Transcriptome Analysis of Microdissected Pancreatic Intraepithelial Neoplastic Lesions

Transcriptome analysis of microdissected pancreatic intraepithelial neoplastic lesions

Malte Buchholz1,4, Mike Braun1,4, Anna Heidenblut2,4, Hans A Kestler1,Gu¨ nter Klo¨ ppel3, Wolff Schmiegel2, Stephan A Hahn2,5, Jutta Lu¨ ttges3,5 and Thomas M Gress*,1,5, for the German Pancreatic Cancer Net of the Deutsche Krebshilfe6

1Department of Internal Medicine I, University Hospital of Ulm, Robert Koch Str. 8, 89081 Ulm, Germany; 2Department of Internal Medicine, University of Bochum, Bochum, Germany; 3Department of Pathology, University of Kiel, Kiel, Germany

Pancreatic ductal adenocarcinoma (PDAC) carries the diagnostic and therapeutic tools for the prevention and most dismal prognosis of all solid tumours. Both the late early diagnosis of PDAC and provide novel insights into clinical presentation of patients, due to lack of early the pathophysiological mechanisms involved in tumour pro- symptoms, as well as the rapid and aggressive course gression in the pancreas. of the disease contribute to the extremely high mortality Oncogene (2005) 24, 6626–6636. doi:10.1038/sj.onc.1208804; of this malignancy. Recently, a multistep progression published online 15 August 2005 model for PDAC integrating morphological, clinical and molecular evidence has been proposed. Putative precursor Keywords: PanIN progression; gene expression; early lesions, termed pancreatic intraepithelial neoplasia diagnosis; target genes (PanIN), are classified into three different grades (PanIN-1 through -3) based on the degree of cellular atypia they display. We have conducted large-scale expression profiling analyses of microdissected cells from normal pancreatic ducts, PanINs of different grades and PDACs using whole-genome oligonucleotide microarrays. Introduction Verification of hybridisation results for selected genes was performed using quantitative real-time PCR and immuno- More than 150 000 deaths per year are estimated to histochemical analyses on PanIN tissue microarrays. occur due to pancreatic ductal adenocarcinoma (PDAC) Comparison of the expression profiles demonstrated that worldwide (Parkin et al., 1999). The extremely high the greatest changes in gene expression occur between mortality rate of PDAC, evidenced by an estimated PanIN stages 1B and 2, suggesting that PanIN-2 may worldwide 5-year survival rate of 1% (Parkin et al., represent the first truly preneoplastic stage in PDAC 1999), is due, among others, to the aggressive behaviour progression. Our results identify a large number of potential of this tumour, the inadequacy of current therapies and target genes for the development of novel molecular the late clinical presentation. Most patients with PDAC do not develop symptoms, such as jaundice or pain, until the tumour is already in a locally advanced or *Correspondence: TM Gress; E-mail: [email protected] metastatic stage. Unfortunately, no curative treatment 4These authors contributed equally to this work and should be options are available for these patients, and even considered joint first authors patients with localised disease where a curative resection 5These authors contributed equally to this work and should be considered joint senior authors is attempted frequently relapse, with mean survival 6The German Pancreatic Cancer Net is a consortium funded by the ranging between 8 and 14 months (Conlon et al., 1996; Deutsche Krebshilfe composed of the following groups at German Sperti et al., 1997; Trede et al., 2001). Recent advances institutes: SHahn and W Schmiegel,Department of Internal Medicine, in adjuvant therapy have achieved survival rates of 20 University of Bochum; G Klo¨ ppel and J Lu¨ ttges, Institute of Pathology, University of Kiel; TM Gress, M Braun and M Buchholz, months (Neoptolemos et al., 2004), which represents an Department of Internal Medicine, University Hospital of Ulm; improvement, though on a low level. On the other hand, H Scha¨ fer and H Mu¨ ller, Institute of Biometry and Epidemiology, curative resection in early-stage PDAC may achieve University of Marburg; HE Meyer, Proteome Center, University of 5-year survival rates of up 40% (Yeo and Cameron Bochum; DK Bartsch and M Rothmund, Department of Visceral 1998). Thus, early detection of PDAC or detection of Surgery, University of Marburg; P Mo¨ ller and C Hasel, Department of Pathology, University Hospital of Ulm; D Henne-Bruns and preneoplastic lesions allowing curative resection is of U Knippschild, Department of Surgery, University Hospital of Ulm; paramount importance in order to improve the dismal M Lerch, Department of Internal Medicine, University of Greifswald; prognosis of PDAC patients. This is particularly true for H Kalthof, Department of Surgery, University of Kiel; R Moll, patients from high-risk groups, such as smokers or Department of Pathology, University of Marburg; W Bechstein, Department of Surgery, University of Bochum persons with a genetic susceptibility for PDAC. It has Received 22 December 2004; revised 20 April 2005; accepted 27 April been estimated that familial aggregation and genetic 2005; published online 15 August 2005 susceptibility play a role in 5–10% of patients with PanIN expression profiles M Buchholz et al 6627 PDAC (Lynch et al., 1990, 1996; Lynch, 1994). To date, precursor lesions such as PanINs. The aim of the present members of families with genetic syndromes with study was to make use of these novel techniques within increased risk for PDAC or with familial PDAC are the framework of the German Pancreatic Cancer Net- screened