Gene expression profiling identifies platelet-derived growth factor as a diagnostic molecular marker for papillary thyroid carcinoma

Papillary Thyroid Cancer: Genetic Alterations and Molecular Biomarker Investigations

Papillary thyroid cancer (PTC) is the most prevalent form of malignancy among all cancers of the thyroid. It is also one of the few cancers with a rapidly increasing incidence. PTC is usually contained within the thyroid gland and generally biologically indolent. Prognosis of the cancer is excellent, with less than 2% mortality at 5 years. However, more than 25% of patients with PTC developed a recurrence during a long term follow-up. The present article provides an updated condensed overview of PTC, which focuses mainly on the molecular alterations involved and recent biomarker investigations.

Identification of key genes and miRNAs markers of papillary thyroid cancer

OBJECTIVE

In this study, crucial genes and microRNAs (miRNAs) associated with the progression, staging, and prognosis of papillary thyroid cancer (PTC) were identified.

METHODS

Four PTC datasets, including our own mRNA-sequencing (mRNA-seq) dataset and three public datasets downloaded from Gene Expression Omnibus and The Cancer Genome Atlas, were used to analyze differentially expressed genes (DEGs) and miRNAs (DEMs) between PTC tumor tissues and paired normal tissues (control). Gene ontology (GO) terms and pathways associated with these DEGs were identified, and protein-protein interactions (PPIs) were analyzed. Additionally, an miRNA-mRNA regulatory network was constructed and the functions of DEMs were explored. Finally, miRNAs/mRNAs associated with tumor staging and prognosis were identified. The expression levels of several key genes and miRNAs were validated by qRT-PCR.

RESULTS

Numerous DEGs and DEMs were identified between tumor and control groups in four datasets. The DEGs were significantly enriched in cell adhesion and cancer-related GO terms and pathways. In the constructed PPI network, ITGA2, FN1, ICAM1, TIMP1 and CDH2 were hub proteins. In the miRNA-mRNA negative regulatory networks, miR-204-5p regulated the largest number of target genes, such as TNFRSF12A. miR-146b, miR-204, miR-7-2, and FN1 were associated with tumor stage in PTC, and TNFRSF12A and CLDN1 were related to prognosis.

CONCLUSIONS

Our results suggested the important roles of ITGA2, FN1, ICAM1, TIMP1 and CDH2 in the progression of PTC. miR-204-5p, miR-7-2, and miR-146b are potential biomarkers for PTC staging and FN1, CLDN1, and TNFRSF12A may serve as markers of prognosis in PTC.

Integrating omics data and protein interaction networks to prioritize driver genes in cancer

Although numerous approaches have been proposed to discern driver from passenger, identification of driver genes remains a critical challenge in the cancer genomics field. Driver genes with low mutated frequency tend to be filtered in cancer research. In addition, the accumulation of different omics data necessitates the development of algorithmic frameworks for nominating putative driver genes. In this study, we presented a novel framework to identify driver genes through integrating multi-omics data such as somatic mutation, gene expression, and copy number alterations. We developed a computational approach to detect potential driver genes by virtue of their effect on their neighbors in network. Application to three datasets (head and neck squamous cell carcinoma (HNSC), thyroid carcinoma (THCA) and kidney renal clear cell carcinoma (KIRC)) from The Cancer Genome Atlas (TCGA), by comparing the Precision, Recall and F1 score, our method outperformed DriverNet and MUFFINN in all three datasets. In addition, our method was less affected by protein length compared with DriverNet. Lastly, our method not only identified the known cancer genes but also detected the potential rare drivers (PTPN6 in THCA, SRC, GRB2 and PTPN6 in KIRC, MAPK1 and SMAD2 in HNSC).

RNA sequencing identifies crucial genes in papillary thyroid carcinoma (PTC) progression

PURPOSE

The study aims to uncover molecular mechanisms of PTC (papillary thyroid carcinoma) progression and provide therapeutic biomarkers.

METHODS

The paired tumor and control tissues were obtained from 5 PTC patients. RNA was extracted and cDNA libraries were constructed. RNA-sequencing (RNA-seq) was performed on the Illumina HiSeq2000 platform using paired-end method. After preprocessing of the RNA-seq data, gene expression value was calculated by RPKM. Then the differentially expressed genes (DEGs) were identified with edgeR. Functional enrichment and protein-protein interaction (PPI) network analyses were conducted for the DEGs. Module analysis of the PPI network was also performed. Transcription factors (TFs) of DEGs were predicted.

RESULTS

A cohort of 496 up-regulated DEGs mainly correlating with the ECM degradation pathways, and 440 down-regulated DEGs predominantly enriching in transmembrane transport process were identified. Hub nodes in the PPI network were RRM2 and a set of collagens (COL1A1, COL3A1 and COL5A1), which were also remarkable in module 3 and module 5, respectively. Genes in module 3 were associated with cell cycle pathways, while in module 5 were related to ECM degradation pathways. PLAU, PSG1 and EGR2 were the crucial TFs with higher transcriptional activity in PTC than in control.

CONCLUSION

Several genes including COL1A1, COL3A1, RRM2, PLAU, and EGR2 might be used as biomarkers of PTC therapy. Among them, COL1A1 and COL3A1 might exert their functions via involving in ECM degradation pathway, while RRM2 through cell cycle pathway. PLAU might be an active TF, whereas EGR2 might be a tumor suppressor.

Notch and TGF-β/Smad3 pathways are involved in the interaction between cancer cells and cancer-associated fibroblasts in papillary thyroid carcinoma

Accumulating evidence suggests that cancer-associated stromal fibroblasts (CAFs) contribute to tumor growth by actively communicating with cancer cells. Our aim was to identify the signaling pathways that are involved in tumor-stromal cell interactions in human papillary thyroid carcinoma (PTC). Immunohistochemical analyses were performed with 127 archived formalin-fixed and paraffin-embedded thyroid tissue samples that included 70 cases of PTC, 35 cases of nodular goiter (NG), and 22 cases of normal thyroid tissues. The results showed that the expression levels of Notch1, transforming growth factor β (TGF-β1), and p-Smad3 in PTC cells and α-smooth muscle actin (α-SMA) in the stroma of PTC were all significantly higher than in NG and normal thyroid tissues. Further analysis showed that in PTC, higher expression levels of Notch1 and TGF-β1 were closely related with lymph node metastasis (P < 0.05), whereas for α-SMA and p-Smad3, the percent expression increased significantly with advanced tumor stages (P < 0.05). Correlation analysis revealed that TGF-β1 expression increased with increased Notch1 and p-Smad3 levels in PTC cells (P < 0.05). Moreover, a significant correlation was found between higher TGF-β1 expression in PTC cells and increased α-SMA levels in the fibroblasts surrounding the cancer cells (P < 0.05). We identified TGF-β1 as an important factor from PTC cells that act in a paracrine manner to influence the activation of stromal fibroblasts. These data suggest that the activation of Notch and TGF-β/Smad3 pathways in cancer cells influence tumor growth. Moreover, cancer cell-derived-TGF-β ligands also affect stromal cells in a paracrine fashion and enhance tumor growth.

