Discovery of di�erentially expressed genes in human breast cancer usingsubtracted cDNA libraries and cDNA microarrays

Yuqiu Jiang*,1, Susan L Harlocker1, David A Molesh1, David C Dillon1, John A Stolk1,Raymond L Houghton1, Elizabeth A Repasky2, Roberto Badaro3, Steven G Reed1,4 andJiangchun Xu1

1Corixa Corporation, 1124 Columbia Street, Suite 200, Seattle, Washington, WA 98104, USA; 2Department of Immunology,Roswell Park Cancer Institute, Bu�alo, New York, NY 14263, USA; 3Hospital Aristides Maltez, Salvador, Bahia, Brazil;4Department of Pathobiology, University of Washington, Seattle, Washington, WA 98195, USA

Identifying novel and known genes that are di�erentiallyexpressed in breast cancer has important implications inunderstanding the biology of breast tumorigenesis anddeveloping new diagnostic and therapeutic agents. In thisstudy we have combined two powerful technologies, PCR-based cDNA subtraction and cDNA microarray, as a highthroughput methodology designed to identify cDNA clonesthat are breast tumor- and tissue-speci®c and are over-expressed in breast tumors. Approximately 2000 cDNAclones generated from the subtracted breast tumor librarywere arrayed on the microarray chips. The arrayed targetcDNAs were then hybridized with 30 pairs of ¯uorescent-labeled cDNA probes generated from breast tumors andnormal tissues to determine the tissue distribution andtumor speci®city. cDNA clones showing overexpression inbreast tumors by microarray were further analysed byDNA sequencing, GenBank and EST database searches,and quantitative real time PCR. We identi®ed severalknown genes, including mammaglobin, cytokeratin 19,®bronectin, and hair-speci®c type II keratin, which havepreviously been shown to be overexpressed in breast tumorsand may play an important role in the malignance ofbreast. We also discovered B726P which appears to be anisoform of NY-BR-1, a breast tissue-speci®c gene. Twoadditional clones discovered, B709P and GABAA receptorp subunit, were not previously described for their over-expression pro®le in breast tumors. Thus, combining PCR-based cDNA subtraction and cDNA microarray allowedfor an e�cient way to identify and validate genes withelevated mRNA expression levels in breast cancer thatmay potentially be involved in breast cancer progression.These di�erentially expressed genes may be of potentialutility as therapeutic and diagnostic targets for breastcancer.Oncogene (2002) 21, 2270 ± 2282. DOI: 10.1038/sj/onc/1205278

Keywords: breast cancer; genes; PCR-based cDNAsubtraction; cDNA microarray; quantitative PCR

Introduction

Breast cancer is one of the most common malignanciesand a leading cause of death among women. There are200 000 new cases diagnosed every year and about50 000 women die annually from breast cancer in theUnited States (Lopez-Otin and Diamandis, 1998).Although localized breast cancer can be e�ectivelytreated, the prognosis of breast cancer is poor andthere are a very limited number of treatment optionsavailable for patients with advanced and metastaticforms of the disease. Thus, there is a clear need to ®ndnew targets for the development of new therapeuticagents as well as breast tumor markers for monitoringboth progression and treatment of the disease.

Genetic alterations resulting in altered mRNA andprotein levels have been described in breast tumorigen-esis, such as the activation or ampli®cation of oncogenesor the loss of tumor suppressor genes (Jones et al., 1995;Walker et al., 1997). Historically, a number of thesegenes have been identi®ed such as Her-2/neu, a surfacegrowth factor receptor shown to be overexpressed in30% of breast cancers (Hadden, 1999; Disis andCheever, 1997). The p53 gene that normally functionsas a tumor suppressor gene has been found to beparadoxically overexpressed in 57% of breast tumors asan outcome of gene mutation and changes in proteinstabilization (Hadden, 1999). MUC-1 is another genethat is up regulated about 10-fold in 90% of breasttumors (Hadden, 1999; McKenzie and Xing, 1990). Eachof these proteins has become the target for novelimmunotherapy approaches in the treatment of breastcancer (Cheever et al., 1995; Ozturk et al., 1992;Apostolopoulos et al., 1996). It should be noted,however, that all genes mentioned above show expres-sion in some normal tissues that could cause toxicity andnon-speci®city when used as therapeutic and diagnosticagents. Furthermore, breast cancer is a disease withextreme complexity (Lopez-Otin and Diamandis, 1998;Jones et al., 1995; Walker et al., 1997). Identifyingadditional genes that may be up- or down-regulated inbreast tumors will help us to better understand theprocess of breast tumorigenesis and provide additionalmarkers for treatment and diagnosis of the disease.

Oncogene (2002) 21, 2270 ± 2282ã 2002 Nature Publishing Group All rights reserved 0950 ± 9232/02 $25.00

www.nature.com/onc

*Correspondence: Y Jiang; E-mail: jiang@corixa.comReceived 24 August 2001; revised 14 December 2001; accepted 19December 2001

ON

CO

GE

NO

MIC

S

Suppression subtractive hybridization (SSH) technol-ogy, also known as PCR-based cDNA subtraction, wasdeveloped by Diatchenko et al. (1996). This methodallows selective ampli®cation of target cDNAs, whilesimultaneously suppressing non-target cDNA ampli®-cation. An advantage of the PCR-based cDNAsubtraction method is that in addition to the recoveryof abundant clones regularly obtained by conventionalcDNA subtraction (Xu et al., 2000), rare transcriptsare also recovered due to the incorporated hybridiza-tion and PCR steps that normalize sequence abun-dance. As a result, the subtracted cDNA librarygenerated by SSH technology contains an increasednumber of di�erentially expressed genes. Recentadvances in technology, especially in the area ofhigh-density cDNA microarrays (Schena et al., 1995,1996; DeRisi et al., 1997), have allowed us tosimultaneously monitor the gene expression pro®lesof thousands of genes, thereby providing a way torapidly identify genes up-regulated in breast cancers.

