Transcriptional Profiling Reveals CoordinatedUp-Regulation of Oxidative Metabolism Genes inThyroid Oncocytic Tumors

OLIVIER BARIS, FREDERIQUE SAVAGNER, VALERY NASSER, BEATRICE LORIOD,SAMUEL GRANJEAUD, SERGE GUYETANT, BRIGITTE FRANC, PATRICE RODIEN,VINCENT ROHMER, FRANCOIS BERTUCCI, DANIEL BIRNBAUM, YVES MALTHIERY,PASCAL REYNIER, AND REMI HOULGATTE

Institut National de la Sante et de la Recherche Medicale, Equipe Mixte INSERM-Universitaire 0018, Laboratoire deBiochimie et Biologie Moleculaire (O.B., F.S., P.Ro., V.R., Y.M., P.Re.), Service d’Endocrinologie, Nutrition et MedecineInterne, Centre Hospitalier Universitaire (P.Ro., V.R.), Angers F-49033, France; Departement d’Oncologie Moleculaire,Institut Paoli-Calmettes and Unite 119, Institut National de la Sante et de la Recherche Medicale (V.N., F.B., D.B.),Marseille F-13273, France; Laboratoire Technologies Avancées pour le Génome et la Clinique/Institut National de la Santeet de la Recherche Medicale, Equipe de Recherche et d’Innovation Technologique et Methodologique 206 (B.L., S.Gr., R.H.),Marseille F-13009, France; Laboratoire d’Anatomie Pathologique, Centre Hospitalier Recherche Universitaire (S.Gu.), ToursF-37044, France; and Laboratoire d’Anatomie Pathologique, Hopital A. Pare (B.F.), Boulogne F-92104, France

Oncocytomas are large cell tumors characterized by an ab-normal proliferation of mitochondria. To investigate this phe-nomenon in thyroid oncocytomas, we determined gene ex-pression profiles of 87 samples using microarrays of 6720 PCRproducts from cDNA clones. Samples included 29 thyroid on-cocytomas and six papillary carcinomas, the remainder rep-resenting other thyroid pathologies or mitochondria-rich tu-mor samples, normal thyroid samples, and two thyroid celllines. Hierarchical clustering and supervised analysis iden-tified two specific oncocytic clusters and 163 distinctly reg-ulated genes between oncocytoma and normal thyroid. Dif-ferential expression of five selected genes (APOD, BCL-2, COX,CTSB, and MAP2) was confirmed by immunohistochemistry.

The two specific oncocytic clusters were rich in mitochondrialgenes and revealed coordinated expression of nuclear andmitochondrial respiratory chain genes. We also observed theup-regulation of genes involved in mitochondrial biogenesis,such as nuclear respiratory factor 1 and the endothelial nitricoxide synthase. Several oxidative metabolism genes wereoverexpressed in oncocytomas, including those from the tri-carboxylic acid cycle (MDH1) and cytosolic glycolysis (GAPD,ENO1, and GPI). On the contrary, the lactate dehydrogenaseA gene, involved in anaerobic metabolism, was down-regu-lated. Our results suggest that, unlike a large number of solidtumors, thyroid oncocytomas produce energy through an aer-obic pathway. (J Clin Endocrinol Metab 89: 994–1005, 2004)

ONCOCYTOMAS (OR OXYPHILIC tumors) affect awide variety of human tissues, including the thyroid,

kidneys, salivary glands, parotid glands, liver, and lungs.However, they occur most frequently in the thyroid glandand represent a subgroup of follicular thyroid neoplasms(3.6%), according to the latest World Health Organizationclassification (1). Thyroid oncocytomas, also known asHuthle cell tumors, are defined by the presence of at least75% large oxyphilic cells (or oncocytes). These cells, charac-terized by abnormally abundant mitochondria, are often as-sociated with the increased activity of respiratory chain en-zymes, including cytochrome c oxidase and succinatedehydrogenase (2). The vast numbers of mitochondria,which show up on histological sections of the cells as a finegranular eosinophilic cytoplasm, are responsible for theswollen appearance of the oncocytes. Oncocytic metaplasia,

which occurs frequently in epithelial endocrine cells withhigh metabolic activity, is also associated with inflammation,degenerative processes, or cellular ageing (3).

The clinical behavior of thyroid oncocytoma and the dis-tinction between benign and malignant tumors have givenrise to considerable controversy. The mortality rate due tooxyphilic carcinoma appears to be higher than that due toother follicular thyroid carcinomas. This may be relatedto the poor responsiveness of oxyphilic cell carcinoma toradioiodine therapy. The classification of oncocytoma aseither adenoma or carcinoma using the conventional cri-terion of vascular or capsular invasion is generally used asan indicator of malignancy in oncocytoma (4). However, thepercentage of oncocytic tumors with capsular or vascularinvasion is higher than that of nononcocytic follicular tumorsshowing signs of malignancy. The high prevalence of ma-lignancy and the putative higher aggressiveness of oncocyticcarcinoma contrasts with the trend toward benignity or lowmalignancy of most oxyphilic tumors in other organs (5).

The relationship between mitochondrial proliferation andthe pathogenesis of oncocytic tumors is still unknown. It hasbeen suggested that mitochondrial proliferation may repre-sent a compensatory mechanism against mitochondrial de-

Abbreviations: DS, Discriminating score; EST, established sequencetag; mtDNA, mitochondrial DNA; NOS3, nitric oxide synthase; NRF-1,nuclear respiratory factor 1; PGC, peroxisome proliferator-activated re-ceptor � coactivator.JCEM is published monthly by The Endocrine Society (http://www.endo-society.org), the foremost professional society serving the en-docrine community.

0021-972X/04/$15.00/0 The Journal of Clinical Endocrinology & Metabolism 89(2):994–1005Printed in U.S.A. Copyright © 2004 by The Endocrine Society

doi: 10.1210/jc.2003-031238

994

fects (6). This hypothesis is supported by the fact that in-creased mitochondrial numbers are frequently reported inmitochondrial diseases associated with respiratory chain de-fects. However, the greater histochemical activity of the re-spiratory chain complexes is not associated with improvedcellular performance (7), suggesting a defect in the energy-producing machinery of the affected cells. No mitochondrialDNA (mtDNA) deletions appear to be specifically involvedin the pathogenesis of oxyphilic tumors, and the common4977-bp mtDNA deletion, which has been described in on-cocytoma, has also been shown to be involved in inflamma-tion and ageing (8).

