Combined Use of Oligonucleotide and Tissue Microarrays Identifies Cancer/Testis Antigens as Biomarkers in Lung Carcinoma1

[CANCER RESEARCH 62, 3971–3979, July 15, 2002]

Combined Use of Oligonucleotide and Tissue Microarrays Identifies Cancer/TestisAntigens as Biomarkers in Lung Carcinoma1

Michio Sugita, Mark Geraci, Bifeng Gao, Roger L. Powell, Fred R. Hirsch, Gary Johnson, Razvan Lapadat,Edward Gabrielson, Roy Bremnes, Paul A. Bunn, and Wilbur A. Franklin2

Departments of Pathology [M. S., R. L. P., W. A. F.], Medicine [M. G., B. G., F. R. H., R. B., P. A. B.], and Pharmacology[G. J., R. L.], University of Colorado Health SciencesCenter, Denver, Colorado 80262, and Department of Pathology, F. S. Key Medical Center, Baltimore, Maryland 21224 [E. G.]

ABSTRACT

High density oligonucleotide microarrays (OMAs) have been used re-cently to profile gene expression in lung carcinoma tissue homogenates.The length of the lists of potentially interesting genes generated by thesestudies is daunting, and biological and clinical relevance of these listsremains to be validated. Moreover, specific identification of individualbiomarkers that might be used for early detection and surveillance has notbeen the objective of these early studies. We have developed a schema forcombining the data derived from the OMA analysis of a few lung cancercell lines with immunohistochemical testing of tissue microarrays to rap-idly identify biomarkers of potential clinical relevance. Initially, we pro-filed gene expression in lung tumor cell lines using the Affymetrix HG-U95Av2 OMA. RNA from 2 non-small cell lung cancer (NSCLC) cell lines(A549 and H647) and 2 small cell lung cancer (SCLC) cell lines (SHP-77and UMC-19) were tested. Cells from 1 histologically and cytogeneticallynormal bronchial epithelial primary culture from a volunteer who hadnever smoked and 10 samples of histologically unremarkable lung tissuefrom resection specimens served as normalization controls. Array resultswere analyzed with Gene Spring software. Results were confirmed byreverse transcription-PCR in an expanded number of cell lines. We thenvalidated the cell line data by immunohistochemical testing for proteinusing a tissue microarray containing 187 NSCLC clinical samples. Of the20 most highly expressed genes in the tumor lines, 6 were members of thecancer/testis antigen (CTAG) gene group including 5 MAGE-A subfamilymembers and NY-ESO-1. SCLC lines strongly expressed all of theMAGE-A genes as well as NY-ESO-1, whereas NSCLC lines expressed asubset of MAGE-A genes at a lower level of intensity and failed to expressNY-ESO-1. Reverse transcription-PCR of an extended series of 25 lungcancer cell lines including 13 SCLC, 9 NSCLC, and 3 mesothelioma linesindicated that MAGE-A10 and NY-ESO-1 were expressed only by SCLC,and that MAGE-A1, 3, 6, 12, and 4b were expressed by both SCLC andNSCLC. By immunohistochemistry using the monoclonal antibody 6C1that recognizes several MAGE-A gene subfamily members, 44% ofNSCLC clearly expressed MAGE-A proteins in cytoplasm and/or nucleus.Expression of MAGE-A genes did not correlate with survival but didcorrelate with histological classification with squamous carcinomas morefrequently MAGE-A positive than other NSCLC types (P < 0.00002). Weconclude that expression of CTAG gene products, whereas apparently notof prognostic importance, may be useful for early detection and surveil-lance because of a high level of specificity for central airway squamousand small cell carcinomas.

INTRODUCTION

Late stage at detection significantly and adversely affects survivalin lung cancer (1, 2). The most difficult obstacles to earlier detectionare the inaccessibility of the sites of tumor origin and the multiplicity

of sites from which tumors may arise. Several approaches to over-coming these problems are currently being tested ranging from newimaging technologies (helical CT; Refs. 3, 4) to aggressive efforts toidentify high-risk cohorts (5). Biological properties of the tumor cellsthemselves (biomarkers) may also be exploited to identify subjectswho might harbor clinically inapparent tumors. Molecules that areexpressed uniquely or at high level by tumor cells in comparison tonormal tissues and that may be secreted into accessible fluids such asblood, urine, or sputum may be useful as lung cancer biomarkers.

It might be expected that, because of their stark morphologicaldistinction from normal lung cells and their aggressive biologicalbehavior, lung cancer cells may exhibit many molecular differencesfrom non-neoplastic lung cells. To date there have been numerousattempts to identify such molecules with limited success. Lung cancerbiomarkers measurable in the peripheral blood have included carbo-hydrate-rich cell matrix molecules such as carcinoembryonic antigen(6), cytokeratin-derived intermediate filament molecules such as CY-FRA-21.1 (7, 8), tissue polypeptide antigen (TPA) (9), and tissuepolypeptide specific antigen (TPS) (10), peptides such as proGRP(11), neural markers such as neuron specific enolase (12, 13) andchromogranin A (14, 15), and antibodies to immunogenic moleculessuch as Hu (16), calcium channel proteins (17), and p53 (18, 19). Thusfar tests for these molecules have had limited clinical impact becauseof low specificity or low frequency of positive results in early stagepatients. However, it is likely that the list of biomarkers already testedrepresents only a fraction of the molecular changes that occur in tumorcells, and that more sensitive and specific biomarkers remain to bediscovered.

