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Cancer Research 68, 1572, March 1, 2008. doi: 10.1158/0008-5472.CAN-07-5020
© 2008 American Association for Cancer Research
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Endocrinology

Discovery and Validation of Protein Abundance Differences between Follicular Thyroid Neoplasms

Romana T. Netea-Maier1, Stephen W. Hunsucker3,6, Brigiet M. Hoevenaars2, Steve M. Helmke4, Pieter J. Slootweg2, Ad R. Hermus1, Bryan R. Haugen4,5,6 and Mark W. Duncan3,4,6

Departments of 1 Endocrinology and 2 Pathology, Radboud University Nijmegen Medical Centre, Nijmegen, the Netherlands and 3 Section of Pulmonary Medicine, Department of Pediatrics, 4 Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, 5 Department of Pathology, and 6 University of Colorado Cancer Center, School of Medicine at the University of Colorado at Denver and Health Sciences Center, Aurora, Colorado

Requests for reprints: Bryan R. Haugen, Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, University of Colorado Cancer Center, University of Colorado at Denver and Health Sciences Center, MS 8106, P. O. Box 6511, Aurora, CO 80045. Phone: 303-724-3921; Fax: 303-724-3920. E-mail: bryan.haugen{at}uchsc.edu.


   Abstract
Top
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 References
 
Distinguishing between benign follicular thyroid adenoma (FTA) and malignant follicular thyroid carcinoma (FTC) by cytologic features alone is not possible. Molecular markers may aid distinguishing FTA from FTC in patients with indeterminate cytology. The aim of this study is to define protein abundance differences between FTC from FTA through a discovery (proteomics) and validation (immunohistochemistry) approach. Difference gel electrophoresis (DIGE) and peptide mass fingerprinting were performed on protein extracts from five patients with FTC and compared with six patients with FTA. Individual gel comparisons (i.e., each FTC extract versus FTA pool) were also performed for the five FTC patients. Immunohistochemical validation studies were performed on three of the identified proteins. Based on DIGE images, 680 protein spots were matched on individual gels. Of these, 102 spots showed statistically significant differences in abundance between FTC and FTA in the individual gel analyses and were therefore studied further. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry was used to identify 54 of these protein spots. Three candidates involved in protein folding (heat shock protein gp96, protein disulfide isomerase A3, and calreticulin) were studied by immunohistochemistry. Moderate calreticulin immunohistochemical staining was the best single marker with a high negative predictive value (88%); combining all three markers (any marker less than moderate staining) had the best positive predictive value (75%) while still retaining a good negative predictive value (68%). With DIGE, we identified 54 proteins differentially abundant between FTC and FTA. Three of these were validated by immunohistochemistry. These findings provide further insights into the diagnosis, prognosis, and pathophysiology of follicular-derived thyroid neoplasms. [Cancer Res 2008;68(5):1572–80]


   Introduction
Top
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 References
 
Thyroid cancer is the most common endocrine malignancy and its most frequent clinical presentation is as a thyroid nodule, either solitary or within a multinodular goiter. Approximately 5% to 10% of adults have palpable thyroid nodules and 30% to 50% have nodules identified by ultrasound. Although the majority of these are benign, approximately 5% to 7% of thyroid nodules are malignant (1). Fine-needle aspiration biopsy (FNAB) is the most important diagnostic test in the initial evaluation of a patient with a thyroid nodule and offers a diagnostic accuracy of between 70% and 97% in experienced centers (2). Typically, ~70% of FNAB are classified as benign, 4% are classified as malignant [predominantly papillary thyroid carcinomas (PTC)], 2% to 10% supply insufficient sample, and the remainder are classified as either indeterminate or suspicious (5–23%; refs. 1, 2). Typically, patients returning either indeterminate or suspicious results undergo diagnostic hemithyroidectomy or complete thyroidectomy to exclude malignancy.

It is particularly challenging to distinguish between thyroid neoplasms of the follicular type [i.e., benign follicular thyroid adenoma (FTA), malignant follicular thyroid carcinoma (FTC), and follicular variant of papillary carcinoma] based on cytologic examination alone. All these tumors have similar cytologic features and surgery is usually required to obtain a definitive tissue sample. However, because only 5% to 7% of the clinically identified nodules prove to be malignant, the indeterminate findings subject most patients to unnecessary surgery, potential risks, and, occasionally, irreversible complications. Improving the diagnostic accuracy of FNAB is therefore of crucial clinical importance.