The considerable difference between the mtDNA and themtRNA content in thyroid oncocytoma suggests a defect inthe coordination of mitochondrial DNA transcription andreplication (8, 9). mtDNA encodes for the 13 polypeptides ofthe respiratory chain complexes as well as the 12S and 16Sribosomal RNAs and the 22 transfer RNAs required for mi-tochondrial protein synthesis. As the whole mitochondrialproteome is estimated to contain approximately 800-1000proteins, the majority of mitochondrial proteins must benuclear encoded. Only a few nuclear factors involved inmitochondrial biogenesis have been identified, such as themitochondrial transcription factor A, the nuclear respiratoryfactors (NRF-1 and NRF-2), and members of the peroxisomeproliferator-activated receptor � coactivator 1 family, such asPGC-1�, PGC-1�, and PRC (10).

cDNA array technology allows quantitative measurementof mRNA expression for thousands of genes simultaneously(11). Among its multiple applications, the molecular classi-fication of tumors has led to major advances in understand-ing the mechanisms underlying cancer. For example, distinctmolecular subgroups were identified for the first time bygene expression profiling reflecting two differentially pro-liferative types of tumor (12). Gene profiling in breast cancerhas allowed the identification of new tumor subgroups withdifferential clinical outcomes, thereby improving the histo-logical criteria of tumor classification (13, 14). Comprehen-sive molecular analysis may therefore be expected to providenew insights into oncocytic neoplasms and lead to betterunderstanding of the mechanisms involved in mitochondrialbiogenesis and nuclear-mitochondrial cross-talk.

We present a global gene expression profile for sporadicthyroid oncocytoma on the basis of the analysis of 76 samplesfrom various conditions, including benign or malignant thy-roid oncocytomas, and samples from two human thyroid celllines. Our aim was to identify the gene expression patternsof oncocytomas to understand the mitochondrial prolifera-tion in oncocytes and to improve tumor diagnosis.

Materials and MethodsTissue samples

Samples were taken from 22 benign and seven malignant oxyphilicthyroid tumors. We also examined samples from seven follicular thyroidadenomas, two follicular thyroid carcinomas, six papillary thyroid car-cinomas, four Grave’s disease thyroids, one renal oncocytoma, one para-thyroid oncocytoma, and one carotid paraganglioma. Samples from 25paired normal thyroids served as controls. All of these cases were di-agnosed between 1994 and 2001 at the Ambroise Pare Hospital (Paris,France; 29 cases) and the University Hospital (Angers, France; 47 cases).All of the samples used were rendered anonymous before the study by

the deletion of all patient identifiers. The diagnoses were made accord-ing to the World Health Organization classification. The distinctionbetween oxyphilic thyroid adenomas and carcinomas was made on thebasis of vascular or capsular invasion. The patients consisted of 15 menand 42 women (mean age, 49 yr; range, 18–75 yr). The average tumorsize was 26.1 � 11.0 mm (mean � sd; range, 10–55 mm). Normal thyroidsamples were taken at a sufficient distance from the tumors to avoidcontamination. All of the samples were stored immediately after resec-tion in liquid nitrogen until required for total RNA extraction.

Cell cultures

Two human thyroid cell lines were used: the XTC.UC1 cell linederived from an oxyphilic thyroid carcinoma, and the B-CPAP cell linederived from a papillary thyroid cancer (15, 16). The growth medium ofXTC.UC1 cells consisted of DMEM supplemented with 10% fetal calfserum (Seromed, Biochrom AG, Berlin, Germany), 100 U/ml penicillin,100 �g/ml streptomycin, and 0.25 �g/ml fungizone. The B-CPAP cellswere cultured in RPMI 1640 medium with 10% fetal calf serum, 100U/ml penicillin, 100 �g/ml streptomycin, and 0.25 �g/ml fungizone.All of the products were obtained from Life Technologies, Inc. (Paisley,UK) unless otherwise stated. Both cell lines were cultured with 10mU/ml TSH (Sigma-Aldrich Corp., Lyon, France), and without TSHover three generations to take into account the effect of TSH on theexpression of the different genes studied.

Total RNA isolation

Total RNA was isolated from tissue samples using a standard gua-nidium isothiocyanate protocol (TRIzol reagent, Life Technologies, Inc.,Gaithersburg, MD) and from cultured cells using the RNeasy kit (QiagenGmbH, Hilden, Germany). RNA integrity was determined using a Bio-Analyzer 2100 (Agilent Technologies, Waldbronn, Germany).

cDNA arrays

Gene expression was analyzed by hybridization of nylon cDNA ar-rays with radioactive probes. The arrays contained spotted PCR prod-ucts from 6720 selected IMAGE (MRC Rosalind Franklin Centre forGenomics Research, GeneService, Cambridge, UK) human cDNA clonesand control clones. Clones were selected on the basis of the followingcriteria: the 3� location of the corresponding mRNA sequences, the samecloning vector (pT3T7), the same host bacteria, and approximately thesame insert size. The majority of clones were selected such that theycontained genes with a proven or putative implication in cancer or immunereactions (full list available soon at http://tagc.univ-mrs.fr/pub). The IM-AGE clones consisted of approximately 84% genes and 16% establishedsequence tags (ESTs). The control clones consisted of three differently sizedpolyadenylated sequences and pT7T3D cloning vectors (negative controls).PCR amplification and robotic spotting of PCR products onto Hybond N�

membranes (Amersham Pharmacia Biotech, Little Chalfont, UK) were per-formed according to protocols described previously (17).