Recently, high-density OMAs3 have been introduced that permitrapid analysis of expression levels simultaneously for large numbersof genes (20). This approach overcomes limitations inherent in ex-pression analysis of single genes. With completion of human genome(21) sequencing, comprehensive OMA expression profiles can becreated for individual tumors as well as for large classes of tumors.Early OMA analyses of lung cancers have centered on phenotypicclassification of specific tumor type (22) and have not specificallyfocused on biomarker discovery.

Our objective in the present study was to discover potentially usefulbiomarkers for lung cancer by first identifying large gene expressiondifferences between tumor cell lines and normal lung using highdensity OMAs. The microarray used (Affymetrix HG-U95Av2) in-corporates 12,600 probes accounting for a large fraction of the ex-pressed human genome. We searched for biomarkers that were over-expressed in relation to normal tissue, because they are more likely tobe useful for detection and screening of accessible specimens such assputum, peripheral blood, or urine than biomarkers that are underex-pressed. We confirmed the expression levels of the gene group(CTAG) most frequently represented on a list of highly expressedgenes by testing a broader series of cell lines using relatively inex-

Received 2/20/02; accepted 5/17/02.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 with18 U.S.C. Section 1734 solely to indicate this fact.

1 Supported by NIH Grants U01 CA85070, Early Detection Research Network, andP50-CA85070.

2 To whom requests for reprints should be addressed, at Departments of Pathology,Box B216, University of Colorado Health Sciences Center, 4200 E. 9th Avenue, Denver,CO 80262. Courier Address: Wilbur A. Franklin, MD, EDRN Biomarker DevelopmentLaboratory, Administrative Office Building, Room 065, 4210 E. 11th Avenue, Denver,CO 80262.

3 The abbreviations used are: OMA, oligonucleotide microarray; RT-PCR, reversetranscription-PCR; IHC, immunohistochemistry; NSCLC, non-small cell lung carcinoma;SCLC, small cell lung carcinoma; TMA, tissue microarray; CT, cancer/testis; ASH,Achete-Scute Homologue.

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pensive RT-PCR methodology. Finally, results of this preliminarytesting were confirmed at the protein level by IHC using a TMAcontaining 187 early stage NSCLCs. This algorithm for biomarkerdevelopment takes advantage of two high throughput microarraytechnologies to rapidly identify potentially important biomarkerslinked to clinical outcomes and prognostic importance.

MATERIALS AND METHODS

Samples and RNA Extraction Procedures. Four established celllines including 2 SCLC (SHP-77 and UMC-19) and 2 NSCLC (A549and H647) lines were analyzed. Before harvesting, SCLC and NSCLCcells were grown in RPMI 1640 supplemented with 5–10% fetalbovine serum. Substrate adherent cultures (SHP-77, A549, and H647)were grown to subconfluence and harvested by rapid removal ofmedium and application of RNeasy extraction medium (Qiagen, Va-lencia, CA) containing guanidinium isothiocyanate. Nonadherent cellswere harvested at a concentration of �1 million cells/ml after �1week in culture after thawing.

Two controls were used for comparison to expression profiles oftumor cell lines. For one control, bronchial epithelial primary cellcultures were obtained from a bronchoscopic biopsy of a healthy48-year-old female who had never smoked and who had volunteeredunder a Colorado Combined Institutional Review Board-approvedprotocol. The biopsy was explanted onto a T25 culture flask contain-ing bronchial epithelial cell growth medium (Clonetics, Inc., Walkers-ville, MD) and epithelial cells were allowed to grow from the explantto a diameter of 1 cm (10 days). Cells were then passaged into asecond T25 flask and grown to �90% confluence (4 days). Theculture cells were again split onto glass coverslips to perform spectralkaryotyping on metaphase cells according to the manufacturer’s pro-tocol (Applied Spectral Imaging, Inc., Carlsbad, CA). A second ali-quot was split into two T75 flasks and again grown to 90% confluence(4 days). One flask was additionally split into three T75 flasks andexpanded for an additional 3 days. Finally, 90% confluent cells wereharvested by removal of culture medium followed by immediateaddition of RNeasy extraction medium as described above. The totaltime from biopsy date to RNA harvest was 21 days. Primary culturesprocessed in this way grow as substrate-adherent monolayers, whichare 100% cytokeratin positive on immunohistochemical staining (23).Spectral imaging karyotype was diploid with no detectable subchro-mosomal abnormalities.

A second set of controls consisted of archival data obtained fromexperiments in which RNA was extracted from benign lung tissueobtained at the time of surgical resection for carcinoma elsewhere inthe lung. For these experiments, duplicate tissue samples from 10 lungspecimens were snap frozen and stored in liquid nitrogen until use.For RNA extraction, frozen tissue fragments were placed in RNeasyextraction medium and homogenized with a Tissue Tearor homoge-nizer (Biospec Products, Bartlesville, OK) followed by filtrationthrough a QIAshredder column. The filtrate was used for RNA ex-traction using the Qiagen RNeasy Mini protocol.

