Gene expression profiling of differentiated thyroid neoplasms: diagnostic and clinical implications

Gene expression signature discriminates sporadic from post-radiotherapy-induced thyroid tumors

Both external and internal exposure to ionizing radiation are strong risk factors for the development of thyroid tumors. Until now, the diagnosis of radiation-induced thyroid tumors has been deduced from a network of arguments taken together with the individual history of radiation exposure. Neither the histological features nor the genetic alterations observed in these tumors have been shown to be specific fingerprints of an exposure to radiation. The aim of our work is to define ionizing radiation-related molecular specificities in a series of secondary thyroid tumors developed in the radiation field of patients treated by radiotherapy. To identify molecular markers that could represent a radiation-induction signature, we compared 25K microarray transcriptome profiles of a learning set of 28 thyroid tumors, which comprised 14 follicular thyroid adenomas (FTA) and 14 papillary thyroid carcinomas (PTC), either sporadic or consecutive to external radiotherapy in childhood. We identified a signature composed of 322 genes which discriminates radiation-induced tumors (FTA and PTC) from their sporadic counterparts. The robustness of this signature was further confirmed by blind case-by-case classification of an independent set of 29 tumors (16 FTA and 13 PTC). After the histology code break by the clinicians, 26/29 tumors were well classified regarding tumor etiology, 1 was undetermined, and 2 were misclassified. Our results help shed light on radiation-induced thyroid carcinogenesis, since specific molecular pathways are deregulated in radiation-induced tumors.

Detection and classification of thyroid follicular lesions based on nuclear structure from histopathology images

Follicular lesions of the thyroid are traditionally difficult and tedious challenges in diagnostic surgical pathology in part due to lack of obvious discriminatory cytological and microarchitectural features. We describe a computerized method to detect and classify follicular adenoma of the thyroid, follicular carcinoma of the thyroid, and normal thyroid based on the nuclear chromatin distribution from digital images of tissue obtained by routine histological methods. Our method is based on determining whether a set of nuclei, obtained from histological images using automated image segmentation, is most similar to sets of nuclei obtained from normal or diseased tissues. This comparison is performed utilizing numerical features, a support vector machine, and a simple voting strategy. We also describe novel methods to identify unique and defining chromatin patterns pertaining to each class. Unlike previous attempts in detecting and classifying these thyroid lesions using computational imaging, our results show that our method can automatically classify the data pertaining to 10 different human cases with 100% accuracy after blind cross validation using at most 43 nuclei randomly selected from each patient. We conclude that nuclear structure alone contains enough information to automatically classify the normal thyroid, follicular carcinoma, and follicular adenoma, as long as groups of nuclei (instead of individual ones) are used. We also conclude that the distribution of nuclear size and chromatin concentration (how tightly packed it is) seem to be discriminating features between nuclei of follicular adenoma, follicular carcinoma, and normal thyroid.

Genetic markers differentiating follicular thyroid carcinoma from benign lesions

Thyroid nodules are commonly encountered during routine medical care. The main problem established by a discovery of a thyroid nodule is to discriminate between a benign and malignant lesion. Fine-needle aspiration (FNA) is the most widely used and cost-effective preoperative test for initial evaluation of a thyroid nodule. While the overall accuracy of FNA for classical papillary thyroid carcinoma (PTC) approaches 100%, it has limited accuracy with follicular lesions. Patients with a cytological report of indeterminate or follicular lesions are referred to surgery for a more accurate diagnosis. A more acute molecular-based test for thyroid nodules is needed not only to improve treatment decisions, but also to potentially reduce the long-term health costs. Several studies have looked into biologic markers that could be used as an adjuvant to distinguish the benign from malignant nodules. This review will focus on those biomarkers that are potentially useful in the diagnosis of thyroid lesions commonly classified as indeterminate.

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.

Are adenosquamous lung carcinomas a simple mix of adenocarcinomas and squamous cell carcinomas, or more complex at the molecular level?

