Journal of Clinical Endocrinology & Metabolism
, doi:10.1210/jc.2008-0201
The Journal of Clinical Endocrinology & Metabolism Vol. 93, No. 9 3286-3294
Copyright © 2008 by The Endocrine Society
Perspectives for Improved and More Accurate Classification of Thyroid Epithelial Tumors
Markus Eszlinger,
Knut Krohn,
Steffen Hauptmann,
Henning Dralle,
Thomas J. Giordano and
Ralf Paschke
Third Medical Department (M.E., K.K., R.P.) and Interdisciplinary Center for Clinical Research Leipzig (K.K.), University of Leipzig, D-04103 Leipzig, Germany; Institute for Pathology (S.H.) and Department of General, Visceral, and Vascular Surgery (H.D.), University of Halle, D-06099 Halle, Germany; and Department of Pathology (T.J.G.), University of Michigan, Ann Arbor, Michigan 48109
Address all correspondence and requests for reprints to: R. Paschke, M.D., III. Medical Department, University of Leipzig, Ph.-Rosenthal-Str. 27, D-04103 Leipzig, Germany. E-mail: pasr{at}medizin.uni-leipzig.de.
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Abstract
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Context: Histologic examination of thyroid nodules is the current standard to distinguish benign from malignant thyroid epithelial tumors and to classify histologic subtypes. This review analyzes the problems in histological differential diagnosis as well as contradictions between histology and molecular data and describes possibilities to combine histology with molecular data in an effort to more accurately classify thyroid epithelial tumors.
Evidence Acquisition: Published literature, addressing the current recommendations for thyroid tumor classification, as well as literature on the application of histology and molecular studies on the etiology of thyroid tumors is analyzed.
Evidence Synthesis: The current histologic criteria to classify thyroid tumors, especially follicular-patterned tumors, are hampered by considerable interobserver variability. The detection of somatic mutations via genotyping and the definition of potentially informative gene expression signatures by microarray analyses, which can distinguish cancer subtypes as well as low- and high-risk cohorts, have recently demonstrated significant diagnostic potential. Moreover, in a routine diagnostic setting, micro-RNA profiling appears most promising due to their relative stability and the high accuracy of their expression profiles.
Conclusions: It is very likely that molecular definitions of thyroid tumors mentioned in the current World Health Organization classification will be further developed, leading to future progress in defining thyroid tumor types by an integrated histologic and molecular approach. These integrated classifications need to be evaluated for their specific impact on thyroid tumor diagnosis and prognosis.
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Introduction
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Most patients with differentiated thyroid carcinomas can be cured by surgery and radioiodine therapy. However, about 30% will develop metastatic disease and some will not respond to radioiodine during the further course of the disease (1). Current survival predictions for patients with thyroid carcinomas are based on relatively simple clinical and pathological characteristics, like age and tumor size. Moreover, new drugs targeting specific molecular mechanisms primarily designed to treat radioiodine-insensitive or resistant tumors need precise indications, e.g. tumors with well characterized targets. The histologic classification of thyroid epithelial tumors is the current standard to distinguish benign from malignant thyroid tumors and to assign specific tumors into histologic subtypes. The World Health Organization (WHO) classification has recently been revised and distinguishes thyroid tumor types (as listed in Table 1
). For many of these tumor types the histologic criteria are subjective and thus difficulty to implement. Furthermore, reliable biologic prognostic factors are still lacking (2). Moreover, it is likely that some of the histologic subtypes of thyroid carcinomas, such as some of the variants of papillary carcinoma, are not biologically justified and contribute to problems in differential diagnosis. Conversely, because of the frequent difficulties in separating the different entities, additional thyroid epithelial tumor subtypes have been suggested to accommodate these classification difficulties (3).