Total RNA extracted from each sample described above was testedfor degradation and applied to a separate HG-U95Av2 microarray.Each control RNA from cultured normal bronchial cells or whole lunghomogenate was used as a separate normalization control in theGenespring filtering algorithms described below.

Preparation of Labeled cRNA and Hybridization to OMAs.Before application to test chips the quality of RNA was tested usingthe one step duplex RT-PCR assay (24). In this assay, the ratio ofshort to long segment �-actin PCR product is used to quantify theextent of RNA degradation. All of the samples in this study had ratiosof �2.6 indicating a low level of degradation.

Double-stranded cDNA was synthesized from 16 to 20 �g totalRNA using an oligodeoxythymidylic acid 24 primer with a T7 RNApolymerase promoter site added to the 3� end (Superscript cDNASynthesis System; Life Technologies, Inc., Rockville, MD). Aftersecond-strand synthesis, in vitro transcription was performed using aT7 Megascript kit (Ambion, Austin, TX) in the presence of biotin-11-CTP and biotin-16-UTP (Enzo Diagnostics, Farmingdale, NY) toproduce biotin labeled cRNA. Twenty �g of the cRNA product wasfragmented at 94°C for 35 min into 35–200 bases in length. Thesample was then added to a hybridization solution containing 100mmol/liter 4-morpholinepropanesulfonic acid, 1 mol/liter Na�, and20 mmol/liter of EDTA in the presence of 0.01% Tween 20 to a finalcRNA concentration of 0.05 mg/ml. Hybridization was performed for18–20 h by incubating 200 �l of the sample to HG-U95Av2 microar-rays, and each microarray was stained with streptavidin-phycoerythrinand scanned at 6-�m resolution by Gene Array scanner G2500A(Hewlett Packard, Boise, ID) according to procedures developed byAffymetrix.

Statistical Analysis. Detailed protocols for data analysis of Af-fymetrix microarrays, and extensive documentation of the sensitivityand quantitative aspects of the method have been described (20, 25).Briefly, mismatch probes act as specificity controls that allow thedirect subtraction of both background and cross-hybridization signals.To determine the quantitative RNA abundance, the average of thedifference representing perfect match � mismatch for each gene-specific probe family is calculated. This data were transferred toGeneSpring software (Silicon Genetics, Redwood City, CA) for ad-ditional analysis.

Using the GeneSpring software package, a two step filtering algo-rithm was implemented to select genes highly expressed by tumorcells in comparison with non-neoplastic lung cells and tissue. In thefirst step, cultured normal epithelial cells were compared with tumorcell lines using the following settings: the 80th percentile of allmeasurements was used as a positive control for each sample, andeach measurement was divided by this control. The 0.1% measure-ment was used as a control for background correction. The measure-ment for each gene was then divided by the corresponding value forthe sample of normal bronchial epithelium. A list was compiled of allof the genes expressed by at least two tumor cell lines at �100� overthe normal control. This filtering step resulted in the identification of42 genes. In the second filtering step, the 50th percentile of allmeasurements was used as a positive control for each sample, andeach measurement was divided by this control. The measurement foreach gene was then divided by the corresponding value for 19 samplesfrom 10 non-neoplastic lung specimens. A list was then compiled of107 genes that were expressed in the tumor cell lines at �20� overthe non-neoplastic tissue. The contents of the two lists was thencompared using the GeneSpring Venn diagram feature and a list of 20highly overexpressed genes common to the two lists was compiled.

The selected genes were annotated using the GeneOntology data-base4 within the NetAffx5 analysis system offered by Affymetrix.GeneOntology stores a dynamic controlled vocabulary organized onmolecular function, cellular component, and biological process thatcan be applied to all organisms. The cellular component attributeswere used to search for genes that were either extracellular (secreted)or transmembrane molecules as potential biomarkers.

The secretory attributes of the selected genes were further investi-gated by looking at the leader sequence signal. Briefly the masterprotein model sequences were obtained from the LocusLink database

4 Internet address: http://www.geneontology.org.5 Internet address: http://www.netaffx.com.

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and analyzed using the program SignalP6 (SignalP version2.0) thatdetects secretory signal peptides in amino acid sequences. The pro-gram splices the first 70 amino acids and runs two different types ofdetection algorithms: one based on neural network prediction and theother based on Hidden Markov Models. Both are trained against alibrary of known signal peptides and calculate a final score, which willassign the protein to one of three classes: (a) nonsecretory; (b) signalanchor (NH2 terminus of type II membrane proteins, uncleaved signalpeptides); and (c) signal peptide (secretory signal).

Spearman correlation was used for clustering of all of the hybrid-ization experiments. To evaluate the expression profile for melanoma-associated antigens, a list of 64 melanoma-associated genes wascompiled using the GeneSpring search feature for melanoma, andPearson correlation was used for clustering of this list (see Fig. 1).

To evaluate the relationship between MAGE-A expression as de-termined by IHC (see below) and survival, log rank test was per-formed using the SPSS statistical package, version 11.0 (SPSS, Inc.,Chicago, IL). �2 analysis was performed using Microsoft Excel.