Differentiated epithelial thyroid tumors represent a spectrum of morphologically and biologically diverse neoplasms and the molecular etiology and pathogenesis of thyroid carcinoma, especially of the follicular type, is unknown (3, 4). Thyroid cancer is believed to result from the accumulation of oncogene mutations or rearrangements (RAS, BRAF, RET, NTRK1, and MET) and silencing of tumor suppressor genes (p53, RASSF1A, PTEN, PPAR{gamma}, and CDK inhibitors; ref. 3). Recent data suggest that the so-called atypical FTA, which is characterized by high cellular density, mitoses, and a less regular cytologic pattern, may share genetic features with both FTC and PTC (5), but the progression of thyroid adenoma to carcinoma has not been clearly shown. Therefore, defining the differences in protein levels that distinguish between FTA and FTC will provide additional insight in the earliest steps of follicular neoplasia transformation and might also deliver a clinical tool that could improve the diagnostic accuracy of FNAB in patients with indeterminate cytology.

The aim of the present study was to define protein abundance differences between FTA and FTC tissue. We sought changes at the protein level for several reasons. First, many cellular processes are regulated posttranscriptionally and mRNA studies are incapable of determining some differences that may affect tumor biology. Consequently, proteomics is seen as an essential tool to enhance our understanding of disease processes (6). Second, peptides and proteins can be measured by well-established methods with high sensitivity, precision, and accuracy. Any changes we observe have the potential to form the basis of a sensitive and specific protein-based diagnostic test for follicular-derived thyroid neoplasms.

Our studies used difference gel electrophoresis (DIGE) in combination with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). The DIGE component of this study allows the precise quantitative comparison of thousands of distinct proteins; MALDI-TOF MS provides identity of the proteins after they are excised from the gel (7). A similar approach has been adopted by us and others in studies that aim to identify biomarkers (8, 9).


   Materials and Methods
Top
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 References
 
Tissue samples for DIGE analysis. Snap-frozen tumor tissue samples from 11 patients undergoing surgery for follicular neoplasms were obtained through the Cooperative Human Tissue Network. At final histopathologic diagnosis, five were identified as FTC (three women, ages 31–75 years, tumor sizes of 3.5–8 cm) and six were FTA (all women, ages 29–58 years, tumor sizes of 1.3–5.5 cm). In all FTC patients, tumor capsular invasion was present, and in two of these, the capsular invasion was extensive. In three FTC patients, vascular invasion was present, and in one of these, the vascular invasion was extensive.

Preparation of tissue protein extracts. Protein was extracted from each fresh-frozen tissue sample (50 mg) as previously described (8). Proteins were precipitated with methanol/chloroform (10), dried in a SpeedVac, and then rehydrated overnight in 400 µL of reaction buffer [7 mol/L urea, 2 mol/L thiourea, 4% (w/v) CHAPS]. Each sample was then supplemented with 10 mmol/L DTT (20 µL of 200 mmol/L DTT in reaction buffer), homogenized with a small pellet pestle (Kimble Kontes), and incubated for 2 h. Samples were thoroughly mixed and centrifuged (16,000 x g, 15 min, room temperature), and the solubilized protein supernatants were collected. An aliquot was diluted 50-fold with water immediately before protein assay by the method of Bradford (11). Based on these findings, each sample was diluted to 5 mg/mL protein with reaction buffer containing 10 mmol/L DTT. Samples were flash frozen with liquid N2 and stored at –80°C until analysis.

DIGE experiment. Each analytic DIGE gel was composed of the following: 50 µg of total protein isolated from an individual FTC sample (e.g., labeled with Cy5), 50 µg of total protein from a pool prepared from all FTA samples (e.g., labeled with Cy3), and 50 µg of total protein from a pooled internal standard. The FTA pool was created by combining equal amounts of total protein isolated from individual FTA tissue samples. We had a limited number of well-defined (histopathologically) snap-frozen FTA samples with some yielding limited amounts of total protein. We therefore decided to pool protein from these tissues and compare the pool against individual FTC samples (a more heterogeneous group) rather than omit one FTA sample and randomly compare one FTA sample with one FTC sample. The internal standard, composed of an equal amount of total protein isolated from all tissue samples (five FTC plus six FTA), was always labeled with Cy2 and included on every gel to improve quantitative precision and enhance spot matching (12). The labeling of FTC and FTA samples was reversed on alternate gels to minimize any dye bias.