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Histologic and functional classification of benign thyroid tumors
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The distinction between follicular adenoma (FTA) and adenomatoid nodule is sometimes rather arbitrary. Adenomatoid nodules are multiple and lack a well-defined fibrous capsule and are composed of follicles morphologically similar to those in the surrounding thyroid tissue. FTAs are usually solitary and surrounded by a thin capsule. Occasionally they arise on a background of nodular hyperplasia. However, there is a lack of consistent criteria for distinguishing hyperplastic nodules and adenomas in many studies and pure histologic criteria are difficult to apply especially in a frequent background of nodular hyperplasia or thyroiditis, in the surrounding tissue, which is often abnormal. Therefore, the current WHO classification recommends that the biological basis for separating hyperplastic thyroid nodules from true tumors (adenomas) should depend on their clonality (4). However, due to a recognized technical failure rate of about 10% and other discrepancies, the clonality approach is not always decisive (5), although a clear distinction between adenoma and hyperplastic nodule has been demonstrated in an animal model with another method (6).
With respect to their endocrinological function, histologically benign thyroid nodules can be subdivided into autonomously functioning thyroid nodules (AFTNs), cold thyroid nodules (CTNs), or less often as so-called warm nodules. Warm nodules do not show detectable differences by a (nonspect) scintigraphy compared with the surrounding thyroid tissue. This can be due to a dorsal cold nodule with ventral normal thyroid tissue. A further differentiation between hot and cold nodules within the entity of benign nodules appears important for appropriate phenotype correlations as the histologic distinction between adenomas and adenomatoid nodules is not related to thyroid function or specific entities defined by specific molecular defects. However, in studies examining TSH receptor (TSHR) exons 9 and 10, the prevalence of TSHR mutations in AFTNs has been reported to vary from 38 to 82%, and the prevalence of Gs
mutations varies from 8 to 75%, respectively (5, 7, 8, 9, 10, 11, 12, 13, 14, 15). The variable mutation frequencies can most likely be explained by different sensitivities of the mutation screening methods and the different qualities of the tissue samples studied (16).
To date no obvious relationship between the activating mutations in vitro activity and the patient’s phenotype could be shown (for review see Refs. 17, 18, 19). Likely reasons for this lack of correlation are additional genetic/epigenetic factors, environmental factors (e.g. the iodine supply), feedback and downstream secondary mechanisms (e.g. altered TSHR desensitization/internalization, cAMP degradation, TGFβ signaling), and the limited significance of the in vitro characterization by heterologous overexpression for the in vivo situation (17, 18, 19). Therefore, currently a TSHR or Gs mutation screening does not seem helpful with regard to diagnosis, prognosis, or the treatment of hot nodules.
In contrast to AFTNs, benign CTNs do not contain somatic TSHR and Gs mutations but a defective targeting of the sodium-iodide-symporter to the cell membrane, leading to a decreased iodide uptake (20, 21, 22). Therefore, a distinction between hot and cold nodules will more likely reflect different pathopysiologies than the histologic distinction between FTAs and adenomatoid nodules because the molecular pathophysiology of CTNs is very different from AFTNs and because CTNs and AFTNs exhibit marked differences in gene expression, which further explain these functional differences (20, 23, 24, 25, 26, 27, 28) in addition to different TSHR mutation profiles. An integrated view of the different current approaches for the classification of thyroid tumors is summarized in Fig. 1 (according to Ref. 29).
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FIG. 1. Today: The classification of thyroid nodules on the basis of results from clonality studies (reproduced from Ref. 29 ). Such studies imply that the majority of thyroid nodules are true thyroid tumors, compared with polyclonal hyperplastic nodules. Traditionally, only thyroid adenomas are considered true tumors, on the basis of an exclusive histologic definition: the presence of a capsule and a growth pattern that is different from the surrounding normal parenchyma in an otherwise normal thyroid gland. Strict histologic criteria are, however, difficult to obtain in the frequent presence of goiter or thyroiditis. According to the current WHO classification of thyroid tumors, the biological basis for separating hyperplastic thyroid nodules from true tumors should therefore also depend on their clonality (4 ). In the light of many thyroid nodules without a capsule (adenomatoid nodules) that are monoclonal, a mixed functional and molecular definition of true thyroid tumors appears more consistent.