Adenocarcinomas (AC), squamous cell carcinomas (SCC) and adenosquamous carcinomas (ASC) are three histological subtypes of non-small-cell lung carcinomas (NSCLC). ASC are morphologically mixed tumours that contain the two cell components AC and SCC. To understand if they are a "simple" mix of AC and SCC or if they present molecular specificities, as compared with the molecular characterization of both components, we performed a comparative transcriptome analysis on a series of nine ASC, five AC and five SCC induced in rats by radon exposure. We found that 72, 40 and 39 genes were differentially expressed when comparing AC_SCC, ASC_SCC and AC_ASC, respectively. Moreover, when classifying the three histological subtypes, using genes that discriminated AC and SCC, we observed that all ASC were classified as intermediate between the AC and SCC, some being closer to AC, others to SCC. These results indicated that, regarding gene expression, ASC could be considered as a mix of AC and SCC, both in various proportions. However, they also exhibit molecular specificities since we found specific genes discriminating ASC_SCC and AC_ASC. In conclusion, the ASC mixed lung tumours are more complex than simple mixes of AC and SCC components. Neuroendocrine differentiation and ERK proliferation pathways seemed preferentially deregulated in ASC compared to AC and SCC respectively, pathways that are worthy of being explored because they could partially explain the high clinical aggressiveness of ASC.

Proteomics in thyroid tumor research

BACKGROUND

In recent years, "OMICS" technologies have paved novel ways for the broad-scale identification of molecular signatures and signaling pathways specific to tumorigenesis. Related to this are high hopes for the discovery of biomarkers facilitating diagnosis and prognosis of cancer as well as the option for pathway-targeted tumor treatment. Among the different OMICS methods, the potential of proteomics is just beginning to emerge, and according to the current literature, the proteome is to date the most feasible tool to reflect tumor biology.

OBJECTIVE

In this review we discuss the application of proteomics to the field of thyroid tumor research.

CONTEXT

First, we provide an overview of different methods for protein expression profiling and then discuss specific requirements and challenges of thyroid proteomics. Furthermore, we summarize results of published proteomics studies on human thyroid tumors and finally explore perspectives of thyroid proteomics, which, combined with mRNA expression profiling and traditional biochemical methods, is increasingly contributing to an improved understanding of thyroid tumorigenesis and may in the future open novel avenues in thyroid cancer therapy.

Modeling thyroid cancer in the mouse

Thyroid carcinomas, the most common endocrine tumors in humans, have an increasing incidence in the U.S. and worldwide. There are four major types of thyroid cancers: papillary, follicular, anaplastic, and medullary carcinomas. In recent years, significant progress has been made in the identification of genetic alterations in thyroid carcinomas, particularly, papillary and medullary thyroid cancers. Mouse models of thyroid cancer are valuable tools in elucidating molecular genetic changes underlying thyroid carcinogenesis and in identifying potential molecular targets for therapeutic intervention. Representative mouse models of papillary, follicular, and medullary carcinomas are reviewed here with particular emphasis on those for follicular thyroid carcinomas. Challenges for further development in the modeling of thyroid cancer will also be discussed.

Feedback regulation of DUSP6 transcription responding to MAPK1 via ETS2 in human cells

DUSP6/MKP-3 is a dual specificity phosphatase exclusively specific to MAPK1/ERK2 for its substrate recognition and dephosphorylating activity. DUSP6 is demonstrated to play a negative regulatory role in MAPK1 in a feedback loop manner; however, the regulation mechanisms of its expression in human cells have been largely unknown. We previously found that human pancreatic cancer cells frequently lost DUSP6 expression, which could induce constitutively active MAPK1, and the loss was associated with hypermethylation of the CpG cluster region of intron 1 of DUSP6. In this study, we investigated the promoter activity of intron 1 of DUSP6 in human cells. We demonstrated that the intron indeed had promoter activity and this activity was associated with MAPK1 activity. Moreover, promoter activity depended on a consensus binding sequence of ETS transcription factors and ETS2 was specifically associated with the intron. Because ETS2 is a direct target of MAPK, these results indicate that intron 1 of DUSP6 plays a crucial role in transcriptional regulation of DUSP6 in a feedback loop manner responding to MAPK1 via ETS2 in human cells.