Differentially abundant proteins were identified from preparative gels containing 50 µg of the pooled internal standard labeled with Cy2 and 950 µg of unlabeled pooled internal standard. The inclusion of the Cy2-labeled proteins is necessary to facilitate spot matching between analytic and preparative gels. Labeled and unlabeled proteins can have slightly different migration behavior resulting from dye conjugation, and therefore, gels were also poststained with Deep Purple (GE Healthcare) to visualize the corresponding unlabeled protein spots (see Supplementary Fig. S1). This method ensures that the unlabeled and labeled proteins are correctly matched and the desired protein spot is picked.

Labeling reactions were carried out as previously described (7, 8). After labeling, the samples were combined (e.g., one sample labeled with Cy5, one sample labeled with Cy3, and the internal standard labeled with Cy2) and the mixture was taken to a final volume of 450 µL with reaction buffer, hydroxyethyl disulfide (0.1 mol/L, 5.4 µL, Destreak, GE Healthcare), 1% broad range Pharmalytes 3-10 NL (GE Healthcare), and bromphenol blue (0.003%).

After resuspension in the rehydration buffer, protein samples were passively rehydrated into 24-cm immobilized pH gradient strips (IPG 3-10 NL, GE Healthcare) for 24 h and then focused (IPGphor System, GE Healthcare) for 66,000 Vh (analytic gels) or 133,000 Vh (preparative gels). Cysteine side chains were reduced and alkylated by incubating the focused strips (10 min, room temperature) in equilibration solution [6 mol/L urea, 100 mmol/L Tris (pH 8.8), 30% glycerol, 2% SDS, 0.25% saturated aqueous bromphenol blue] containing 0.5% DTT followed by incubation in equilibration solution with 4.5% iodoacetamide (10 min, room temperature).

Gel electrophoresis was performed on precast 8% to 16% acrylamide gradient gels (Jule, Inc.) as previously described (8). Voltage and current were continuously monitored throughout all runs for quality control.

Gels were scanned on a Typhoon 9400 Variable Mode Laser Imager (GE Healthcare) at 100 µm resolution. Laser and filter settings for each of the dyes were as follows: Cy3 (excitation, 532 nm; emission, 580 nm; bandpass, 30 nm), Cy5 (excitation, 633 nm; emission, 670 nm; bandpass, 30 nm), Cy2 (excitation, 468 nm; emission, 520 nm; bandpass, 40 nm), and Deep Purple (excitation, 532 nm; emission, 610 nm; bandpass, 30 nm).

DeCyder software (version 5.0; GE Healthcare) was used for spot detection and relative quantification of protein spots on the fluorescence images. For each gel image, the DeCyder Differential In-gel Analysis software module was initially adjusted to detect an estimated number of 2,500 spots. Individual spots at the extreme edges of the gel, extremely low intensity spots, and dust particles (i.e., those spots with a high slope) were excluded. Volumes were measured for each protein spot in the three fluorescent channels (i.e., Cy3, Cy5, and Cy2). Individual DIGE gels were matched using the Biological Variation Analysis (BVA) software module (GE Healthcare). Spots matched on at least four of the five individual gels were subjected to statistical analysis in BVA. Spot volumes of the Cy2 internal standard were used to calculate standardized volume ratios for the Cy5- and Cy3-labeled FTC and FTA protein spots. A Student's t test was used to compare the differences in protein spot volumes between the FTC and the pooled FTA samples in the individual gel analysis. Statistical significance was defined as P < 0.05 (two sided).

Spots that showed a statistically significant difference in abundance between FTC and FTA were used to generate a list of candidate spots for identification. These spots were matched on the preparative gel, excised, and subjected to in-gel enzymatic digestion and identification by MALDI-TOF MS. Additional protein spots were also processed to serve as internal molecular weight (MW) and isoelectric point (pI) markers. The positions of these markers were used to generate calibration curves for protein MW (cubic spline) and pI (log linear) and to determine the observed pI and MW for each protein spot. The measured MW and pI reported in Table 1 have an approximate error of ±20% of the predicted values and deviations larger than this are likely the result of posttranslational modification. Predicted protein MW and pI were derived from the Swiss-Prot database7 using the mature protein form (chain) when available.


