Pancreatic endocrine neoplasms are neoplastic proliferations of islet cells or islet cell precursors and are capable of secreting a variety of synthetic products, including insulin, glucagon, gastrin, and vasoactive intestinal peptide. The biological behavior of pancreatic endocrine neoplasms is often unpredictable, and there are few reliable histopathologic criteria reliably correlating with metastatic ability. We have used the Affymetrix U133 GeneChip set (HG_U133 A and B; Affymetrix; Santa Clara, CA) representing ∼33,000 characterized transcripts to examine global gene expression profiles from well-differentiated nonmetastatic (n = 5) and metastatic (n = 7) pancreatic endocrine neoplasms to determine molecular markers that predict disease progression. Microarray hybridization data were normalized using the GeneLogic GeneExpress Software System to identify differentially up- and down-regulated genes in metastatic versus nonmetastatic pancreatic endocrine neoplasms. Using a 3-fold change in gene expression as a threshold, we have identified 65 overexpressed and 57 underexpressed genes in metastatic pancreatic endocrine neoplasms as compared with nonmetastatic pancreatic endocrine neoplasms. Several classes of genes, including growth factors and growth factor-related molecules (IGFBP1, IGFBP3, and MET), developmental factors (TBX3 and MEIS2), cytoskeletal factors (β 1 tubulin and ACTN2), cholesterol homeostasis mediators (LRP5, SLC27A2, and RXRG), intracellular signaling pathway mediators (DYRK1A, PKIB, and AK2), methyltransferases (MGMT and GAMT), and DNA repair and regulatory molecules (CHEK1 and ZNF198), were identified as differentially over- or underexpressed via this method. Immunohistochemical validation of microarray data were performed for two overexpressed genes, namely, the met proto-oncogene (MET) and insulin-like growth factor binding protein 3 (IGFBP3) with tissue microarrays of nonmetastatic (n = 24) and metastatic (n = 15) pancreatic endocrine neoplasms. Increased expression of IGFBP3 was confirmed in metastatic versus nonmetastatic pancreatic endocrine neoplasms (12 of 15, 80% versus 10 of 24, 42%), as well as in lymph node (6 of 7, 86%) and liver (9 of 9, 100%) metastases. Similarly, overexpression of MET was confirmed in metastatic versus nonmetastatic pancreatic endocrine neoplasms (5 of 15, 33% versus 4 of 24, 17%), as well as in lymph node metastases (4 of 7, 57%) and liver metastases (5 of 9, 56%). The majority of genes that demonstrated altered expression has not been previously identified as differentially expressed in metastatic pancreatic endocrine neoplasm lesions and may therefore represent newly identified molecules in the progression of these lesions.

Pancreatic endocrine neoplasms are neoplastic proliferations of islet cells or islet cell precursors and may be classified as functional or nonfunctional lesions (1). Functional pancreatic endocrine neoplasms frequently present with symptoms related to excessive hormonal secretion such as insulin, gastrin, glucagon, somatostatin, and vasoactive intestinal peptide, whereas nonfunctional pancreatic endocrine neoplasms present secondary to mass effect. Frequently used histopathologic criteria that may herald aggressive behavior in pancreatic endocrine neoplasms include angioinvasion, perineural invasion, and prominent cytologic atypia, among others; however, besides the presence of synchronous metastases, there are few consistently reliable criteria for predicting clinical outcome. A recent study, however, has identified that mitotic index and presence of necrosis may be useful indicators of patient prognosis (2).

Alterations in molecular profiles underlying the development of pancreatic endocrine neoplasms have only recently begun to be elucidated, and little is known regarding the molecular changes that confer less favorable prognostic outcomes. The identification of the gene responsible for the multiple endocrine neoplasia 1 (MEN1) syndrome, MEN1, has led to additional understanding of the subset of pancreatic endocrine neoplasms arising in association with this syndrome, although MEN1 alterations appear to vary in sporadic pancreatic endocrine neoplasms (3, 4). Examination of well-characterized tumor suppressor genes in sporadic lesions has led to the identification of only rare mutations in such genes as p53(5), p16/MTS1(6), PTEN(7), among others. Overexpression of KRAS2 has been reported in pancreatic endocrine neoplasms, although this also appears to represent a rare event (8). Finally, loss of a single sex chromosome, either X or Y, in pancreatic endocrine neoplasms appears to correlate with a worsened prognosis, although the genes underlying this phenotype are unknown (9).