with a combination of imaging and endoscopic work (GPCN) funded by the German Cancer Aid techniques such as multislice computed tomography foundation (Deutsche Krebshilfe) to perform high- (CT), magnetic resonance imaging (MRI), endosono- throughput expression analyses of microdissected graphy (EUS) and enodoscopic retrograde cholangio- PanINs using whole-genome oligonucleotide arrays. The pancreatography (ERCP) (Brentnall et al., 1999; results of this study provide a large number of novel Hruban et al., 2001c; Canto et al., 2004). However, potential target genes for the development of molecular changes observed in EUSand ERCP are often diagnostic and therapeutic tools that may be applied unspecific and may as well be observed in patients to risk populations. Moreover, this study provides in- suffering from chronic pancreatitis. Furthermore, the sights into interesting pathophysiological mechanisms sensitivity of these screening methods for the detection involved in tumour progression in the pancreas. of early neoplastic or precursor lesions remains unclear. Similar to the adenoma-carcinoma sequence in colon cancer (Fearon and Vogelstein, 1990), a multistep Results progression model for the development of PDAC has been proposed based on growing morphological, clinical Microrray hybridization and evaluation of expression and molecular evidence (Hruban et al., 2000; Luttges profiles et al., 2001; Kloppel and Luttges, 2004). Putative precursor lesions of ductal adenocarcinoma, defined as For microarray hybridization, PanIN-1B lesions from microscopic papillary or flat noninvasive neoplasms 15 patients, PanIN-2 lesions from six patients, PanIN-3 arising in the pancreatic duct, have been termed lesions from eight patients and PDAC tissues from eight pancreatic intraepithelial neoplasia (PanIN) (Hruban patients as well as normal ducts and acinar cells from 14 et al., 2001a, 2004). PanINs are characterised by patients were prepared from PDAC tumour specimens columnar to cuboidal cells with varying amounts of and resection margins. Manual microdissection was mucin and increasing degrees of cytological and employed for this purpose, since this method yielded architectural atypia. PanINs usually involve ducts of RNA of superior quality and quantity compared to laser less than 5 mm (Hruban et al., 2004). Three PanIN capture microdissection (LCM) and laser pressure grades are distinguished based on the degree of catapulting (LPC), respectively. A total of 45 micro- structural and cellular atypia present in the lesions. array hybridizations were performed using pools of at PanINs are believed to progress from flat (PanIN-1A) least three individual lesions each. The complete and papillary lesions (PanIN-1B) without dysplasia, to hybridization data are available as part of the supple- papillary lesions with dyplasia (PanIN-2), to carcinoma mentary information at http://www.uni-ulm.de/klinik/ in situ (PanIN-3). PanINs, especially the intermediate medklinik/innere1/forschung/ag-gress/panin_array. and higher grade lesions, display a number of genetic Comparing the expression profiles of PanIN’s of abnormalities also observed in invasive cancers, includ- different stages or PDAC with that of normal pancreatic ing mutations of the KRAS, CDKN2A/p16INK4A, ducts, a total of 1251 genes were identified as differen- BRCA2, TP53 and SMAD4 genes (Wilentz et al., 1998, tially expressed using the criteria described in the 2000; Luttges et al., 1999, 2001; Goggins et al., 2000; Materials and methods section. Interestingly, the num- Wilentz et al., 2000; Luttges et al., 2001), which is bers of differentially expressed genes varied greatly suggestive of their neoplastic potential (Hruban et al., across the different stages of preneoplastic and neoplas- 2000; Luttges et al., 2001). However, efforts to develop tic lesions. While only 16 genes were upregulated and 31 molecular screening approaches based on the detection genes downregulated in PanIN-1B as compared to of some of these molecular alterations have so far been normal pancreatic ducts (estimated false disovery rate of limited success (see Vimalachandran et al., 2004 for (FDR): 3.2%), these numbers rose sharply to 76 up- an overview). and 362 downregulated genes in PanIN-2 (FDR: 1.7%), Detailed knowledge of molecular changes occurring 418 up- and 160 downregulated genes in PanIN-3 during PanIN progression is thus urgently required for (FDR: 1.4%), and 303 up- and 307 downregulated genes the development of novel screening strategies or in PDAC (FDR: 1.1%) (Figure 1). There was a chemopreventive approaches for PDAC. The availabil- prominent overlap, ranging between 30 and 61%, bet- ity of robust and high-throughput techniques for the ween the genes deregulated in individual PanIN lesions analysis of complete transcriptomes of cells and tissues and PDAC. using approaches such as microarry technology or SAGE has made it possible to study the whole spectrum Clustering of expression profiles of microdissected cells of transcriptional changes involved in the process. At the same time, the introduction of tissue microdissection Hierarchical cluster analysis was performed using all as well as development of RNA amplification techniques 1251 genes differentially expressed in at least one of the for generating hybridisation probes from as few as pairwise comparisons. Expression levels in acini were several hundred cells offer the chance to perform a included in this analysis for control purposes (see global analysis of the transcriptome of microscopic below). It was very interesting to note that the