Confirmatory RT-PCR Assay. Gene expression was confirmedby RT-PCR in 25 cell lines with SCLC, NSCLC, and mesotheliomahistologies (representative gel shown in Fig. 3). The RT-PCR assaywas performed using One-Step RT-PCR system (Life Technologies,Inc.) with MAGE A-1, 3, 4, 6, 10, 12, ASH1, PGP 9.5, and NY-ESO-1primers (Table 1). Reagents were mixed in a single tube for reversetranscription and amplification for 22 to 30 cycles including denatur-ation at 94°C for 1 min, annealing at 55°C for 1 min, and extensionat 72°C for 2 min. The RT-PCR products were separated on 1.5%agarose gels and visualized by UV transillumination of the gelsstained with ethidium bromide.

Preparation of Cell Lines for IHC. Protein expression was eval-uated in the 19 cell lines by immunoperoxidase staining of cell pelletscreated by centrifugation of cultured cells that were then fixed informalin for 30 min and embedded in paraffin. Sections of theresulting paraffin blocks were stained with the same anti-MAGEmonoclonal antibody (6C1; Novacastra, Newcastle, United Kingdom)and by the same methods used for the TMAs described below.

TMA IHC. Paraffin blocks of tumor tissue from 187 patients withNSCLC (stages I-III) were obtained from the University of ColoradoCancer Center and Johns Hopkins Medical Institutions according toIRB-approved protocols. Follow-up of patients represented on theTMA ranged from 18 to 100 months. The distribution of tumorhistologies and clinical stage in this group of patients is shown inTable 2.

The TMAs were assembled using a tissue-arraying instrument(Beecher Instruments, Silver Spring, MD), consisting of thin-walledstainless steel biopsy needles and stylets used to empty and transferthe needle content. The assembly is held in an X-Y position guide thatis manually adjusted by micrometers. A large diameter stylet (1.5mm) was used for sampling, and non-necrotic areas of the blocks wereroutinely over-sampled with three replicate core samples of tumor(different areas) and normal (one, if present) regions from each donor

block. Normal lung and 15 other control tissues were included in eachtissue array block. Four-�m sections of the resulting microarrayblocks were cut with a Leitz microtome. Sections were transferred toadhesive coated slides using the adhesive-coated tape sectioning sys-tem (Instrumedics Inc., Hackensack, NJ; Ref. 22). Subsequently, UVlight treatment of the slides for 60 s polymerized the adhesive coatinginto a plastic layer and sealed the sections to the slides. Thereafter, thetape could be removed in a solvent (Instrumedics Inc.).

The sections were then deparaffinized with standard xylene andhydrated through graded alcohols into water. Antigen retrieval wasperformed using the DAKO Target Retrieval system in a BiocareMedical decloaking chamber. Peroxide blocking was performed with3% hydrogen peroxide in water. After incubation of the mouse mono-clonal anti-MAGE-A antibody, 6C1 (Novacastra) for 1 h at roomtemperature, the DAKO Envision Plus detection was applied for 30min also at room temperature. This was followed by application ofdiaminobenzidine chromogen. The slides were then counterstained inhematoxylin and coverslipped.

Outcome data on cases used for microarray construction was ob-tained from the University of Colorado tumor registry. Patients werefollowed for a median of 51 months (range, 18–100).

Scoring of IHC Results. Each core on the TMA was examined byconventional white light microscopy and the observed staining patterngraded for each core. Percentage of tumor cells positive and intensityof staining was recorded for both tumor cytoplasm and nucleus. Agrading score was obtained by multiplying the intensity of staining onan arbitrary 0–4� scale by the percentage of cells stained separatelyfor nuclear and cytoplasmic staining. The same grading system wasused for both TMA samples and lung cancer cell lines.

RESULTS

OMA Detection of Overexpressed Genes. Cluster analysis ofmicroarray cell line experiments in which cell lines were comparedwith primary cultures of normal bronchial epithelium and homoge-nates of non-neoplastic lung tissue indicated that tumors clusteredaccording to histological type, with the two SCLC lines clusteringtogether, the two NSCLC lines clustering together, and each of thetumor types clustering separately from the cultured benign epitheliumand lung tissue homogenates (Fig. 1). Each sample of non-neoplasticlung tissue invariably clustered with its corresponding duplicate sam-ple. Complete hybridization data for cell lines, the primary culture,and the tissue homogenates are available.7

The dual normalization and filtration process yielded 20 separategenes (Table 3) represented by 21 probe sets that were highly over-expressed by at least 2 of the cell lines. Expression levels were relatedto cell type with 14 genes overexpressed only in SCLC, 4 in NSCLC,and 2 in both SCLC and NSCLC. With the exception of the CTAGgene group, the chromosomal distribution of the overexpressed genesappeared to be random. A wide diversity of gene functions andsubcellular localizations were represented among the gene products,ranging from a membrane-associated ion transport protein to nucleartranscription factors (Table 4). Four of the genes, ASH1, claudin 10,

6 Internet address: http://www.cbs.dtu.dk/services/SignalP-2.0.

7 Internet address: http://uch.uchsc.edu/uccc/research/GeneExpression/index.html.

Table 1 Cell line properties

Cell line HistologyDegradation

indexSpectral

karyotype

UMC19 SCLC 2.58 AbnormalSHP77 SCLC 1.89 AbnormalH647 NSCLC 2.01 AbnormalA549 NSCLC 1.84 AbnormalBronchial epithelium

(� day culture, nonsmoker)Benign Epithelium 1.42 2N (normal)

Table 2 Stage and histology for TMA

Stage 1 Stage 2 Stage 3a Stage 3b Totals

Squamous 52 14 16 9 91Adeno 30 18 16 7 71Large cell 8 3 2 2 15Bronchioloalveolar 9 0 1 0 10Total 99 35 35 18 187

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and the secretogranins I and II, contained signal peptide sequencessuggesting the possibility that the gene products are secreted. Only 1gene, ABCC2, contained a signal anchor peptide sequence.