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  		Table 1. Proteins differentially abundant in FTC versus FTA tissue samples as determined by DIGE

 

Figure 1
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  		Figure 1. Representative two-dimensional gel image of the Cy2-labeled proteins that comprise the internal standard. The grey outlines give the position of identified protein spots that had statistically different abundance (P < 0.05) between FTC and FTA. A, protein spots underabundant in FTC. B, protein spots overabundant in FTC. The spot numbers correspond to the spot numbers listed in Table 1.

 
Protein identification by mass spectrometry. Protein spot excision and in-gel enzymatic digestion were performed automatically by the Ettan Spot Picker and Ettan Spot Digester (GE Healthcare) as previously described (8). All digests were analyzed by MALDI-TOF MS (Voyager DE-PRO, Applied Biosystems), again as described previously (13). Spectra were collected over the range m/z 500 to 5,000. Peptide mass fingerprints were internally calibrated to monoisotopic trypsin peaks (i.e., m/z 515.33, 842.51, 1,045.56, and 2,211.10). Spectra were processed using ProTS Data (Efeckta Technologies) to generate a peak list that was then submitted to Mascot (Matrix Science Ltd.) for database searching. Spectral preprocessing included defining the baseline, noise, and signal-to-noise ratio as well as monoisotopic peak selection. A signal-to-noise ratio in ProTS Data of >4 was required for inclusion in the peak list. Database searches were conducted using the mammalian subset of the nonredundant protein database (National Center for Biotechnology Information, database release 05/07/2006 with 446,224 mammalian sequences) and the Swiss-Prot database (release 49.6 with 193,477 mammalian sequences). Other settings in ProTS included the following: peak amplitude, 100; peak width, 250; and chemical noise factor, 1.5. Settings in Mascot were as follows: peptide mass tolerance of ±100 ppm, fixed modification of carbamidomethylation of cysteine side chains, and trypsin selected as the enzyme with one missed cleavage accepted. Searches were not constrained by pI or MW. Minimum requirements for positive protein identification were described previously (13) and peptide and protein assignments were made according to recently published guidelines (14).

Immunohistochemistry. In accordance to the requirements of the local Medical Ethical Committee, all specimens used in this phase of the work were stripped of linked patient identifiers.

We retrospectively selected archival tissue blocks from 16 patients with FTC (5 widely invasive) and 18 patients with FTA who underwent thyroid surgery at the Radboud University Nijmegen Medical Centre (Nijmegen, the Netherlands). Of the patients with FTC, preoperative FNAB was inconclusive in 10 patients (follicular cell proliferation) and suspect for carcinoma in 4 patients. In the remaining 2 patients, the FTC was found incidentally after the patients had their goiter removed because of mechanical complaints. Four-micrometer-thick sections of the paraffin-embedded tissue samples were deparaffinized in xylene and rehydrated. Antigen retrieval was performed in 20 mmol/L citrate buffer (pH 6.0) following heating in a household microwave oven (10 min at 95°C followed by cooling down to room temperature) and brief washing in PBS. Endogenous peroxidase blocking was performed in the PT Module (Lab Vision) using H2O2 in methanol for 10 min and rinsing the slides thrice in PBS (pH 7.4). Immunohistochemistry was performed on an Autostainer (Lab Vision). Following incubation with the primary antibody [protein disulfide isomerase A3 (PDI A3) monoclonal antibody (clone RL 77), Abcam; calreticulin monoclonal antibody (clone FMC 75), Abcam; heat shock protein (HSP) gp96 polyclonal antibody (clone ZMD 287), Zymed Laboratories, Invitrogen Immunodetection] for 60 min at a dilution of 1:1600 (PDI A3), 1:400 (calreticulin), and 1:200 (anti–HSP gp96), slides were reacted with an immunoperoxidase detection system (poly-HRP-ant Ms/Rb/Ra IgG, Immunologic). The slides were then rinsed in PBS (pH 7.4) thrice and localization of the staining was performed for 5 min with 3,3'-diaminobenzidine tetrahydrochloride (DAB+, Power DAB, Immunologic). After rinsing in PBS, the slides were finally counterstained with Mayer's hematoxylin, dehydrated in ethanol and xylene, and coverslipped using a nonaqueous mounting medium. Cytoplasmatic and nuclear staining was considered as a positive reaction and intensity of staining was measured. A pathologist (B.M. Hoevenaars) was blinded to the histologic diagnosis and reported the results in a semiquantitative fashion: that is, no staining (0), faint (+1), low (+2), moderate (+3), and intense (+4) staining.