Oncogene PanIN expression profiles M Buchholz et al 6628 700 A fourth cluster, depicted in Figure 2e, contained a upregulated spectrum of genes showing elevated expression levels downregulated from PanIN-1B throughout the PDAC samples, thus 600 presumably representing genes upregulated very early in carcinogenesis. In addition to a large number of new 500 potential markers, this cluster included known markers for pancreatic tumours, such as the S100 calcium- binding protein (S100P) (Crnogorac-Jurcevic et al., 400 2003), the trefoil factors 1 and 2 (TFF1/2)(Terris et al., 2002) and matrix metalloproteinase 1 (MMP1). 300 Validation of expression data 200 Quantitative real-time PCR Quantitative real-time PCR (qRT–PCR) analysis was conducted for 12 of the 100 genes differentially expressed between normal ducts and Number of differentially expressed genes the PanIN lesions to confirm differential expression in an independent set of individual microdissected lesions 0 (Figure 3). The results of the qRT–PCR analysis were PanIN-1B PanIN-2 PanIN-3 PDAC generally in good agreement with the microarray data. Figure 1 Number of genes identified as differentially expressed in Differential expression between normal ducts and the various PanIN stages and PDAC as compared to normal PanIN lesions was confirmed for nine of the 12 genes pancreatic ducts (PCOLN3, PLAC8, RAI3, TSPAN-1, TFF2, PKIA, CBFB, S100P, Pim1). In three instances, the changes in expression obtained by the microarray experiments were expression profiles of the different histological entities not seen or contradicted by the qRT–PCR results were ordered into two main branches of the dendro- (S100A14, CARD10, Hypothetical protein gram, with PanIN-1B lesions associating closely with DKFZP434I0714). The failure rate was thus higher normal ducts and acini to form a cluster of benign/ than would be expected from the estimated false hyperplastic tissues, while PanIN-2 and PanIN-3 lesions discovery rates, which may in part be explained by the joined the PDAC samples to form a cluster of fact that in contrast to the microarray experiments, dysplastic/neoplastic tissues (Figure 2a). where material from different patients was pooled to Hierachical clustering of genes identified various obtain sufficient quantities, the qRT–PCR analyses were clusters with distinct expression patterns across the performed on individual samples, thus altering the different types of microdissected lesions. The cluster potential influence of individual samples on the outcome depicted in Figure 2b, which shows that the acini- of the analysis. specific pancreatic enzymes, pancreatic elastases 3A and B, pancreatic lipase (PNLIP) and carboxyl ester lipase Immunohistochemistry of selected genes using PanIN (CEL), produced very high hybridisation signals that tissue microarrays (TMAs) In addition to the qRT– were strictly confined to the acinar tissue samples, serves PCR validation experiments, the expression of three to demonstrate the accuracy of the microdissection and upregulated genes (RAB1B, CEACAM5, Cathepsin E) RNA amplification procedure. was investigated immunohistochemically using PanIN Figure 2c shows a cluster of genes selectively TMAs (Figure 4). As predicted by the microarray expressed in ductal cells, thus presumably representing results, staining was weak (CTSE) or absent (RAB1B, genes whose expression is lost very early in the chain of CEACAM5) in normal ducts. For all three gene events leading to tumour formation. These included, products, the number of positive lesions and/or the among others, the putative cytokine high in normal 1 staining intensities increased across the PanIN stages, (SCGB3A1), the amiloride sensitive cation channel 2 with strongest staining intensities observed in PDAC. (ACCN2), the epithelial transmembrane mucin 13 (MUC13) and the developmental regulator norrie Functional categories of genes differentially expressed disease (NDP). in PanIN lesions Figure 2c shows a cluster of genes upregulated in later stage dysplastic/neoplastic lesions, for example, PanIN-2, Analysis of the functional roles of the genes differen- PanIN-3 and/or PDAC, thus potentially representing tially expressed in preneoplastic and neoplastic lesions markers of advanced preneoplastic and/or neoplastic may provide novel insights into the underlying biologi- lesions. In addition to genes previously implicated in cal mechanisms involved in tumour formation and carcinogenesis, for example, serine/threonine kinase 11 progression in the pancreas. In order to obtain hints at (STK11) and fibronectin (FN1), this cluster contained the cell biological implications of the differences the Ras-GTPase activating protein SH3 domain-binding detected between PanIN lesions and normal duct cells, protein 2 (G3BP2), plastin 3 (PLS3) and the homeobox it was of major interest to query the data for protein D11 (HOXD11). accumulations of genes with interesting expression