A notable feature of the list of overexpressed genes is the frequencyof the CT group with 5 MAGE-A and the NY-ESO-1 CTAG genesconstituting 30% of the total list (Fig. 2). Here again levels ofexpression were related to tumor type with SCLC lines more highlyexpressive of MAGE genes than NSCLC. High level overexpressionwas restricted to a subset of MAGE-A subfamily genes (Fig. 2). Whenthe database normalized to cultured bronchial epithelial cells wasqueried regarding levels for all of the MAGE-A genes on the HG-U95Av2 array, MAGE-A2, 3, 6, 10, and 12 were found to be over-expressed at �100-fold, whereas MAGE-A 1, 4b, and 5a were over-expressed at 40–100-fold. The remaining MAGE family members (8,

9, and 11) were not overexpressed or were overexpressed in only asingle tumor. When the query was expanded to include all 64 of themelanoma-associated probes on the array, including 12 for MAGE-A,4 for MAGE-B, 9 for GAGE, 1 for BAGE, and 4 NY-ESO-1 (LAGE-1),we found only the MAGE-A and NY-ESO genes were overexpressed athigh levels (Fig. 1), again suggesting that MAGE profiles are tissue-specific, with lung cancer expressing only a fraction of the genes thathave been associated with melanocytic differentiation.

Confirmatory RT-PCR. By RT-PCR, the differences in expres-sion patterns for several of the highly expressed genes were confirmedin 25 cell lines with SCLC, NSCLC, and mesothelioma histologies(representative gel shown in Fig. 3). As graphically depicted in Fig. 4,most of the high expression markers were detected in similar percent-ages of cell lines, but NY-ESO-1, MAGE-A10, and ASH-1 were

Fig. 1. Dendograms showing clustering of celllines, the bronchial epithelial culture, and tissuehomogenates on the vertical axis based on the anal-ysis of all of the expressed genes (Spearman cor-relation) and by melanoma-associated gene expres-sion (Pearson correlation) on the horizontal axis.High level expression is coded in the diagram asred, low level expression as green, and intermedi-ate expression as yellow or orange. Duplicate sam-ple non-neoplastic lung tissue homogenates areidentified to the right of the expression diagram as“Nl Lu” followed by a patient number and a letteridentifying the individual homogenate sample. Thecell lines and the primary culture of bronchial ep-ithelial cells are indicated by bolding. The locationof a gene cluster containing many CTAG genes isindicated below the diagram.

Table 3 Genes highly overexpressed in lung cancer cell lines

Gene (abbreviation) Genbank no.Affymetrixprobe no.

1 Achaete-Scute homologue 1 (ASH1, HASH1) L08424 40543_at1 Achaete-Scute homologue 1 (duplicate) L08424 40544_g_at2 Aldo-keto reductase family 1, member B10 (aldose reductase, AKR1B10) U37100 37482_at3 ATP-binding cassette, sub-family C (CFTR/MRP), member 2 (ABCC2, canalicular multispecific

anion transporter, cMOAT)U49248 33721_at

4 Cancer/testis antigen (CTAG1, NY-ESO-1, LAGE2) U87459 33636_at5 Claudin-10 (CLDN10, CPETRL3 OSP-L) U89916 39579_at6 Dopa decarboxylase (Aromatic amino acid decarboxylase, AADC) M76180 40201_at7 Insulinoma associated 1 (IA-1, INSM1) M93119 33157_at8 Keratin, hair, basic, 1 (KRTHB1keratin, hHKb1) X81420 36288_at9 KIAA0282 protein (TRIM9, tripartite motif-containing 9) D87458 36903_at

12 Melanoma antigen, family A, 2 (MAGE-A2) L18920 33518_f_at13 Melanoma antigen, family A, 3 (MAGE-A3) U03735 33517_f_at14 Melanoma antigen, family A, 6 (MAGE-A6) U10691 31599_f_at10 Melanoma antigen, family A, 10 (MAGE-A10) U10685 35491_at11 Melanoma antigen, family A, 12 (MAGE-A12) L18877 31480_f_at15 Na�,K�-ATPase, subunit �-III M37457 35670_at16 Neurofilament light polypeptide (NEFL) X05608 40995_at17 Prostaglandin E synthase (PGE synthase; microsomal glutathione transferase homolog; p53

induced)AF010316 38131_at

18 Secretogranin I (chromogranin B) Y00064 33426_at19 Secretogranin II (chromogranin C) M25756 36924_r_at20 Ubiquitin COOH-terminal esterase L1 (ubiquitin thiolesterase, UCHL1, PGP 9.5) X04741 36990_at

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expressed frequently by SCLC but infrequently or not at all byNSCLC. By �2 analysis, differences in expression frequencies weresignificant at Ps of �0.02, �0.03, and �0.03 for MAGE-10, NY-ESO-1, and ASH, respectively.