Hybridization of cDNA arrays

cDNA arrays were first hybridized with a labeled vector oligonu-cleotide to determine the precise amount of cDNA accessible for hy-bridization in each spot. After stripping, each array was hybridized witha complex target prepared from 5 �g total RNA by simultaneous RT and[�-33P]deoxy-CTP labeling as described previously (http://tagc.univ-mrs.fr/pub/cancer/). Each sample was hybridized on an individualarray. After washing, hybridization images were obtained by scanningwith an imaging plate device (Fuji BAS 5000, Raytest, Paris, France).Signal intensities were quantified using ArrayGauge software (FujifilmMedical Systems, Stanford, CT).

cDNA array analysis

Complex target measurement was first corrected for the amount ofspotted DNA measured by the oligovector hybridization. Spots exhib-iting weak oligovector hybridization (low amounts of spotted DNA)were considered missing values. Genes with an expression similar to thebackground expression and genes with missing values greater than 25%

Baris et al. • Expression Profiling of Thyroid Oncocytoma J Clin Endocrinol Metab, February 2004, 89(2):994–1005 995

of the samples were withdrawn from the analysis. This finally allowedus to retain a set of 1626 genes with significant expression in most of thesamples. Normalization between arrays was obtained by dividing eachgene measurement by the median value of the array. Data were logtransformed, and classifications were obtained by hierarchical clusteringusing the uncentered correlation distance and average linkage methodprovided by Cluster software, and visualized using Tree View (18).Supervised analysis was performed using a discriminating score (DS)calculated as follows. DS � (�1 � �2)/(�1 � �2), where �1 and �1represent the mean and sd, respectively, of the expression levels of a givengene in sample subgroup 1, and �2 and �2 represent the mean and sd,respectively of the expression levels of the same gene in sample subgroup2 (19). Random permutations of the samples in the two subgroups wereused to calculate the significance level at a risk of 0.01%, giving less thanone false positive gene (number of false positive genes, 0.32) (20).

Immunohistochemistry

To validate our microarrays data for five genes, we looked for theirprotein expression by immunohistochemistry. We selected five onco-cytoma/normal thyroid pairs randomly chosen among the samplespreviously tested with microarrays and 10 independent oncocytoma/normal thyroid pairs. After morphological examination of hematoxylin-and eosin-stained sections, the corresponding 3-�m sections of the par-affin blocks were prepared for the detection of proteins encoded byseveral genes that discriminate between oncocytic and normal thyroids.We used five monoclonal IgG1 antibodies against BCL-2, cathepsin-B(Ab-2), apolipoprotein D, microtubule-associated protein 2 (all four fromCalbiochem, Biosciences, Inc., Darmstadt, Germany), and a complex IVsubunit of the respiratory chain (clone 113-1, from Biogenex Laborato-ries, Inc., San Ramon, CA). Immunostaining was performed using thestandard avidin-biotin peroxidase technique with antigen retrieval. Fornegative control slides, the primary antibody was either omitted orreplaced by a suitable concentration of normal IgG of the same species.

ResultsDescription of the complete cluster diagram

Each of the 87 samples was hybridized on a microarraycontaining cDNA for 6720 known genes and ESTs. Afternormalization, 1626 genes were selected for further analysis.Data were clustered using a hierarchical algorithm and wererepresented in a color-coded matrix (18). The complete clus-ter diagram is shown in Fig. 1. The tissue samples wereseparated into two groups (group I, 50 samples; group II, 26samples), as shown in Fig. 1A. Significantly, all of the sam-ples in group II (except one, which was a thyroid papillarycarcinoma) were oncocytic tumors. Similarly, several sam-ples in group I belonging to the same histological class (suchas papillary carcinoma or normal thyroid) were clusteredtogether, confirming the presence of specific gene clusters.The cell line samples were separated into two distinct groupsaccording to their origin (Fig. 1A, XTC-UC1 and B-CPAP).An enlarged view of several interesting gene clusters in thecomplete diagram (Fig. 1B, colored bars) is shown in Fig. 1C.

A mitochondrial cluster (Fig. 1, yellow bar) was clearlyup-regulated in thyroid oncocytomas and in XTC-UC1 cellsas well as in renal and parathyroid oncocytomas comparedwith the other samples. This cluster was rich in nuclearencoded genes of the five respiratory chain complexes(ATP5B, ATP5C1, ATP5I, COX4I1, COX5A, COX5B, COX6A1,COX7A2, COX7B, CYC1, HCS, NDUFA4, NDUFA8, NDUFS4,NDUFS8, SDHA, SDHB, UQCR2, UQCRB, and UQCRFS1).Also included were some nuclear genes encoding proteinslocated in the matrix and on the outer mitochondrial mem-brane (PMPCB and BZRP) as well as some energy metabo-lism genes (GPI and MDH1).

A second set of genes (Fig. 1, blue bar) was overexpressedin thyroid oncocytic tumors. This thyroid oncocytic tumorcluster was composed of approximately 200 genes, includingmitochondrial genes (ANT2, COX7RP, HSPC051, ME3,MTND4, MTCYB, MTATP6, MTCO3, NDUFB9, MRPL49,NRF1, and PPOX) involved in various mitochondrial func-tions, such as heme biosynthesis, pyruvate metabolism, ATPtransport, and oxidative phosphorylation. We also observedoverexpression of these genes in both parathyroid and renaloncocytoma samples. One notable finding was the overex-pression of NRF-1, which is known to be a transcriptionfactor regulating the expression of many mitochondrial pro-teins. This cluster also included genes involved in proteinmetabolism, DNA replication and maintenance, DNA tran-scription, and the cell cycle, thus reflecting the proliferativestatus of these tumors. Incidentally, several muscle-specificgenes (MYH2, TNNT1, TPM2, TNNI1, MB, and MYH1) wereclustered together, possibly representing the myofibroblasticcontent of these tumors, as myofibroblasts are known toexpress muscle-specific genes (21).

Seven clustered genes were specific to both thyroid pap-illary and oncocytic tumors (Fig. 1, green bar). Their stronglycorrelated expression suggests a common involvement inthe same cellular process. These genes are involved in pro-teolysis (CTSB and CSTB), signaling (MST1R, IGF2R, andIGFBP6), DNA repair (PRKDC), and regulation of cell pro-liferation (RBL2).

We also identified two clusters reflecting differential pro-liferative status. The first, a proliferation cluster (Fig. 1, tur-quoise bar), was overexpressed in both XTC.UC1 and B-CPAPcell lines, reflecting their highly proliferative status. This setwas rich in cytoskeleton genes, DNA maintenance and rep-lication genes, cell cycle genes, transcription factors, andprotein metabolism genes. It also included the PCNA gene,which is frequently used as a marker of proliferation. Thesecond, an immediate response cluster (Fig. 1, pink bar), wasoverexpressed in normal thyroid samples and was composedof genes involved in growth, proliferation, and differentia-tion stimuli (ATF3, EGR1, FOS, JUN, JUNB, JUND, and SRF).A similar gene cluster has been identified in normal ovariantissue compared with tumoral tissue (22). This might indicatethe differential of proliferative status between normal andmalignant tissues, because overexpression of ATF3 andEGR1 results in slower growth rates (23, 24).