In this study our goal was to identify breast tumor-and tissue-speci®c genes as targets for immunotherapy.Historically, the development of immunotherapy ofcancer was focused on the induction of immuneresponses against tumor-speci®c antigens, since theore-tically, immune responses targeted to tumor-speci®cantigens would be exclusively against the tumor andwould cause no damage to the normal cells. Also onecould reasonably presume that self-tolerance to tumor-speci®c antigens could be broken more easily than totissue-speci®c self-antigens. In 1994 Coulie et al.discovered that a melanoma-speci®c CD8+ T cell clonegrown from a melanoma patient was against wild-typetyrosinase, a melanocyte speci®c gene (Coulie et al.,1994). Subsequently, a number of similar ®ndings thatthese melanoma-speci®c CD8+ T cells indeed recog-nized melanocyte-speci®c antigens rather than melan-oma-speci®c antigens were published (Bakker et al.,1994; Cox et al., 1994; Kawakami et al., 1994). Basedon these ®ndings and given that breast tissues aredispensable, inducing immune responses against tissue-speci®c antigens might represent a reasonable approachfor breast cancer therapy whose autoimmune sidee�ects would be acceptable. We utilized SSH technol-ogy and cDNA microarray as an initial highthroughput screen followed by quantitative real timePCR analysis to discover genes that are overexpressedin breast tumor and/or breast normal tissues. Here wereport on four genes, B709P, hair-speci®c type IIkeratin, B726P, and GABAa receptor p subunit, whichare overexpressed in primary and metastatic breasttumors.

Results

Characterization of the subtracted cDNA library

Poly(A)+ RNAs from three primary breast tumorswere used as the starting material for tester cDNAsynthesis. In order to identify breast tumor- and tissue-

speci®c sequences, mRNAs from a variety of normaltissues and cells including breast, brain, liver, pancreas,and peripheral blood mononuclear cells (PBMC) wereutilized for driver cDNA synthesis. The library wasconstructed according to the established protocol(Clontech Inc. CA, USA) with modi®cations. In theoriginal procedure, the tester and driver cDNAs weredigested with RsaI, a four base-pair DNA endonu-clease, creating cDNA fragments with an average sizeof 256 bp. To maximize the sensitivity of the cDNAmicroarray under the hybridization conditions used, wechose to increase the average size of the cDNAfragments. To accomplish this, we substituted RsaIwith a combination of ®ve six-base cutter DNAendonucleases. Theoretically, the average cDNA sizeafter digestion with this group of enzymes is 819 bp.We analysed 96 randomly selected clones from thesubtracted library and the average cDNA insert sizewas approximately 650 bp (data not shown). Subtrac-tion e�ciency was determined by two methods: dotblot and DNA sequencing. We found that about onethird of the 96 randomly selected clones showedpositive hybridization to the tester probes, while onlya few clones showed positive hybridization to thedriver probes. All the clones showed up positive withsubtracted cDNA probes (data not shown). We nextperformed DNA sequencing analysis of these 96 clones,which revealed several genes that are known to beoverexpressed in breast tumors (Table 1). These genesare mammaglobin (Watson and Fleming, 1996),keratin (Trask et al., 1990), and estrogen receptor(Kurebayashi et al., 2000). Of the 96 clones examined,four clones did not match any entry (550% identity)in the public databases including GenBank DNA andhuman EST. Additionally, forty clones were found tohave no GenBank matches but did exhibit signi®canthomology (498% identity) to one or more humanESTs. Furthermore, relatively few housekeeping geneswere recovered and most of the clones were representedonly once in this 96 clone set. Collectively, these datasuggested that the library was well subtracted andnormalized, and contained su�cient complexity toexploit cDNA microarray analysis.

cDNA microarray analysis

A total of two thousand randomly selected cDNAclones generated by PCR-based cDNA subtractionwere analysed by microarray with 30 probe pairs. Theprobes consisted of 22 primary breast tumor samples;three breast tumors metastasized to lymph nodes, threebreast tumor pleural e�usion samples, two normalbreast tissue samples, and 30 samples from a variety ofhuman normal essential tissues. In most cases, a breasttumor was paired randomly with a normal tissue. Theaverage ¯uorescent intensity of all probes generatedfrom breast tumors including metastatic breast tumorswas compared with the average ¯uorescent intensity ofall the normal tissues excluding normal breast tissues.Sixty-two clones with a ratio between these two probegroups (all breast tumors vs all normal non-breast

Oncogene

Gene discovery and profiling in breast cancer

Y Jiang et al

2271

tissues) greater than three were selected and sequenced,as shown in Table 2. Among these clones there were 31known genes including mammaglobin, 40 kDa keratin,and ®bronectin, which have previously been shown tobe associated with breast cancers (Watson andFleming, 1996; Loridon-Rosa et al., 1990; Trask etal., 1990).

Identification of cDNAs differentially expressed in breasttumor

The 62 clones with larger than threefold overexpressionin breast tumors were further analysed by examiningthe microarray pro®le of each individual clone for itsexpression in each probe pair tested in order to identifyclones that are overexpressed in breast tumors vsnormal tissues including normal breast (tumor-speci®c)and clones overexpressed in breast tumors vs normalnon-breast tissues (tissue-speci®c). We looked forclones that had a strong signal (breast tumor signalvs paired normal tissue signal is equal to or greaterthan three) in multiple breast tumor samples (at least20% of breast tumors) while having very little or nosignal in the majority of the normal non-breast tissuesamples. Based on these criteria, we selected fourclones which had the best breast tumor/tissue-speci®cexpression pro®le for further characterization. The fourclones selected were not necessarily the clones with thehighest tumor/normal ratio, but rather the ones withthe cleanest expression pro®le in the normal non-breasttissues. Figure 1 shows the microarray pro®les of thesefour genes discovered from the DNA microarray chip:B709P, B726P, hair speci®c type II keratin, andGABAA receptor p subunit. It is evident from themicroarray pro®le that these genes are overexpressed inbreast tumors and/or normal breast tissues comparedto other normal tissues. Another characteristic is thatwhile each of the four genes is expressed in a di�erentsubset of the breast tumor panel, there is complementa-tion such that, taken together, expression of these fourgenes shows threefold upregulation in 64% (18 out of27) of the breast tumor samples (Houghton et al.,2001).