Platelet-derived growth factor receptor-α promotes lymphatic metastases in papillary thyroid cancer

Lymph node metastases are common in papillary thyroid cancer (PTC) and can be resistant to surgical extirpation or radioiodine ablation. We examined the role of platelet-derived growth factor receptor (PDGFR) in mediating lymph node metastases in PTC. Clinical specimens of PTC (n = 137) were surveyed in a tissue array and by western blots to examine the relationship between expression of the α and β subunits of PDGFR and lymph node metastases. PDGFR-α was found at high levels in primary tumours with known lymphatic metastases but not in those tumours lacking nodal involvement (p < 0.0001). However, PDGFR-β expression was not linked to metastatic disease (p = 0.78) as it was found in virtually all PTC specimens. A matching analysis in fresh PTC specimens (n = 13) confirmed that PDGFR-α expression was strongly linked to metastatic spread (p = 0.0047). PDGFR-α and -β were not found in normal thyroid tissue (p < 0.0001). PTC cell lines selectively expressing PDGFR-α or -β were assessed for invasive potential and activation of downstream signal transduction pathways. PTC cell lines expressing PDGFR-α responded to PDGF-BB stimulation with increased invasive potential and this process can be blocked by the tyrosine kinase receptor inhibitor sunitinib (p < 0.009). Cell lines with only PDGFR-β, or no PDGFR, did not show significant changes in invasive potential. Activation of PDGFR-α led to downstream up-regulation of both the MAPK/ERK and PI3K/Akt pathways and disruption of either pathway is sufficient to block PDGFR-mediated increases in invasive potential. Thus, PDGFR-α is associated with lymph node metastases in papillary thyroid carcinoma and PDGFR-α promotes increased invasive potential in PTC cell lines. PDGFR-α is a strong candidate for a diagnostic biomarker to identify patients at risk of nodal metastases. Our results also strengthen the rationale for selection of tyrosine kinase receptor inhibitors that target PDGFR in the treatment of progressive, metastatic PTC.

Gene expression profile of human thyroid cancer in relation to its mutational status

This review describes the gene expression profile changes associated with the presence of different mutations that contribute to thyroid cell carcinogenesis. The results are discussed in the context of thyroid cancer biology and of the implications for disease prognosis, while the diagnostic aspect has been omitted. For papillary thyroid cancer (PTC), the most characteristic gene expression profile is associated with the presence of BRAF mutation. BRAF-associated PTC differ profoundly from RET/PTC or RAS-associated cancers. Simultaneously, they retain many characteristic gene expression features common for all PTCs, induced by the alternative mutations activating MAPK pathway. Although the difference between papillary and follicular thyroid cancer (FTC) is significant at the gene expression profile level, surprisingly, the RAS-related signature of FTC is not well specified. PAX8/peroxisome proliferator-activated receptor γ (PPARγ) rearrangements, which occur in FTC as an alternative to the RAS mutation, are associated with specific changes in gene expression. Furthermore, the difference between well-differentiated thyroid cancers and poorly differentiated and anaplastic thyroid cancers is mainly a reflection of tumor degree of differentiation and may not be attributed to the presence of characteristic mutations.

Significantly high expression of platelet-derived growth factor (PDGF) in benign nodules of the thyroid: relevance in the development of goitre recurrence?

PURPOSE

Platelet-derived growth factor (PDGF) is a critical regulator of cell proliferation and influences the development of tumors. The role of PDGF in benign thyroid diseases is presently not well-determined. The purpose is to evaluate PDGF isoforms and receptors in primary culture of thyrocytes isolated from human thyroid tissue.

METHODS

Forty patients with uninodular (n = 11), multinodular (n = 15) and recurrent goitre (n = 14) were investigated. Nodular and corresponding paranodular thyroid tissues were characterized. RNA and protein were extracted from primary thyrocyte monoculture. RT-PCR, western blot and ELISA were performed to evaluate PDGF isoforms AA, BB, CC, DD and PDGF receptors α and β.

RESULTS

Significantly higher mRNA expression of PDGF-AA, -BB, -CC and PDGFR molecules α and β was measured by RT-PCR in thyrocytes from uninodular and recurrent nodular tissue compared with corresponding paranodular tissue. Elevated PDGF protein and PDGFR-α and -β were confirmed by western blot. Likewise, higher secretion of PDGF-AA and -BB was detected in the supernatant of thyrocyte culture from all nodular tissue compared with paranodular tissue. Interestingly, comparison of nodular and corresponding paranodular tissues in multinodular goitre did not show significant difference of expression levels of PDGF isoforms or receptors.

CONCLUSION

These findings suggest that the overexpression of PDGF isoforms and receptors may play a crucial role in the development of thyroid nodules and recurrent goitre.

Proteome profiling reveals gender differences in the composition of human serum

Proteome analysis using human serum is a technological advancement that will enable the discovery of novel biomarkers and biomarker patterns of various human diseases. Although proteome analysis using serum has potential in disease prevention, early diagnosis and treatment of diseases, and evaluation of pharmacotherapies, this technology is still in its infancy. Thus, we sought to develop an advanced method of conducting proteome analysis on human serum. In this study, we report the development of the semi-comprehensive protein analytical technique, which involves the systematic use of iTRAQ labeling, HPLC, nano-LC and MS. We compared the composition of the serum proteome in males and females using this technique and detected gender-based differences in serum protein composition. This technology will enable the generation of databases that may ultimately lead to the discovery of specific biomarkers or biomarker patterns of various diseases.