Lastly, an immune response cluster (Fig. 1, brown bar) wasidentified, mainly reflecting T and B lymphocyte populationsand immune response mechanisms such as antigen presen-tation or interferon signaling. Overexpression of this clusterwas concordant with the lymphocytic infiltrates revealed byhistological examination of the corresponding tissue sec-tions. Moreover, the four Graves’ disease samples showedincreased expression of the Ig genes, reflecing the humoralautoimmune origin of Graves’ disease. Among the six on-cocytomas that were not clustered in the branch correspond-ing to group II (Fig. 1A), histology confirmed the presence ofextensive lymphocytic infiltrates in two of the samples. Thewithdrawal of the immune response cluster genes followedby two-dimensional reclustering resulted in the inclusion ofboth samples in group II (data not shown).

996 J Clin Endocrinol Metab, February 2004, 89(2):994–1005 Baris et al. • Expression Profiling of Thyroid Oncocytoma

FIG. 1. Hierarchical average linkage clustering of 76 tissue samples and 11 cell line samples based on expression patterns of 1626 cDNA clones.Each row represents a gene, and each column represents a single sample. Genes are referenced by their HUGO abbreviation as used in LocusLink (http://www.ncbi.nlm.nih.gov/LocusLink). Each cell in the matrix represents the expression level of a transcript in a single sample relativeto its median abundance across all samples. Red and green indicate expression levels respectively above and below the median. Gray squaresindicate missing values. The fold changes in transcript abundance relative to the median are represented by a color scale at the bottom of thefigure. Hierarchical average linkage clustering was first applied to group genes according to the similarity of their expression patterns acrossall samples. The same clustering method was then separately applied to tissue and cell line samples using the criterion of the similarity of theirexpression patterns. A, Dendrogram of samples representing overall similarities in gene expression profiles across all samples. Tissues arerepresented by colors according to the color bar on the left (TO, thyroid oncocytoma; NT, normal thyroid; PTC, papillary thyroid carcinoma;TA, thyroid adenoma; FTC, follicular thyroid carcinoma; GD, Grave’s disease; RO, renal oncocytoma; PO, parathyroid oncocytoma; P, carotidparaganglioma). B, Complete cluster diagram of expression levels. Colored bars on the right indicate the location of the gene clusters of interestshown in C (yellow bar, mitochondrial cluster; turquoise bar, proliferation cluster; brown bar, immune response cluster; pink bar, immediateresponse cluster; blue bar, oncocytic tumor cluster; green bar, papillary thyroid carcinoma and thyroid oncocytic tumor cluster). Mitochondrialgenes are shown in red.

Baris et al. • Expression Profiling of Thyroid Oncocytoma J Clin Endocrinol Metab, February 2004, 89(2):994–1005 997

Thyroid oncocytoma-specific profile

To further characterize thyroid oncocytoma, we comparedall thyroid oncocytoma samples with the normal thyroidtissue samples that served as controls. For each gene wecalculated a DS that enabled us to determine significantlydistinct gene expression profiles for two groups of samples.The first group comprised the 29 thyroid oncocytomas, andthe second group comprised the 25 normal thyroid samples.We performed 100 random permutations of the samples ineach group to select the genes that discriminated betweenthese two groups at a risk of significance of 0.01%. Using thisapproach we identified 163 genes that discriminated, to astatistically significant degree, between the two groups. Fig-ure 2 shows a hierarchical clustering diagram of the 163genes and the 54 samples analyzed. Thirty-seven genes wereunderexpressed, and 126 genes were overexpressed in thy-

roid oncocytoma compared with normal thyroid tissue. Therobustness of our approach was illustrated by the fact that 26of the 29 oncocytomas were grouped in the same clusterbranch. The three remaining oncocytoma samples were his-tologically considered atypical. Despite the usual presence ofgranular cytoplasm and mitochondria stained with a cyto-chrome oxidase antibody, the three samples also exhibitedatypical nuclear or structural aspects. These samples wereamong the thyroid oncocytic samples that clustered in groupI of the unsupervised hierarchical clustering (Fig. 1A). Inaddition, we tried to identify the genes that discriminate bestbetween thyroid oncocytic adenomas and carcinomas, but,unfortunately, obtained no statistically significant results.

The 37 genes found to be underexpressed in thyroid on-cocytomas (Table 1) were involved in various cellular pro-cesses, such as lipid metabolism (APOD), inflammation

FIG. 2. Hierarchical average linkage clusteringof the 163 most discriminating genes betweenoncocytic and normal thyroid samples. A dis-criminating score between the group of oncocy-toma samples and that of normal thyroid tissuewas calculated for each of the 1626 genes. Onehundred random column permutations wereperformed to select statistically discriminatinggenes at a risk of 0.01%. The fold changes intranscript abundance relative to the median arerepresented by a color scale on the left side of thefigure.

998 J Clin Endocrinol Metab, February 2004, 89(2):994–1005 Baris et al. • Expression Profiling of Thyroid Oncocytoma

(PTGS2 and TNFAIP3), transcription (FOS, JUN, JUNB,CHD2, and CREB1), adhesion (GJA1), signaling (DUSP1 andNBL1), and membrane structure (CAV1). The lowest expres-sion levels were observed for 11 genes: APOD, FOS, JUN,CAV1, EPB41L2, EGR1, JUNB, POLD2, IFITM1, MATN2,and RAF1. As expected, the 126 up-regulated genes (Table 2)included several mitochondrial genes and, in particular, thenuclear genome-encoded genes, COX5B, COX6A1, SDHA,CYBA, CYC1, COX5A, COX7B, ATP5B, NDUFA4, HCS, andCOX4I1, together with the mitochondrial genome-encodedgenes, MTATP6 and MTND4. The proliferative status ofthyroid oncocytic cells was illustrated by overexpression ofthe genes involved in DNA replication (RPA1, RFC4, andPOLD1), the cell cycle (CCNA2, CCNE1, CCNG2, etc.), orprotein synthesis (RPS8, RPS18, RPS19, and EIF2S2). Alsoincluded were genes involved in cell adhesion, cytoskeletonformation, cell cycle regulation, proteolysis, DNA repair, andtranscription. Among these 126 up-regulated genes, 66 dis-played a 2- to 6-fold increase in expression. The highestexpression levels in thyroid oncocytomas were observed for11 genes: ZNF42, ADA, HINT1, IGF2R, DTR, CYBA, RPS18,MRLP49, MTND4, PRKDC, and POLD1.

