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Journal of Clinical Endocrinology & Metabolism , doi:10.1210/jc.2006-1255
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The Journal of Clinical Endocrinology & Metabolism Vol. 93, No. 4 1390-1393
Copyright © 2008 by The Endocrine Society

BRIEF REPORT

TFF3-Based Candidate Gene Discrimination of Benign and Malignant Thyroid Tumors in a Region with Borderline Iodine Deficiency

Kerstin Krause, Markus Eszlinger, Oliver Gimm, Stefan Karger, Cornelia Engelhardt, Henning Dralle and Dagmar Fuhrer

Department of Internal Medicine (K.K., M.E., S.K., C.E., D.F.), University of Leipzig, 04103 Leipzig, Germany; and Department of Surgery (O.G., H.D.), University of Halle, 06120 Halle, Germany

Address all correspondence and requests for reprints to: Dagmar Fuhrer, M.D., Ph.D., Department of Internal Medicine, Universität Leipzig, Ph.-Rosenthal-Str. 27, 04103 Leipzig, Germany. E-mail: fued{at}medizin.uni-leipzig.de.


   Abstract
Top
 Abstract
Introduction
 Patients and Methods
 Results
 Discussion
 References
 
Background: With the advent of microarray technology, increasing numbers of marker genes are proposed to distinguish benign and malignant thyroid lesions. However, most markers await confirmation through independent studies. In this paper, we re-evaluate the diagnostic potential of 10 proposed candidate genes in benign and malignant thyroid pathologies in a region with borderline iodine deficiency.

Methods: Quantitative real-time PCR was performed for CCND2, PLAB, PCSK2, HGD1, TFF3, B4GALT, LGALS3, ETS1, ADM3, and TG in 150 thyroid specimens, including 52 benign thyroid nodules (28 follicular adenoma and 24 adenomatous nodules), 52 corresponding normal thyroid tissues, 20 follicular carcinomas, 20 papillary carcinomas, and six undifferentiated carcinomas.

Results: On a single-gene basis, significant differences in mRNA expression were found for TFF3, PLAB, and ADM3 in benign thyroid nodules and thyroid malignancy. Using two-marker gene sets, we identified 11 combinations, which allowed both a distinction of benign and malignant thyroid nodules and a discrimination of follicular adenoma and carcinoma. However, for cancer prediction, analysis of a minimum of six genes per sample was necessary and allowed correct prediction of a benign thyroid lesion and thyroid cancer with 94% accuracy in the most discriminative set (TFF3/PLAB/TG/ADM3/HGD1/LGALS3).

Conclusion: We confirm the applicability of a number of recently proposed marker genes for the distinction of benign and malignant thyroid tumor and suggest that their diagnostic usefulness is independent of the iodide supply. We propose that the most discriminative marker set identified in our validation study together with marker combinations proposed by other investigators should now be evaluated in multicenter trials.


   Introduction
Top
 Abstract
 Introduction
Patients and Methods
 Results
 Discussion
 References
 
With an increasing understanding of the molecular processes involved in thyroid tumorigenesis, the application of molecular tools has become particularly attractive to improve differential diagnosis of thyroid nodules (1, 2, 3). As a result of transcriptome studies, an increasing list of candidate genes for the molecular discrimination of benign and malignant thyroid tumors is now emerging (4, 5, 6, 7, 8, 9, 10). However, with the exception of very few, candidate markers have been investigated only in single studies and have not been validated by independent investigators. In addition, the analyzed thyroid samples were derived from different populations (mostly from the United States and Japan), and it is unclear how far environmental factors, such as iodine supply, may influence the candidate gene expression.

In the present study, we evaluated a set of 10 recently proposed marker genes (4, 6, 7, 8, 11) and investigated their diagnostic potential to distinguish benign and malignant thyroid tumors, including follicular neoplasia, in a defined population living in a region with borderline iodine deficiency. To this aim we analyzed quantitative mRNA gene expression and determined single as well as combined marker gene ratios in a series 150 thyroid specimen comprising 46 thyroid cancers, 52 benign thyroid nodules, and 52 normal thyroid tissues.


   Patients and Methods
Top
 Abstract
 Introduction
 Patients and Methods
Results
 Discussion
 References
 
Thyroid samples

Thirty solitary cold thyroid (CTN) nodules (14 adenomatous nodules and 16 follicular adenomas), 22 solitary toxic thyroid nodules (TTNs) (10 adenomatous nodules and 12 follicular adenomas), 52 surrounding normal thyroid tissues of the same patient (stCTN, stTTN), 20 follicular thyroid carcinomas (FTCs), 20 papillary thyroid carcinomas (PTCs), and six undifferentiated (anaplastic) thyroid carcinomas (UTCs) were studied. Patients with TTNs received antithyroid medication and had euthyroid function or subclinical hyperthyroidism at time of surgery. Patients with CTNs, FTCs, PTCs, and UTCs did not receive thyroid medication. Thyroid samples were obtained at time of surgery from the Department of Surgery, Martin-Luther-University Hospital Halle; the Department of Surgery, University Hospital Leipzig; and local Leipzig hospitals. Thyroid samples were selected by corresponding results for ultrasound, scintiscan and intraoperative inspection and were classified according to function and histology as previously described (6, 11) (a list of clinical data and TMN stage of the thyroid cancers is provided as a supplement, published as supplemental data on The Endocrine Society’s Journals Online Web site at http://jcem.endojournals.org). Informed consent was obtained from all patients. The local ethics committee approved the study.