Recently, global gene analysis has been used by our group to identify differentially up-regulated genes in well-differentiated nonmetastatic pancreatic endocrine neoplasms versus normal human islet cells (10). This screening technique identified 66 overexpressed transcripts in pancreatic endocrine neoplasms, many of which may function in islet cell carcinogenesis. We have now extended our analysis of pancreatic endocrine neoplasm lesions to examine the differential expression of genes in well-differentiated metastatic versus nonmetastatic pancreatic endocrine neoplasms to determine markers of disease progression. Although the precise pathogenesis of pancreatic endocrine neoplasm development remains unclear, a progression model leading from normal islet cell to primary pancreatic endocrine neoplasm to metastatic pancreatic endocrine neoplasm appears functionally plausible. Furthermore, as only a limited subset of pancreatic endocrine neoplasms metastasize, the identification of altered gene expression profiles in this population may reflect commonly altered pathways relevant to a variety of metastatic cancers.

Pancreatic Endocrine Neoplasm Tissue Collection.

Permission for this study was obtained from The Johns Hopkins Joint Committee for Clinical Investigation. Specimens were obtained from patients undergoing distal pancreatectomies or Whipple resection for functional and nonfunctional pancreatic endocrine neoplasms. Metastatic (n = 7) and nonmetastatic (n = 5) pancreatic endocrine neoplasms were used for analysis. The male:female ratio was 5:2 and 2:3 for metastatic and nonmetastatic lesions, respectively. Pancreatic endocrine neoplasm tissue was harvested within 10 minutes of surgical resection, snap frozen in liquid nitrogen, and stored at −80°C. H&E-stained sections from adjacent frozen tissue were prepared before sample harvest to confirm the diagnosis (10) and assess neoplastic cellularity. A subset of pancreatic endocrine neoplasms included in this study were additionally classified as functional lesions by clinical hormone production or specific immunolabeling panels.

RNA Extraction and Hybridization.

RNA extraction and processing were performed at GeneLogic, Inc. (Gaithersburg, MD). Sample preparation and processing procedure was performed as described in the Affymetrix GeneChip Expression Analysis Manual (Santa Clara, CA). Briefly, each frozen tissue was crushed to powder by using the Spex CertiPrep 6800 Freezer Mill (Metuchen, NJ). Total RNA was then extracted from crushed metastatic and nonmetastatic pancreatic endocrine neoplasm tissue using TRIzol (Life Technologies, Inc., Rockville, MD) and cleaned using RNeasy columns according to the manufacturer’s protocol (Qiagen, Valencia, CA). Using 5 to 40 μg of total RNA, double-stranded cDNA was synthesized following SuperScript Choice system (Life Technologies, Inc.). T7-(dT24) oligomer was used for priming the first-strand cDNA synthesis. The resultant cDNA was purified using Phase Lock Gel, phenol/chloroform extraction, and precipitated with ethanol. The cDNA pellet was collected and dissolved in the appropriate volume. Using cDNA as a template, cRNA was synthesized using a T7 MegaScript In Vitro Transcription kit (Ambion, Austin, TX). Biotinylate-11-CTP and 16-UTP ribonucleotides (Enzo Diagnostics, Inc., Farmingdale, NY) were added to the reaction as labeling reagents. In Vitro Transcription reactions were performed at 37°C for 6 hours, and the labeled cRNA obtained was purified using RNeasy columns (Qiagen). The cRNA was fragmented in fragmentation buffer (40 mmol/L Tris-acetate (pH 8.1), 100 mmol/L KOAc, and 30 mmol/L MgOAc] for 35 minutes at 94°C. Fragmented cRNA prepared from each sample (10 to 11 μg/probe array) was hybridized to the human GeneChip set (HG_U133A and U133B) noncompetitively at 45°C for 24 hours in a hybridization oven with constant rotation (60 rpm). Fragmented cRNA are hybridized to the GeneChip set by way of multiple 20 to 25 oligonucleotide probes specific for each gene, with each probe corresponding to a different region of the mRNA of interest. The probes specific for each mRNA are scattered across the surface of each GeneChip to control for technical issues that occur in each hybridization. The chips were washed and stained using Affymetrix fluidics stations. Staining was performed using streptavidin-phycoerythrin conjugate (Molecular Probes, Eugene, OR), followed by the addition of biotinylated antibody to streptavidin (Vector Laboratories, Burlingame, CA) and finally with streptavidin-phycoerythrin conjugate. Probe arrays were scanned using fluorometric scanners (Hewlett Packard Gene Array Scanner; Hewlett Packard Corporation, Palo Alto, CA).

The scanned images were inspected and analyzed using established quality control measures, with the hybridization intensities reflecting in a linear manner the mRNA expression in the tissues being assayed. Hybridization was controlled for each probe by the use of a mismatch control that has a single base mismatch. This mismatch control is analyzed using the GeneLogic informatics filter that compares the hybridization intensity of mismatched to perfect matched probes (to eliminate those that are nonspecific over a specified threshold), as well as different probes to the same gene.

DNA Filtering and Analysis.