The cDNA microarray results indicated that B709Pis at least threefold overexpressed in approximately20% of the breast tumors. The two normal breast andhuman epithelial mammary gland cell (HEMC)samples showed no expression. B709P also showedsome expression in normal lymph node, trachea, andsalivary gland. Other normal tissues, such as brain,heart, pancreas, liver, kidney, and bone marrow didnot show any expression on the array (Figure 1). Theaverage overexpression ratio of B709P in breast tumorsvs non-breast normal tissues is 3.1 (Table 2). The fulllength B709P cDNA was recovered from a breasttumor oligo(dT)-primed cDNA library by hybridiza-tion screening using the original cDNA fragmentgenerated from the subtracted breast tumor library asa probe. Complete sequencing of B709P resulted in a491 bp sequence encoding an 85 amino acid predictedopen reading frame (ORF) (Figure 2). PSORT, a

program for protein localization prediction, predictedB709P to be a secreted protein with a 17 amino-acidsignal peptide sequence for secretion at its aminoterminal end. The cDNA sequence of B709P isidentical to full length insert cDNA clone ZA74F12in the GenBank nonredundant DNA database (Acces-sion number AF086120). A BlastP search of theGenBank protein database failed to reveal anysigni®cant matches. This protein has a high prolinecontent comprising about 20% of its coding sequence.

The second gene identi®ed was the human hair-speci®c type II keratin gene (hHb1). Microarray datashowed that hHb1 has at least threefold overexpressionin approximately 30% of breast tumors compared tothe paired normal tissues. Additionally, some expres-sion was observed in human mammary epitheliumcells. Signi®cantly, hair-speci®c type II keratin expres-sion was not seen in normal breast or any other normaltissues examined (Figure 1). The average overexpres-sion of hHb1 in breast tumors vs non-breast normaltissues is 3.5 (Table 2). The hHb1 gene is located onthe q11-q13 region of chromosome 12 where the typeII keratin cluster resides (Bowden et al., 1998). It hasbeen demonstrated that hHb1 is abundantly expressedin the di�erentiating cortex of growing hair (Bowden etal., 1998). Additionally, Regnier et al. (1998) havedemonstrated that a truncated version of the hHb1gene, which is missing about 800 base pairs of DNA atthe 5' end, is expressed in human breast carcinomas.We have found both full length and truncated forms ofhHb1 gene in breast tumors.

The third gene, B726P, was at least threefoldoverexpressed in 36% of breast tumors and was alsoexpressed at a lower level in one of two normal breasttissues by cDNA microarray analysis. In two breasttumor samples, B726P has a greater than 20-foldincrease in expression compared to the paired normaltissues (Figure 1). The average overexpression ofB726P in breast tumors vs non-breast normal tissuesis 3.6 (Table 2). Full-length cloning e�orts resulted in a3681 base pair cDNA and a GenBank database searchwith this sequence revealed that B726P matched toNY-BR-1, which was recently identi®ed by usingserological analysis of recombinant expression libraries(SEREX) method and was predicted to function as atranscription factor based on its motif (Jager et al.,2001). B726P also has several matching EST hits fromnormal breast, breast tumor, and testis. MultiplemRNA splice forms exist for this gene, which generateputative ORFs of 1002 amino acids, 650 amino acids,and 317 amino acids (Harlocker et al. manuscript inpreparation). The predicted 317 amino-acid sequenceshares a 42% homology with a hypothetical protein ofunknown function in GenBank, KIAA0565 (GenBankaccession number BAA25491). The longest predicted1002 amino acid ORF is identical to amino acid 340 to1341 of NY-BR-1.

The cDNA microarray also identi®ed g-aminobutyricacid (GABAa) receptor p subunit as an overexpressedgene in breast tumors and normal breast tissues. Thisprotein was ®rst reported as a novel subtype of the

Gene discovery and profiling in breast cancer

Y Jiang et al

2272

Oncogene

Table 1 Summary of GenBank and EST database search results of the randomly selected 96 cDNA clones from subtracted library

GenBank accession number GenBank identity Number of clones

AF015224 Human mammaglobin mRNA 3Z22754 Human HLA-Cw6 Exons 6-8 2M16247 Human gamma actin gene 2J03607 Human keratin gene 1X03635 Human estrogen receptor 1U72938 Human putative DNA dependent ATPase and helicase 1J04718 Human proliferating cell nuclear antigen 1AF072860 Human protein activator of interferon-induced protein kinase 1AB006782 Human galectin-9 isoform 1X03342 Human ribosomal protein L32 1AJ223812 Human caldesmon 3' UTR 1U97519 Human podocalyxin-like protein 1AF068754 Human heat shock factor binding protein 1 1AB011125 Human KIAA0553 gene 1AL021683 Human cDNA homologous to Yeast SCO1 and 2 gene 1AC004752 Human BAC clone 8e5 1AF077345 Human C-type lectin 1Z30183 Human mig-5 gene 1AF070639 Human cDNA clone unknown 24700 1AF023268 Human clk2 kinase 1AJ001902 Human thyroid receptor interacting protein 1M55998 Human alpha-1 collagen type I 1U39840 Human hepatocyte nuclear factor-3 alpha 1S50732 Human immunoglobulin M light chain V region 1U22970 Human interferon-inducible peptide (6-16) gene 1AF012281 Human PZD domain containing-protein 1AF001893 Human MEN1 region clone 1X93036 Human MAT8 protein 1AF030424 H. sapiens histone acetyltransferase 1D44467 H. sapiens 26S proteasome subunit p45 1X03558 H. sapiens elongation factor 1 alpha subunit 1L12401 Human nuclear lamin A and C gene 1L07615 H. sapiens neuropeptide Y receptor Y1 mRNA 1M25171 Human Hsa3 mitochondrial cytochrome oxidase subunit II 1Z81308 BAC397C4 on chromosome 22q12 contain ESTs and STS 1D29805 Human beta-1,4-galactosyltransferase 1AJ224442 Human putative methyltransferase 1D00017 Human mRNA for lipocortin II 1X69150 Human ribosomal protein S18 1M33197 Human GAPDH gene 1AB007187 Human robosomal protein P0 1

W80987 EST 1AA402358 EST 1C04353 EST 1T81537 EST 1W73936 EST 1AA022617 EST 1AA315629 EST 1AA582004 EST 1AA235437 EST 1AA716156 EST 1R26228 EST 1AA150277 EST 1AA101311 EST 1AA299023 EST 1AA535081 EST 1R09841 EST 1AA039895 EST 1W37653 EST 1C02141 EST 1AA507382 EST 1AA676608 EST 1AA442821 EST 1W49801 EST 1AA487683 EST 1W07459 EST 1AA838499 EST 1W23450 EST 1