Molecular classification of thyroid nodules by cytology

OBJECTIVES

Fine needle aspiration (FNA) biopsy of thyroid nodules provides cytologic specimens whose interpretation can direct patients toward either thyroidectomy or observation. Approximately 20% of FNA specimens yield an indeterminate result. Recent studies have characterized differences in gene expression between benign and malignant conditions, most often using whole tissue. Our goal was to determine the feasibility of quantitative polymerase chain reaction (qPCR)-based gene expression analysis in cytologic samples. For five genes shown to be over-expressed in thyroid carcinomas (fibronectin, galectin-3, Met/HGFR, MUC1, and GA733-precursor), we compared expression among pathologic states.

STUDY DESIGN

Prospective laboratory analysis of 20 thyroidectomy specimens.

METHODS

Routine microscopy was performed. Cytologic samples were obtained from the dominant nodules, and RNA was extracted. Preliminary analysis using fluorometry and reverse-transcriptase (RT)-PCR was performed. Expression levels of the test genes in nodules and from control samples were measured by real-time qPCR. Fold changes in gene expression were compared.

RESULTS

Only one specimen did not yield sufficient intact RNA for gene expression analysis. RT-PCR revealed satisfactory RNA recovery in all other specimens. qPCR showed significant over-expression of fibronectin in the papillary carcinomas compared with the goiters (P = .0013), follicular adenomas (P = .0014), and follicular carcinomas (P = .0001). Differences in both fibronectin and MUC1 expression between the follicular carcinomas and the follicular adenomas were also significant (P = .025 and .045, respectively).

CONCLUSIONS

Cytologic specimens were a satisfactory source of tissue for qPCR-based gene expression analysis. Both fibronectin and MUC1 were differentially expressed in follicular adenomas and follicular carcinomas, and fibronectin expression differed in papillary carcinomas compared with the other lesions. These results may form the basis of a clinical predictor for lesions with indeterminate or suspicious cytology.

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.

In vivo and microarray analysis of rexinoid-responsive anaplastic thyroid carcinoma

PURPOSE

Anaplastic thyroid carcinoma is rare, yet lethal despite aggressive therapy. Molecular targeting may be beneficial using the rexinoid LGD1069, a retinoid X receptor-selective agonist, as a novel treatment. In this report, we describe the efficacy of LGD1069 in anaplastic thyroid carcinoma in vitro and assess the in vivo treatment effects on a responsive cancer. Additionally, we explore potential mediators of the rexinoid effect on a responsive anaplastic thyroid cancer using comparative microarray analysis.

EXPERIMENTAL DESIGN

Anaplastic thyroid cancer cell lines DRO, ARO, and FRO were treated with LGD1069 in vitro. Responsive DRO xenograft tumors were treated with control chow or chow containing a low dose (30 mg/kg/d) or a high dose (100 mg/kg/d) of LGD1069. Comparative microarray analysis of DRO cells treated with LGD1069 compared with volume-equivalent control was assessed after 24 h of treatment to evaluate early gene expression changes.

RESULTS

DRO xenograft tumor growth was inhibited by LGD1069 treatment in a dose-dependent manner. Comparative microarray analysis showed that 80 genes had a significant increase in expression and 29 genes had a decrease in expression after 24 h of treatment with LGD1069. Expression of angiopoietin-like 4 (ANGPTL4) mRNA was increased 6.5-fold. A trend towards an increase in ANGPTL4 mRNA (not statistically significant) was seen in treated tumors in vivo and this correlated with decreased tumor vascularity and increased necrosis.

CONCLUSIONS

LGD1069 therapy decreases proliferation in an anaplastic thyroid cancer cell line that expresses retinoid X receptor-gamma, and this effect is confirmed with decreased tumor size in vivo in a nude mouse model. ANGPTL4 is increased in DRO in response to LGD1069 and may be a potential mediator of the effects of rexinoid treatment.

Follicular neoplasm of the thyroid--vanishing cytologic diagnosis?