The GeneExpress Software System Fold Change Analysis tool was used to identify genes expressed at least 5-fold greater in the metastatic pancreatic endocrine neoplasms compared with nonmetastatic lesions. For each gene fragment, the ratio of the geometric means of the expression intensities in the normal control tissues and the pancreas cancer samples was calculated, and the fold change then calculated on a per fragment basis. Confidence limits were calculated using a two-sided Welch modified t test on the difference of the means of the logs of the intensities.

Immunohistochemistry.

Tissue microarrays were prepared from 24 nonmetastatic and 15 metastatic pancreatic endocrine neoplasms banked at The Johns Hopkins Hospital from 1993 through 2002. When available, metastatic lesions to the liver (n = 9) or lymph nodes (n = 7) were additionally sampled. Each cancer specimen was represented by four 1.4-mm cores on the tissue microarrays to obtain adequate representation of different regions of neoplastic cells to assess for intratumoral heterogeneity. In addition, nonneoplastic pancreatic islets from the corresponding patients and additional nonneoplastic tissue from the gallbladder, colon, skin, breast, prostate, thymus, and brain were sampled on the tissue microarrays. Slides were deparaffinized in fresh xylenes and rehydrated through sequential-graded ethanol steps. Antigen retrieval was performed by citrate buffer incubation [18 mmol/L sodium citrate (pH 6.0)] using a household vegetable steamer for 60 minutes. Slides were incubated for 5 minutes with 3% hydrogen peroxide, washed in TBS/T [20 mmol/L Tris, 140 mmol/L NaCl, 0.1% Tween 20 (pH 7.6)], and incubated in appropriate antibody dilutions for IGFBP3 (1:50; Santa Cruz Biotechnology, Santa Cruz, CA) and Met (1:1000; Santa Cruz Biotechnology) for 60 minutes at room temperature. Normal saline was substituted for the primary antibody in control sections. The avidin-biotin-peroxidase complex method from DAKO (Glostrup, Denmark) was used, and slides were subsequently counterstained with hematoxylin. Assessment of immunohistochemical labeling in the tissue microarrays was performed by two of the authors (D. Hansel and A. Maitra). IGFBP3 was scored as positive if any level of cytoplasmic staining was detected. Met was scored as positive for membranous staining only. Comparison of immunolabeling between populations was performed using the Fisher’s exact test, and prediction of metastatic spread was performed using positive- and negative-predictive value scores.

Differentially Expressed Transcripts in Metastatic versus Nonmetastatic Pancreatic Endocrine Neoplasms.

Normalization and comparison of the Affymetrix microarray hybridization data were performed using the GeneLogic GeneExpress Software System Fold Change Analysis tool. Sixtyfive overexpressed transcripts and 57 underexpressed transcripts were identified in well-differentiated metastatic versus nonmetastatic pancreatic endocrine neoplasms in our analysis (Table 1). Overexpression of multiple factors involved in growth regulation (MET, IGFBP1, and IGFBP3), cholesterol homeostasis (NPC1L1, LRP5, and SLC27A2), osmotic regulation (AQP3 and solute carrier 6), chemical modification (UGT2B4), cytoskeletal-related molecules (β 1 tubulin and myosin X), coagulation (FGA and coagulation factor V), and hypoxia-inducible factors (IGFBP1 and LDHB) was identified. Underexpressed transcripts were notable for multiple cell-cycle regulatory (CHEK1 and ZNF198), developmental regulatory molecules (MEIS2), second messenger signaling mediators (RAB25 and DYRK), and DNA damage repair (MGMT and GAMT) molecules. Overall pathway modifications were evident for the IGF-signaling cascade (IGFBP1, IGFBP3, EHD1, and ACTN2) in which changes in gene expression would promote pathway activation.

A literature search of PubMed using transcript names paired with “islet cell,” “pancreatic endocrine,” “metastasis,” or “carcinoma” revealed that a subset of overexpressed transcripts had been previously identified in pancreatic endocrine neoplasms, such as IGFBP3(10), as well as in other cancer types.5 Overexpression of MET has been previously described in a wide variety of carcinomas and associated metastases, including pancreatic endocrine neoplasms (11), breast carcinoma (12), and squamous cell carcinoma (13). In addition, three altered transcripts reflected a similar overexpression pattern in our metastatic pancreatic endocrine neoplasm lesions as in human hepatocellular carcinoma specimens analyzed by global gene analysis (IGFBP1, UGT2B4, and VTN; ref. 14). The majority of transcripts identified as over- or underexpressed by our method, however, have not been previously reported in pancreatic endocrine neoplasms or in metastatic lesions and may therefore represent novel cellular targets in this cancer type.

Validation of Differentially Expressed Genes in Metastatic and Nonmetastatic Pancreatic Endocrine Neoplasms.