Continued

Oncogene

Gene discovery and profiling in breast cancer

Y Jiang et al

2273

GABAA receptor subunit, sharing 30 ± 40% amino acidhomology with other GABAA family members (Hed-blom and Kirkness, 1997). The microarray dataindicated that approximately 30% of the breast tumorsexamined have more than threefold overexpression. Wealso detected some GABAA receptor p subunitexpression in normal breast, uterus, and trachea(Figure 1). The average overexpression of GABAa

receptor p subunit in breast tumors vs non-breastnormal tissues is 4.0 (Table 2). GABAa receptors wereshown to be located on central neurons and astroglia,and were also detected on non-neuronal cells includingendocrine cells of the pituitary pars intermediate andsmooth muscle cells of the urinary bladder and uterus(Amenta et al., 1988; Erdo et al., 1989). The functionof GABAA receptors in non-neuronal cells is not clear,although their function in the uterus appears to berelated to the regulation of uterine motility byinhibiting contraction (Majewska and Vaupel, 1991).The expression of the p subunit of GABAA at themRNA level has been shown to be present at low levelsin prostate, ovary, placenta, gall bladder, lung, smallintestine, and at a high level in uterus by PCR(Hedblom and Kirkness, 1997). A hybridization signalfrom prostate, ovary, placenta, bladder, lung, andsmall intestine was not observed on the microarrayimages, but signal in uterus was seen. The di�erence wehave seen here may be due to detection sensitivitydi�erence between these two methods.

Quantitative real-time PCR analysis

B709P, hair-speci®c type II keratin, B726P, andGABAA receptor p subunit, were further evaluatedby quantitative real time PCR on panels consisting ofprimary breast tumors, metastatic breast tumors,normal breasts, and other normal tissues. Data arepresented in Figure 3. The expression pro®les fromreal-time PCR are consistent with the microarray data.Additionally, real time PCR further demonstrated thatthe patterns of gene expression in breast tumors areconsiderably di�erent among these genes.

Similar to what we observed with microarray, B709Pwas expressed in 24% (6 out of 25) of breast tumorsand detected in fewer breast tumors than the otherthree genes. The three normal breast samples did notshow any expression, while normal trachea and spleendid show some level of expression for B709P. Hair-speci®c type II keratin showed a very breast tissuespeci®c expression pattern and was overexpressed in52% (13 out of 25) of breast tumors, with very lowexpression in normal prostate and adrenal gland. Twoof the breast tumors showed very high copy numbers.B726P revealed overexpression in 44% (11 out of 25)of breast tumors and had no expression in the normaltissues examined except for one of the three normalbreast samples, which has moderate expression com-pared to breast tumors. The GABAa receptor p subunitreal-time PCR pro®le is consistent with its microarrayresults. It is overexpressed in 36% (9 out of 25) ofbreast tumors and is also detected at low to moderatelevels in normal breast, trachea, and uterus. Othernormal tissues tested did not show expression. Insummary, consistent with the results from microarrayanalysis, the quantitative PCR con®rmed that therewas di�erential expression between breast tumors andother non-breast normal tissues in all genes and thatthe percentage of breast tumors showing overexpres-sion varies from gene to gene, ranging from 20% toover 50%. Another feature observed from thequantitative PCR is that these four genes are over-expressed in di�erent subsets of breast tumors. Thisresult corresponds very well with the previous observa-tions that the genetic variations in breast tumors arediversi®ed (Lopez-Otin and Diamandis, 1998; Jones etal., 1995; Walker et al., 1997).

The gene expression pro®les of the four genes inmetastatic breast tumors were also analysed by realtime PCR. The metastatic breast tumors tested werebreast tumors metastasized to ovary and to lymph nodetissues. Primary breast tumors and normal breastsample were also included in the panel in order tocompare gene expression levels between primarytumors and metastatic tumors. As shown in Figure 4,

Table 1 (Continued )

GenBank accession number GenBank identity Number of clones

AA424977 EST 1AA157740 EST 1H25624 EST 1AI669229 EST 1AA081351 EST 1AA903206 EST 1H86290 EST 1H93575 EST 1AA193285 EST 1AI127760 EST 1BI712375 EST 1BF373998 EST 1AW119026 EST 1

Novel (without GenBank and EST database hits) 4a

aThe number indicates four di�erent individual clones

Gene discovery and profiling in breast cancer

Y Jiang et al

2274

Oncogene

60% of the metastatic tumors tested have elevatedexpression of B709P gene. In comparison, B709P isonly overexpressed in 20% of primary breast tumors inthe same panel. This data indicated that B709Poverexpression might be correlated with metastasis ofbreast tumor. Hair-speci®c type II keratin wasexpressed in 16% (3 out of 19) of breast metastatictumors and 36% of the primary breast tumors in thesame panel. The percentage of breast metastatic tumors

expressing B726P gene (52%) is similar to thepercentage of primary breast tumors (50%) expressingthis gene. Similarly, GABAa receptor p subunit geneshowed expression in an equal percentage of metastaticbreast tumors and primary breast tumors (32% and36%). So, contrary to B709P, the percentage ofoverexpression for hair-speci®c type II keratin, B726P,and GABAa receptor p subunit is not increased inmetastatic tumors compared to primary breast tumors.