The significance of making a diagnosis of follicular neoplasm on fine needle aspiration (FNA) biopsy remains a controversial issue, considering that the diagnosis of follicular carcinoma is based on histological criteria and the significantly decreasing incidence of follicular carcinoma in the general population. On FNA the main differential diagnoses of follicular neoplasm includes follicular variant of papillary carcinoma (FVPC), follicular adenoma, follicular carcinoma and benign solitary nodule occurring in a goiter. Several studies have looked at immunohistochemical and molecular markers to distinguish benign from malignant lesions but none of them have proved to be infallible. Although, FVPC is a distinct entity from the follicular neoplasm group, it is not always possible to separate it from the other follicular lesions because of overlapping cytologic features and often-sporadic presence of nuclear features, follicular variant of papillary carcinoma remains the main pitfall in a diagnosis of follicular neoplasm. Since a significant number of cases that are malignant on follow-up are usually FVPC, consequently, follicular neoplasm is an essential diagnostic consideration on FNA. In addition, follicular carcinoma, despite a decreasing incidence continues to be a real entity. Therefore, it is essential that follicular neoplasm continue to be part of our diagnostic repertoire.

Genome-wide expression analysis of Middle Eastern papillary thyroid cancer reveals c-MET as a novel target for cancer therapy

In an attempt to find genes that may be of importance in malignant progression of papillary thyroid carcinoma (PTC) in the Middle East, which therefore can be targeted in cancer therapy, we screened and validated the global gene expression in PTC using cDNA expression arrays and immunohistochemistry (IHC) on tumour tissue microarrays. Twenty-nine PTC tissue specimens were compared with seven non-cancerous thyroid specimens by use of cDNA microarray. Results for selected genes were confirmed by quantitative real-time PCR. Protein expression of selected genes was further studied using a tissue microarray consisting of 536 PTCs and compared with histologically non-cancerous tissue samples. One hundred and ninety-six genes were overexpressed in PTC tissues relative to non-cancerous thyroid tissues. The genes that were up-regulated in PTC were involved in cell cycle regulation, cell signaling, and oncogenesis. Among these genes, c-MET was identified by immunohistochemical methods as a protein that is overexpressed in 37% of PTCs and was significantly associated with more aggressive behaviour, eg higher stage, nodal involvement, and tall cell variant (p value = 0.01, 0.01 and 0.04, respectively). In this study, 55% of the PTC cases expressed activated AKT (P-AKT), which suggests that activated AKT may play an important role in PTC tumourigenesis. The fact that most of the PTC cases that had activated AKT showed overexpression of c-MET (p = 0.027) leads us to hypothesize that c-MET may be an alternative mechanism of AKT activation in Middle Eastern PTCs. Finally, our data suggest that c-MET dysregulation is associated with aggressive behaviour and may serve as a molecular biomarker and potential therapeutic target in this disease.

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

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

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.

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.

Transcriptional response of wild-type and ataxia telangiectasia lymphoblasts following exposure to equitoxic doses of ionizing radiation

Experiments were designed to compare the transcriptional response to ionizing radiation (IR) of wild-type (WT) and ataxia telangiectasia (AT) cells. mRNA levels were assessed 2, 4 and 24 h after exposure to equitoxic doses using cDNA microarrays. Data reveal distinct patterns of gene expression between AT and WT cells since IR-responsive genes were mostly cell-type specific, this group representing 87 and 94% of the responding genes in WT and AT cells, respectively. In both cell lines, transcriptional alterations of genes associated with proliferation correlated with the observed cell cycle and growth data. Deregulated genes involved in apoptosis suggest that wild-type cells were more prone to cell death by apoptosis than AT cells. Furthermore, genes associated with the response to oxidative stress were particularly deregulated in wild-type cells whereas alterations of genes related to unexpected pathways including RNA processing, protein synthesis and lipid metabolism were specifically found in irradiated AT cells. These data suggest that under radiation conditions leading to a similar survival of WT and AT cells, the mechanisms triggered after radiation were mainly dependent on ATM status and thus on the intrinsic radiosensitivity.

Microarray analysis of thyroid nodule fine-needle aspirates accurately classifies benign and malignant lesions

Current preoperative diagnostic procedures for thyroid nodules rely mainly on the cytological interpretation of fine-needle aspirates (FNAs). DNA microarray analysis has been shown to reliably distinguish benign and malignant thyroid nodules in surgically resected specimens, but its diagnostic potential in thyroid FNA has not been examined. In the present study, the expression profiles of 50 benign thyroid lesions and papillary thyroid carcinoma tissue samples were compared, generating a list of 25 differentially expressed genes from this training set. A test set of 22 FNA specimens was evaluated by unsupervised hierarchical cluster analysis using this gene list, and the results were compared to FNA cytology. FNA specimens were found to fall into three clusters: malignant (n = 10), benign (n = 7), and indeterminate (n = 5). The benign and malignant groups showed complete concordance with the final histological diagnosis except for one histologically benign lesion, which was rediagnosed as follicular variant of papillary thyroid carcinoma on histological review. Paired analysis between FNA and matched tissues samples illustrated adequate sampling with FNA. These results illustrate that microarray analysis of FNA is feasible and has the potential to improve the accuracy of FNA in categorizing benign from malignant lesions beyond routine cytological evaluation.