Confirmation of altered gene expression patterns was performed using a tissue microarray comprised of 24 nonmetastatic pancreatic endocrine neoplasms, 15 metastatic pancreatic endocrine neoplasms, 9 liver metastases, and 7 lymph node metastases arising from pancreatic endocrine neoplasm primary lesions (Table 2). Lesions were represented by four cores on the tissue microarray to assess for intratumoral heterogeneity; in all cases, the presence of labeled protein appeared uniform throughout all cores. Expression of two overexpressed transcripts, IGFBP3 (4.88-fold overexpression) and MET (4.90-fold overexpression), was performed using immunolabeling analysis (Table 3).

Nonneoplastic pancreatic tissue demonstrated focal expression of MET in small ductal epithelium cells but not in islet or acinar cells. Examination of metastatic primary pancreatic endocrine neoplasms revealed that 5 of 15 (33%) of these lesions demonstrated MET expression in contrast to only 17% (4 of 24) of nonmetastatic pancreatic endocrine neoplasms (Fig. 1, A and B; Fisher’s exact test, P = 0.4150). Furthermore, analysis of pancreatic endocrine neoplasm metastases identified a still higher proportion of MET-positive lesions metastatic to lymph nodes (4 of 7, 57%; Fisher’s exact test, P = 0.1056) and liver (5 of 9, 56%; Fisher’s exact test, P = 0.0788) as compared with expression in nonmetastatic pancreatic endocrine neoplasms. All MET-expressing lesions demonstrated robustly positive membranous labeling.

IGFBP3 demonstrated a weak granular immunolabeling pattern within the cytoplasm of normal pancreatic islet cells but not in pancreatic ducts or acinar cells. Similar to MET, IGFBP3 also demonstrated an approximate 2-fold increase in the percentage of IGFBP3-positive lesions in metastatic pancreatic endocrine neoplasms (12 of 15, 80%) versus nonmetastatic pancreatic endocrine neoplasms (10 of 24, 42%; Fig. 1, C and D). In this study, any level of cytoplasmic immunolabeling was scored as positive. A Fisher’s exact test comparing these two populations demonstrated a borderline significant P of 0.0408. Prominent expression of IGFBP3 was also confirmed in lymph node (6 of 7, 86%; Fisher’s exact test, P = 0.1001) and liver metastases (9 of 9, 100%; Fisher’s exact test, P = 0.0048) as compared with expression in nonmetastatic pancreatic endocrine neoplasms.

Statistical analysis of MET and IGFBP3 expression was performed on primary pancreatic endocrine neoplasms to determine whether immunolabeling for these molecules could predict metastatic spread. MET immunolabeling demonstrated a specificity of 83% for metastatic spread, and IGFBP3 labeling demonstrated a sensitivity of 80%; neither molecule, however, demonstrated a robust positive predictive value for the development of metastases. The finding of proportionally increased expression within metastases, however, suggests that these molecules may function at a molecular level to promote metastatic spread.

Subclassification of pancreatic endocrine neoplasms by IGFBP3 and MET expression revealed that the majority of glucagonomas (2/2), gastrinomas (1/2), and VIPomas (1/1) were positive for IGFBP3, whereas only the VIPoma demonstrated MET immunoreactivity. Of note, none of the insulinomas (n = 3), which frequently do not metastasize, demonstrated immunoreactivity for MET or IGFBP3. In our study population of 39 patients with primary pancreatic endocrine neoplasms, 3 patients expired 6, 8, and 26 months after initial diagnosis and surgical intervention (the remaining 36 patients were alive without evidence of pancreatic endocrine neoplasm recurrence). Lesions collected from these patients demonstrated either IGFBP3 (2/3) or MET (1/3) expression in all three cases.

Pancreatic endocrine neoplasms encompass a wide spectrum of lesions that often defy standard forms of categorization and therefore lead to challenges in the understanding of the underlying biology of these lesions. Examination of multiple indices of unfavorable patient outcomes and aggressive biological behavior, including proliferation index, necrosis, chromogranin reactivity, and size, have led in certain instances to useful histologic criteria, although molecular alterations that influence patient outcome are lacking. Metastatic spread of pancreatic endocrine neoplasms has been proposed to represent a negative prognostic indicator, as often disseminated disease may not be amenable to surgical cure or adjuvant treatment. To gain additional insight into the molecular alterations that occur in disseminated pancreatic endocrine neoplasm disease, we performed global gene analysis expression of well-differentiated metastatic versus nonmetastatic primary pancreatic endocrine neoplasms and confirmed selected gene expression profiles on tissue microarrays composed of 39 primary pancreatic endocrine neoplasms and 16 pancreatic endocrine neoplasm metastases.