Inverse correlation between PDGFC expression and lymphocyte infiltration in human papillary thyroid carcinomas

Background

Members of the PDGF family have been suggested as potential biomarkers for papillary thyroid carcinomas (PTC). However, it is known that both expression and stimulatory effect of PDGF ligands can be affected by inflammatory cytokines. We have performed a microarray study in a collection of PTCs, of which about half the biopsies contained tumour-infiltrating lymphocytes or thyroiditis. To investigate the expression level of PDGF ligands and receptors in PTC we measured the relative mRNA expression of all members of the PDGF family by qRT-PCR in 10 classical PTC, eight clinically aggressive PTC, and five non-neoplastic thyroid specimens, and integrated qRT-PCR data with microarray data to enable us to link PDGF-associated gene expression profiles into networks based on recognized interactions. Finally, we investigated potential influence on PDGF mRNA levels by the presence of tumour-infiltrating lymphocytes.

Methods

qRT-PCR was performed on PDGFA, PDGFB, PDGFC, PDGFD, PDGFRA PDGFRB and a selection of lymphocyte specific mRNA transcripts. Semiquantitative assessment of tumour-infiltrating lymphocytes was performed on the adjacent part of the biopsy used for RNA extraction for all biopsies, while direct quantitation by qRT-PCR of lymphocyte-specific mRNA transcripts were performed on RNA also subjected to expression analysis. Relative expression values of PDGF family members were combined with a cDNA microarray dataset and analyzed based on clinical findings and PDGF expression patterns. Ingenuity Pathway Analysis (IPA) was used to elucidate potential molecular interactions and networks.

Results

PDGF family members were differentially regulated at the mRNA level in PTC as compared to normal thyroid specimens. Expression of PDGFA (p = 0.003), PDGFB (p = 0.01) and PDGFC (p = 0.006) were significantly up-regulated in PTCs compared to non-neoplastic thyroid tissue. In addition, expression of PDGFC was significantly up-regulated in classical PTCs as compared to clinically aggressive PTCs (p = 0.006), and PDGFRB were significantly up-regulated in clinically aggressive PTCs (p = 0.01) as compared to non-neoplastic tissue. Semiquantitative assessment of lymphocytes correlated well with quantitation of lymphocyte-specific gene expression. Further more, by combining TaqMan and microarray data we found a strong inverse correlation between PDGFC expression and the expression of lymphocyte specific mRNAs.

Conclusion

At the mRNA level, several members of the PDGF family are differentially expressed in PTCs as compared to normal thyroid tissue. Of these, only the PDGFC mRNA expression level initially seemed to distinguish classical PTCs from the more aggressive PTCs. However, further investigation showed that PDGFC expression level correlated inversely to the expression of several lymphocyte specific genes, and to the presence of lymphocytes in the biopsies. Thus, we find that PDGFC mRNA expression were down-regulated in biopsies containing infiltrated lymphocytes or thyroiditis. No other PDGF family member could be linked to lymphocyte specific gene expression in our collection of PTCs biopsies.

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.

Potential utility and limitations of thyroid cancer cell lines as models for studying thyroid cancer

BACKGROUND

Tumor-derived cell lines are widely used to study the mechanisms involved in thyroid carcinogenesis but recent studies have reported redundancy among thyroid cancer cell lines and identification of some "thyroid cell lines" that are likely not of thyroid origin.

SUMMARY

In this review, we have summarized the uses, the limitations, and the existing problems associated with the available follicular cell-derived thyroid cancer cell lines. There are some limitations to the use of cell lines as a model to "mimic" in vivo tumors. Based on the gene expression profiles of thyroid cell lines originating from tumors of different types it has become apparent that some of the cell lines are closely related to each other and to those of undifferentiated carcinomas. Further, many cell lines have lost the expression of thyroid-specific genes and have altered karyotypes, while they exhibit activation of several oncogenes (BRAF, v-raf murine sarcoma viral oncogene homolog B1; RAS, rat sarcoma; and RET/PTC, rearranged in transformation/papillary thyroid carcinoma) and inactivation of tumor suppressor gene (TP53) which is known to be important for thyroid tumorigenesis.

CONCLUSIONS

A careful selection of thyroid cancer cell lines that reflect the major characteristics of a particular type of thyroid cancer being investigated could be used as a good model system to analyze the signaling pathways that may be important in thyroid carcinogenesis. Further, the review of literature also suggests that some of the limitations can be overcome by using multiple cell lines derived from the same type of tumor.

Genetic copy number alterations and IL-13 expression differences in papillary thyroid cancers and benign nodules

Thyroid nodules were the extremely common endocrine tumors, in which papillary thyroid carcinomas (PTCs) were the most prevalent endocrine malignancy, representing 80-90% of all thyroid malignancies. It was still a dilemma to discriminate PTCs and benign thyroid nodules. With a new molecular genetics technology of Multiplex ligation-dependent probe amplification (MLPA), we investigated 13 PTC and 14 benign nodule tissue samples. The results showed that PTCs had more genetic copy number alteration than benign nodules (P < 0.001). Receiver operating characteristic (ROC) curve analysis suggested that genomic aberrations would provide a moderate accuracy method to discriminate PTCs and benign nodules. The gain of interleukin 13 (IL-13) gene obviously identified the great difference between PTCs and benign nodules. Immunohistochemistry also confirmed significantly higher IL-13 expression in the PTCs (P < 0.001). The current study showed that MLPA should be an effective method to diagnose PTCs and benign thyroid nodules, and also provided a clue to another relationship between IL-13 and PTCs.

Transcriptome analysis of endocrine tumors: clinical perspectives

There is considerable interest in the application of DNA microarrays to the pathologic evaluation of endocrine neoplasms. Improvements in tumor classification and prognostication, prediction of response to therapy, and comprehensive assessment of tumoral hormone production represent the major anticipated benefits. Here, some of the microarray studies that support the clinical use of transcriptome profiling for endocrine tumors are reviewed. In addition, some of the barriers to clinical implementation are discussed.