Correlation of RT-PCR with IHC in Cell Lines. Of the 25 celllines tested by RT-PCR, 19 were also tested by IHC. IHC stainingpatterns of cell lines were similar to those described below for TMA.Cytoplasmic and nuclear staining were frequently present in the samecells but were scored separately. There was nearly complete concord-ance between RT-PCR and IHC results with all of the specimens withIHC scores �1 positive by RT-PCR, and only 1 line that was negativeby IHC and was positive by RT-PCR (�2, P � 0.0003).

TMA IHC. Nuclear and cytoplasmic staining were analyzed bothseparately and combined for prognostic significance. Staining was ofvariable intensity (Fig. 5) with labeling scores (described on page 13)ranging from 0 to 387; scores were interpreted as positive if they were1 or higher. MAGE-A was interpreted as highly overexpressed iflabeling score was �100. Of the 187 arrayed tumor samples, 44%exhibited some level of nuclear or cytoplasmic staining. There was astrong concordance (�2, P � 0.00001) between nuclear and cytoplas-

mic staining, and in those cases where there was discordance thepositive staining was weak. There was also strong correlation betweentumor histology and MAGE-A expression status. Squamous carcino-mas were more frequently positive than adenocarcinomas, large cellcarcinomas, or bronchioloalveolar carcinomas (Table 5; �2,P � 0.00002).

As expected, there was a strong association between stage andsurvival among the patients with tumors represented on the TMA, butlog rank test indicated no significant correlation between MAGE-Aexpression status and survival regardless of whether cases were strat-ified by tumor histology, stage, or by weak or strong (labeling score�100) nuclear staining, weak or strong (labeling score �100) cyto-plasmic staining, or combinations of these patterns.

DISCUSSION

The schema created in this study for biomarker discovery includedthree steps: first, a few lung tumor cell lines were analyzed for geneexpression using high-density oligonucleotide arrays. This step hadthe advantages that pure tumor cells could be tested without micro-dissection and that usage of microarrays was efficient and minimal. Atthis step, a stringent filtering algorithm was used incorporating bothcultured epithelial cells as well as lung tissue homogenates as nor-malizing controls to limit the list of highly overexpressed genes to just20. Remarkably, 30% of the genes that survived the filtration were

Fig. 2. Expression of MAGE A and NY-ESO-1 genes normalized to expression ofcultured normal bronchial epithelium. Highest levels were found in SCLC lines butseveral genes (see text) were also overexpressed in NSCLC.

Fig. 3. RT-PCR products visualized in ethidium bromide-stained agarose gels. Expres-sion of MAGE A-3/6 is visible in products prepared from a variety of cell types, whereasexpression of MAGE A-10 and NY-ESO-1 is confined primarily to SCLC.

Table 4 Properties overexpressed genes and gene products

Gene abbreviation Cell type Function Subcellular localization Predicted secretionChromosomal

location

Claudin-10 Both Caspase Integral membrane protein Signal peptide 13q31-q34PGP 9.5 Both Proteosome regulatory protein Nuclear/cytoplasmic Nonsecretory protein 4p14Aldose reductase NSCLC Aldehyde dehydrogenase Cytoplasm Nonsecretory protein 7cMOAT NSCLC Ion/peptide transport Integral membrane protein Signal anchor 10q24hHKb1 NSCLC Cell size/shape/motor control Cytoplasmic Nonsecretory protein 12q13PGE synthase NSCLC Prostaglandin metabolism Intracellular/perinuclear Nonsecretory protein 9q34.3ASH1 SCLC Transcription factor Nucleus Signal peptide 12q22-q23Chromogranin B SCLC Protein secretion Secretory granule Signal peptide 20pter-p12Chromogranin C SCLC Calcium binding Secretory granule Signal peptide 2q35-q36Dopa decarboxylase SCLC Aromatic amino acid metabolism Mitochrondrial outer membrane Nonsecretory protein 7p11IA-1 SCLC Transcription factor Nucleus Nonsecretory protein 20p11.2KIAA0282 SCLC Function not defined Cytoplasmic Nonsecretory protein 14MAGE-A2 SCLC Tumor antigen Nucleus/plasma membrane Nonsecretory protein Xq28MAGE-A3 SCLC Tumor antigen Nucleus/plasma membrane Nonsecretory protein Xq28MAGE-A6 SCLC Tumor antigen Nucleus/plasma membrane Nonsecretory protein Xq28MAGE-A10 SCLC Tumor antigen Nucleus/plasma membrane Nonsecretory protein Xq28MAGE-A12 SCLC Tumor antigen Nucleus/plasma membrane Nonsecretory protein Xq28Na�,K�-ATPase SCLC Sodium/potassium-transporting ATPase Integral membrane protein Nonsecretory protein 19q13.2NEFL SCLC Cell size/shape/motor control Cytoplasmic/nuclear lamina Nonsecretory protein 8p21NY-ESO-1 SCLC Tumor antigen Membrane fraction Nonsecretory protein Xq28