We tested the accuracy of the differentiation between geneexpression in oncocytic and normal tissues by immunohis-tochemical evaluation of the expression of five proteins:COX, MAP2, CTSB, APOD, and BCL-2. We used five thyroidoncocytomas and paired normal tissues randomly selectedamong our first set of sample as well as 10 independentoncocytoma/thyroid pairs (Fig. 3). The results obtained werein agreement with the corresponding mRNA expression val-ues, indicating that these proteins are good tumoral markersfor thyroid oncytoma (Table 3). Our COX antibody repre-sents a positive control; in fact, it is commonly used to de-termine the proportion of oncocytes in thyroid tumors toconfirm the diagnosis of oncocytomas. The overexpression ofMAP2, a microtubule-associated protein, which binds to theouter membrane of mitochondria (25), suggests that mito-chondrial proliferation in oncocytoma is accompanied by amodification of the expression of mitochondria-associatedcytoskeleton proteins. In normal thyroid samples, cathepsinB was localized apically in the thyroid cells, as has beenreported previously (26). However, in the oncocytoma samples,we found a homogeneous cytoplasmic distribution of the pro-tein in the oncocytes, even when these cells were still polarized.

TABLE 1. Genes found underexpressed in thyroid oncocytomas compared with normal thyroid tissue

Gene symbol Description Function Ratio O/T

APOD Apolipoprotein D Lipid metabolism 0.18FOS v-fos FBJ murine osteosarcoma viral oncogene homolog Transcription 0.20JUN v-jun sarcoma virus 17 oncogene homolog (avian) Transcription 0.24CAV1 Caveolin 1 Structure, tumor suppressor 0.28EPB4IL2 Erythrocyte membrane protein band 4.1-like 2 Cytoskeleton 0.30EGR1 Early growth response 1 Transcription 0.33JUNB jun B protooncogene Transcription 0.35POLD2 Polymerase (DNA directed), �2, regulatory subunit 50 kDa DNA replication 0.36IFITM1 Interferon induced transmembrane protein 1 (9–27) Cell cycle regulation 0.47MATN2 Matrilin 2 Extracellular matrix 0.49RAF1 v-raf-1 murine leukemia viral oncogene homolog 1 Cell proliferation regulation, apoptosis 0.50DUSP1 Dual specificity phosphatase 1 Cell cycle regulation 0.51MMP2 Matrix metalloproteinase 2 Proteolysis 0.53BCL2 B Cell CLL/lymphoma 2 Apoptosis 0.54NBL1 Neuroblastoma, suppression of tumourigenicity 1 Tumor suppressor 0.54TNFAIP3 TNF�-induced protein 3 Inflammation 0.55IFRD1 Interferon-related developmental regulator 1 Muscle differentiation 0.55CHD2 Chromodomain helicase DNA-binding protein 2 Transcription regulation 0.58FHL1 Four and a half LIM domains 1 0.59IGFBP5 IGF-binding protein 5 Signal transduction 0.59FOXO1A Forkhead box O1A (rhabdomyosarcoma) Transcription 0.60NEDD5 Neural precursor cell expressed, developmentally down-regulated 5 0.61PTGS2 Prostaglandin-endoperoxide synthase 2 (prostaglandin G/H synthase

and cyclooxygenase)Inflammation 0.63

HDGF Hepatoma-derived growth factor (high mobility group protein 1-like) Cell proliferation regulation 0.64PSCD1 Pleckstrin homology, Sec7 and coiled/coil domains 1 (cytohesin 1) Signal transduction 0.64CREB1 cAMP-responsive element-binding protein 1 Signal transduction, transcription 0.65FGB Fibrinogen B �-polypeptide Blood coagulation 0.66TNFSF10 TNF (ligand) superfamily, member 10 Apoptosis 0.66GJA1 Gap junction protein, �1, 43 kDa (connexin 43) Adhesion 0.66ANXA4 Annexin A4 Blood coagulation 0.67FBLN1 Fibulin 1 Extracellular matrix 0.67LMO7 LIM domain only 7 Protein-protein interaction 0.67GLG1 Golgi apparatus protein 1 Receptor, vesicle traffic 0.69CTSF Cathepsin F Proteolysis 0.71C9orf9 0.71LDHA Lactate dehydrogenase A Metabolism 0.72EST-512919 0.73

The 37 genes are referenced by their HUGO abbreviations as used in “Locus Link” (http://www.ncbi.nlm.nih.gov/LocusLink). Ratio O/T isthe ratio between the median gene expression value of thyroid oncocytomas and that of normal thyroid tissues. Ratios O/T were found significantat a risk of 0.01% (number of False-Positive genes � 0.32).

Baris et al. • Expression Profiling of Thyroid Oncocytoma J Clin Endocrinol Metab, February 2004, 89(2):994–1005 999

TABLE 2. Genes found overexpressed in thyroid oncocytomas compared with normal thyroid tissue

Gene symbol Description Function Ratio O/T

ZNF42 Zinc finger protein 42 (myeloid-specific retinoic acid-responsive) Transcription 6.15RPS18 Ribosomal protein S18 Protein synthesis 3.95HINT1 Histidine triad nucleotide-binding protein 1 Signal transduction 3.92ADA Adenosine deaminase 3.92MRPL49 Mitochondrial ribosomal protein L49 Mitochondrial protein synthesis 3.64IGF2R IGF-II receptor Signal transduction 3.58DTR Diphtheria toxin receptor (heparin-binding epidermal growth factor-

like growth factor)Smooth muscle cell mitogen 3.38

MTND4 NADH dehydrogenase 4 Mitochondrial respiratory chain 3.22CYBA Cytochrome b-245, �-polypeptide Cytochrome b 3.18PRKDC Protein kinase, DNA-activated, catalytic polypeptide DNA repair 3.15POLD1 Polymerase (DNA directed), �1, catalytic subunit 125 kDa DNA replication 3.11MAP2 Microtubule-associated protein 2 Cytoskeleton 2.84DDIT3 DNA-damage-inducible transcript 3 DNA repair 2.76THBS3 Thrombospondin 3 Angiogenesis 2.73MYCL v-myc myelocytomatosis viral oncogene homolog 1, lung carcinoma