Table 2 Summary of GenBank and EST database search results of the 62 clones with threefold overexpression in breast tumors

Ratio GenBank GenBank Number(tumor/normal) identity accession number of clones

8.7 Mammaglobin gene AF015224 55.8 Lipophilin B AJ224172 33.2 Human 40 kDa keratin gene J03607 24.7 Human lipophilin C AJ224173 14.0 Human high mobility group box M86737 14.0 Human GABA-A receptor pi subunit U95367 13.7 Retinoic acid receptor responder 3 AF060228 13.6 EST AA694120 13.6 B726P AF269087 13.6 Human polymorphic epithelial mucin J05581 13.5 Chondroitin sulfate proteoglycan protein U16303 13.5 Human AP-2 gene X77343 13.5 Mus musculus proteinase-3 AA557271 13.5 Human hair-specific keratin AJ000263 13.5 Human fibronectin U41724 13.5 Human hXBP-1 transcription factor L13850 13.5 Human pro-urokinase precursor M15476 13.5 EST AI160667 13.5 None None 13.4 Mitogen activated protein kinase AF032437 13.4 EST AA236418 13.4 DNA binding regulatory factor X85786 13.4 None None 13.4 PAC clone 179N16 AI097002 13.4 Human PAC 128M19 clone None 13.3 Secreted cement gland protein XAG-2 AF038451 13.3 EST R56414 13.3 Human ikB kinase-b gene AF080158 13.3 Type I epidermal keratin J00124 13.3 Human pS2 protein gene X52003 13.2 Human palmitoyl-protein thioesterase L42809 13.2 EST AI048523 13.2 Human alpha-1 collagen AF017178 13.2 Chromosome 17 clone hRPK.209_J_20 AA187922 13.2 Clone 102D24 on chromosome 22q13.31 AA774267 13.2 Human nicein B2 chain X73902 13.2 Human cytochrome P450-IIB M29873 13.2 Human lysyl hydroxylase gene L06419 13.2 Human thrombospondin 2mRNA L12350 13.2 EST H77996 13.2 EST AA612943 13.2 MyD88 mRNA U70451 13.2 EST AA402322 13.1 EST AA443172 13.1 EST AA631694 13.1 EST AI274876 13.1 Human clone 24976 mRNA W95853 13.1 Human chromosome 17 AI452980 13.1 Human BCL-1 gene M73554 13.1 Human GATA-3 transcription factor X58072 13.1 EST AA058515 13.1 B709P AF086120 13.1 None None 13.1 EST AI590680 13.0 Human tissue plasminogen activator gene K03021 1

Oncogene

Gene discovery and profiling in breast cancer

Y Jiang et al

2275

Figure 1 Microarray analysis of B709P, hair-speci®c type II keratin, B726P, and GABAA receptor p subunit. Pseudo-color imagesof ¯uorescence intensity from 30 pairs of probes were shown. White color represents the highest intensity and the black representsthe lowest, as shown at the bottom right of the ®gure. P1/P2 represents the ratio of ¯uorescence intensity of probe 1 vs probe 2.Blank P1/P2 ratio means that both P1 and P2 channels are below the detection level of the ¯uorescence scanner. Positive P1/P2value means P1 is larger than P2 and negative P1/P2 value means P2 is larger than P1. BT, breast tumor; Met-BT-LN, metastaticbreast tumor to lymph node; HEMC, human epithelial mammary gland cell

Gene discovery and profiling in breast cancer

Y Jiang et al

2276

Oncogene

Discussion

Gene expression pro®ling and identi®cation of novelgenes can provide a signi®cant increase in our under-standing of the mechanisms and pathways that regulatethe transition from normal growth to malignantproliferation. Furthermore, both tumor- and tissue-speci®c genes are potential candidates for cancertherapy and diagnosis. Coupling subtraction andmicroarray provides robust and e�cient revenuetowards the discovery of genes that are di�erentiallyexpressed between breast and normal non-breasttissues. PCR-based cDNA subtraction is an e�cientand convenient way to obtain large numbers of clonesthat are already selected for overexpression in targetedtissues. This method eliminates the common house-keeping genes from the library pool, thereby reducingthe number of clones to be analysed by microarrayfrom a given target sample. Furthermore, the suppres-sion subtractive hybridization technology utilizes anormalization step that enables the recovery of notonly abundant genes but also less abundant genes fromthe subtracted library. For instance, mammaglobin is avery abundant gene in breast tumors as demonstratedby Northern (Watson et al., 1999), microarray, andquantitative RT±PCR (Houghton et al., 2001). Thisgene has been identi®ed by PCR-based subtraction,di�erential display PCR, and conventional subtraction.On the other hand, B709P and GABAA receptor psubunit are less abundant, and these two genes werenot discovered by other approaches such as conven-tional cDNA subtraction, di�erential display PCR, andserological analysis of recombinant tumor cDNAexpression libraries. Thus, using PCR-based subtrac-tion to generate clones for microarray analysis hasadvantages when compared with unsubtracted cDNAlibraries or subtracted cDNA libraries generated by theconventional method, which does not have a normal-ization step and is biased towards the recovery of

abundant genes (Xu et al., 2000). In this study we alsopooled three breast tumor samples for the subtractionto increase the probability of identifying genes that areonly expressed in a subpopulation of breast cancerpatients. The normal tissues used for drivers werepreferentially selected to eliminate more e�cientlynonspeci®c clones that could have expression in vitalnormal organs.

The advantages of cDNA microarray technology arethat it has made it possible to analyse thousands ofclones simultaneously, and the use of two ¯uorescentlabels enables a direct comparison of the relativemRNA abundance between two RNA populations.However, compared to other techniques such asNorthern hybridization and quantitative RT±PCR,there are also potential disadvantages associated withmicroarray. These include the lack of assay sensitivityfor rare genes, cross reactivity with homologoussequences, and the fact that it is less quantitativeespecially for genes that are either rare or abundant.Therefore, quantitative real time PCR was implemen-ted as a con®rmatory assay due to the increasedsensitivity and speci®city of this method, as the ®nalstep of our antigen discovery process. This provides uswith two independent methodologies to verify themRNA expression pro®le of any particular gene ofinterest. The panel of tissues used for both microarrayand real-time PCR was constructed to ful®l ourselection criteria for identifying breast tumor andtissue speci®c genes. In both panels a large numberof breast tumors and other vital normal tissues but fewnormal breast samples were included to assess thetissue distribution of target genes. We used primarytissues for both normal and tumor to re¯ect naturalbiological processes.