   Results
Top
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 References
 
DIGE image analysis and protein identification. More than 1,500 protein spots were detected on each analytic DIGE gel and a total of 680 of these were matched on four of five individual gels and the pooled sample gel. Fifty-four of the protein spots that showed statistically significant (P < 0.05) abundance differences between individual FTC samples and the FTA pool were identified (Fig. 1 ). Eleven proteins were excluded from further analysis: that is, albumin, β-globin, thyroglobulin (four distinct spots), and five spots that were identified as a mixture of several proteins. This left 43 protein spots for further consideration (Table 1). Of these, 27 spots, corresponding to 23 distinct protein entities, were less abundant (average fold changes, 1.28–4.63) in FTC versus FTA; 16 spots, corresponding to 14 distinct proteins entities, were more abundant (average fold changes, 1.20–2.62) in FTC versus FTA. Figure 2 shows that most of the more abundant proteins in the FTC tumors are involved in cytoskeletal structure and cell organization, whereas nearly half of the proteins underabundant in FTC function in protein synthesis and folding. For some of the proteins (e.g., HSP gp96, PDI A3, cytokeratin 8, and β-actin), several distinct isoforms were shown to change in the same direction. In three cases (cytokeratin 8, β-actin, and histone H2B), some isoforms showed a lower abundance in the FTC sample, whereas other isoforms showed a higher abundance in the FTC compared with the FTA samples (Table 1).


Figure 2
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  		Figure 2. Distribution of the identified proteins [underabundant (A) and overabundant (B) in FTC versus FTA] according to their cellular function.

 
Immunohistochemistry. Immunohistochemical validation studies were performed on independent paraffin-embedded tissue samples from patients with benign and malignant follicular thyroid tumors using antibodies against three of the identified proteins: HSP gp96, calreticulin, and PDI A3. We chose to study these proteins based on their abundance, large volume ratio difference, absence of prior studies reporting their association with follicular thyroid neoplasia, and the availability of commercial antibodies. Figure 3 shows the immunostaining of HSP gp96, calreticulin, and PDI A3 on 18 FTA and 16 FTC tissue samples. The staining intensity scores for the individual samples are presented in Table 2 .


Figure 3
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  		Figure 3. Immunohistochemical analysis showing lower intensity staining for PDI A3 (PDI), calreticulin, and HSP gp96 in FTC versus FTA in the paraffin-embedded tissue samples. Magnification, x40.

 

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  		Table 2. Results of HSP gp96, PDI A3, and calreticulin staining in 16 patients with FTC and 18 patients with FTA

 
All three putative markers were underabundant in FTC based on DIGE analysis. An optimal marker (or combination of markers) should identify most or all malignancies (high sensitivity/negative predictive value), especially all widely invasive carcinomas, while minimizing the number of "benign" follicular adenomas subjected to surgery (high specificity/positive predictive value). Sensitivity analysis for these markers is shown in Table 3 . Calreticulin (staining ≤3+) was the best single marker with a high negative predictive value, whereas combining the three markers (any marker ≤2+) had the best positive predictive value while still retaining a fairly high negative predictive value.


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  		Table 3. Sensitivity analysis of immunohistochemical staining

 

   Discussion
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 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
References
 
We have used discovery (proteomics) and validation (immunohistochemistry) tools to identify and confirm novel molecular markers that distinguish between FTA and FTC tissue. These protein identifications provide insight into the pathogenesis of follicular thyroid neoplasia and a subset of these biomarkers may serve as sensitive and specific markers that differentiate between benign and malignant form of follicular-derived thyroid neoplasia. We specifically selected an analytic strategy measuring intact proteins (two-dimensional gels) because this allowed us to detect and quantify changes in specific isoforms.