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Limitations of the histologic classification
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The application of the current WHO classification in clinical routine is hampered by considerable interobserver variability that is most pronounced for follicular-patterned tumors (30, 31). The distinction between FTAs and follicular carcinomas (FTCs) is not trivial; the level of agreement among five pathologists’ initial diagnosis and the final consensus diagnosis has been reported as 37% in the mean, and even the interobserver agreement for defined criteria like capsular invasion and vascular invasion was very low (only 27 and 20%, respectively) (32). Moreover, the probability of missing a focus of capsular invasion is rather high, depending on how many sections are submitted for review. This can be illustrated by calculating the spherical surface of a nodule with a diameter of 2 cm, which is approximately 1250 mm2. Such a nodule is completely embedded within 12 orange-like segments, each approximately 3 mm thick, resulting in six complete circular sections for histological evaluation. Each circular section has 6.3 cm. So of this large area of 1250 mm2, we investigate six strips with a length of 63 mm and a thickness of 2 µm. Therefore, even though pathologists may perform serial sections, the basis for the diagnosis of such focal events like capsular or vascular invasion of the whole nodule definitely remains a very small spot check within the per thousand range.
It has been reported very early on that the distinction between FTA and FTC is directly related to the number of tissue blocks examined (33). Therefore, a thorough histological investigation of most of the nodule capsule is mandatory. Although some studies indicate that capsular invasion is of less importance than vascular invasion and although the degree and extent of invasion of follicular carcinomas have been shown to correlate with the patient’s prognosis (34), we definitely need better criteria for such an important differential diagnosis. This naturally does not apply for the widely invasive FTC cases and for undifferentiated carcinomas, which are relatively easy to classify by histology. However, some disagreement between pathologists has also been reported for papillary carcinomas (30, 31, 35). A similar problem arises for the classification of fine-needle aspiration biopsies (FNAB). Because morphology of FTAs and FTCs is very similar, it is impossible to make the differential diagnosis in FNAB smears. FNAB is currently the best method to select suspicious thyroid nodules for surgery. However, about 20% of the FNAB samples show follicular proliferation, which cannot distinguish between FTAs and FTCs (36). Although many immunohistological markers have been investigated in recent years to improve the differential diagnosis between benign or reactive changes and malignant thyroid tumors, little has entered daily routine work because many of the immunohistological markers show prominent overlap between cold FTAs and differentiated thyroid carcinomas (37).
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Molecular classification: limitations and improvements
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The discovery of the prominent mutations for about two thirds of papillary carcinomas (PTCs) and FTCs has generated new perspectives for the classification of thyroid tumors. However, it soon became apparent that the incidence of the different somatic mutations in FTCs and PTCs varied from study to study (38), which could, among other reasons, be related to the different sensitivities of the various methods used (39, 40). Very sensitive methods detect RET/PTC rearrangements, once thought to be specific for PTCs, in Hashimoto’s disease (41). Likewise, PAX8/PPAR
rearrangements thought to be specific for FTCs are definitely present in some FTAs (42, 43, 44, 45, 46). These results raise the following questions: 1) whether these mutations are not as specific as initially believed, 2) whether the histological diagnosis was not correct, or 3) whether the tissue used for the analysis was not histologically investigated before extraction. Alternatively, finding mutations typically associated with carcinomas in tumors diagnosed as benign also raises the issues of carcinoma in situ, specifically FTC in situ. This is a controversial topic, but molecular biology in general is providing some support for this idea. Unfortunately, this is a difficult subject to investigate because surgical removal of a noninvasive nodule impacts the natural history of a tumor. Thus, it is not possible to know whether a PAX8/PPAR-positive FTA is destined to become a bona fide invasive FTC but simply not given the opportunity.