The 62 clones with over threefold overexpressioninclude many known and unknown genes/clones thatwill be of great interest to breast cancer researchers.Mammaglobin and lipophilin B are two clones with the

Figure 2 Nucleotide sequence and the predicted amino acid sequence of B709P

Oncogene

Gene discovery and profiling in breast cancer

Y Jiang et al

2277

Figure 3 Quantitative real time PCR analysis of B709P, hair-speci®c type II keratin, B726P, and GABAA receptor p subunit withprimary breast tumors and various normal tissues. The Y-axis represents the copy number for the gene of interest per 1 ng of b-actin. Lane 1 ± 25, breast tumors; 26 ± 28, normal breast; 29, normal uterus; 30, normal activated PBMC; 31, normal resting PBMC;32, normal pancreas; 33, normal live; 34, normal colon; 35, normal spleen; 36, normal esophagus; 37, normal thyroid gland; 38,normal spinal cord; 39, normal bone; 40, normal thymus; 41, normal cartilage; 42, normal lung; 43, normal trachea; 44, normaladrenal gland; 45, normal brain; 46, normal bone marrow; 47, normal small intestine; 48, normal stomach; 49, normal heart; 50,normal kidney; 51, normal prostate; 52 normal skin; 53, normal pituitary gland; 54, normal skeletal muscle; 55, normal ovary; 56,normal retina

Gene discovery and profiling in breast cancer

Y Jiang et al

2278

Oncogene

highest tumor/normal ratio (Table 2) on microarray.Both genes were identi®ed multiple times withmicroarray. Mammaglobin is a well-documented breastspeci®c gene and has been evaluated as a marker for

assessing response to therapy or recurrence and fordetection of metastatic breast tumor cells (Fleming andWatson, 2000). Lipophilin B has recently been reportedto form a complex with mammaglobin and they are co-

Figure 4 Quantitative real time PCR analysis of B709P, hair-speci®c type II keratin, B726P, and GABAA receptor p subunit withmetastatic breast tumors, primary breast tumors, and normal breast. The Y-axis represents the copy number for the gene of interestper 1 ng of b-actin. Lane 1, metastatic breast tumor to ovary; 2 ± 19 metastatic breast tumors to lymph node; 20 ± 33 primary breasttumors; 34 normal breast

Oncogene

Gene discovery and profiling in breast cancer

Y Jiang et al

2279

expressed in breast tumors (Colpitts et al., 2001).Among the 62 clones we also found GATA-3transcription factor, thrombospondin-1, and AP-2.Studies on the GATA-3 transcription factor gene haveindicated that its expression is associated with estrogenreceptor expression and is likely to be involved in theregulation of genes that are critical to the hormone-responsive breast cancers (Hoch et al., 1999). Throm-bospondin-1, which is an extracellular matrix glyco-protein, has been shown to be involved in breast tumorprogression (Bertin et al., 1997). Expression of AP-2transcription factor in breast cancer has also beenreported in the literature (Turner et al., 1998). Thisgene is required for normal growth and morphogenesisduring mammalian development. Interestingly AP-2 isinvolved in the regulation of the expression of Her2/neu and estrogen receptor genes and may play a role inthe control of cell growth and di�erentiation of breastcancer (Bosher et al., 1995).

In this study we have demonstrated a highthroughput approach to identify genes di�erentiallyexpressed in breast tumors by combining SSHsubtraction and microarray. The four genes presentedin this report, B709P, B726P, hair-speci®c type IIkeratin and GABAA receptor p subunit, are examplesof breast tumor- and tissue-speci®c genes discoveredthrough our methodology. Their mRNA expressionpro®les have been demonstrated by cDNA microarrayhybridization and quantitative real time PCR analysis.We are currently developing antibodies for each of thefour proteins, and will use these antibodies to conductimmunohistochemistry studies to further analyse theirexpression pattern at the protein level. These genescould potentially be used as targets for antibody andvaccine therapy, and as diagnostic markers for breastcancer. Additionally, understanding the functions ofthese four genes may lend us greater insight into themechanisms of tumorigenesis of breast tumor.

Materials and methods

Preparation of total RNA and poly(A)+ RNA from humantumor and normal tissues

All tumor and normal human tissue samples obtained fromvarious clinical sources were accompanied by clinicalinformation and pathological reports, and were histologicallycon®rmed by pathologists. The tissue samples were snap-frozen in liquid nitrogen and stored at 7808C until use.Total RNAs were isolated from tissue samples using TRIzoltotal RNA isolation kit (Gibco BRL Life Technology, Inc.Rockville, MD, USA), according to the manufacturer'sprotocol. Poly(A)+ RNAs were extracted from total RNAsusing the mRNA Puri®cation Kit from Amersham Pharmacia(Piscataway, NJ, USA).

Subtracted cDNA libraries

Three primary breast tumor mRNA samples were mixed inequal proportion and 2 mg of the poly(A)+ RNAs were usedto synthesize tester cDNAs. The driver cDNAs were

generated from 2 mg of mRNAs containing equal amountsof poly(A)+ RNAs from normal breast, brain, liver,pancreas, and peripheral blood mononuclear cells (PBMC).The ®rst and second strand cDNAs were synthesized usingreagents included in the PCR-Select cDNA Subtraction kit(Clontech Inc., Palo Alto, CA, USA). The tester and drivercDNAs were blunt-ended with T4 DNA polymerase, andthen digested with a mixture of ®ve endonucleases includingMluI, MscI, PvuII, SalI, and StuI. A ®lling-in reaction withKlenow fragment was carried out after the digestion toregenerate the blunt ends. The digested tester cDNAs wereligated to adapter 1 and adapter 2 (Clontech Inc., Palo Alto,CA, USA) in separate ligation reactions. The ligationreaction mixtures were incubated overnight at 168C. Thesubtractive hybridization of adapter-ligated testers withdrivers was performed according to the protocol (Clontech),using a tester to driver ratio of 1 : 60. Two rounds of PCRampli®cation were performed to complete the subtraction andamplify the subtracted cDNA fragments. The ®rst ampli®ca-tion was performed as follows: 5 min adapter extension at758C, 27 cycles of 948C, 30 s; 668C, 30 s and 728C, 90 s. Thesecond PCR was performed with conditions of 948C, 30 s;688C, 30 s and 728C, 90 s for 12 cycles. The primers used forPCR were supplied with the Clontech kit.

Dot blot

Plasmid DNAs of 96 randomly selected clones from thesubtracted library were spotted onto nylon membranes. Threemembranes were probed separately with tester-speci®c probe,driver-speci®c probe, and cDNAs from the subtracted libraryusing the same conditions. The probes were [a-32P]dCTP-labeled using a random primed DNA labeling kit (AmershamPharmacia, Piscataway, NJ, USA). Equal amounts of cDNAswere used for probe labeling. All three blots were exposed toKodak ®lm (X-OMAT) for 16 h.