Analysis of gene expression profiles revealed that 65 genes were overexpressed, and 57 genes were underexpressed in metastatic versus nonmetastatic primary pancreatic endocrine neoplasms. In addition to a variety of factors that have been implicated in cell proliferation and metastatic spread in other cancer types, our findings were notable for altered expression of genes involved in cell cycle and DNA repair regulation, cellular growth, cholesterol and lipid homeostasis, intracellular signaling, and coagulation, as well as factors that are induced under hypoxic conditions. To validate the gene expression profiles obtained by our analysis, we examined the expression patterns of IGFBP3 and MET on tissue microarrays containing 24 nonmetastatic and 15 metastatic primary pancreatic endocrine neoplasms, as well as 9 liver and 7 lymph node metastases.

IGFBP3 functions as a carrier molecule for both IGF-I and IGF-II in the circulation (15, 16). IGFBP3 mediates both pro- and antiproliferative effects on various cell types (16), and increased serum levels of IGFBP3 have been associated with progression of breast cancer in several studies (17, 18). We have previously identified the overexpression of IGFBP3 (4.1-fold) in nonmetastatic pancreatic endocrine neoplasms versus normal human islet cells (10). In comparison, IGFBP3 appears to be additionally up-regulated in metastatic versus nonmetastatic pancreatic endocrine neoplasms (4.88-fold), suggesting a continuum of IGFBP3 expression and influence on pancreatic endocrine neoplasm progression and metastases. Analysis of IGFBP3 expression in metastatic versus nonmetastatic pancreatic endocrine neoplasms identified IGFBP3 expression in 42% of nonmetastatic pancreatic endocrine neoplasms versus 80% of metastatic primary pancreatic endocrine neoplasms. In addition, IGFBP3 expression was identified in 86 and 100% of lymph node and liver metastases, respectively.

In addition to IGFBP3, several additional components of the IGF signaling pathway demonstrated altered expression levels, including IGFBP1, ACTN2, and EHD1. IGFBP1 functions as a carrier molecule for IGF-I and IGF-II, undergoes induction by hypoxic conditions (19), and reflects a poorer outcome in cancer patients with elevated circulating levels of this molecule. ACTN2 has been proposed to function as a key transducing molecule in the signaling pathway leading from IGF receptor I activation to cell membrane microspike production, cell-cell separation, and cell migration (20). Finally, EHD1 has been shown to influence the endocytosis of IGF receptor I from the cell surface (21); decreased expression of this molecule, as identified in this study, could potentially lead to an increased cell surface half-life of, and therefore increased signaling through, IGF receptor I. Overall, IGF signaling appears to be enhanced in metastatic versus nonmetastatic pancreatic endocrine neoplasms secondary to altered gene expression.

An additional validation of our data were performed by examining MET expression (overexpressed 4.90-fold) in metastatic versus nonmetastatic pancreatic endocrine neoplasms. MET functions as a transmembrane receptor tyrosine kinase that is activated by hepatocyte growth factor/scatter factor (22). Inappropriate expression of MET has been documented in the majority of solid tumor types (23) and appears to often correlate with worsened prognosis. MET signaling also results in disruption of cell-cell adhesion, branching morphogenesis, and invasive and metastatic behavior of a large array of neoplasms (24). We have identified the expression of MET in 17% of nonmetastatic pancreatic endocrine neoplasms versus 33% of primary pancreatic endocrine neoplasms demonstrating concurrent metastases. MET expression appeared most prevalent in lymph node (57%) and liver (56%) metastases. As with IGFBP3, MET expression may also demonstrate a continuum of expression with neoplastic progression.

Several molecules involved in DNA repair and maintenance of cell-cycle checkpoints appeared to be globally down-regulated in our analysis, including the methyltransferase MGMT, as well as DNA repair and regulatory molecules such as CHEK1 and ZNF198. The expression of MGMT, a DNA repair gene, is regulated by methylation of CpG islands within the promoter region of the gene, and decreased expression of MGMT has been reported in gastric cancer (25), lung (26), and brain (27) cancer. CHEK1 encodes a protein kinase that prevents progression of the cell cycle after double-stranded DNA breaks via a Cdc25A-regulated mechanism (28) and has therefore been suggested to represent a novel tumor suppressor gene (29). Recent analysis of the normal function of ZNF198 has revealed that this molecule may also serve in the DNA repair process through interactions with RAD18 and HHR6(30).

A final global pathway that demonstrated multiple alterations of gene expression involves lipid metabolism and cholesterol homeostasis. Neoplastic growth requires the formation of new cell membranes, which are dependent upon cholesterol derivatives and subsequent phospholipid formation (31). Renal and brain cancer (32), for example, demonstrate alterations in cholesterol homeostasis that appear to influence cancer growth and metastatic behavior. Our study has identified the overexpression of LRP5 and solute carrier family 27 (SLC27A2), as well as the underexpression of RXRG, all of which influence lipid balance within the cell. LRP5 is a cell surface protein that mediates ligand-internalization, is required for cholesterol balance (33) and is involved in promoting canonical Wnt signaling within cells (34). SLC27A2 is a transmembrane protein that transports long-chain and very long-chain fatty acids into the cell and activates intracellular signaling pathways such as protein kinase C and peroxisome proliferator-activated receptors (35). Additional fatty acid and cholesterol-modifying molecules overexpressed in our study include NPC1-like-1 (NPC1L1, subcellular cholesterol trafficking (36), aquaporin 3 (AQP3, glycerol channel), and peroxisomal matrix protein (catalyzes the oxidation of very long chain fatty acids).