Oncogene PanIN expression proﬁles M Buchholz et al 6629

Figure 2 Hierarchical cluster analysis of differentially expressed genes. Mean expression levels for the different experimental groups are shown in columns, genes are shown in rows. Both the samples (experimental groups) as well as the genes were hierarchically clustered (two-dimensional cluster analysis) using uncentred Pearson correlation as the similarity measure. Red cells indicate high expression, black intermediate expression and green low expression of a gene in the respective group. (a) Complete cluster of all 1251 differentially expressed genes. (b) Subcluster of acinispeciﬁc genes. (c) Subcluster of genes downregulated early during carcinogenesis. (d) Subcluster of genes upregulated in advanced PanIN lesions. (e) Subcluster of genes upregulated early during carcinogenesis. Ac ¼ acini, D ¼ ducts, 1B ¼ PanIN-1B, 2 ¼ PanIN-2, 3 ¼ PanIN-3, Ca ¼ PDAC

patterns in distinct functional categories. To this end, we Within the ‘structure’ category, clusters of benign/ used the ‘GoMiner’ tool (Zeeberg et al., 2003) to query hyperplastic tissue-specific genes and dysplastic/neoplas- the Gene Ontology (GO) database (http://www.geneon tic tissue-specific genes were readily distinguishable tology.org) for functional categories associated with the (Figure 5a). While the former included the matrix 1251 differentially expressed genes. Differentially ex- metalloproteinases 3 and 17 (MMP3, MMP17) as well pressed genes were then organised into functional as laminin gamma 3 (LAMC3), the latter encompassed categories such as development, structure, signal trans- fibronectin 1 (FN1), keratin 16 (KRT16), plastin 3 duction, etc. according to their Gene Ontology annota- (PLS3), matrix metalloproteinase 7 (MMP7) and tions and each category analysed separately using one- collagen type III alpha-1 (COL3A1). Similar clusters dimensional hierarchical clustering. Clusters of genes were observed in the ‘development/differentiation’ with PanIN stage-dependent expression patterns were category: Here, the benign/hyperplastic tissue-specific identified by visual inspection of the clustering results cluster contained the homeobox gene HB8 (HLXB8), The ‘structure’ and ‘development/differentiation’ cate- the NUMB homolog (Drosophila) (NUMB), the ephrin gories, respectively, gave particularly interesting results. receptor A3 (EphA3), and the protocadherins a4and

Oncogene PanIN expression proﬁles M Buchholz et al 6630 PLAC8 PKIA TFF2 S100P

5 5 5 5

3 3 3 3

1 1 1 1

-1 -1 -1 -1

-3 -3 -3 -3 D1B23 Ca D1B23 Ca D 1B 23 Ca D 1B 23 Ca

PCOLN3 RAI3 CBFB TSPAN-1 )

T 3 3 3 3 C ∆ ∆ ∆∆ 2 2 2 2

1 1 1 1

0 0 0 0

-1 -1 -1 -1 D1B23 Ca D1B23 Ca D 1B 23 Ca D 1B 23 Ca log2rel. expression( PIM1 S100A14 CARD10 Hyp-Prot

3 3 1 1

2 2 0 0

1 1 -1 -1

0 0 -2 -2

-1 -1 -3 -3 D1B23 Ca D1B23 Ca D 1B 23 Ca D 1B 23 Ca

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Figure 3 Quantitative real-time PCR validation of microarray data. Displayed are mean values (log2 of relative expression ¼ DDCT)7s.e.m. from ﬁve individual experiments per gene. Colour panels above the bars symbolise log2-transformed mean expression values obtained in the array hybridisations (see reference colour bar). Expression levels in normal duct cells were arbitrarily set to 0 for both the qRT–PCR and the microarray results

b13 (PCDHA4, PCDHB13), while the dysplastic/neo- the analysis of the differentially expressed genes resulted plastic tissue-specific cluster included the genes FN1, in the identification of 22 known genes and eight ESTs homeobox D11 (HOXD11), plastin 3 (PLS3) and core (Figure 6). In addition to genes previously not binding factor, beta subunit (CFBF). implicated in carcinogenesis, these included a number of candidates that have previously been suggested as Potential early diagnostic target genes markers for pancreatic tumours, for example, S100 calcium-binding protein (S100P) (Crnogorac-Jurcevic The most promising candidates to serve as markers for et al., 2003) and Trefoil factor 1 (TFF1) (Terris et al., the early detection of PDAC would be genes that are 2002), or which have been implicated in cancerogenesis, significantly upregulated in preneoplastic and neoplastic for example, interferon alpha-inducible protein 27 lesions from early stages on. Since our results indicate (IFI27) (Suomela et al., 2004), cell division cycle 37 that PanIN-2 is the first truly preneoplastic stage in homolog (CDC37) (Stepanova et al., 2000) and anterior PDAC progression, we have compiled a list of potential gradient 2 homolog (AGR2) (Kristiansen et al., 2004). early diagnostic target genes by selecting genes that displayed low expression in acini and normal ducts, which were upregulated (as defined by the criteria described in the Materials and methods section) in Discussion PanIN-2 lesions as compared to normal ducts and which retained their high expression levels throughout the The progressive accumulation of morphological changes progression to PDAC. Application of these criteria to and the presence of typical mutations strongly argue for