Establishment of a Discriminant Mathematical Model for Diagnosis of Deficiency-Cold Syndrome Using Gene Expression Profiling

OBJECTIVE

To screen diagnostic markers of Deficiency-Cold syndrome by gene expression profile and to establish a discriminant mathematical milliliters model for the clinical diagnosis of this syndrome based on a support vector machine (SVM).

METHODS

A family suffering from Deficiency-Cold syndrome is chosen for this study. This family has 5 patients with Deficiency-Cold syndrome and 10 normal members. The peripheral blood samples for these 5 patients and 5 normal members are tested by using cDNA microarray with 18,816 clones to get their differential expression genes. These genes are further explored to understand their biological functions and pathways through existing databases. A SVM model for clinical diagnosis is then developed based on these differential expression genes.

RESULTS

A total of 83 differential expression genes were identified between patients and normal members, in which 21 genes were recorded in the FATIGO database and 16 genes were related to metabolism. Eight (8) pathways were sorted out in the KEGG database, and half pathways were associated with human metabolism. A discriminant mathematical model based on a support vector machine successfully predicted a normal person and a patient with heavy Deficiency-Cold syndrome based on their gene differential expression profiles. Thus, this model may classify the Deficiency-Cold syndrome.

CONCLUSION

This work demonstrates that the differential expression genes can be used to identify normal persons and patients with Deficiency-Cold syndrome. Deficiency-Cold syndrome is mainly associated with the metabolism-related gene regulations. In addition, the discriminant mathematical model based on a support vector machine is applicable to the clinical diagnosis for Deficiency-Cold syndrome.

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.

PPARgamma insufficiency promotes follicular thyroid carcinogenesis via activation of the nuclear factor-kappaB signaling pathway

The molecular genetic events underlying thyroid carcinogenesis are poorly understood. Mice harboring a knock-in dominantly negative mutant thyroid hormone receptor beta (TRbetaPV/PV mouse) spontaneously develop follicular thyroid carcinoma similar to human thyroid cancer. Using this mutant mouse, we tested the hypothesis that the peroxisome proliferator-activated receptor gamma (PPARgamma) could function as a tumor suppressor in thyroid cancer in vivo. Using the offspring from the cross of TRbetaPV/+ and PPARgamma+/- mice, we found that thyroid carcinogenesis progressed significantly faster in TRbetaPV/PV mice with PPARgamma insufficiency from increased cell proliferation and reduced apoptosis. Reduced PPARgamma protein abundance led to the activation of the nuclear factor-kappaB signaling pathway, resulting in the activation of cyclin D1 and repression of critical genes involved in apoptosis. Treatment of TRbetaPV/PV mice with a PPARgamma agonist, rosiglitazone, delayed the progression of thyroid carcinogenesis by decreasing cell proliferation and activation of apoptosis. These results suggest that PPARgamma is a critical modifier in thyroid carcinogenesis and could be tested as a therapeutic target in thyroid follicular carcinoma.

Molecular genetic study comparing follicular variant versus classic papillary thyroid carcinomas: association of N-ras mutation in codon 61 with follicular variant