Genome-wide studies in thyroid neoplasia

There is much interest in the application of genome biology to the field of thyroid neoplasia, despite the relatively low mortality rate associated with thyroid cancer in general. The principal reason for this interest is that the field of thyroid neoplasia stands to benefit from the application of genomic information to address a variety of pathologic and clinical issues. In addition to practical patient care issues, there is an excellent opportunity of expand the basic understanding of thyroid carcinogenesis. In this article, the most relevant genomic work on thyroid tumors performed to date is reviewed along with some general comments about the potential impact of genomic biology on thyroid pathology and the management of patients with thyroid nodules and cancer.

Evaluation of gene expression profiles in thyroid nodule biopsy material to diagnose thyroid cancer

CONTEXT

Detection of thyroid cancer among benign nodules on fine-needle aspiration biopsies (FNAB), which presently relies on cytological examination, is expected to be improved by new diagnostic tests set up from genomic data.

OBJECTIVE

The aim of the study was to use a set of genes discriminating benign from malignant tumors, on the basis of their expression levels, to build tumor classifiers and evaluate their capacity to predict malignancy on FNAB.

DESIGN

We analyzed the level of expression of 200 potentially informative genes in 56 thyroid tissue samples (benign or malignant tumors and paired normal tissue) using nylon macroarrays. Gene expression data were subjected to a weighted voting algorithm to generate tumor classifiers. The performances of the classifiers were evaluated on a series of 26 sham FNAB, i.e. FNAB carried out on thyroid nodules after surgical resection.

RESULTS

A series of 19 genes with a similar expression in follicular adenomas and normal tissue and discriminating follicular adenomas+normal tissue from the following: 1) follicular thyroid carcinomas (FTCs), 2) papillary thyroid carcinomas (PTCs), or 3) both FTCs and PTCs. These were used to generate four classifiers, the FTCs, PTCs, common (FTC+PTCs), and global classifiers. In 23 of the 26 sham FNAB, the four classifiers yielded a diagnosis in agreement with the diagnosis of the pathologist used as reference; in the three other cases, the correct diagnosis was given by three of four classifiers.

CONCLUSIONS

We developed a procedure of molecular diagnosis of benign vs. malignant tumors applicable to the material collected by FNAB. The molecular test complied with a preclinical validation stage; it must be now evaluated on ultrasound-guided FNAB in a large-scale prospective study.

A radiation-induced gene signature distinguishes post-Chernobyl from sporadic papillary thyroid cancers

We investigated selected gene targets to differentiate radiation-induced papillary thyroid cancers (PTCs) from other etiologies. Total RNA was isolated from 11 post-Chernobyl PTCs and 41 sporadic PTCs characterized by a more aggressive tumor type and lacking a radiation exposure history. RNA from 10 tumor samples from both groups was pooled and hybridized separately on a whole genome microarray for screening. Then 92 selected gene targets were examined quantitatively on each tumor sample using an RTQ-PCR-based low-density array (LDA). Screening for more than fivefold differences in gene expression between the groups by microarray detected 646 up-regulated and 677 down-regulated genes. Categorization of these genes revealed a significant (P < 0.0006) over-representation of the number of up-regulated genes coding for oxidoreductases, G-proteins and growth factors, while the number of genes coding for immunoglobulin appeared to be significantly down-regulated. With the LDA, seven genes (SFRP1, MMP1, ESM1, KRTAP2-1, COL13A1, BAALC and PAGE1) made a complete differentiation between the groups possible. Gene expression patterns known to be associated with a more aggressive tumor type in older patients appeared to be more pronounced in post-Chernobyl PTC, thus underlining the known aggressiveness of radiation-induced PTC. Seven genes were found that completely distinguished post-Chernobyl (PTC) from sporadic PTC.

Perspectives and limitations of microarray-based gene expression profiling of thyroid tumors

Microarray technology has become a powerful tool to analyze the gene expression of tens of thousands of genes simultaneously. Microarray-based gene expression profiles are available for malignant thyroid tumors (i.e., follicular thyroid carcinoma, and papillary thyroid carcinoma), and for benign thyroid tumors (such as autonomously functioning thyroid nodules and cold thyroid nodules). In general, the two main foci of microarray investigations are improved understanding of the pathophysiology/molecular etiology of thyroid neoplasia and the detection of genetic markers that could improve the differential diagnosis of thyroid tumors. Their results revealed new features, not known from one-gene studies. Simultaneously, the increasing number of microarray analyses of different thyroid pathologies raises the demand to efficiently compare the data. However, the use of different microarray platforms complicates cross-analysis. In addition, there are other important differences between these studies: 1) some studies use intraindividual comparisons, whereas other studies perform interindividual comparisons; 2) the reference tissue is defined as strictly nonnodular healthy tissue or also contains benign lesions such as goiter, follicular adenoma, and hyperplastic nodules in some studies; and 3) the widely used Affymetrix GeneChip platform comprises several GeneChip generations that are only partially compatible. Moreover, the different studies are characterized by strong differences in data analysis methods, which vary from simple empiric filters to sophisticated statistic algorithms. Therefore, this review summarizes and compares the different published reports in the context of their study design. It also illustrates perspectives and solutions for data set integration and meta-analysis, as well as the possibilities to combine array analysis with other genetic approaches.

Expression microarray analysis of papillary thyroid carcinoma and benign thyroid tissue: emphasis on the follicular variant and potential markers of malignancy

The most common sub-variant of papillary thyroid carcinoma (PTC) is the so-called follicular variant (FVPTC), which is a particularly problematic lesion and can be challenging from a diagnostic viewpoint even in resected lesions. Although fine needle aspiration cytology is very useful in the diagnosis of PTC, its accuracy and utility would be greatly facilitated by the development of specific markers for PTC and its common variants. We used the recently developed Applied Biosystems 1700 microarray system to interrogate a series of 11 benign thyroid lesions and conditions and 14 samples of PTC (six with classic morphology and eight with follicular variant morphology). TaqMan(R) reverse transcriptase-polymerase chain reaction was used to validate the expression portfolios of 50 selected transcripts. Our data corroborates potential biomarkers previously identified in the literature, such as LGALS3, S100A11, LYN, BAX, and cluster of differentiation 44 (CD44). However, we have also identified numerous transcripts never previously implicated in thyroid carcinogenesis, and many of which are not represented on other microarray platforms. Diminished expression of metallothioneins featured strongly among these and suggests a possible role for this family as tumour suppressors in PTC. Fifteen transcripts were significantly associated with FVPTC morphology. Surprisingly, these genes were associated with an extremely narrow repertoire of functions, including the major histocompatibility complex and cathepsin families.