Cloning and sequencing analysis of the subtracted cDNA library

Secondary PCR products generated from the subtractedcDNAs were subcloned into the pCR2.1 TOPO T/A cloningvector using conditions suggested by the manufacturer(Invitrogen, Carlsbad, CA, USA). The ligated cDNAs werethen transformed into DH10B electro-competent cells byelectroporation (Gibco BRL Life Technology, Inc., Rock-ville, MD, USA). Ninety-six clones were randomly pickedfrom the library, and plasmid DNAs were prepared using aQIAprep 96 Turbo Miniprep kit (Qiagen Inc. Valencia, CA,USA) according to the manufacturer's protocol. DNAsequencing was performed at Corixa using an ABI377automated sequencer with M13 forward and reverse primers.DNA homology database searches were performed using theBLAST program (Nakai and Horton, 1999).

cDNA microarray

cDNA microarray was performed as described previously(Xu et al., 2000). Cloned inserts from the subtracted cDNAlibrary were PCR ampli®ed with the pCR2.1 vector speci®cM13 forward and M13 reverse primers. The ampli®ed PCRfragments were analysed visually on a 1.2% agarose gel toensure the quality and quantity of the DNA prior to the ®nalarraying step. PCR products were arrayed onto glass slidesusing Incyte patented chemistry. The arrayed cDNAs werehybridized with a 1 : 1 mixture of Cy3- and Cy5-labeled ®rststrand cDNAs generated from 200 ng of poly(A)+ RNAfrom breast tumors and normal tissues (Incyte Pharmaceu-

Gene discovery and profiling in breast cancer

Y Jiang et al

2280

Oncogene

ticals, Palo Alto, CA, USA). Both the hybridization andsubsequent imaging were performed by Incyte. Incyte hasimplemented a 96-well control plate which utilizes yeast genesof 1 kb fragments that are from the inter-ORF regions of theyeast genome and have no homology to the other targetsequences arrayed on chips. This control plate was used fordeterminations of reverse transcription e�ciency of both Cy3and Cy5 labeled probes, hybridization e�ciency of the probesto the array, and the sensitivity of detection. Detailedinformation on the control plate is posted on the Incyteweb site: http://www.incyte.com/reagents/catalog/support/gem/controls/Qcdoc-cdedit.pdf. The ®nal array images wereanalysed using Incyte Gemtools software. The ¯uorescentintensities between experiments were normalized by using asubset of cDNA clones, which enabled us to compare databetween di�erent experiments.

Quantitative real-time PCR

The speci®city of genes discovered from cDNA microarraywas analysed further using quantitative PCR analysis tocon®rm their expression pro®les. Primary and metastaticbreast tumors and normal breast tissues along with othernormal tissues were tested using quantitative real-time PCR.cDNAs used in the PCR were synthesized from 20 mg of totalRNA using Superscript RT (Gibco BRL Life Technology,Rockville, MD, USA) as described by the manufacturer. Thetotal RNAs were treated with DNaseI (Ampli®cation Grade,Gibco BRL Life Technology, Rockville, MD, USA) prior to®rst-strand synthesis. The real-time PCR was performedusing the GeneAmp1 5700 sequence detection system (PEBiosystems, Foster City, CA, USA). The 5700 system usesSYBR1 green, a ¯uorescent dye that only intercalates withdouble stranded DNA, and a set of gene speci®c forward andreverse primers. The increase in ¯uorescence is monitoredduring the entire ampli®cation process. The forward primersand reverse primers for the genes of interest are as follows:B709P: Forward, 5'-TGGTGGAAGTGGGCGAA-3'; Re-verse, 5'-TCAGTGACAGCGATGAATTAGCTT-3'; Hair-speci®c type II keratin: Forward, 5'-GGTCTGCCGGAAA-TGTTAGG-3'; Reverse, 5'-GCAAGGCAGGGCAGGAA-3';B726P: Forward, 5'-AACATGCACAAAGAGACCAACGT-3'; Reverse, 5'-TGTTTGTTCACATTATCTTGTTCGTTT-3'; GABAA receptor p subunit: Forward, 5'-AAGCCTCA-

GAGTCCTTCCAGTATG-3'; Reverse, 5'-AAATATAAGT-GAAGAAAAAAATTAGTAGATCAACA-3'.The optimal concentration of primers was determined

using a pool of cDNAs from breast tumors. Each PCRreaction was performed in a 25 ml volume that included 2.5 mlof SYBR green bu�er, 2 ml of cDNA template and 2.5 mleach of the forward and reverse primers for the gene ofinterest. The cDNAs used for the RT reactions were diluted1 : 10 for each gene of interest and 1 : 100 for the b-actincontrol. In order to quantitate the amount of speci®c cDNA(and hence initial mRNA) in the sample, a standard curvewas generated for each run using the plasmid DNAcontaining the gene of interest. Standard curves weregenerated using the Ct values determined in the real-timePCR which were related to the initial cDNA concentrationused in the assay. A set of standard dilutions ranging from20 ± 26106 copies of the gene of interest was used for thispurpose. In addition, a standard curve was generated for b-actin ranging from 200 fg ± 20 ng. This enabled standardiza-tion of initial RNA content of a tissue sample to the amountof b-actin for comparison purposes. The mean copy numberfor each group of tissues tested was normalized to a constantamount of b-actin, allowing the evaluation of the over-expression levels seen with each of the genes.

AbbreviationsEST, expressed sequence tag; GABAp, g-aminobutyratetype A receptor p subunit; ORF, open reading frame;PBMC, peripheral blood mononuclear cells; PCR, poly-merase chain reaction; RT, reverse transcription; SSH,suppression subtractive hybridization

AcknowledgmentsWe thank Incyte Pharmaceutical Inc. for their help inmicroarray technology. Some tissue samples were obtainedfrom the Cooperative Human Tissue Network, which isfunded by the National Cancer Institute, and fromNational Disease Research Interchange. This work wassupported in part by the NIH grant CA75794 (RLHoughton).