Although the follicular variant of papillary thyroid carcinoma (FVPTC) has been classified as a papillary cancer based on nuclear features, its follicular growth pattern and potential for hematogenous spread are more characteristic of follicular carcinoma. To gain insight into the biologic nature of FVPTC, we compared genetic alterations characteristic of papillary and follicular thyroid carcinomas in 24 FVPTCs and 26 classic PTC (CPTCs). In FVPTCs, we observed ras mutation in 6 of 24 cases (25%), BRAF mutation in 1 of 13 cases (7.6%), and ret rearrangement in 5 of 12 cases (41.7%). In CPTCs, we found ras mutation in no case, BRAF mutation in 3 of 10 cases (30%), and ret rearrangement in 5 of 11 cases (45%). One FVPTC exhibited simultaneous ras mutation and ret/PTC1 rearrangement, and one CPTC harbored simultaneous BRAF mutation and ret/PTC3 rearrangement. Based on these findings, we concluded that ras mutation correlates with follicular differentiation of thyroid tumors whereas ret activation is associated with papillary nuclei but not with papillary architecture. ret activation is not exclusive of ras or BRAF mutation, whereas ras and BRAF mutations are mutually exclusive. The implications of these results for follicular and papillary carcinogenesis are discussed.

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.

Vascular endothelial growth factor in thyroid cancers

Vascular endothelial growth factor (VEGF) is an essential peptide in new vessel growth in physiology (endometrial growth, embryonic development); pathological conditions (diabetic retinopathy, rheumatoid arthritis); as well as in tumor cell growth, particularly distant metastases. This study focused on VEGF structure, receptors, and angiogensis in tumors, especially their roles in thyroid cancer. The VEGF mRNA undergoes alternative splicing events that generate four homodimeric isoforms, including VEGF121, VEGF165, VEGF189, or VEGF206. Using VEGF purified from a culture medium conditioned by A-431 human epidermoid carcinoma cells, VEGF-binding site complexes of 230, 170, and 125 kDa were detected on human umbilical vein endothelial cells. The VEGF specifically induced the tyrosine phosphorylation of a 190-kDa polypeptide, which had similar mass to the largest binding site detected through affinity cross-linking. A transmembrane receptor belongs to the tyrosine kinase family, fms-like tyrosine kinase (FLT). These receptor tyrosine kinases encoded by the FLT gene family have distinct functions in regulating blood vessel growth and differentiation. Regulation of VEGF is a complex, multistep mechanism in various kinds of cells and tissues. Hypoxia-dependent and -independent mechanisms are illustrated in different cancer tissues. Hypoxic tumor cells may switch to a proangiogenic phenotype, which increases VEGF transcription. Clinical applications of VEGF in cancer have included diagnosis, prediction of prognosis, and treatment in different solid tumors, including thyroid tumors. Studies involving thyroid cancer cell lines, serum level determination, immunohistocytochemical staining, molecular biological studies, and gene therapy to the in vivo clinical trials, have shown that antiangiogensis therapy can provide another treatment modality for thyroid cancer. Future studies focused on recombinant human anti-VEGF research involving patients with advanced thyroid cancer, and investigation of the protection of high-risk patients by using novel antiangiogenic vaccines, are warranted.

Correlation between genetic alterations and microscopic features, clinical manifestations, and prognostic characteristics of thyroid papillary carcinomas

Papillary carcinoma is the most common type of thyroid malignancy. It has been recently shown that these tumors commonly have one of three genetic alterations: BRAF point mutations, RET/PTC rearrangements, or RAS point mutations. In this study, we analyze the relationship between these alterations and the microscopic features of papillary carcinomas, their clinical features, and prognostic characteristics. Ninety-seven papillary carcinomas were studied; in all cases, frozen tissue was available for nucleic acid extraction. Of 96 unselected cases, 42% were positive for BRAF, 18% for RET/PTC, and 15% for RAS mutations. Morphologic features were evaluated in detail in 61 cases and 6 characteristic nuclear features and 3 additional microscopic features were assessed quantitatively. At least 4 nuclear features were found in each tumor, with nuclear pseudoinclusions being the least frequent finding in all mutation groups. BRAF mutations were associated with older patient age, typical papillary appearance or the tall cell variant, a higher rate of extrathyroidal extension, and more advanced tumor stage at presentation. RET/PTC rearrangements presented at younger age and had predominantly typical papillary histology, frequent psammoma bodies, and a high rate of lymph node metastases. Tumors with RAS mutations were exclusively the follicular variant of papillary carcinoma and correlated with significantly less prominent nuclear features and low rate of lymph node metastases. These findings demonstrate that BRAF, RET/PTC, and RAS mutations are associated with distinct microscopic, clinical, and biologic features of thyroid papillary carcinomas.

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.