RNA extraction and quantitative real-time PCR

Snap-frozen tissue samples were pulverized and transferred into TRIzol reagent (Invitrogen, Carlsbad, CA). RNA extraction and cDNA synthesis were carried out as described and expression of housekeeping genes [β-actin (ACTB) and glyceraldehyde-3-phosphate dehydrogenase] was demonstrated in all samples by RT-PCR (6, 11). Real-time PCR (LightCycler system, LightCycler-DNA Master SYBR Green I kit; Roche, Mannheim, Germany) was performed using intron-spanning primers for ADM3, B4GALT, CCND2, ETS1, HGD1, LGALS3, PCSK, PLAB, TFF3, TG, and the housekeeping gene ACTB. For each PCR annealing temperatures and MgCl2 concentrations were optimized to create a one-peak melting curve (primer sequences for and PCR condition are available on request).

Statistical analysis

The fold difference (n) in up- or down-regulation of mRNA expression was calculated as follows:

n = 2(threshold cycle of normal tissue – threshold cycle of diseased tissues)/2(threshold cycle of ACTB (normal tissue) – threshold cycle of ACTB (diseased tissues)]

Normal tissue corresponds to the surrounding tissue of toxic thyroid nodules and cold thyroid nodules for CTN, FTC, PTC, and UTC, respectively. For the molecular discrimination of benign and malignant thyroid tumors, mRNA expression levels in 28 follicular adenomas and 24 adenomatous nodules were compared with mRNA expression levels in 47 thyroid cancers (20 FTCs, 20 PTCs, and seven UTCs). For the molecular discrimination of follicular thyroid tumors mRNA expression levels in 28 follicular adenomas were compared with mRNA expression levels in 27 FTCs (including seven follicular variant PTCs). The Mann-Whitney U test within the SPSS software (version 11.5; SPSS, Chicago, IL) was used for statistical analysis of mRNA expression differences.

For the calculation of cancer prediction, we used the prediction analysis of microarrays (PAM), which is a statistical technique for class prediction from gene expression data using nearest shrunken centroids as described elsewhere (12). PAM can be freely downloaded (http://www-stat.stanford.edu/~tibs/PAM).


   Results
Top
 Abstract
 Introduction
 Patients and Methods
 Results
Discussion
 References
 
mRNA expression of ADM3 (7), CCND2, PLAB, PCSK2 (4), LGALS3, TFF3 (8, 13), B4GALT, HGD1(6), TG, and ETS1 (11) was demonstrated in all 150 thyroid specimens. Comparison of benign and malignant thyroid pathologies showed higher mRNA expression levels for HGD1, B4GALT, and TFF3 in benign nodules (CTN and TTN) and PLAB, LGALS3, and ADM3 in thyroid cancers (FTCs, PTCs, and UTCs). On a single-gene basis, this reached statistical significance only for Trefoil factor-3 (TFF3), prostate differentiation factor (PLAB), and adrenomedullin-3 (ADM3) (Table 1Go).


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  		TABLE 1. Median ratios of three single genes and two-marker gene sets

 
Given the heterogeneity of thyroid tumors, combination of genes may very likely improve the molecular discrimination of benign and malignant thyroid pathologies. We therefore calculated two-gene ratios, based on genes, which are up- or down-regulated in thyroid malignancy vs. nonmalignant thyroid specimen and normal thyroids, respectively: 1) using this approach, we identified 11 two-marker gene sets, which allowed both a distinction of benign and malignant thyroid nodules and a discrimination of follicular adenoma and carcinoma (Table 1Go); 2) of all investigated markers, down-regulation of TFF3 in malignant tumors was the best indicator for thyroid malignancy, and all TFF3-based gene ratios were significantly increased in the thyroid cancers (Table 1Go); and 3) for the discrimination of follicular adenoma and carcinoma, the best marker sets were PLAB/TFF3, PLAB/TG, LGAL3/TFF3 and ADM3/TFF3 (Fig. 1AGo). Protein convertase 2 (PCSK2) was the only proposed marker (4), for which inclusion in a two-marker gene set did not confer an additional diagnostic value.


Figure 1
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  		FIG. 1. A, Molecular discrimination of follicular thyroid tumors. Box plots showing median and distribution (box area = 50% of samples) of two-marker gene ratios, which allowed significant separation (P < 0.001 MWU test) of follicular adenoma (FA; 28) and follicular carcinoma (FTC/follicular variant PTC = 27). Ratios were calculated as described in Patients and Methods. B, Predictive scores of the six significant genes (TFF3, PLAB, TG, ADM3, HGD1, LGALS3), which were used for the classification of 104 benign and 46 malignant thyroid tumors at threshold = 2 using the PAM technique (12 ).