The BRAF mutation T1799A has been reported in 29–69% of PTCs (38). Due to its high prevalence and its specificity to PTCs and PTC-derived anaplastic carcinomas (47), the BRAF mutation has become a target of intensive investigations (for review see Ref. 48). There are controversial results regarding to the association of the BRAF mutation with clinicopathological characteristics of PTC. Most of these studies demonstrate a significant association of the BRAF mutation with extrathyroidal invasion, lymph node metastasis, and advanced disease stage [pro: Refs. 48, 49, 50, 51, 52, 53, 54, 55, 56 , whereas others do not (58, 59, 60, 61, 62)]. Moreover, the BRAF mutation occurs most commonly in PTC subtypes that are known to be more aggressive (53). In support for this finding, a correlation of the BRAF mutation with a lower expression of both the sodium-iodide symporter and the thyroperoxidase has been shown, suggesting an early dedifferentiation, which might be the basis for a poor prognosis (63). Based on these associations, the BRAF mutation currently represents a promising potential prognostic and predictive molecular marker for PTC, which may guide the medical management of PTC both before surgery and during the follow-up of the patients. The accuracy of BRAF detection for PTC is high in FNAB samples (47, 48). A preoperative test on FNAB samples of cytologically diagnosed PTC patients might be promising for prognosis (48) and has been investigated in FNAB samples in several studies (64, 65, 66, 67, 68, 69, 70). Moreover, the BRAF mutation may represent a novel therapeutic target for the treatment of PTCs. However, the most frequent FNAB problem is the indeterminate follicular neoplasm, which comprises and is unable to distinguish FTAs and FTCs and much less frequently the follicular variant of PTCs. For these indeterminate follicular tumors, the diagnostic potential of BRAF mutation detection is low. Likewise, the diagnostic potential of RAS mutations is low because RAS mutations were detected in both malignant and benign tumors (45, 71, 72, 73, 74). Moreover, the finding that there is no overlap of RAS mutations and PAX8/PPAR rearrangements in conventional FTCs suggests that these entities consists of at least two subgroups of tumors developing through distinct molecular mechanisms (45).
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Improvements due to gene expression signatures
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It is very promising that recent DNA microarray gene expression studies of breast (75, 76), lung (77), and other cancers were able to define gene expression signatures, which can clearly distinguish low- and high-risk cohorts. Unfortunately, this kind of prognostic gene expression profile analysis has to date not been reported for thyroid tumors, largely due to the need for very long follow-up for thyroid cancer in general. However, there are several microarray/serial analysis of gene expression/PCR-based studies comparing the gene expression profiles of FTAs and FTCs (46, 78, 79, 80, 81, 82, 83, 84, 85, 86). In an early investigation, Barden et al. (78) found 105 differentially expressed genes between both entities, and Finley et al. (84) suggested gene expression profiling to distinguish benign and malignant thyroid tumors. Moreover, although limited by too small sample sizes, three DNA microarray studies (87, 88, 89) were able to show significant differences between FTCs with and without PAX8/PPAR rearrangements (89). These studies thus indicate broad functional consequences of these known somatic mutations and stress their possible discriminatory value. However, one of these studies also showed a clear overlap between PAX8/PPAR-negative FTCs and FTAs, indicating that PAX8/PPAR-negative FTCs might be closer related to FTAs than PAX8/PPAR-positive FTCs (87). This may among other possibilities also be a reflection of their partly shared RAS mutational status.
Unfortunately, several studies show that none of the numerous genes identified by microarray analysis as potential carcinoma marker functioned as single gene predictors (90, 91, 92, 93, 94). Currently an alternative approach that aims at identifying the minimal number of discriminating genes appears more promising for diagnostic purposes (23, 46, 81, 83, 86, 95, 96, 97, 98). Mazzanti et al. (83) compared the gene expression patterns of PTCs, follicular variant of PTCs, FTAs, and hyperplastic nodules and identified two classifiers comprising six and 10 genes, respectively, which allowed a correct classification with regard to malignancy in all samples of the test set (83). In a further study, a 20-gene classifier was established, which allowed a reliable classification of PTC gene expression data derived from different microarray generations and also correctly classified data sets of AFTNs and CTNs as non-PTCs (23, 96). Using a linear discriminant analysis, which finds the best combination of genes to discriminate different entities, Weber et al. (86) identified a combination of three genes (CCND2, PCSK2, and PLAB) that allowed accurate differentiation between benign and malignant follicular neoplasia with a high sensitivity and specificity. Foukakis et al. (81) established two classifiers to predict high- vs. low-risk in the first model and the presence or not of malignancy in the second model in a set of well subclassified follicular tumors (FTAs and atypical follicular adenomas, with a benign histopathology at diagnosis and no recurrent disease; minimally invasive FTCs without metastasis at diagnosis and during follow-up; widely invasive FTCs and minimally invasive FTCs with metastatic disease) by a PCR-based approach. The first classifier differentiating between high- and low risk comprised five genes (TERT, TFF3, PPARG, CITED1, and EGR2) that highly significantly and highly specifically predict the aggressiveness of FTCs (81). Although only two genes (TERT and TFF3) were used in the second classifier, malignancy was predicted with a high specificity (81).