Genomic research has shown several genetic alterations associated with follicular neoplasia (4, 15–17), but these alterations have only been documented in a small subset of tumors. Further, the utility of these findings is limited because the level of mRNA expression frequently does not reflect the amount of protein in the cell, in part because gene sequences cannot predict posttranslational modifications nor reflect dynamic cellular processes. Clearly, thyroid tumorigenesis is a complex process and the additional quantitative and qualitative information intrinsic to the proteomic data is critical to understanding this complex pathophysiologic process.

Although used extensively in other forms of malignancy, the proteomic approach has had limited application in studies of thyroid cancer. Berger et al. (18) performed a quantitative proteomic analysis in benign thyroid nodular disease and identified several proteins showing abundance differences between benign nodular tissue and matched normal thyroid tissue from the same patients. Krause et al. (19) applied two-dimensional GE and MS to study the protein abundance differences between cold thyroid nodules and normal thyroid tissue and found up-regulation of proteins involved in thyroglobulin folding and thyroid hormone synthesis as well as up-regulation of proteins that reflect increased oxidative stress in the cold thyroid nodule tissue. Our studies have shown that proteins involved in protein synthesis and folding represent a large group of underabundant proteins in FTC compared with FTA. Using two-dimensional DIGE and peptide mass fingerprinting by MALDI-TOF MS, we have previously investigated quantitative and qualitative differences in protein abundance between human PTC and matched normal thyroid tissue (8). This approach uncovered novel potential biomarkers and confirmed several known biomarkers for PTC, illustrating the advantages offered by this approach.

In the present report, we have identified a subset of 43 protein spots (corresponding to 37 distinct proteins) that show statistically significant differences in abundance between FTC and FTA tissue. Several of these proteins have previously been described in relation to thyroid or other cancers. Among the proteins underrepresented in FTC tissue are proteins involved in protein folding (e.g., HSP gp96, PDI A3, calreticulin, HSP40, HSP90β, and BiP); proteins involved in nuclear stability, chromatin structure, and gene expression (lamin A/C); and thyroglobin. Of the proteins overabundant in FTC, some are involved in cell stabilization against mechanical stress (e.g., cytokeratins 7, 8, and 18 and tubulin), whereas others are linked to tumor invasiveness and metastatic potential in other malignancies, and kinase signaling (e.g., nucleoside diphosphate kinase 1 isoform b). Our results also confirm the presence of other proteins previously associated with follicular-derived thyroid neoplasia, including nucleoside diphosphate kinase 1 (also known as nm23-H1), the nm23 metastatic suppressor gene product. Published mRNA and immunohistochemical studies suggest that the level of expression of nm23-H1 might be useful as a prognostic marker, especially for FTC and, less so, for PTC (20–22). Notably, because the present study compared two types of follicular neoplasia, we did not find galectin 3 nor cytokeratin 19, both known markers for PTC. We have also identified nine proteins that are novel to the thyroid neoplasm literature.

One major advantage of the DIGE approach we used is the capability to run several different samples on a single gel. This leads to a dramatic improvement in quantitative precision and increases the likelihood of obtaining statistically meaningful results, even when the fold change is small. However, a limitation of our discovery study is the small sample size. When measuring many hundreds, even thousands of variables simultaneously, especially in a small population, there will be differences arising by chance alone and unrelated to any biochemical dissimilarity between the groups under investigation. There are statistical approaches to account for chance events, but these indiscriminate correction factors result in the loss of potentially important findings. Therefore, it is important to acknowledge that in this instance the sample size is too small to fully define the groups and some of the observed differences will likely be artifacts of the study design. The situation is exacerbated by the heterogeneity of the follicular neoplasms (particularly the FTC). We selected the FTA samples based on histology and exercised extreme caution to ensure that these were indeed FTA and not minimally invasive FTC. Therefore, we had limited snap-frozen FTA samples. We feel that pooling the FTA samples was justified as we were able to incorporate an additional sample and this group is more homogeneous than the FTC group (minimally invasive, widely invasive, and vascular invasion). We acknowledge that this is not an optimal study design but feel the only other practical alternative (i.e., randomly omit one of the FTA sample and randomly pair individual FTA and FTC samples) was also not without limitations.

Given the limitations of the study design, the data on proteins that were not further validated must be interpreted with caution and any potential marker found in this initial discovery phase must be verified in a larger, more comprehensive study. In the present study, we took this additional step and validated three of the identified proteins by immunohistochemistry in an independent subset of paraffin-embedded tissue samples, showing that our DIGE approach was robust for these three identified proteins. Ultimately, this validation is the only way to establish the clinically relevant markers within the identified protein candidates.