Oncogene PanIN expression proﬁles M Buchholz et al 6631

Figure 4 Immunohistochemical analysis of RAB1B (a), CTSE (b) and CEACAM5 (c). Displayed are representative sections of normal duct cells (1), PanIN-1B (2), PanIN-2 (3), PanIN-3 (4) and PDAC (5). The table provides a comparison of immunohistochemistry (IHC) and microarray (MA) results. Listed are the numbers of positive staining lesions per total number of lesions analysed. Microarray results are expressed as fold changes relative to expression in normal duct cells. Asterisks denote differential expression (as deﬁned in the Material and methods section) compared to normal duct cells in the microarray analysis. For all three gene products, the number of positive lesions and/or the staining intensities increased with increasing stages of dysplasia

a role of PanINs as precursor lesions of PDAC and a more advanced stages of dysplasia, the gene expression progression from normal pancreatic ducts to PDAC via changes were not simply additive but showed extensive the different PanIN stages (Hruban et al., 2000; Luttges fluctuations across the different tissue types. In addition et al., 2001; Kloppel and Luttges, 2004). Our results to genes whose expression was constantly or progres- provide for the first time global expression profiles of sively changed, a significant proportion of the genes was highly pure preparations of normal, preneoplastic and deregulated in a stage-specific manner, with transcript neoplastic pancreatic duct cells as well as a comprehen- levels returning to control levels in later PanIN stages sive analysis of the gene expression changes associated and/or PDAC. This was somewhat unexpected, since with the different PanIN stages. One striking result of earlier studies investigating the mutation/deregulation this analysis was the observation that in comparison to of limited numbers of individual genes in PanIN lesions more advanced PanIN lesions or PDAC, PanIN-1B was had suggested an ordered sequence of cumulative associated with very few expression changes (47 mutations associated with the stepwise progression to differentially expressed genes as compared to 438 genes PDAC (Heinmoller et al., 2000; Hruban et al., 2000; in PanIN-2, 578 in PanIN-3 and 610 in PDAC). Luttges et al., 2001; Maitra et al., 2003). It can be Consequently, PanIN-1B lesions clustered very closely speculated that the transient expression changes de- with normal duct cells in the hierarchical cluster tected in our analysis reflect the activation of counter- analysis. Earlier reports have shown that PanIN-1A active mechanisms in the cells in response to early and B lesions are frequently observed in non-neoplastic ‘gatekeeper’ mutations (Vimalachandran et al., 2004), pancreata (Luttges et al., 1999; Hruban et al., 2001b), which impair the normal function of the cells. During strongly suggesting that the risk of progression to the progression towards PDAC, many of the control invasive carcinoma is very low for PanIN-1. Together, mechanisms that are operative in normal pancreatic these results indicate that PanIN-2 rather than PanIN-1B duct cells become inactivated, thus resulting in the represents the earliest truly preneoplastic lesion in the reversion of some of the gene expression changes seen in pancreas. earlier PanIN stages. It was very interesting to note that while the number While transient changes can provide hints at counter- of differentially expressed genes steadily increased with regulatory mechanisms, persistent expression changes

Oncogene PanIN expression proﬁles M Buchholz et al 6632

Figure 5 Clusters of structure (a) and development/differentiation (b) related genes. Genes were assembled in functional categories according to their Gene Ontology annotations and each category analysed separately by one-dimensional hierarchical clustering of genes. Clusters with clear distinctions between benign/hyperplastic tissues (ducts and PanIN-1B) and dysplastic/neoplastic tissues (PanIN-2, PanIN-3 and PDAC) are obvious in both categories

are more likely to reveal basic genetic principles under- become increasingly evident that ECM components can lying malignant transformation in the pancreas. Persis- actively regulate growth, death, adhesion, migration, tent or progressive changes in transcript levels were in invasion, gene expression and differentiation in adjacent particular detected for structure- and development/ cells (Liotta and Kohn, 2001; Pupa et al., 2002). This is differentiation-related genes, respectively. Profound additionally emphasised by the fact that many of the changes in the composition and turnover of extracellular differentially expressed structural genes also appear in matrix (ECM) components, produced both by tumour the gene ontology-derived list of development/differen- cells and surrounding stromal cells, is a hallmark feature tiation-related genes. Active modification of the micro- of PDAC (Bramhall et al., 1997; Ellenrieder et al., 2000; environment is therefore likely to be an important early Buchholz et al., 2003). Our results demonstrate that event during cancerogenesis in the pancreas. significant changes in the composition of ECM compo- One of the main goals of this study was the nents, for example, upregulation of MMP7, fibronectin identification of potential new targets for early detection and type 3 collagens as well as downregulation of and/or intervention in PDAC. As mentioned above, our MMP17, are already detectable in the PanIN-2 stage. results strongly suggest that PanIN-2 represents the first While the ECM has traditionally been regarded as an truly preneoplastic stage in the process of cancerogen- inert scaffold providing structural support for the esis. Ideal targets should therefore be significantly and functional cells within an organ or tissue, it has recently continuously upregulated from PanIN-2 through PDAC