derived (avian)Transcription 2.65

CSNK2A2 Casein kinase 2, ��-polypeptide Signal transduction 2.62EST-358162 2.60RPL13P2 Ribosomal protein L13 pseudogene 2 2.60MTATP6 ATP synthase 6 Mitochondrial respiratory chain 2.57PSMC5 Proteasome (prosome, macropain) 26S subunit, ATPase 5 Proteolysis, transcription 2.53GAPD Glyceraldehyde-3-phosphate dehydrogenase Glycolysis 2.53H2AFA H2A histone family, member A DNA structure 2.53CTSB Cathepsin B Proteolysis 2.52COX5B Cytochrome c oxidase subunit Vb Mitochondrial respiratory chain 2.50PTPN21 Protein tyrosine phosphatase, nonreceptor type 21 Signaling 2.50RPS19 Ribosomal protein S19 Protein synthesis 2.49LNPEP Leucyl/cystinyl aminopeptidase Proteolysis 2.46RPA1 Replication protein A1, 70 kDa DNA replication 2.46MST1R Macrophage stimulating 1 receptor (c-met-related tyrosine kinase) Signal transduction 2.44SMC4L1 SMC4 structural maintenance of chromosomes 4-like 1 (yeast) DNA structure 2.43NPM1 Nucleophosmin (nucleolar phosphoprotein B23, numatrin) RNA binding 2.38VIPR1 Vasoactive intestinal peptide receptor 1 Signaling 2.38PTCH Patched homolog (Drosophila) Cell proliferation regulator 2.38RBL2 Retinoblastoma-like 2 (p130) Cell proliferation regulator 2.37MYCN v-myc myelocytomatosis viral related oncogene, neuroblastoma-

derived (avian)Transcription 2.37

CCNG2 Cyclin G2 Cell cycle 2.35PIAS1 Protein inhibitor of activated STAT1 Transcription 2.32MAX MAX protein Transcription 2.31TNFRSF25 TNF receptor superfamily, member 25 Apoptosis 2.31ETR101 Immediate-early protein Transcription 2.30TP53 Tumor protein p53 (Li-Fraumeni syndrome) Cell cycle regulator 2.29EST-33084 2.24ACE Angiotensin I-converting enzyme (peptidyl-dipeptidase A) 1 Circulation 2.24ACTN2 Actinin, �-2 Cytoskeleton 2.23PTPRN Protein tyrosine phosphatase, receptor type, N Signaling 2.22EIF2S2 Eukaryotic translation initiation factor 2, subunit 2�, 38 kDa Protein synthesis 2.22BDNF Brain-derived neurotrophic factor Growth factor 2.20CSTB Cystatin B (stefin B) Proteolysis 2.17ZNF135 Zinc finger protein 135 (clone pHZ-17) Transcription 2.17K-ALPHA-1 Tubulin �, ubiquitous Cytoskeleton 2.16EST-44839 2.15COX6A1 Cytochrome c oxidase subunit VIa polypeptide 1 Mitochondrial respiratory chain 2.15SEMA4D Sema domain, Ig domain, transmembrane domain (TM) and short

cytoplasmic domain, (semaphorin) 4DAdhesion 2.14

CTNNB1 Catenin (cadherin-associated protein) �1, 88 kDa Signal transduction, adhesion 2.09ZNF45 Zinc finger protein 45 [a Kruppel-associated box (KRAB) domain

polypeptide]Transcription 2.09

MYH1 Myosin, heavy polypeptide 1, skeletal muscle, adult Muscle 2.09CCNE1 Cyclin E1 Cell cycle 2.08SAR1 SAR1 protein 2.05MAP2K2 MAPK kinase 2 Signal transduction 2.05MNFG Manic fringe homolog (Drosophila) Notch pathway regulation 2.05STK11 Serine/threonine kinase 11 (Peutz-Jeghers syndrome) Protein phosphorylation 2.05ABCC2 ATP-binding cassette subfamily C (CFTR/MRP), member 2 Transporter 2.05EP300 E1A binding protein p300 Transcription 2.03SDHA Succinate dehydrogenase complex, subunit A, flavoprotein (Fp) Mitochondrial respiratory chain 2.01

1000 J Clin Endocrinol Metab, February 2004, 89(2):994–1005 Baris et al. • Expression Profiling of Thyroid Oncocytoma

TABLE 2. Continued

Gene symbol Description Function Ratio O/T

CYC1 Cytochrome c-1 Mitochondrial respiratory chain 2.01NOS3 Nitric oxide synthase, endothelial Angiogenesis 2.00COPB Coatomer protein complex, subunit-� Vesicle transport 1.96EST-34872 1.96EFNA1 Ephrin-A1 Cell to cell signaling 1.94COX5A Cytochrome c oxidase subunit Va Mitochondrial respiratory chain 1.93VASP Vasodilator-stimulated phosphoprotein Cytoskeleton 1.91LMO2 LIM domain only 2 (rhombotin-like 1) Development 1.91ERCC5 Excision repair cross-complementing rodent repair deficiency,

complementation group 5DNA repair 1.88

ATP6V1D ATPase H� transporting, lysosomal 34 kDa, V1 subunit D Vacuolar ATPase 1.88YARS Tyrnsyl-tRNA synthetase Protein synthesis 1.87FLI1 Friend leukemia virus integration 1 Transcription 1.87NME1 Nonmetastatic cells 1. protein (NM23A) expressed in Cell cycle regulation 1.84COX7B Cytochrome c oxidase subunit VIIb Mitochondrial respiratory chain 1.83LGALS7 Lectin, galactoside-binding, soluble 7 (galactin 7) Adhesion 1.82TIE Tyrosine kinase with Ig and epidermal growth factor homology

domainsAngiogenesis 1.82

CRABP1 Cellular retinoic acid-binding protein 1 Signal transduction 1.81CDH18 Cadherin 18, type 2 Adhesion 1.81NME2 Nonmetastatic cells 2, protein (NM23B) expressed in Cell cycle regulation 1.81ATP5B ATP synthase, H� transporting mitochondrial F1 complex,