References

Amenta F, Cavallotti C, Ferrante F and Erdo SL. (1988).Pharmacol. Res. Commun., 20, 863 ± 868.

Apostolopoulos V, McKenzie IFC and Pietersz GA. (1996).Cell Biol., 74, 457 ± 464.

Bakker AB, Schreurs MW, de Boer AJ, Kawakami Y,Rosenberg SA, Adema GJ and Figdor CG. (1994). J. Exp.Med., 179, 1005 ± 1009.

Bertin N, Clezardin P, Kubiak R and Frappart L. (1997).Cancer Res., 57, 396 ± 399.

Bosher JM, Williams T and Hurst HC. (1995). Proc. Natl.Acad. Sci. USA, 92, 744 ± 747.

Bowden PE, Hainey SD, Parker G, Jones DO, Zimonjic D,Popescu N and Hodgins MB. (1998). J. Invest. Dermatol.,110, 158 ± 164.

Cheever MA, Disis ML, Bernhard H, Gralow JR, Hand SL,Huseby ES, Qin HL, Takahashi M and Chen W. (1995).Immunol. Rev., 145, 33 ± 59.

Colpitts TL, Billing-Medel P, Friedman P, Granados EN,Hayden M, Hodges S, Menhart N, Roberts L, Russell Jand Stroupe SD. (2001). Biochemistry, 40, 11048 ± 11059.

Coulie PG, Brichard V, Van PA, Wolfel T, Schneider J,Traversari C, Mattei S, De PE, Lurquin C and Szikora JP.(1994). J. Exp. Med., 180, 35 ± 42.

Cox AL, Skipper J, Chen Y, Henderson RA, Darrow TL,Shabanowitz J, Engelhard VH, Hunt DF and Slinglu�CLJ. (1994). Science, 264, 716 ± 719.

DeRisi JL, Iyer VR and Brown PO. (1997). Science, 278,680 ± 686.

Diatchenko L, Lau YC, Campbell AP, Chenchik A,Moqadam F, Huang B, Lukyanov S, Lukyanov K,Gurskaya N, Sverdlov ED and Siebert PD. (1996). Proc.Natl. Acad. Sci. USA, 93, 6025 ± 6030.

Disis ML and Cheever MA. (1997). Adv. Cancer Res., 65,343 ± 371.

Oncogene

Gene discovery and profiling in breast cancer

Y Jiang et al

2281

Erdo SL, Mione MC, Amenta F and Wol� JR. (1989). Br. J.Pharmacol., 96, 313 ± 318.

Fleming TP and Watson MA. (2000). Ann. N.Y. Acad. Sci.,923, 78 ± 89.

Hadden JW. (1999). Int. J. Immunopharmacol., 21, 79 ± 101.Hedblom E and Kirkness EF. (1997). J. Biol. Chem., 272,

15346 ± 15350.Hoch RV, Thompson DA, Baker RJ and Weigel RJ. (1999).

Int. J. Cancer, 84, 122 ± 128.Houghton RL, Dillon DC, Molesh DA, Zehentner BK, Xu J,

Jiang J, Schmidt C, Frudakis A, Repasky E, Filho A,Nolasco M, Badaro R, Zhang X, Roche PC, Persing DHand Reed SG. (2001). Mol. Diag., 6, 79 ± 91.

Jager D, Stockert E, Gure AO, Scanlan MJ, Karbach J, JagerE, Knuth A, Old LJ and Chen YT. (2001). Cancer Res., 61,2055 ± 2061.

Jones KA, BrownMA and Solomon E. (1995). Cancer. Surv.,25, 315 ± 334.

Kawakami Y, Eliyahu S, Delgado CH, Robbins PF,Sakaguchi K, Appella E, Yannelli JR, Adema GJ, MikiT and Rosenberg SA. (1994). Proc. Natl. Acad. Sci. USA,91, 6458 ± 6462.

Kurebayashi J, Otsuki T, Kunisue H, Tanaka K, YamamotoS and Sonoo H. (2000). Clin. Cancer Res., 6, 512 ± 518.

Lopez-Otin C and Diamandis EP. (1998). Endo. Rev., 19,365 ± 396.

Loridon-Rosa B, Vielh P, Matsuura H, Clausen H,Cuadrado C and Burtin P. (1990). Cancer Res., 50,1608 ± 1612.

Majewska MD and Vaupel DB. (1991). J. Endocrinol., 131,427 ± 434.

McKenzie IF and Xing PX. (1990). Cancer Cells, 2, 75 ± 80.Nakai K and Horton P. (1999). Trends Biochem. Sci., 24,

34 ± 36.Ozturk M, Ponchel F and Puisieux A. (1992). Bone Marrow

Trans., 1, 164 ± 170.Regnier CH, Boulay A, Asch PH, Wendling C, Chenard MP,

Tomasetto C and Rio MC. (1998). Br. J. Cancer, 78,1640 ± 1644.

Schena M, Shalon D, Davis RW and Brown PO. (1995).Science, 270, 467 ± 470.

Schena M, Shalon D, Heller R, Chai A, Brown PO and DavisRW. (1996). Proc. Natl. Acad. Sci. USA, 93, 10614 ±10619.

Trask D, Band V, Zajchowski DA, Yaswen P, Suh T andSager R. (1990). Proc. Natl. Acad. Sci. USA, 87, 2319 ±2323.

Turner BC, Zhang J, Gumbs AA, Maher MG, Kaplan L,Carter D, Glazer PM, Hurst HC, Ha�ty BG and WilliamsT. (1998). Cancer Res., 58, 5466 ± 5472.

Walker RA, Jones JL, Chappell S, Walsh T and Shaw JA.(1997). Cancer Metast. Rev., 16, 5 ± 27.

Watson MA and Fleming TP. (1996). Cancer Res., 56, 860 ±865.

Watson MA, Dintzis S, Darrow CM, Voss LE, DiPersio J,Jensen R and Fleming TP. (1999). Cancer Res., 59, 3028 ±3031.

Xu J, Stolk JA, Zhang X, Silva SJ, Houghton RL,Matsumura M, Vedvick TS, Leslie KB, Badaro R andReed SG. (2000). Cancer Res., 60, 1677 ± 1682.

Gene discovery and profiling in breast cancer

Y Jiang et al

2282

Oncogene