Our study has identified the over- and underexpression of genes involved in multiple facets of cell growth and metastases in primary pancreatic endocrine neoplasm lesions. This study represents the first systematic analysis of altered expression in metastatic lesions of this cancer subtype. Comparison of metastatic versus nonmetastatic primary pancreatic endocrine neoplasms have yielded a limited novel group of altered transcripts that may serve as functional targets for metastases arising from primary pancreatic endocrine neoplasms. Additional analysis using a larger set of pancreatic endocrine neoplasms with paired metastases may be useful in the analysis of various transcripts identified within this screen, especially in the context of predicting metastatic spread. Finally, the comparison of altered gene profiles from islet cell to nonmetastatic to metastatic pancreatic endocrine neoplasms may yield additional information regarding the underlying pathophysiology of pancreatic endocrine neoplasm progression.

Fig. 1.

Immunolabeling analysis of MET expression in (A) nonmetastatic and (B) metastatic well-differentiated pancreatic endocrine neoplasms. Expression of IGFBP3 was also increased in metastatic pancreatic endocrine neoplasms (C and D).

Fig. 1.

Immunolabeling analysis of MET expression in (A) nonmetastatic and (B) metastatic well-differentiated pancreatic endocrine neoplasms. Expression of IGFBP3 was also increased in metastatic pancreatic endocrine neoplasms (C and D).

Close modal

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

Requests for reprints: Donna E. Hansel, Department of Pathology, 720 North Rutland Avenue, Ross 632, Baltimore, MD 21205.

5

Internet address: http://www.ncbi.nlm.nih.gov/PubMed.

Table 1

Differentially regulated genes in metastatic versus nonmetastatic pancreatic endocrine neoplasms