�-polypeptideMitochondrial respiratory chain 1.79

RPS8 Ribosomal protein S8 Protein synthesis 1.78DDX24 DEAD/H (Asp-Glu-Ala-Asp/His) box polypeptide 24 RNA processing 1.78PLCG1 Phospholipase C �1 (formerly subtype 148) 1.77MIF Macrophage migration inhibitory factor (glycosylation-inhibiting

factor)Cytokine 1.77

RFC4 Replication factor C (activator 1), 4.37 kDa DNA replication 1.76MGC3178 Thioredoxin-related protein 1.76SYT1 Synaptotagmin 1 Synaptic transmission 1.73SPR Sepiapterin reductase (7.8-dihydrobiopterin:NADP� oxidoreductase) Tetrahydrobiopterin synthesis 1.73PPP1R1A Protein phosphatase 1, regulatory (inhibitor) subunit 1A Phosphatase inhibitor 1.71SNT2 Syntrophin�1 (dystrophin-associated protein A1, 59 kDa, basic

component 1)Muscle contraction 1.70

HKE4 HLA class II region expressed gene KE4 1.69IGFBP6 IGF-binding protein 6 Signal transduction 1.68RPN2 Ribophorin II Protein modification 1.68LYN v-yes-1 Yamaguchi sarcoma viral-related oncogene homolog Signal transduction 1.65ADCYAP1 Adenylate cyclase-activating polypeptide 1 (pituitary) Cell to cell signaling 1.65GGT1 �-Glutamyltransferase 1 Amino acid metabolism 1.64EST-67457 1.63NDUFA4 NADH dehydrogenase (ubiquinone)-1� subcomplex, 4.9 kDa Mitochondrial respiratory chain 1.62SMC2L1 SMC2 structural maintenance of chromosomes 2-like 1 (yeast) DNA structure 1.62EDN3 Endothelin 3 Angiogenesis 1.62GYPA Glycophorin A (includes MN blood group) Membrane protein 1.60CCNA2 Cyclin A2 Cell cycle 1.58EST-108303 1.58GT2F1 General transcription factor IIF, polypeptide 1, 74 kDa Transcription 1.58C12orf10 1.57CAP Adenylyl cyclase-associated protein Signal transduction 1.57TBL1 Transducin (�-like 1X-linked Signal transduction 1.56STS Steroid sulfatase (microsomal), arylsulfatase C, isozyme S Steroid catabolism 1.56AQP1 Aquaporin 1 (channel-forming integral protein, 28 kDa) Transporter 1.55PPGB Protective protein for �-galactosidase (galactosialidosis) Proteolysis 1.54HCS Cytochrome c, somatic Cytochrome c 1.52USP11 Ubiquitin-specific protease 11 Deubiquitination 1.49RRM1 Ribonucleotide reductase M1 polypeptide DNA synthesis 1.48SGCE Sarcoglycan-� Extracellular matrix 1.47COX4I1 Cytochrome c oxidase subunit IV isoform 1 Mitochondrial respiratory chain 1.44KIAA0788 U5 snRNP-specific protein, 200 kDa 1.43CRNKL1 Crn, crooked neck-like 1 (Drosophila) 1.42PPP2CA Protein phosphatase 2 (formerly 2A), catalytic subunit, �-isoform Cell cycle regulation 1.38SMTN Smoothelin Smooth muscle 1.35ARHI ras homolog gene family, member I Signal transduction 1.32DDT D-Dopachrome tautomerase Dopachrome isomerase 1.32EST-298808 1.29

The 126 genes are referenced by their HUGO abbreviations as used in Locus Link (http://www.ncbi.nlm.nih.gov/LocusLink). Ratio O/T isthe ratio between the median gene expression value of thyroid oncocytomas and that of normal thyroid tissues. Ratios O/T were found significantat a risk of 0.01% (number of false positive genes, 0.32).

Baris et al. • Expression Profiling of Thyroid Oncocytoma J Clin Endocrinol Metab, February 2004, 89(2):994–1005 1001

Discussion

Thyroid oncocytomas are a distinct type of tumor char-acterized by cells with abnormally abundant mitochondria.Although these tumors have been widely described, little is

known about the origin of the mitochondrial proliferation.To explore the mechanisms involved, we used a highthroughput method to determine the specific expression pro-file of thyroid oncocytoma. We explored 29 thyroid oncocy-

FIG. 3. Immunoperoxidase staining of oncocyto-mas and paired normal thyroids. Respiratorychain complex IV subunit (A, normal thyroid; B,oncocytoma), cathepsin B (C, normal thyroid; D,oncocytoma), microtubule-associated protein 2 (E,normal thyroid; F, oncocytoma), BCL-2 (G, normalthyroid; H, oncocytoma), and apolipoprotein D (I,normal thyroid; J, oncocytoma). Original magnifi-cation: A, B, I, and J, �20; C–H, �40.

1002 J Clin Endocrinol Metab, February 2004, 89(2):994–1005 Baris et al. • Expression Profiling of Thyroid Oncocytoma

tomas together with samples from other thyroid pathologiesby means of microarrays containing 6720 cDNAs fromknown genes and ESTs.

The gene profiling of thyroid oncocytic tumors revealedspecific expression patterns that at the molecular level cor-respond to the mitochondrial proliferation histologically ob-served in oncocytomas. Two gene clusters were specificallyoverexpressed in 25 of the 29 thyroid oncocytomas, as wellas in the two other nonthyroidal oncocytoma samples (kid-ney and parathyroid). One cluster, the mitochondrial cluster,composed mainly of genes coding for subunits of the fivecomplexes of the respiratory chain, was overexpressed inoncocytic tumors and in the oncocytoma-derived cell line.The other cluster, the thyroid oncocytic tumor cluster, wascomposed of approximately 200 genes and included mito-chondrial genes involved not only in oxidative phosphory-lation, but also in various other mitochondrial functions. Theunderexpression of this cluster in XTC-UC1 cells probablyreflects either the behavior of oncocytic cells in a tumoralenvironment or the loss of certain features in highly prolif-erative cultured cells. In addition, the mtDNA-encoded aswell as the nuclear-encoded subunits of the respiratory chainwere found in these two clusters, suggesting coordinatedregulation of their expression in oncocytomas, as describedby Heddi et al. (27).

Our findings support the hypothesis of the up-regulationof mitochondrial biogenesis in oncocytic tumors. Indeed,NRF-1, a mitochondrial ribosomal protein (MRLP49), and amitochondrial processing peptidase (PMPCB), all involvedin mitochondrial biogenesis, were overexpressed in thesetumors. Among the genes that were overexpressed in onco-cytic tumors, we also found the gene encoding endothelialnitric oxide synthase (NOS3). Recently, it has been shownthat endogenous nitric oxide can trigger mitochondrial bio-genesis in various cell types through the induction of thePGC-1� (28). The up-regulation of both NOS3 and NRF-1suggests that mitochondrial biogenesis in oncocytic tumorsis mediated by endogenous nitric oxide through the induc-tion of PGC-1� or related factors.