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CTAG genes. The second step consisted of confirmation by RT-PCRof overexpression of selected candidate biomarkers in an expanded setof cell lines. This provided an independent and economical way forassessing expression profiles in cell lines of specific histological type.It also proved to be highly predictive of protein expression level. Thethird step was the application of specific monoclonal antibody to alarge TMA that was linked to clinical follow-up. This provided a rapidway to assess prognostic importance of expression of the candidatebiomarker. It also provided an opportunity to verify the distribution ofprotein at a cellular level. A step beyond this discovery schema wouldconsist of testing blood, urine, and sputum for the presence of specificRNA and protein in clinical cohorts with and without invasive carci-noma or preinvasive lesions. Such clinical testing is expensive andtime consuming, and before being launched requires the maximumrigor in estimating specificity of the putative biomarker. The schemaused in this study efficiently answers many of the preliminary ques-tions that should be answered before proceeding to larger clinicaltrials.

A surprising feature of the list of biomarkers that emerged from this

schema was strong representation of CTAG genes. This gene groupcomprised 30% of the 20 biomarker genes identified. Expression ofCTAG genes is restricted to normal testicular (and ovarian) germ cellsand tumors of a number of cell types (26, 27). The first of these genesto be identified were the MAGE-A genes, which were originallynamed MAGE 1 through 3. They were discovered because they elicitan HLA I-dependent cytotoxic response in sensitized lymphocytesagainst the melanoma cell line MZ2-MEL (28). It is of interest thatthis first report indicated that MAGE expression could be demon-strated not only in melanoma cell lines but also in SCLC and NSCLCas well. The original 3 MAGE genes were soon supplemented by 9additional MAGE genes discovered by screening cosmid librariestemporarily bringing the total number of MAGE genes to 12 (29), allencoded at chromosome Xq28 (29, 30). Sequencing of chromosomalregion Xp21.3 led to the identification of a second subfamily ofMAGE genes named MAGE-B (31–33). In recent years, the list ofMAGE family genes has continued to increase, and the MAGE familynow is thought to contain 55 homologous members divided into 9subfamilies (34). Although structurally homologous, some recentlydescribed MAGE subfamilies are ubiquitously expressed (35–37) andare not members of the CTAG gene group. Early reports indicatingthat MAGE genes may be expressed by tumors of many types (28)have been confirmed in many different laboratories for many differenttypes of tumors including brain (38, 39), skeletal muscle (40), esoph-agus and stomach (41), Reed-Sternberg cells (42), bladder (43), bili-ary tract (44), and breast (45).

A second CTAG gene family, NY-ESO-1, was identified by autol-ogous screening of a cDNA expression library constructed from a caseof esophageal carcinoma (26). A similar if not identical gene wasreported a short time later as LAGE-1 (46). Like the MAGE-A genefamily, NY-ESO-1/LAGE-1 maps to chromosome Xq28 (46).

Expression of CTAG genes by lung tumors has been documented byIHC and RT-PCR in a limited number of studies. In two separatestudies using monoclonal antibodies 57B and MA454 that react withMAGE-A protein, Jungbluth et al. (47) have found heterogeneousexpression in 32% and 56% (48) of NSCLC, respectively. IHC studiesare complicated by the high degree of homology among differentMAGE-A proteins so that many anti-MAGE antibodies cross-reactwith several different MAGE-A subfamily members (49–51). Themonoclonal antibody used in the present study, 6C1, reacts with anepitope in the COOH-terminal regions of MAGE-A1, -A2, -A3, -A4,-A6, -A10, -A11, and -A12 (51) and may thus be considered an antipan-MAGE-A reagent. The use of antibody in a sensitive immunoper-oxidase procedure on 187 tumors in a TMA linked to clinical andhistological data allowed us to determine that 44% NSCLC expressMAGE-A protein, that expression varied according to tumor histol-ogy, and that expression is unrelated to prognosis.

By RT-PCR, MAGE-A1, -A3, and B2 RNA sequences have beenfound recently in 70%, 85%, and 85% of a small series of NSCLC andis often accompanied by promoter hypomethylation (52). Also ofinterest, this report indicated that bronchial epithelium from a largeproportion of 20 former smokers without lung carcinoma also fre-quently expressed MAGE genes and suggested that MAGE gene

Fig. 4. Graphic representation of RT-PCR results for tumor cell lines of various celltypes using primers for genes found to be overexpressed at high level by OMA. Markerswith specificity for SCLC include NY-ESO-1, MAGE-A10, and ASH1.

Fig. 5. TMA stained for MAGE-A proteins using the monoclonal antibody 6C1 in asensitive immunoperoxidase method. On the left is an image of the microarray slide andon the right a high magnification of tumor cells exhibiting strong (4�) nuclear and weaker(2�) cytoplasmic staining.

Table 5 Histology versus MAGE-A status

Histology

MAGE-A status

Positive Negative Totals

Squamous carcinoma 57 34 91Adenocarcinoma 19 52 71Large cell carcinoma 3 12 15Bronchioloalveolar carcinoma 1 9 10Totals 80 107 187

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expression may occur early in lung carcinogenesis and may be asuitable target for lung cancer prevention.