Oncogene PanIN expression proﬁles M Buchholz et al 6633

Figure 6 Potential early diagnostic target genes. Selection of genes upregulated from PanIN-2 (presumably the ﬁrst truly preneoplastic stage in pancreatic carcinogenesis) throughout PDAC resulted in the identiﬁcation of 30 candidate target genes. Displayed are mean normalised expression values for the different tissue types. Red indicates high expression, black intermediate expression and green low expression in the respective tissue

to ensure applicability of potential new procedures (Yamakawa et al., 1998), galectin 4 (LGALS4), which independently of the exact type of lesion(s). We have is secreted in a soluble form by many epithelial cancer identified a total of 30 genes satisfying these criteria, cells and has been proposed as a marker for breast and including genes that have previously been suggested as liver tumours (Huflejt and Leffler, 2004), and the markers of pancreatic tumours, for example, S100 procollagen (type III) N-endopeptidase (PCOLN3), a calcium-binding protein (S100P) (Crnogorac-Jurcevic matrix metalloproteinase not previously implicated in et al., 2003) and trefoil factor 1 (TFF1) (Terris et al., carcinogenesis. 2002), or genes that have been suggested as targets for In summary, the combined use of tissue microdissec- tumour therapy, for example, the interleukin receptor tion, RNA amplification and global microarray analysis alpha 1 (Kawakami et al., 2001). Of special interest for has proven to be a powerful tool for profiling the diagnostic purposes were the many extracellular and cell molecular changes associated with the progression of surface genes contained within this set. A particularly normal pancreatic duct cells to invasive ductal adeno- promising candidate may be the secreted proteinase carcinoma. Our results both provide valuable new inhibitor cystatin C (CST3), which was strongly insights into the biology of PanINs and identify a host upregulated from PanIN-1B on. Cystatin C has of candidate target genes for the development of novel previously been shown to be linked to prognosis in strategies for early detection and treatment of PDAC. breast, lung, colorectal, brain and head and neck cancer (Kos et al., 2000) and serum levels of cystatin C have been used as markers for diagnosis and prognosis in Materials and methods melanoma, colorectal and head and neck cancer (Kos et al., 2000; Strojan et al., 2004). In addition, cystatin C Microdissection of pancreatic tissues as well as S100P have recently been identified as markers Tissue was obtained from 51 patients with PDAC in the head of PDAC in a global proteome analysis of pancreatic of the pancreas. Informed consent was obtained from all juice samples (Gronborg et al., 2004). Other candidates patients undergoing surgery and the trial was approved by the identified in our analysis included the extracellular ethics committees at the Universities of Kiel and Ulm. protease inhibitor 15 (PI15), which has been proposed Immediately after surgical resection, pancreas specimens as a marker for neuroblastoma and glioblastoma were placed on ice and tissue from the carcinoma, the