Low-level genomic instability is a feature of papillary thyroid carcinoma: an array comparative genomic hybridization study of laser capture microdissected papillary thyroid carcinoma tumors and clonal cell lines

CONTEXT

Previous chromosomal comparative genomic hybridization (CGH) studies of papillary thyroid carcinoma (PTC) have demonstrated a low prevalence of aberrations, with the majority of tumors showing no evidence of chromosomal instability. The technique of CGH can be optimized, however, using array CGH and laser capture microdissection to ensure pure cell populations for analysis.

OBJECTIVE

To assess PTC using array CGH applied to laser capture microdissected tumor cells and pure cell cultures.

DESIGN

Well-characterized PTC (known ret/PTC and BRAF mutation status), including samples from 5 tumors with classic morphology, 3 follicular variant tumors, and 3 clonal PTC cell lines, were analyzed.

RESULTS

Copy gain and loss occurred in all of the tumor cases and cell lines examined. The most common recurrent aberrations involved gains on chromosomes 1, 5, 7, 11, 15, 17, and 22, with recurrent deletions occurring on chromosomes 4, 18, and 19. Analysis of the data from the 8 tumor samples showed that amplifications of TP73 (1p36.33), SNRPN (15q12), and PDGFB (22q13.1) occurred exclusively in tumors with a wild type BRAF.

CONCLUSIONS

This study shows a higher prevalence of aberrations detected using array CGH allied to laser capture microdissection than previously described in the literature, and it appears that the combination of laser capture microdissection and arrayed clones optimizes studies utilizing CGH. Copy gain of PDGFB occurs in a subset of tumors showing no evidence of mutated BRAF or rearranged ret, suggesting that copy gain of PDGFB may underlie the increased expression of platelet-derived growth factor described recently in the literature.

Contemporary diagnostic approach to the thyroid nodule

Thyroid nodules are common, with an estimated incidence of 5%-10% in the United States. The current gold standard for diagnosis is fine needle aspiration biopsy (FNAB). The incidence of indeterminate diagnoses varies from 10% to 25%. Surgical resection is usually indicated to exclude the diagnosis of cancer in these patients. However, only a minority (about 20%) of indeterminate thyroid nodules actually harbor a malignancy, resulting in surgery for diagnostic purposes alone in many patients. The increased detection of benign nodules and microcarcinomas reinforces the need for improved non-operative methods to differentiate benign from malignant disease and discriminate low-risk from high-risk cancers. In this article we present a current, rational diagnostic approach to the patient with a thyroid nodule, evaluate new advances including thyroid genomic and predictor models, and propose the development of prospective trials to incorporate these new additions into clinical decision making. Given how many questions still exist for patients with thyroid nodules, partnership and collaboration, or the "bench to bedside" concept should find its way into most every thyroid surgeon and endocrinologist's lexicon.

Effect of ret/PTC 1 rearrangement on transcription and post-transcriptional regulation in a papillary thyroid carcinoma model

Background

microRNAs (miRNAs) are a group of non-coding single stranded RNAs measuring approximately 22 nt in length that have been found to control cell growth, differentiation and apoptosis. miRNAs negatively regulate their target genes and recently have been implicated in tumourigenesis. Furthermore, miRNA expression profiling correlates with various cancers, with these genes thought to act as both tumour suppressors and oncogenes. ret/PTC 1 is an oncogene with constitutive kinase activity implicated in the development of papillary thyroid carcinoma (PTC). This rearrangement leads to aberrant MAPK activation that is implicated in PTC tumourigenesis.

Aim

The aim of this study was to identify the effect that ret/PTC 1 has on transcription and post-transcriptional regulation in PTC by using DNA microarray and microRNA analysis.

Results

DNA microarray analysis revealed a group of genes differentially expressed between normal thyroid cell lines and those harbouring a ret/PTC 1 rearrangement.

Furthermore, a unique miRNA expression signature differentiated between PTC cell lines with ret/PTC 1 and a normal thyroid cell line. 21 miRNAs showed significant overexpression and 14 miRNAs showed underexpression in these cell lines when compared to normal thyroid. Several of these up/down regulated miRNAs may be involved in PTC pathogenesis.

Meta-analysis and meta-review of thyroid cancer gene expression profiling studies identifies important diagnostic biomarkers

PURPOSE

An estimated 4% to 7% of the population will develop a clinically significant thyroid nodule during their lifetime. In many cases, preoperative diagnoses by needle biopsy are inconclusive. Thus, there is a clear need for improved diagnostic tests to distinguish malignant from benign thyroid tumors. The recent development of high-throughput molecular analytic techniques should allow the rapid evaluation of new diagnostic markers. However, researchers are faced with an overwhelming number of potential markers from numerous thyroid cancer expression profiling studies.

MATERIALS AND METHODS

To address this challenge, we have carried out a comprehensive meta-review of thyroid cancer biomarkers from 21 published studies. A gene ranking system that considers the number of comparisons in agreement, total number of samples, average fold-change and direction of change was devised.

RESULTS

We have observed that genes are consistently reported by multiple studies at a highly significant rate (P < .05). Comparison with a meta-analysis of studies reprocessed from raw data showed strong concordance with our method.

CONCLUSION

Our approach represents a useful method for identifying consistent gene expression markers when raw data are unavailable. A review of the top 12 candidates revealed well known thyroid cancer markers such as MET, TFF3, SERPINA1, TIMP1, FN1, and TPO as well as relatively novel or uncharacterized genes such as TGFA, QPCT, CRABP1, FCGBP, EPS8 and PROS1. These candidates should help to develop a panel of markers with sufficient sensitivity and specificity for the diagnosis of thyroid tumors in a clinical setting.

