderline tumors that are distinct molecularly from benign and malignant tumors.

Molecular markers in thyroid cancer diagnostics

Although fine-needle aspiration biopsy (FNA) remains the mainstay of the preoperative workup of thyroid nodules, it does not provide a diagnosis in up to 20% of nodules. This group of indeterminate lesions, including lesions with cellular atypia, suspicious cytology, and demonstrating a follicular pattern, provides one of the greatest challenges to researchers in thyroid cancer today. Over the last 2 decades, considerable work has been done to find molecular markers to resolve this diagnostic dilemma. This article explores some of the markers including galectin-3, HBME-1, BRAF, RET/PTC, PAX8-PPARgamma, hTERT, telomerase, miRNA, and microarray and multigene assays. Although no one marker has proven to be a panacea, several combinations of markers have shown great promise as an adjunct to FNA.

Clinical features and genetic predisposition to hereditary nonmedullary thyroid cancer

BACKGROUND

Approximately 5% of the nonmedullary thyroid cancers are hereditary. Hereditary nonmedullary thyroid cancer may occur as a minor component of familial cancer syndromes (familial adenomatous polyposis, Gardner's syndrome, Cowden's disease, Carney's complex type 1, Werner's syndrome, and papillary renal neoplasia) or as a primary feature (familial nonmedullary thyroid cancer [FNMTC]). The goal of this article was to review our current knowledge on the hereditary nonmedullary thyroid cancer.

SUMMARY

Epidemiologic and clinical kindred studies have demonstrated that FNMTC is a unique clinical entity. Most studies suggest that FNMTC is associated with more aggressive disease than sporadic cases, with higher rates of multicentric tumors, lymph node metastasis, extrathyroidal invasion, and shorter disease-free survival. A hereditary predisposition to nonmedullary thyroid cancer is well established, but the susceptibility genes for isolated FNMTC have not been identified. However, additional susceptibility loci for FNMTC have been recently identified in classic isolated cases of FNMTC (1q21, 6q22, 8p23.1-p22, and 8q24).

CONCLUSIONS

More studies are needed to validate chromosomal susceptibility loci and identify the susceptibility genes for FNMTC. The discovery of the predisposing genes may allow for screening and early diagnosis, which could lead to improved outcomes for patients and their families.

PGC-1-related coactivator modulates mitochondrial-nuclear crosstalk through endogenous nitric oxide in a cellular model of oncocytic thyroid tumours

Background

The PGC-1 related coactivator (PRC), which shares structural and functional features with PGC-1α, is believed to regulate several metabolic pathways as well as mitochondrial biogenesis. Its involvement in the early programming of cell proliferation suggests the existence of finely regulated crosstalk between mitochondrial functions and the cell cycle status.

Methodology/Principal Findings

PRC-regulated pathways were explored in a cell-line model derived from mitochondrial-rich tumours with an essentially oxidative metabolism and specifically high PRC expression. The functional status of mitochondria was compared to the results of microarray analysis under conditions of temporal PRC inhibition. To specify the fine PRC regulation, the expression levels of the genes and proteins involved in the oxidative phosphorylation process were studied by real time quantitative PCR and western blotting. As in earlier studies on PGC-1α, we investigated the role of nitric oxide in PRC-regulated mitochondrial biogenesis and determined its action in the control of the phosphorylation status of the mitogen-activated protein kinase pathway.

Conclusion/Significance

We found that nitric oxide rapidly influences PRC expression at the transcriptional level. Focusing on mitochondrial energetic metabolism, we observed that PRC differentially controls respiratory chain complexes and coupling efficiency in a time-dependent manner to maintain mitochondrial homeostasis. Our results highlight the key role of PRC in the rapid modulation of metabolic functions in response to the status of the cell cycle.

Increasing the number of thyroid lesions classes in microarray analysis improves the relevance of diagnostic markers

Background

Genetic 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.

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.

Perspectives for improved and more accurate classification of thyroid epithelial tumors

CONTEXT

Histologic examination of thyroid nodules is the current standard to distinguish benign from malignant thyroid epithelial tumors and to classify histologic subtypes. This review analyzes the problems in histological differential diagnosis as well as contradictions between histology and molecular data and describes possibilities to combine histology with molecular data in an effort to more accurately classify thyroid epithelial tumors.

EVIDENCE ACQUISITION

Published literature, addressing the current recommendations for thyroid tumor classification, as well as literature on the application of histology and molecular studies on the etiology of thyroid tumors is analyzed.

EVIDENCE SYNTHESIS

The current histologic criteria to classify thyroid tumors, especially follicular-patterned tumors, are hampered by considerable interobserver variability. The detection of somatic mutations via genotyping and the definition of potentially informative gene expression signatures by microarray analyses, which can distinguish cancer subtypes as well as low- and high-risk cohorts, have recently demonstrated significant diagnostic potential. Moreover, in a routine diagnostic setting, micro-RNA profiling appears most promising due to their relative stability and the high accuracy of their expression profiles.

CONCLUSIONS

It is very likely that molecular definitions of thyroid tumors mentioned in the current World Health Organization classification will be further developed, leading to future progress in defining thyroid tumor types by an integrated histologic and molecular approach. These integrated classifications need to be evaluated for their specific impact on thyroid tumor diagnosis and prognosis.