Oncogene PanIN expression profiles M Buchholz et al 6634 peritumoural parenchyma and from the resection margin was incubation for 15 min at 251C in the dark. Uncoupled dyes removed, snap frozen and stored at À801C. For the were removed by RNeasy-Kit (Qiagen, Hilden, Germany) and identification of acini, normal ducts and the various PanIN the final volume adjusted to 30 ml. lesions, 5 mm thin frozen sections were prepared from tissue Reference cDNA was reverse transcribed from 10 mgof blocks from peritumoral pancreatic parenchyma, in particular universal human reference RNA (Stratagene, La Jolla, CA, tissue from resection margins. They were briefly placed in USA) using Superscript III Reverse Transcriptase (Invitrogen, RNAse-free ethanol (Merck, Darmstadt, Germany), stained Carlsbad, CA, USA), oligo-d(T)-primers and dTTP/aminoal- with H&E and subsequently reviewed. Duct lesions were lyl-dUTP at a ratio of 1 : 2, according to the manufacturer’s classified as PanINs according to the criteria of the WHO instructions. The aminoallyl cDNA was coupled with 5.6 mg/6l classification (Hruban et al., 2001a). Tissue blocks that were Cy3 monoreactive dye (Amersham Biosciences, Uppsala, found to harbour the required tissue components were serially Sweden) and purified as described above. sectioned, the slides were stained using H&E and immediately stored at À201C. PanIN lesions from the stained serial sections were manually microdissected under microscopic Microarray hybridisations control (BH2, Olympus, Wetzlar, Germany) using a sterile injection needle (size 0.65 Â 25 mm, Fa. Braun, Melsungen, Following preincubation for 1 h at 421C in prehybridisation Germany). Intermediate ducts were preferably chosen in order buffer (3 Â SSC, 0.25% SDS, 1% BSA), slides were denatured to avoid contamination by acinar tissue. Microdissected at 751C for 1 min. In total, 30 ml each of the labelled cells were sampled in a 100 ml reaction tubes containing experimental and reference samples were hybridised for 50 ml extraction buffer (MWG; Mu¨ nich, Germany) and placed 14–18 h at 371C in hybridisation buffer (3 Â SSC, 0.25% on ice. SDS, 0.3 mg/ml poly dA, 0.5 mg/ml yeast tRNA, 1 mg/ml salmon Total RNA was isolated from 1000 to 10 000 microdissected sperm DNA) using a GeneTac hybridisation chamber (Geno- cells using the Pico Pure RNA Isolation Kit (Arcturus, mic Solutions, Cambridgeshire, UK). Slides were washed three Mountain View, USA), according to the manufacturers times in 2 Â SSC, 5% formamide, 0.1% Tween 20 (pH 7.0) at instructions. 371C, once in 1 Â PBS(pH 7.4), 0.05% Tween 20 (pH 7.0) at 251C, once in 1 Â PBS(pH 7.4), 0.1% Tween 20 (pH 7.0) at 251C for 3 min and once in 0.5 Â PBS(pH 7.4), 0.05% Tween Microarrays 20 (pH 7.0) at 251C for 5 min in the dark. Slides were dried in a centrifuge by spinning for 5 min at 1250 g. The Human Genome Oligo-Set-Version 2.0 (Operon, Ger- many) representing 21 329 genes in the form of optimized 70-mer oligonucleotides was spotted onto GAPSII Slides (Corn- ing, USA) using a OmniGrid Microarrayer (GeneMachines, Image and data analysis San Carlos, USA), equipped with Stealth SMP3 Micro Spotting Pins (Telechem, Sunnyvale, CA, USA) at the Chip- Hybridisation signals were visualised using a dual laser Facility of the University of Ulm. Printing concentration of the scanner (Axon 4000B) and analysed with GenePix Pro 4.0 imaging software (Axon Instruments, Union City, CA, USA). oligos was 40 mM in 3 Â SSC, 1.5 M Betain. Information about On visual inspection, spots of insufficient quality were each oligo and its representative gene is available online at excluded from further analysis. For the purposes of this study, http://www.operon.com/arrays/omad.php. we analysed the signal intensities from the Cy5 channel only, Oligonucleotides were immobilized on the slides by 15 min since low signal intensities in the reference channel for incubation at 801C, followed by irradiation with UV light at individual spots can lead to loss of data points when using 254 nm with an energy output of 120 mJ/cm2 in a Stratalinker the common reference ratio method. Print-tip LOESS-normal- Model 2400 UV illuminator (Stratagene). ised ratios of experimental and common reference samples obtained with the LIMMA software package (Smyth, 2004) for comparison with external data sets are available as part of Linear amplification and hybridisation probe generation the supplementary data (http://www.uni-ulm.de/klinik/medk In order to obtain sufficient amounts of RNA for hybridisa- linik/innere1/forschung/ag-gress/panin_array). tion, 5–50 ng of purified total RNA was linearly amplified To correct for differences between the microarray slides and under the presence of UTP and 5-(3-aminoallyl)-UTP (each for gradients within a slide, a block normalisation was 3.75 mM) using the MessageAMPt aRNA Kit (Ambion, performed. Following local background correction, signal Woodward, Austin, USA), according to the manufacturer’s intensities were normalised to the average of medians of all instructions. The quality and quantity of the total and spots within individual 4-by-4 subarray blocks on each slide. amplified RNA samples was determined with a 2100 Agilent Block normalised expression values of all individual hybridi- Bioanalyser (Agilent Technologies, Palo Alto, CA, USA). sations are available as part of the supplementary data To ensure adequate representation of different patients and accompanying this paper. to allow for replicate hybridisations, amplified RNA samples For the identification of differentially expressed genes, the were combined to form pools of at least three different patients block normalised data were first filtered to include only genes (see supplementary material for numbers of patients per that exceeded a mean normalised expression value of 1 in at individual pool). At least two pools per type of lesion were least one of the experimental groups. Genes were defined as analysed, and all pools were hybridised at least in triplicate (see differentially expressed between normal ducts and PanIN supplementary material). lesions or PDAC if (1) the difference between the mean For each microarray hybridisation, 700 ng of amplified normalised expression values was at least two-fold; and (2) a aminoallyl RNA was resuspended in 75 mM sodium carbonate two-sided T-test yielded a P-value of o0.01. False discovery buffer (pH 9.0) and coupled with 7.3 pM/5.6 mg/ml Cy5 rates were estimated by analysing all possible permutations of monoreactive dye (Amersham Biosciences, Uppsala, Sweden) group assignments (Tusher et al., 2001). Lists of genes in DMSO for 1 h at room temperature in the dark. The differentially expressed between the different sample sets are reaction was quenched by adding 1.3 M hydroxylamine and available as part of the supplementary data.