Expression profiling of adrenocortical neoplasms suggests a molecular signature of malignancy

BACKGROUND

Distinguishing between adrenocortical adenomas and carcinomas is often difficult. Our aim was to investigate the differences in transcriptional profiles between benign and malignant adrenocortical neoplasms using complementary DNA microarray techniques.

METHODS

We studied 7 patients with adrenocortical carcinomas and 13 with adenomas. Histopathology was reviewed in all patients; clinical follow-up was at least 1 year. Hybridizations were performed in duplicate against RNA reference. Expression levels were analyzed in the R environment for statistical computing with the use of aroma, limma, statistics, and class packages.

RESULTS

Transcriptional profiles were homogeneous among adenomas, while carcinomas were much more heterogeneous. Hierarchical clustering and self-organizing maps could separate clearly carcinomas from adenomas. Among genes that were most significantly upregulated in carcinomas were 2 ubiquitin-related genes (USP4 and UFD1L) and several insulinlike growth factor-related genes (IGF2, IGF2R, IGFBP3 and IGFBP6). Among genes that were most significantly downregulated in carcinomas were a cytokine gene (CXCL10), several genes related to cell metabolism (RARRES2, ALDH1A1, CYBRD1 and GSTA4), and the cadherin 2 gene (CDH2).

CONCLUSIONS

Through the use of cDNA arrays, adrenocortical adenomas and carcinomas appear to be clearly distinguishable on the basis of their specific molecular signature. The biologic importance of the up- and downregulated genes is yet to be determined.

Gene-expression profiling in differentiated thyroid cancer – a viable strategy for the practice of genomic medicine?

Thyroid neoplasias have been largely ignored as an active field of investigation due to the overall favorable prognosis of differentiated nonmedullary thyroid cancers. However, differentiated thyroid cancers have the highest estimated annual percentage increase in incidence amongst all cancer sites. Furthermore, no significant progress has been made to improve survival, especially for advanced disease. Compounding the problem, there remains a lack of highly accurate preoperative markers or molecular-based predictive models to differentiate benign from malignant follicular neoplasias, thus we continue to rely upon surgery for diagnostic purposes in this subset of patients. Therefore, new approaches are necessary to identify potential novel diagnostic, prognostic and therapeutic algorithms, which would not only allow accurate early diagnosis but also personalized patient management, with clinical management and surveillance tailored according to the genetic signature of the patient. The advent of modern genomic technologies, such as global gene-expression profiling, may begin to provide the data required for the evidence-based practice of genomic medicine as it relates to thyroid neoplasia. However, it is already clear that genomic technology alone is insufficient to fully achieve this vision.

Molecular classification of papillary thyroid carcinoma: distinct BRAF, RAS, and RET/PTC mutation-specific gene expression profiles discovered by DNA microarray analysis

Thyroid cancer poses a significant clinical challenge, and our understanding of its pathogenesis is incomplete. To gain insight into the pathogenesis of papillary thyroid carcinoma, transcriptional profiles of four normal thyroids and 51 papillary carcinomas (PCs) were generated using DNA microarrays. The tumors were genotyped for their common activating mutations: BRAF V600E point mutation, RET/PTC1 and 3 rearrangement and point mutations of KRAS, HRAS and NRAS. Principal component analysis based on the entire expression data set separated the PCs into three groups that were found to reflect tumor morphology and mutational status. By combining expression profiles with mutational status, we defined distinct expression profiles for the BRAF, RET/PTC and RAS mutation groups. Using small numbers of genes, a simple classifier was able to classify correctly the mutational status of all 40 tumors with known mutations. One tumor without a detectable mutation was predicted by the classifier to have a RET/PTC rearrangement and was shown to contain one by fluorescence in situ hybridization analysis. Among the mutation-specific expression signatures were genes whose differential expression was a direct consequence of the mutation, as well as genes involved in a variety of biological processes including immune response and signal transduction. Expression of one mutation-specific differentially expressed gene, TPO, was validated at the protein level using immunohistochemistry and tissue arrays containing an independent set of tumors. The results demonstrate that mutational status is the primary determinant of gene expression variation within these tumors, a finding that may have clinical and diagnostic significance and predicts success for therapies designed to prevent the consequences of these mutations.