Molecular determination of benign and malignant thyroid tumors

Recent molecular studies have revolutionized our understanding of the pathogenesis of thyroid tumors and particular advances have been made in three areas. First, toxic thyroid nodules, which originate from constitutive activation of thyroid-stimulating hormone receptor/Gs α signaling and represent the dominant cause of thyrotoxicosis in regions with iodine deficiency. Second, papillary thyroid cancer, the most frequent thyroid malignancy, which is characterized by a common fingerprint of constitutive mitogen-activated protein kinase activation. Importantly, this is caused by distinct genetic alterations in radiation-induced (RET/PTC, NTRK and AKAP9/BRAF rearrangements) and sporadic tumors (BRAF and RAS point mutation) and, recently, there exciting in vitro have emerged explaining the structural basis for this. These findings suggest a scenario in which the fate of a thyroid tumor is determined by the specific genetic defect at the beginning. Third, application of microarray analysis in nodular pathologies in which the oncogenic pathway is less clear, notably follicular neoplasia, has led to the identification of a number of promising genetic markers (TFF-3, Gal-3, PLAB, CCND2 and PCKD2) for the diagnostic distinction of follicular adenoma and carcinoma. In addition to the diagnostic perspective, the identification of molecular fingerprints of thyroid tumors opens novel avenues for an improved therapeutic approach; for example, selective antagonism of cell signaling in treatment-refractory thyroid cancer.

Quantitative and qualitative differences in protein expression between papillary thyroid carcinoma and normal thyroid tissue

In order to better understand basic mechanisms of tumor development and identify potential new biomarkers, we have performed difference gel electrophoresis (DIGE) and peptide mass fingerprinting on pooled protein extracts from patients with papillary thyroid carcinoma (PTC) compared with matched normal thyroid tissue. Image analysis of DIGE gels comparing PTC and matched normal thyroid tissue protein indicated that 25% of the protein spots were differentially expressed at a 2.5-fold cutoff and 35% at two-fold. Comparison between two different pools of protein from normal thyroid tissues revealed differential protein expression of only 4% at 2.5-fold and 6% at two-fold cutoff. One hundred ninety-two protein spots were identified by MALDI-TOFMS, representing 90 distinct proteins. Excluding albumin, globins and thyroglobulin, imaging software determined 31 proteins to be differentially expressed at the two-fold (or greater) level. Individual gel comparisons (PTC vs. matched normal) from five patients established that 15/31 (48%) of these proteins exhibited statistically significant differential expression. Previously identified molecular markers in this group of proteins include cathepsin B, cytokeratin 19, and galectin-3. Novel differentially expressed proteins include S100A6, moesin, HSP70 (BiP), peroxiredoxin 2, protein phosphatase 2, selenium binding protein 1, vitamin D binding protein, and proteins involved in mitochondrial function. The use of two-dimensional gel electrophoresis (2DGE) revealed a significantly altered protein mass and/or pI in 10%-15% of proteins, suggesting alternatively spliced forms and other posttranslational modification of proteins revealed by this approach. We confirmed S100A6 as a potentially useful biomarker using immunohistochemical analysis (85% sensitivity and 69% specificity for distinguishing benign from malignant thyroid neoplasms). In summary, proteomic analysis of PTC using DIGE and mass spectrometry has confirmed several known biomarkers, uncovered novel potential biomarkers, and provided insights into global pathophysiologic changes in PTC. Many of the differences observed would not have been detected by genomic or other proteomic approaches.

Repression of the antiapoptotic molecule galectin-3 by homeodomain-interacting protein kinase 2-activated p53 is required for p53-induced apoptosis

Galectin 3 (Gal-3), a member of the beta-galactoside binding lectin family, exhibits antiapoptotic functions, and its aberrant expression is involved in various aspects of tumor progression. Here we show that p53-induced apoptosis is associated with transcriptional repression of Gal-3. Previously, it has been reported that phosphorylation of p53 at Ser46 is important for transcription of proapoptotic genes and induction of apoptosis and that homeodomain-interacting protein kinase 2 (HIPK2) is specifically involved in these functions. We show that HIPK2 cooperates with p53 in Gal-3 repression and that this cooperation requires HIPK2 kinase activity. Gene-specific RNA interference demonstrates that HIPK2 is essential for repression of Gal-3 upon induction of p53-dependent apoptosis. Furthermore, expression of a nonrepressible Gal-3 prevents HIPK2- and p53-induced apoptosis. These results reveal a new apoptotic pathway induced by HIPK2-activated p53 and requiring repression of the antiapoptotic factor Gal-3.

Meta- and reanalysis of gene expression profiles of hot and cold thyroid nodules and papillary thyroid carcinoma for gene groups

CONTEXT

There are an increasing number of studies analyzing gene expression profiles in various benign and malignant thyroid tumors. This creates the opportunity to validate results obtained from one microarray study with those from other data sets. This process requires rigorous methods for accurate comparison.

OBJECTIVE

The ability to compare data sets derived from different Affymetrix GeneChip generations and the influence of intra- and interindividual comparisons of gene expression data were evaluated to build multigene classifiers of benign thyroid nodules to verify a previously proposed papillary thyroid carcinoma (PTC) classifier and to look for molecular pathways essential for PTC oncogenesis.

METHODS

Gene expression profile data sets from autonomously functioning and cold thyroid nodules and from PTC were analyzed by support vector machines. GenMAPP analysis was used for PTC data analysis to examine the expression patterns of biologically relevant gene sets.

RESULTS

Only intraindividual reference samples allowed the identification of subtle changes in the expression patterns of relevant signaling cascades, such as the MAPK pathway in PTC. Using an artificial intelligence approach, the autonomously functioning and cold thyroid nodule multigene classifiers were derived and evaluated by cross-comparisons.

CONCLUSION

We recommend defining classifiers within one generation of gene chips and subsequently checking them across different array generations. Using this approach, we have demonstrated the specificity of a previously reported PTC classifier on an independent collection of benign tumors. Moreover, we propose multigene classifiers for different types of benign thyroid nodules.

Pathogenetic mechanisms in thyroid follicular-cell neoplasia

Thyroid cancer is one of the few malignancies that are increasing in incidence. Recent advances have improved our understanding of its pathogenesis; these include the identification of genetic alterations that activate a common effector pathway involving the RET-Ras-BRAF signalling cascade, and other unique chromosomal rearrangements. Some of these have been associated with radiation exposure as a pathogenetic mechanism. Defects in transcriptional and post-transcriptional regulation of adhesion molecules and cell-cycle control elements seem to affect tumour progression. This information can provide powerful ancillary diagnostic tools and can also be used to identify new therapeutic targets.

Identification of Differentially Expressed Genes in Papillary Thyroid Carcinomas With and Without Rearrangements of the Tyrosine Kinase Receptors RET and/or NTRK1

BACKGROUND

The transforming capacities of RET and/or NTRK1 chimeric oncogenes as well as the molecular background of non-rearranged papillary thyroid carcinomas (PTCs) remain to be elucidated. To assess altered gene expression, we examined PTCs with and without tyrosine kinase receptor rearrangements by mRNA differential display (DD).