Oncogene PanIN expression proﬁles M Buchholz et al 6635 Table 1 qRT–PCR primer sequences Gene RefSeq ID 50-primer 30-primer

PCOLN3 NM_002768 1588-TGTTTGTCTCCTCGACAGGGA-1608 1717-ATCGTCATGAAGCAGGGCC-1699 PLAC8 NM_016619 212-CGGAGTCTGTCTCTGTGGCA-231 312-TCATTGCGACGCTTGTTCC-294 RAI3 NM_003979 2200-TCACTAGCACAAGCCCGGTT-2219 2331-GCAGCCGTAAATGCGGTAAA-2312 TFF2 NM_005423 255-CCCCTCCCAAAGCAAGAGTC-274 357-ACTTCCGAGAGGCGCATTC-339 S100A14 NM_020672 156-AGGGCCATTGAGACCCTCA-174 246-CCAGGTCCCGTAGCTCAGAA-227 PIM1 NM_002648 1821-AATCTGCCTGGGTTTTGTTCC-1841 1921-TCAGCGTTTGGCCCTGTAG-1903 PKIA NM_006823 608-TTCCTCTGCAAGTGGCAACA-627 764-AGGTGTGGTCGAGGGTCAAA-783 CBFB NM_001755 774-GCTGGCAGTAACTGGCAAGAA-794 869-AGATGGGCAGCACACATCTG-888 T-SPAN1 NM_005727 456-ACACCACAATGGCTGAGCAC-475 576-CAGCACTTGAGCCCTTTCATG-556 S100P NM_005980 287-GGAGATGCCCAGGTGGACTT-306 415-GCTCTGCCAGGAATCTGTGAC-395 CARD10 NM_014550 3667-TGTGTAAATGTCACGCCCCA-3686 3845-CCCGTTAATCATCCACGGG-3827 Hyp-Prot AL137273 1841-GTGCTGAGGAACAGAAGGGC-1860 1961-TCCTGTTATCAAGCTGGGTGC-1941

Nucleotide sequences and relative positions within the RefSeq mRNA sequences of the primers used for qRT–PCR validation of the microarray data

To further analyse the biological function of differentially Immunohistochemistry expressed genes, the GoMiner package (Zeeberg et al., 2003) Protein expression of the genes that was found to be was used to organise lists of genes for biological interpretation differentially expressed was tested using a TMA that included in the context of the Gene Ontology (GO) data base. the various grades of PanINs, normal pancreatic tissue and Hierarchical cluster analysis of expression profiles was per- PDAC. Briefly, cores of 0.2 mm diameter that included the formed using the ‘Genesis’ software tool (Sturn et al., 2002) requested PanIN lesion were taken from the donor block and with uncentred Pearson correlation as the similarity measure. transferred to the recipient block using a microarrayer (Beecher Instruments, Silver Springs, MD, USA) (Bubendorf et al., 2001). For histological investigation, 5 mm sections were Data validation by real-time RT–PCR cut and transferred to uncovered superfrost slides (Menzel, Real-time PCR was performed using the comparative Gla¨ ser, Braunschweig, Germany). The various antibodies were tested using the required different control tissues. In most CT method on the ABI Prism Sequence Detection System (PE Applied Biosystems, Forster City, CA, USA), according cases, antigen demasking was necessary and performed by the to the manufacturer’s instructions. In brief, cDNA was pressure cooker method. Immunostaining was carried out by reverse transcribed from 0.2 mg of amplified antisense RNA the ABC method as described previously (Luttges et al., 2004). using Superscript III Reverse Transcriptase (Invitrogen, Briefly, the slides were incubated for 45 min with the primary Carlsbad, CA, USA) and random decamers, according to antibodies followed by an incubation with a biotinylated the manufacturer’s instructions. Primers for 12 genes were secondary antibody (5 mg/ml, Vector Laboratories, Burlin- defined using the PrimerExpress program (PE Applied game, CA, USA) and avidin-biotin-peroxidase (ABC ELITE, Biosystems) and are listed in Table 1. Samples were Vector Laboratories). Diaminobenzidine served as chromogen amplified using the SYBR Green PCR Master Mix system for antigen detection. Subsequently, the slides were briefly (PE Applied Biosystems). The human cyclophilin gene counterstained with haematoxylin. For CEACAM5, the (RefSeq ID NM_021130 ) was used as internal standard. APAAP method was applied as previously described (Luttges Variation was assessed by calculating standard errors of the et al., 2000). For the negative control the primary antibody was omitted. mean of all possible differences of individual DCT-values between two sets of samples according to the following formula: qPffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 2 Acknowledgements i;j ðductsi À XjÞ We thank Susanne Braun, Karin Lanz, Claudia Ruhland, Pat SEM ¼ ð#ducts Þð#XjÞ Schreiter and Britta Redeker for excellent technical assistance. i The work of the GPCN is supported by a multicentre grant with Xj representing the different stages of disease progression. form the Deutsche Krebshilfe, Bonn, Germany.

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