Although very promising classifiers have been described in microarray/serial analysis of gene expression/PCR-based studies differentiating benign and malignant tumors, there are several aspects that currently limit the diagnostic application of the proposed markers: 1) all these studies were performed on thyroid tissue samples but not on FNAB samples, 2) often the total number of investigated tumors is rather small, 3) the gene expression profiles of only two or a subset of tumors were compared, 4) different authors used different sample annotations (e.g. FTAs vs. AFTNs/CTNs; for review see Ref. 80), and 5) a diagnostic application of microarray technology on FNAB samples is currently not feasible. One possibility to solve some of these problems is to combine the expression profiles from several studies and to perform a metaanalysis or a metareview (99) of the data, which would strengthen the power of proposed markers. Moreover, all these proposed markers have to be reinvestigated in further samples and especially in FNAB samples by alternative methodologies, e.g. real-time RT-PCR and/or immunocytochemistry to show their applicability to FNAB diagnosis.
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micro-RNA (miRNA) signatures
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Based on a few initial studies, miRNA profiling is diagnostically promising. Two large profiling studies using various tumors and distinct technologies to investigate genome wide miRNA expression show a high diversity of the miRNA expression patterns in different carcinomas (100, 101). Lu et al. found that the expression level of most miRNAs was different between multiple human cancers and normal tissues (100). Poorly differentiated tumors could be successfully classified by miRNA expression profiles, whereas mRNA profiles were highly inaccurate when applied to the same samples (100). Volinia et al. also found a large number of common miRNAs whose expression consistently distinguished various cancers from normal tissues (101). Because the extraordinary level of diversity is encoded in a relatively small number of miRNAs, the miRNAs are characterized by a high amount of diagnostic information. Moreover, an association between a unique miRNA signature and prognostic factors and disease progression has been shown (102). Because miRNAs, in contrast to mRNAs, remain largely intact in routinely collected, formalin-fixed, paraffin-embedded (FFPE) clinical tissues (103), miRNA profiling has an important diagnostic potential.
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Diagnostic potential of miRNAs
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Investigations of the miRNA expression patterns of FTCs and PTCs, compared with benign thyroid tissues, identified several differentially expressed miRNAs (104, 105, 106). Comparison of miRNA expression profiles of 12 FTCs and eight FTAs by microarray methodology revealed a significantly increased expression of four miRNAs (miR-192, -197, -328, and -346) in the FTCs. In vitro experiments showed that overexpression of miR-197 and -346 induces proliferation, whereas their inhibition led to growth arrest (105). Investigation of 235 human miRNAs in 15 PTCs in comparison with their corresponding normal surrounding tissues revealed a differential expression pattern of 23 miRNAs (106). Furthermore, results from a prediction analysis indicated that only five overexpressed miRNAs were sufficient to successfully predict cancer. The fact that no classification errors were made in this analysis underlines the potential diagnostic relevance of miRNA profiling (106). This conclusion is further supported by a study of Pallante et al. (104) that showed strong differences in the expression patterns of miR-221, -222, and -181b between FNABs of PTCs and benign thyroid nodules (5- to 35-fold differences). These results provide support for these miRNAs as diagnostic aids. Moreover, unlike mRNAs, miRNAs remain largely intact in routinely collected FFPE tissues (103), thus presenting the opportunity to perform the large retrospective analyses necessary to confirm the diagnostic role and investigate the prognostic significance of miRNA profiles (102).
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Diagnostic potential of proteomic signatures
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Whereas numerous transcriptome studies have been performed to identify potential biomarkers differentiating benign and malignant thyroid tumors, the application of proteomic approaches is still developing. However, these studies have a high potential because it has been shown that differential mRNA expression captures only 40% of variation in protein expression, reflecting various levels of posttranscriptional, translational, and posttranslational regulation (107). In an initial pilot study using surface-enhanced laser desorption/ionization (SELDI)-time of flight-mass spectrometry, Suriano et al. (108) examined the potential of proteomic profiling of PTCs in comparison with normal adjacent tissues. Using difference gel electrophoresis and subsequent matrix-assisted laser desorption ionization-time of flight-mass spectrometry analysis, Brown et al. (109) confirmed several known biomarkers of PTCs (cathepsin B, cytokeratin 19, and galectin-3) and identified three novel biomarkers [S100A6, peroxiredoxin 2, and HSP 70 (immunoglobin heavy-chain binding protein)]. Moreover, they identified two distinct forms of cathepsin B, one form with a 5-fold lower expression in PTC and a more acidic form with a 2- to 4-fold higher expression in PTC, indicating a high relevance of posttranslational modifications in PTCs (109).