 
To assess the accuracy of cancer prediction we used the PAM method (12). This nearest shrunken centroid method is based on standardization by within-class SD for each gene and has been designed to identify the smallest set of genes that can accurately classify specific disease entities. Using this approach, we found that the analysis of six genes per sample (corresponds to threshold = 2) allows an acceptable prediction or exclusion of cancer (sensitivity, 0.8; specificity, 1.0; positive predictive value, 1.0; negative predictive value, 0.92; accuracy, 0.94). Of the validated 10 markers, expression analysis of TFF3/PLAB/TG/ADM3/HGD1/LGALS3 per sample was found to be the most discriminative combination and allowed correct classification in all benign tumors and in 37 of 46 thyroid malignancies (misclassification error rates: 0 and 0.20 for the benign and malignant entities, respectively). If toxic thyroid nodules were excluded from the analysis (because they may be identified by scintiscanning and may thus not need fine-needle aspiration cytology), the six-marker set correctly classified all benign samples and 42 of 46 thyroid cancers (sensitivity, 0.91; specificity, 1.0; positive predictive value 1.0; negative predictive value, 0.94; accuracy, 0.96).


   Discussion
Top
 Abstract
 Introduction
 Patients and Methods
 Results
 Discussion
References
 
The aim of our study was to validate recently proposed markers (4, 6, 7, 8, 11) for the differential diagnosis of thyroid nodular disease in a region with borderline iodine deficiency. Because the clinical manifestation of thyroid nodular disease is usually that of a visible, palpable, or increasingly (ultrasound diagnosed) incidental thyroid lesion but not of thyroid histopathology, we decided to use a broader (benign vs. malignant thyroid tumor) rather than entity focused (follicular adenoma vs. carcinoma) approach. In addition, in Germany most patients with nodular thyroid disease undergo scintiscanning, and FNAC analysis is usually restricted to cold thyroid nodules (14), whereas abroad FNAC is advocated as the first diagnostic procedure in a patient with a euthyroid nodule (15). Therefore, benign thyroid nodules with different functional entities were included in the study.

Our findings demonstrate that several markers previously identified through transcriptome analysis of follicular tumors from the United States (4, 7) and Japan (8, 13), e.g. from populations with a different genetic and environmental background, can also be applied to discriminate thyroid specimen in a region with borderline iodine deficiency. This suggests that these markers are indeed disease specific. In addition, we found that combinations of markers not only allowed a distinction of follicular adenoma and carcinoma but also at the same time were suitable to separate the more heterogeneous entities of benign and malignant thyroid tumors. However, our data also illustrate that the aim of a molecular discrimination of benign and malignant thyroid tumors is not the Holy Grail of a single marker gene, but in view of the heterogeneity of thyroid tumors, multiple marker sets need to be applied to reach this aim. In our tumor series a six-gene marker set comprising TFF3/PLAB/TG/ADM3/HGD1/LGALS3 allowed the best prediction, i.e. 94% accuracy for the differentiation of benign thyroid lesions and thyroid cancer.

The important next step will be to test independently validated gene sets, such as our or other marker sets, in multicenter trials on large series of thyroid tumors and their FNAC.


   Acknowledgments
 
We thank Monika Gutknecht and Beate Jeβnitzer for excellent technical help. We are grateful to Professor P. Lamesch (Department of Surgery, University of Leipzig) and Dr. M. Mühl (Department of Surgery, Wurzen) for the supply of thyroid tissue samples.


   Footnotes
 
This work was supported by the Deutsch Forschungsgemeinschaft Grant FU 356/1-2.

Disclosure Statement: The authors have nothing to declare.

First Published Online January 15, 2008

Abbreviations: ACTB, β-Actin gene; ADM3, adrenomedullin-3; CTN, cold thyroid nodule; FTC, follicular thyroid carcinoma; PAM, prediction analysis of microarrays; PCSK2, protein convertase 2; PLAB, prostate differentiation factor; PTC, papillary thyroid carcinoma; TFF3, Trefoil factor-3; TTN, toxic thyroid nodule; UTC, undifferentiated (anaplastic) thyroid carcinoma.

Received June 12, 2006.

Accepted January 3, 2008.


   References
Top
 Abstract
 Introduction
 Patients and Methods
 Results
 Discussion
 References
 

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  4. Weber F, Shen L, Aldred MA, Morrison CD, Frilling A, Saji M, Schuppert F, Broelsch CE, Ringel MD, Eng C 2005 Genetic classification of benign and malignant thyroid follicular neoplasia based on a three-gene combination. J Clin Endocrinol Metab 90:2512–2521[Abstract/Free Full Text]
  5. Jacques C, Baris O, Prunier-Mirebeau D, Savagner F, Rodien P, Rohmer V, Franc B, Guyetant S, Malthiery Y, Reynier P 2005 Two-step differential expression analysis reveals a new set of genes involved in thyroid oncocytic tumors. J Clin Endocrinol Metab 90:2314–2320[Abstract/Free Full Text]
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