In this study, several residents of the endoplasmic reticulum (ER) were present at a lower levels in FTC than in FTA tissue. These are molecular chaperones that play an essential role in the quality control system that regulates folding and maturation of newly synthesized proteins as well as the transport of the nascent proteins from the ER to other compartments of the secretory pathway. Among these, BiP, PDI A3, and HSP gp96, a constitutively expressed ER molecular chaperone belonging to the HSP90 family, were underrepresented in the FTC samples. These proteins are involved in the maturation of thyroglobulin, possibly as a part of a macromolecular process, and assist with glycosylation and folding of thyroglobulin monomers (23, 24). Calreticulin, another ER protein identified in our study, plays a key role in the synthesis of glycoproteins, including thyroperoxidase (25, 26). Moreover, in addition to their role in protein folding, calreticulin and HSP gp96 may trigger an anticancer immune response (27) and improve the efficiency of phagocytosis (28).

Krause et al. (19) reported higher levels of calreticulin, PDI A3, and HSP90β in benign cold thyroid nodules compared with normal thyroid tissue, but they could not find any evidence of somatic thyroglobulin mutations. In contrast, Paron et al. reported down-regulation of calreticulin in thyroid cell lines transformed by mutant p53 alleles (29). Our finding of lower levels of these proteins in FTC versus FTA tissue may reflect a lesser degree of differentiation of the malignant transformed thyrocyte in the FTC.

Based on the findings of our discovery study, and a review of the literature, we decided to pursue 3 of the 43 proteins found to be present at different levels in FTC versus FTA (i.e., HSP gp96, PDI A3, and calreticulin). These three proteins were abundant in the tissue samples and showed a large difference in volume ratios between the FTC and FTA.

We chose immunohistochemistry for our verification studies because it is performed at the tissue level and it allowed us to assess our candidate markers in an independent subset of paraffin-embedded tissue samples obtained from patients with follicular thyroid neoplasms. However, we recognize that there is a complex and variable relationship between solubilized protein levels, as identified in our discovery studies, and those measured in tissue samples by immunohistochemistry. Nevertheless, the immunohistochemistry and DIGE findings were consistent for all three proteins. In each instance, the intensity scores for immunohistochemical staining correlated with disease severity (i.e., FTAs showed the highest scores, whereas the widely invasive FTCs showed the lowest scores). All three proteins showed a high sensitivity with respect to detection of widely invasive FTCs. An immunohistochemical staining intensity score of three or less for any of the proteins detected all of the widely invasive FTCs in our series. However, given the complexity of the protein patterns and the anticipated broad range in protein abundances, dependent on the stage of transformation and specific mutational patterns, we believe it is essential to extend our investigations to include more of the identified proteins and to examine a larger number of patients having both minimally invasive and widely invasive FTC.

In conclusion, we used discovery proteomics and a validation approach (immunohistochemistry) to identify potential novel biomarkers that aid in distinguishing between FTC and FTA. In addition, these studies provide insights into the global pathophysiologic changes in thyroid carcinoma. Notably, we identified protein isoform differences and posttranslational modifications that would likely be missed by genomic or other proteomic approaches. Carefully designed, controlled prospective studies are now required to establish the clinical utility of each of these markers.


   Acknowledgments
 
Grant support: Generations Cancer Foundation, Mary Rossick Kern and Jerome H. Kern Endowment in Endocrine Neoplasms Research, and Niels-Stensen Foundation (R.T. Netea-Maier).

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

We thank L. Brown and A. Gemmink for their technical support and the Cooperative Human Tissue Network, which is funded by the National Cancer Institute, for providing thyroid tissue samples.


   Footnotes
 
Note: Supplementary data for this article are available at Cancer Research Online (http://cancerres.aacrjournals.org/).

B.R. Haugen and M.W. Duncan contributed equally to this work.

7 http://us.expasy.org/sprot/ Back

Received 8/23/07. Revised 10/30/07. Accepted 10/31/07.


   References
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 

  1. Mazzaferri EL. Management of a solitary thyroid nodule. N Engl J Med 1993;328:553–9.[Free Full Text]
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