Obviously, these observations cannot be obtained using a transcriptome approach. In a further study comparing the protein abundance of five FTCs and six FTAs, 102 protein spots showed a significantly different abundance (110). Whereas proteins involved in the maturation of thyroglobulin by assisting glycosylation and folding of thyroglobulin monomers (e.g. protein disulfide isomerase A3, heat shock protein 90) and proteins involved in the synthesis of glycoproteins (e.g. calreticulin and thyroperoxidase) are expressed at lower levels in FTCs in comparison with FTAs (110), the proteomic profiling of cold thyroid nodules by Krause et al. (111) revealed a higher abundance of these proteins in cold nodules, compared with their normal surrounding tissue. This most likely counteracts intranodular iodide deficiency due to defective membrane targeting of the sodium-iodide symporter. Therefore, the lower levels of these proteins in FTCs vs. FTAs reflect the lack of differentiation of the malignant FTC (110), whereas their higher abundance in CTNs compared with their surroundings, most likely characterizes compensatory mechanisms of a benign lesion with loss of iodine uptake (111). However, because the current data are mostly limited by small sample numbers a diagnostic application of the identified proteins requires a careful verification in larger sample sets and also by alternative methods. Nevertheless, these studies revealed several new pathophysiologic aspects of benign and malignant thyroid tumors.
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The need for future integrated molecular and histologic tumor classifications
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Because the primary goal of tumor classifications is the distinction of tumor types associated with different pathobiologies, prognoses, and therapeutic strategies, every molecular or morphological classification needs to be validated on several levels (Table 2), including survival. Refinement of the existing classification may lead to the definition of new tumor types but also to the potential elimination of some of the various morphological variants listed in Fig. 1
. Of course, intratumoral heterogeneity needs to be taken into account because most tumors are morphologically and biologically heterogeneous (112, 113). Finally, the microarray analyses should primarily use nonsupervised approaches, and these assays as well as the somatic mutational analyses should be examined for their reproducibility within and between different laboratories. Moreover, the molecular classification methods should also demonstrate their ability to further define histologic borderline cases or tumors of uncertain malignancy, if possible. A first investigation of this topic was recently published for thyroid tumors (79).
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Conclusions
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It is very likely that the first aspects of molecular definitions of thyroid tumors already mentioned in the current WHO classification will be further developed and that molecular characteristics will be instrumental for future progress in defining thyroid tumor types by an integrated histologic and molecular approach (Fig. 2). First reports on the determination of somatic mutations in FNAB samples (68, 114), the discriminatory power of miRNA signatures, combined with the fact that miRNAs are very stable in FFPE tissues, are promising. Moreover, the generation of first- and second-generation tyrosine kinase inhibitors for cancer treatment (115) has demonstrated how the study of specific mutations in various receptors can lead to the development of molecular targeted drugs and their further tailoring if the tumors develop resistance to them. Already there are a number of different new molecular targeted drugs in clinical trials for thyroid cancer (57, 116). The stratification of patients eligible for these new molecularly targeted drugs will increasingly depend on the molecular characterization of the tumors.
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FIG. 2. Tomorrow: Additional molecular approaches complementing the current classification of thyroid tumors.
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Footnotes
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Disclosure Information: All authors have nothing to declare.
First Published Online July 1, 2008
Abbreviations: AFTN, Autonomously functioning thyroid nodule; CTN, cold thyroid nodule; FFPE, formalin fixed, paraffin embedded; FNAB, fine-needle aspiration biopsy; FTA, follicular adenoma; FTC, follicular carcinoma; miRNA, micro-RNA; PTC, papillary carcinoma; TSHR, TSH receptor; WHO, World Health Organization.
Received January 25, 2008.
Accepted June 19, 2008.
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Abstract
Introduction