Our results also reveal a profound modification of energymetabolism in oncocytomas. Twenty-six genes coding forsubunits of the respiratory chain enzymes, three genes cod-ing for glycolytic enzymes (GPI, GAPD, and ENO1), andseveral other genes encoding other energy metabolism en-zymes (MDH1, ME3, and PGM1) were overexpressed in

oncocytic tumors. Up-regulation of genes coding for glyco-lysis, the tricarboxylic acid cycle, and oxidative phosphory-lation enzymes suggests that thyroid oncocytic tumors pro-duce energy through an aerobic pathway. Moreover, thelactate dehydrogenase A gene, frequently overexpressed inhuman cancers characterized by anaerobic glycolysis, wasunderexpressed in the thyroid oncocytoma samples com-pared with normal thyroid tissue. This strengthens our hy-pothesis of the existence of an aerobic glycolytic mechanismin thyroid oncocytoma. The overexpression of energy me-tabolism proteins has been reported in renal oncocytoma,with findings of high activity of the enzymes involved inglycolysis and the tricarboxylic acid cycle coupled with lowlactate dehydrogenase activity (29). This suggests that oxi-dative energy metabolism is a common feature of oncocytictumors. In a previous study we demonstrated that mito-chondrial ATP synthesis is altered in oxyphilic cells, possiblyby uncoupling of the proton gradient in mitochondria, assuggested by the overexpression of uncoupling protein-2 inthyroid oncocytoma (8). A high content of aerobic energymetabolism enzymes and increased expression of the regu-lators of mitochondrial biogenesis in these tumors suggesta close relationship between these two processes. The up-regulation of mitochondrial biogenesis may compensate fordefective mitochondrial ATP production by a feedbackmechanism, or the two pathways may be concomitantly dys-regulated at some higher molecular level (Fig. 4).

Our supervised analytic approach allowed us to identifythe genes that discriminate between thyroid oncocytomasand normal thyroid tissue. The thyroid oncocytoma geneexpression profile picked out several genes known to bedysregulated in thyroid cancers and other neoplasms, suchas APOD, CTSB, DUSP1, and BCL-2 (30–32). Neither theunsupervised approach, based on classification, nor the su-pervised approach, based on a discriminating score, allowedus to make any distinction between oncocytic adenomas andcarcinomas (results not shown); samples from both catego-ries of oncocytic tumors were found clustered in the samebranch of the classification. This supports the hypothesis thatthyroid follicular adenomas progressively develop into car-cinomas (33).

To our knowledge, this is the first report of a global geneexpression profile in thyroid oncocytoma. We have identi-fied 163 dysregulated genes in thyroid oncocytoma com-pared with normal thyroid tissue. Molecular similaritieswere found among oncocytomas originating from three dif-ferent tissues, i.e. thyroid, parathyroid, and kidney. Thus, acommon mechanism may underlie the abnormal mitochon-drial proliferation observed in oncocytic tumors. Neverthe-less, further experiments including more samples from non-thyroidal oncocytic tumors are needed to confirm thishypothesis. We identified a thyroid oncocytic tumor clusterthat highlights the intimate relationship between mitochon-drial biogenesis and cellular energy metabolism in thesetumors. Given the role of NOS3 on oxidative enzyme activ-ities (34), we hypothesize that this gene plays a major rolein thyroid oncocytomas by leading to an increase in mito-chondrial content and promoting an oxidative energeticmetabolism.

TABLE 3. Immunohistochemistry results for five selected genes

Tumor class No. ofsamples

Underexpression (%) Overexpression (%)

APOD BCL-2 COX CTSB MAP2

Adenoma 10 90 90 100 80 70Carcinoma 5 100 100 100 100 100

Immunohistochemistry was performed for 15 oncocytoma/thyroidcouples to validate microarrays data for five selected genes (APOD,BCL-2, COX, CTSB, and MAP2). Underexpression and overexpres-sion are relative to the expression of each protein in paired normalthyroids. The proportion of samples in which microarrays data wereconfirmed by immunohistochemistry is indicated by a percentage.APOD, Apolipoprotein D; BCL-2, B cell CLL/lymphoma 2; COX, cy-tochrome oxidase; CTSB, cathepsin B; MAP2, microtubule-associatedprotein 2.

Baris et al. • Expression Profiling of Thyroid Oncocytoma J Clin Endocrinol Metab, February 2004, 89(2):994–1005 1003

FIG. 4. Model of aerobic energy metabolism in thyroid oncocytic tumors. A, Schematic view of our model of aerobic energy metabolism in thyroidoncocytic tumors. Genes shown in red are up-regulated, and those shown in green are down-regulated in oncocytomas compared with normalthyroid tissue. Defective ATP synthesis triggers signaling between mitochondria and nucleus. This cross-talk leads to an up-regulation ofmitochondrial biogenesis, which compensates for the less efficient energy production in oncocytoma. B, Hierarchical clustering of mitochondrialgenes involved in energetic metabolism and mitochondrial biogenesis. The fold changes in transcript abundance relative to the median arerepresented by a color scale on the left side of the figure.

1004 J Clin Endocrinol Metab, February 2004, 89(2):994–1005 Baris et al. • Expression Profiling of Thyroid Oncocytoma

Acknowledgments

We thank Jocelyne Hodbert for technical help with the cell cultures,and Nicola Jordan and Kanaya Malkani for critical reading of the manu-script. The authors want it to be known that, in their opinion, PascalReynier and Remi Houlgatte equally supervised this work.

Received July 17, 2003. Accepted November 5, 2003.Address all correspondence and requests for reprints to: Dr. Olivier

Baris, Institut National de la Sante et de la Recherche Medicale, EquipeMixte INSERM-Universitaire 0018, Laboratoire de Biochimie et de Bi-ologie Moleculaire, Centre Hospitalier Universitaire, 4 rue Larrey, An-gers F-49033, France. E-mail: olivier.baris@med.univ-angers.fr.

This work was supported by grants from the French Ministry ofResearch, Institut National de la Sante et de la Recherche Medicale, thePaoli-Calmettes Institute, the Anti-Cancer League of the Maine et Loire,the University Hospital of Angers (PHRC 01.10), and the University ofAngers.

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