Affymetrix tag numberGene nameFold changePChromosomeFunction
Up-regulated      
 231029_at Adenylate kinase 2 6.23 0.04728 1p34 Mitochondrial enzyme, phosphorylation 
 39248_at Aquaporin 3 5.49 0.01123 9p13 Water and glycerol channel 
 204714_s_at Coagulation factor V 7.48 0.03040 1q23 Procoagulation factor 
 204154_at Cysteine dioxygenase, type 1 3.90 0.01222 5q22-q23 Cysteine oxidation to inorganic sulfate 
 228124_at DKFZP434P106 protein 3.44 0.00229 20p11.1 Unknown function 
 208399_s_at Endothelin 3 6.84 0.04685 30q13.2-q13.3 Stimulates neural crest cell proliferation 
 205649_s_at Fibrinogen, A alpha polypeptide 10.98 0.03503 4q28 Glycoprotein mediating vasoconstriction 
 218772_x_at Hypothetical protein FLJ10493 4.21 0.00141 9q31.2 Unknown function 
 205302_at Insulin-like growth factor binding protein 1 7.86 0.01370 7p13-p12 Cell growth, induced by hypoxia 
 210095_s_at Insulin-like growth factor binding protein 3 4.88 0.05865 7p13-p12 Cell growth inhibition and promotion 
 213564_x_at Lactate dehydrogenase B 3.62 0.01542 12p12.2-p12.1 Anaerobic glycolysis 
 209468_at Low-density lipoprotein receptor-related protein 5 4.91 0.04834 11q13.4 Wnt signal transducer, cholesterol metabolism, insulin secretion 
 213975_s_at Lysozyme 7.99 0.01948 12q14.3 Antibacterial protein 
 204438_at Macrophage mannose receptor, C type 1, MRC1 4.59 0.01203 10p13 Cell-cell recognition, anti-pathogenic 
 203510_at Met proto-oncogene, MET 4.90 0.00408 7q31 Tyrosine kinase, cell growth 
 201976_s_at Myosin X, MYO10 4.50 0.00479 5p15.1-p14.3 Extension of filopodia, binds calmodulin 
 218128_at NPC1-like 1 5.75 0.00008 7p13 Subcellular cholesterol trafficking 
 218128_at Nuclear transcription factor Y, β 3.05 0.00632 12q22-q23 Regulates MHC expression 
 204873_at Peroxisome biogenesis factor 1 3.08 0.03395 7q21-q22 Peroxisomal matrix protein import 
 232262_at Phosphatidylinositol glycan, class L 5.81 0.01635 17p12-p11 Cell surface protein membrane anchor 
 201120_s_at Progesterone receptor membrane component 1 5.43 0.02150 Xq22-q24 Putative steroid membrane receptor 
 225214_at Proteasome subunit, β type, 7 3.14 0.00281 9q34.11-q34.12 Degradation of ubiquitinated proteins 
 223551_at Protein kinase inhibitor β 3.77 0.00348 6q22.32 cAMP-dependent protein kinase inhibitor 
 219106_s_at Sarcomeric muscle protein 19.25 0.00597 2q31.1 Adult skeletal muscle protein 
 230318_at Serine (or cysteine) proteinase inhibitor, α-1-antitrypsin 15.21 0.00239 14q32.1 Proteinase inhibitor 
 205768_s_at Solute carrier family 27, member 2 12.91 0.00965 15q21.2 Fatty acid transporter 
 228754_at Solute carrier family 6 3.23 0.00641 3p25-p24 Taurine transport 
 219682_s_at T-box 3 4.38 0.04156 12q24.1 Transcription factor, morphogenesis 
 230535_s_at Tubulin, β 1 3.14 0.04101 20q13.32 Microtubule component 
 206505_at UDP glycosyltransferase 2 family, polypeptide B4 (UGT2B4) 8.80 0.04322 4q13 Chemical detoxification 
 204534_at Vitronectin (serum spreading factor) 4.90 0.00445 17q11 Cell attachment and spreading 
Down-regulated      
 203862_s_at Actinin, α 2 5.44 0.03671 1q42-q43 Actin binding protein 
 205393_s_at CHK1 checkpoint homologue 3.70 0.01385 11q22-q23 DNA damage checkpoint kinase 
 211079_s_at Dual-specificity tyrosine phosphorylation regulated kinase 1A (DYRK) 3.20 0.02247 21q22.1 Multiple intracellular signaling pathways 
 208112_x_at EH-domain containing 1 3.10 0.01748 11q13 Endocytosis of IGF-I receptor 
 211164_at EphA3 4.02 0.03566 3p11.2 Receptor tyrosine kinase, angiogenesis 
 205354_at Guanidinoacetate N-methyl-transferase 3.99 0.01697 19p13.3 Methyltransferase 
 207480_s_at Meis1, mouse, homologue of, 2 3.63 0.00542 15q14-q25 Limb development, Shh signaling 
 204880_at O6-methylguanine-DNA methyltransferase (MGMT) 3.70 0.00187 10q26 DNA repair; methylation-sensitive, methyltransferase 
 218186_at RAB25, member RAS oncogene family 3.29 0.04411 1q21.3 Small GTP-binding protein 
 205954_at Retinoid X receptor, γ 6.18 0.01620 1q22-q23 Cholesterol balance, growth inhibition 
 209936_at RNA binding motif protein 5 4.12 0.00249 3p21.3 Putative lung cancer tumor suppressor 
 207199_at Telomerase reverse transcriptase 3.90 0.03164 5p15.33 Telomere synthesis at chromosome end 
 202495_at Tubulin-specific chaperone C 3.04 0.00035 6pter-p12.1 Microtubule dynamics 
 210282_at Zinc finger protein 198 3.03 0.04792 13q11-q12 DNA repair, protein-protein interaction 
Affymetrix tag numberGene nameFold changePChromosomeFunction
Up-regulated      
 231029_at Adenylate kinase 2 6.23 0.04728 1p34 Mitochondrial enzyme, phosphorylation 