MATERIALS AND METHODS

Six of 13 PTCs examined harbored RET chimeras (3x RET/PTC1, 1x RET/PTC3) and/or NTRK1 chimeras (2x trk, 1x TRK-T3, 2 unknown TRK hybrids). The method of DD analysis was refined by a novel fragment-recovery technique using a high-performance fluorescence scanner.

RESULTS

Of 500 up- or down-regulated mRNA transcripts, 19 selected fragments were recovered, cloned, sequenced, and identified. The accuracy and high degree of reproducibility of the method was demonstrated. Differential expression of gene products with potential association to cell proliferation or tumor progression was observed, such as 14-3-3beta and Rab27a. Moreover, several gene products with unknown functions were demonstrated in PTCs bearing RET or NTRK1 hybrids versus rearrangement-negative PTCs, including a homologue of the Ig kappa light chain constant region.

CONCLUSIONS

Candidate transcripts with presumed tumorigenic potential in other solid tumors may prove to be relevant in the progression of PTCs, too. Most promising is the isolation of several differentially expressed, yet unknown, genes that may open new insights in the pathogenesis or progression of PTC.

How to define follicular thyroid carcinoma?

The appropriate diagnosis of follicular thyroid carcinoma (FTC) still depends on its histological discrimination from follicular adenoma (including the distinction of benign from malignant oncocytic variants), papillary thyroid carcinoma (particularly from the follicular variants) and poorly differentiated thyroid carcinoma. The use of immunohistochemical markers contributed only marginally to better defining FTC. The introduction of the micro array technique, however, may offer the possibility of getting a better insight into the natural history, as well as predicting the clinical course, of a given thyroid nodule. This review attempts to recapitulate common standards in the diagnosis of FTC, to summarise current molecular data available to distinguish FTC from other benign and malignant tumours and, finally, to outline future perspectives to define FTC on its specific genetic features.

Gene expression in thyroid autonomous adenomas provides insight into their physiopathology

The purpose of this study was to use the microarray technology to define expression profiles characteristic of thyroid autonomous adenomas and relate these findings to physiological mechanisms. Experiments were performed on a series of separated adenomas and their normal counterparts on Micromax cDNA microarrays covering 2400 genes (analysis I), and on a pool of adenomatous tissues and their corresponding normal counterparts using microarrays of 18,000 spots (analysis II). Results for genes present on the two arrays corroborated and several gene regulations previously determined by Northern blotting or microarrays in similar lesions were confirmed. Five overexpressed and 24 underexpressed genes were also confirmed by real-time RT-PCR in some of the samples used for microarray analysis, and in additional tumor specimens. Our results show: (1) a change in the cell populations of the tumor, with a marked decrease in lymphocytes and blood cells and an increase in endothelial cells. The latter increase would correspond to the establishment of a close relation between thyrocytes and endothelial cells and is related to increased N-cadherin expression. It explains the increased blood flow in the tumor; (2) a homogeneity of tumor samples correlating with their common physiopathological mechanism: the constitutive activation of the thyrotropin (TSH)/cAMP cascade; (3) a low proportion of regulated genes consistent with the concept of a minimal deviation tumor; (4) a higher expression of genes coding for specific functional proteins, consistent with the functional hyperactivity of the tumors; (5) an increase of phosphodiesterase gene expression which explains the relatively low cyclic AMP levels measured in these tumors; (6) an overexpression of antiapoptotic genes and underexpression of proapoptotic genes compatible with their low apoptosis rate; (7) an overexpression of N-cadherin and downregulation of caveolins, which casts doubt about the use of these expressions as markers for malignancy.

Diagnostic usefulness of PCR profiling of the differentially expressed marker genes in thyroid papillary carcinomas

The study was set out to determine whether characteristic changes in the gene expression profile in papillary thyroid carcinoma (PTC) discovered by microarray assays can be used for conventional molecular diagnosis. Expression levels of five reported to be overexpressed and three underexpressed genes were examined in PTC and normal human tissues by real-time PCR and semi-quantitative duplex PCR. Stepwise logistic regression analysis, duplex PCR data evaluation with recursive partition machine algorithm and hierarchical cluster analysis identified SFTPB (upregulated) and TFF3 (downregulated) gene combination as most favorable for differential molecular diagnosis of PTC. Sensitivity, specificity and accuracy obtained in a series of histologically characterized thyroid tumor and normal tissue samples were 88.9, 96.7 and 94.9%, respectively. Applicability of the method to fine needle aspiration biopsy (FNAB) samples was demonstrated using a collection of needle washouts. In spite individual thyroid tumor and normal tissues as well as FNAB samples displayed a substantial degree of variability in the expression levels of analyzed genes, simultaneous molecular analysis of a panel of optimal markers allows making a high probability predictive estimate and may be considered as an informative method of preoperative PTC diagnosis.

Advancing the molecular diagnosis of thyroid nodules: defining benign lesions by molecular profiling

BACKGROUND

Thyroid nodules are common and most are benign. Previous data from our laboratory and others has suggested that gene profiling can accurately distinguish between benign and malignant thyroid nodules and provide new leads in the study of thyroid tumorigenesis. Current preoperative techniques do not permit distinction between neoplastic and hyperplastic follicular neoplasms. These studies were undertaken to determine whether benign follicular tumors could be subcategorized by molecular profiling.

METHODS

Molecular profiles of 8 follicular adenomas and 8 hyperplastic nodules were analyzed by oligonucleotide microarray analysis. A list of 402 differentially expressed genes was produced based on a comparison of these two groups. Seven additional benign follicular lesions were then added to the analysis. A hierarchical clustering analysis was performed on all 23 samples, utilizing the gene list generated from the test set, to examine the groups for potential differences and the ability of the gene list to distinguish tumor types.

RESULTS

Cluster analysis of all 23 samples produced two distinct groups, one containing the adenomas and one containing the hyperplastic lesions. The analysis was able to identify follicular adenomas with a sensitivity of 84.6% and a specificity of 100%.