Whether MAGE-A protein can be found in the blood, urine, orsputum of patients with lung cancer is not known at present. Theabsence of signal sequences in the MAGE-A genes suggests thatMAGE-A proteins are not actively secreted. However, it may not beessential that a protein be actively secreted to be useful as a biomarkerbecause protein may be released from dying tumor cells, which arefrequent in lung carcinomas. Also, tumors that occur frequently incentral airways (SCLC and squamous carcinomas) are most oftenMAGE-A/NY-ESO-1-positive, suggesting that these biomarkers maybe particularly useful for sputum testing.

An advantage of OMA analysis for potential biomarkers is theability to interrogate microarray data for expression patterns of all ormany members of entire functional pathways. In this context it is ofinterest that melanoma genes other than the CTAG genes were foundnot to be overexpressed in lung cancer lines indicating that there aresignificant differences in activation of functional pathways betweenthese two tumor types. The function of CTAG genes in general andMAGE-A genes in particular is not known. Necdin, a 325 amino acidprotein with 30% homology to MAGE proteins (reviewed in Ref. 53)has been shown recently to interact with p53, inhibiting p53-inducedapoptosis. Whether or not the MAGE proteins function in a similarway is unknown at present but such a function would be consistentwith the frequent expression of MAGE proteins in aggressive malig-nancies.

Several of the remaining highly overexpressed genes have proper-ties that suggest they may be useful biomarkers including signalpeptide coding sequences. One of four protein products of genescontaining signal peptides has been tested as a lung cancer biomarker.Chromogranin A has been found in the serum of 50% (14) of all of theneuroendocrine tumors and 61–70% (15, 54) of SCLC, and is gener-ally regarded as a promising marker for the diagnosis of neuroendo-crine neoplasia. A second putatively secreted protein, ASH1, has beenassociated previously with neuroendocrine neoplasia (55) but has notbeen tested as a serum or urinary biomarker. That this protein is in factsecreted is doubtful, given its role as a transcription factor and itsnuclear localization. Other overexpressed genes associated with neu-roendocrine differentiation in pulmonary neoplasia include IA-1 (56)and DOPA decarboxylase (57, 58).

Many of the listed genes may be useful for detection and monitor-ing of NSCLC, or both SCLC and NSCLC. These include aldo-ketoreductase family 1, ABCC2 (59), basic hair keratin 1, prostaglandinE synthase (60), PGP 9.5 (61, 62), Na�, and K(�)-ATPase (63–65).Additional evaluation of these candidate biomarkers either alone or incombination will be required to establish the utility of these overex-pressed genes as useful biomarkers for early detection and monitoring,and to better define their biological role. Better understanding ofexpression profiles for these genes may also suggest novel approachesto therapeutic intervention lung carcinoma.

Several other large-scale gene expression analyses of lung cancerhave been reported recently. An OMA analysis of 186 pulmonarytumors also using the HG-U95A microarray has been performedrecently on tumor homogenates (22). Cluster analysis of the resultingdata indicated that gene expression profiles corresponded to histolog-ical type for SCLC, squamous carcinoma, and carcinoid tumor, butadenocarcinomas were heterogeneous and could be subdivided intofive categories including one for metastasis from colon. Three of thegenes identified in the prior study also appear on the present list ofoverexpressed genes, ASH-1, IA-1, and DOPA decarboxylase. An-other analysis of tumor homogenates using 24,000 element cDNAmicroarrays has also been published recently (66). From among theseveral hundred genes with expression patterns that discriminate

among differing histological types, only four genes were also presentin the current list of overexpressed genes, PGE synthase, cMOAT,ASH-1, and IA-1. Finally, in a recent SAGE analysis (67), 115 highlydifferentially expressed genes were reported and among these was thealdoketo reductase, member B10 gene. CTAG genes were not listed inany of these large-scale gene expression studies.

This small number of overlapping genes between the current andother recent studies has several possible explanations. First, the num-ber of specimens examined is smaller in the present analysis than inthe other analyses. Second, we attached only limited importance tointertumor heterogeneity of gene expression in this current study. Weassumed that lung cancers, because they are heterogeneous in almostevery respect, are likely to also exhibit a high degree of heterogeneityin gene expression profiles. We expected that there would be a greatimbalance of many cellular pathways engendered by chromosomaland genetic instability, potentially resulting in high levels of over-expression of specific genes. Our objective was to identify these genesand to estimate the likelihood that their products could serve as tumorbiomarkers. Finally, we made no distinction among tumors of varioushistological origins in screening for highest level overexpression. Thisallowed us to focus on genes that are massively overexpressed incancer cells in comparison to normal lung regardless of the cell type,an approach specifically tailored for biomarker discovery.

We conclude that the detailed gene expression data can now bereadily obtained using OMAs. Testing of even a few suitable speci-mens can identify potential biomarkers for lung and other cancers thatcan be rapidly validated by high throughput testing of TMA linked toclinical outcome. This model should be a rich source of promisingnew biomarkers. To exploit these new analytical tools it will beimperative that correlative biological materials be collected duringlarge-scale screening and treatment trials that are currently beingdesigned.

ACKNOWLEDGMENT

We thank Dr. Marileila Varella-Garcia for spectral karyotype analysis of thebronchial epithelial cell culture.

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CANCER/TESTIS ANTIGEN GENE EXPRESSION IN LUNG CANCER

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