CONCLUSIONS

These data indicate that benign thyroid lesions can be separated into distinct groups through molecular profiling. Analysis of the gene list may help further the understanding of thyroid tumorigenesis. Expression profiling may ultimately allow us to distinguish potentially malignant from benign follicular nodules.

Gene expression profiles reveal that DCN, DIO1, and DIO2 are underexpressed in benign and malignant thyroid tumors

To investigate the molecular events involved in the pathogenesis and/or progression of thyroid tumors, we compared the gene expression profiles of three thyroid carcinoma cell lines, which represent major tumor subtypes of thyroid cancer and normal thyroid tissue. Using cDNA array methodology, we investigated the expression of 1807 open reading frame expressed sequence tags (ORESTES), selected from head and neck tumor libraries generated through the Brazilian Human Cancer Project-LICR/FAPESP. We found that 505 transcripts were differentially expressed in the thyroid carcinoma cell lines. Using a more stringent criterion, transcripts underexpressed or overexpressed more than fivefold in 1 of 3 or 3 of 3 carcinoma cell lines, a list of 55 ESTs were detected. Five candidate genes were further validated by quantitative polymerase chain reaction (qPCR) in an independent set of 52 thyroid tumors and 22 matched normal thyroid tissues. DCN was found underexpressed in a high percentage of the follicular thyroid adenomas, follicular thyroid carcinomas, and follicular variant of papillary thyroid carcinomas. DIO1 and DIO2 were underexpressed in nearly all papillary thyroid carcinomas. These genes not only could help to better define a tumor signature for thyroid tumors, but may, in part, also become useful as potential targets for thyroid tumor treatment.

Gene Expression Profile of Papillary Thyroid Cancer: Sources of Variability and Diagnostic Implications

The study looked for an optimal set of genes differentiating between papillary thyroid cancer (PTC) and normal thyroid tissue and assessed the sources of variability in gene expression profiles. The analysis was done by oligonucleotide microarrays (GeneChip HG-U133A) in 50 tissue samples taken intraoperatively from 33 patients (23 PTC patients and 10 patients with other thyroid disease). In the initial group of 16 PTC and 16 normal samples, we assessed the sources of variability in the gene expression profile by singular value decomposition which specified three major patterns of variability. The first and the most distinct mode grouped transcripts differentiating between tumor and normal tissues. Two consecutive modes contained a large proportion of immunity-related genes. To generate a multigene classifier for tumor-normal difference, we used support vector machines-based technique (recursive feature replacement). It included the following 19 genes: DPP4, GJB3, ST14, SERPINA1, LRP4, MET, EVA1, SPUVE, LGALS3, HBB, MKRN2, MRC2, IGSF1, KIAA0830, RXRG, P4HA2, CDH3, IL13RA1, and MTMR4, and correctly discriminated 17 of 18 additional PTC/normal thyroid samples and all 16 samples published in a previous microarray study. Selected novel genes (LRP4, EVA1, TMPRSS4, QPCT, and SLC34A2) were confirmed by Q-PCR. Our results prove that the gene expression signal of PTC is easily detectable even when cancer cells do not prevail over tumor stroma. We indicate and separate the confounding variability related to the immune response. Finally, we propose a potent molecular classifier able to discriminate between PTC and nonmalignant thyroid in more than 90% of investigated samples.

Expression profile of malignant and non-malignant diseases of the thyroid gland reveals altered expression of a common set of genes in goiter and papillary carcinomas

Using cDNA microarrays with 3800 cDNA fragments, we determined the expression profile of normal thyroid tissue, goiter, adenoma and papillary carcinoma (10 samples from each class). After background correction and statistical analysis, we identified a set of 160 genes as being differentially expressed in all pair-wise comparisons. Here we demonstrate that, at least on the basis of these differentially expressed genes, a positive correlation between goiter and papillary carcinomas could be observed. We identified a common set of genes whose expression is diminished in both goiter and papillary carcinomas as compared to normal thyroid tissue. Moreover, no genes with inverse correlation in samples from goiter and papillary carcinomas could be detected. Using Real-Time PCR and/or tissue microarrays, we confirmed the altered expression of some of the identified genes. Of notice, we demonstrate that the reduced mRNA levels of p27(kip1) observed in papillary carcinomas as compared to either goiter or normal thyroid tissues (P<0.001) is accompanied by an altered protein distribution within the cell. In papillary carcinomas, P27(KIP1) is preferentially cytoplasmic as opposed to goiter or normal thyroid tissue, where P27(KIP1) is preferentially located in the nucleus. The exploitation of the data presented here could contribute to the understanding of the molecular events related to thyroid diseases and gives support to the notion that common molecular events might be related to the frequent observation of areas of papillary carcinomas in the gland of patients with goiter.

Discrimination of benign and malignant thyroid nodules by molecular profiling

BACKGROUND

The evaluation of thyroid nodules by fine-needle aspiration has been the standard for almost 30 years, despite significant shortcomings in sensitivity and specificity. Recent data from our laboratory have suggested that molecular profiling permits the discrimination of specific types of thyroid nodules. These studies were undertaken to determine whether molecular profiling can discriminate between benign and malignant thyroid nodules with the necessary sensitivity and specificity required of a screening test.

METHODS

Molecular profiles of 11 papillary thyroid carcinomas, 13 follicular variant of papillary thyroid carcinomas, 9 follicular thyroid carcinomas, and 26 benign tumors (follicular adenomas and hyperplastic nodules) were analyzed by oligonucleotide microarray analysis. A gene list was created based on 45 samples. Seventeen samples were then added to the analysis as unknowns. A hierarchical clustering analysis was performed on all 62 samples to examine the groups for potential differences and the ability of the gene list to distinguish tumor types.

RESULTS

Cluster analysis of all 62 samples produced 2 distinct groups, 1 containing the carcinomas and 1 containing the benign lesions. The sensitivity for a diagnosis of cancer was 91.7% with a specificity of 96.2% (3 follicular variant of papillary thyroid carcinomas clustered with the benign lesions). The cancer gene profiles contained both known cancer-associated genes (MET, galectin-3) and previously unidentified genes.

CONCLUSIONS

Molecular profiling readily distinguishes between benign and malignant thyroid tumors with excellent sensitivity and specificity. Elucidated genes may provide insight into the molecular pathogenesis of thyroid cancer. Gene profiling may significantly enhance the evaluation of thyroid nodules in the future.