 39248_at Aquaporin 3 5.49 0.01123 9p13 Water and glycerol channel 
 204714_s_at Coagulation factor V 7.48 0.03040 1q23 Procoagulation factor 
 204154_at Cysteine dioxygenase, type 1 3.90 0.01222 5q22-q23 Cysteine oxidation to inorganic sulfate 
 228124_at DKFZP434P106 protein 3.44 0.00229 20p11.1 Unknown function 
 208399_s_at Endothelin 3 6.84 0.04685 30q13.2-q13.3 Stimulates neural crest cell proliferation 
 205649_s_at Fibrinogen, A alpha polypeptide 10.98 0.03503 4q28 Glycoprotein mediating vasoconstriction 
 218772_x_at Hypothetical protein FLJ10493 4.21 0.00141 9q31.2 Unknown function 
 205302_at Insulin-like growth factor binding protein 1 7.86 0.01370 7p13-p12 Cell growth, induced by hypoxia 
 210095_s_at Insulin-like growth factor binding protein 3 4.88 0.05865 7p13-p12 Cell growth inhibition and promotion 
 213564_x_at Lactate dehydrogenase B 3.62 0.01542 12p12.2-p12.1 Anaerobic glycolysis 
 209468_at Low-density lipoprotein receptor-related protein 5 4.91 0.04834 11q13.4 Wnt signal transducer, cholesterol metabolism, insulin secretion 
 213975_s_at Lysozyme 7.99 0.01948 12q14.3 Antibacterial protein 
 204438_at Macrophage mannose receptor, C type 1, MRC1 4.59 0.01203 10p13 Cell-cell recognition, anti-pathogenic 
 203510_at Met proto-oncogene, MET 4.90 0.00408 7q31 Tyrosine kinase, cell growth 
 201976_s_at Myosin X, MYO10 4.50 0.00479 5p15.1-p14.3 Extension of filopodia, binds calmodulin 
 218128_at NPC1-like 1 5.75 0.00008 7p13 Subcellular cholesterol trafficking 
 218128_at Nuclear transcription factor Y, β 3.05 0.00632 12q22-q23 Regulates MHC expression 
 204873_at Peroxisome biogenesis factor 1 3.08 0.03395 7q21-q22 Peroxisomal matrix protein import 
 232262_at Phosphatidylinositol glycan, class L 5.81 0.01635 17p12-p11 Cell surface protein membrane anchor 
 201120_s_at Progesterone receptor membrane component 1 5.43 0.02150 Xq22-q24 Putative steroid membrane receptor 
 225214_at Proteasome subunit, β type, 7 3.14 0.00281 9q34.11-q34.12 Degradation of ubiquitinated proteins 
 223551_at Protein kinase inhibitor β 3.77 0.00348 6q22.32 cAMP-dependent protein kinase inhibitor 
 219106_s_at Sarcomeric muscle protein 19.25 0.00597 2q31.1 Adult skeletal muscle protein 
 230318_at Serine (or cysteine) proteinase inhibitor, α-1-antitrypsin 15.21 0.00239 14q32.1 Proteinase inhibitor 
 205768_s_at Solute carrier family 27, member 2 12.91 0.00965 15q21.2 Fatty acid transporter 
 228754_at Solute carrier family 6 3.23 0.00641 3p25-p24 Taurine transport 
 219682_s_at T-box 3 4.38 0.04156 12q24.1 Transcription factor, morphogenesis 
 230535_s_at Tubulin, β 1 3.14 0.04101 20q13.32 Microtubule component 
 206505_at UDP glycosyltransferase 2 family, polypeptide B4 (UGT2B4) 8.80 0.04322 4q13 Chemical detoxification 
 204534_at Vitronectin (serum spreading factor) 4.90 0.00445 17q11 Cell attachment and spreading 
Down-regulated      
 203862_s_at Actinin, α 2 5.44 0.03671 1q42-q43 Actin binding protein 
 205393_s_at CHK1 checkpoint homologue 3.70 0.01385 11q22-q23 DNA damage checkpoint kinase 
 211079_s_at Dual-specificity tyrosine phosphorylation regulated kinase 1A (DYRK) 3.20 0.02247 21q22.1 Multiple intracellular signaling pathways 
 208112_x_at EH-domain containing 1 3.10 0.01748 11q13 Endocytosis of IGF-I receptor 
 211164_at EphA3 4.02 0.03566 3p11.2 Receptor tyrosine kinase, angiogenesis 
 205354_at Guanidinoacetate N-methyl-transferase 3.99 0.01697 19p13.3 Methyltransferase 
 207480_s_at Meis1, mouse, homologue of, 2 3.63 0.00542 15q14-q25 Limb development, Shh signaling 
 204880_at O6-methylguanine-DNA methyltransferase (MGMT) 3.70 0.00187 10q26 DNA repair; methylation-sensitive, methyltransferase 
 218186_at RAB25, member RAS oncogene family 3.29 0.04411 1q21.3 Small GTP-binding protein 
 205954_at Retinoid X receptor, γ 6.18 0.01620 1q22-q23 Cholesterol balance, growth inhibition 
 209936_at RNA binding motif protein 5 4.12 0.00249 3p21.3 Putative lung cancer tumor suppressor 
 207199_at Telomerase reverse transcriptase 3.90 0.03164 5p15.33 Telomere synthesis at chromosome end 
 202495_at Tubulin-specific chaperone C 3.04 0.00035 6pter-p12.1 Microtubule dynamics 
 210282_at Zinc finger protein 198 3.03 0.04792 13q11-q12 DNA repair, protein-protein interaction 
Table 2

Characteristics of metastatic and nonmetastatic primary PENs used for immunolabeling analysis

Nonmetastatic (n = 24)Metastatic (n = 15)
Mean age (y) 58 50 
Gender (male:female) 10:14 10:5 
Average diameter (cm) 4.8 5.5 
Diameter   
 ≥2 cm 17/24 (71%) 14/15 (93%) 
 ≥5 cm 6/24 (25%) 9/15 (60%) 
Ki67 index   
 ≥2% 4/24 (17%) 7/15 (47%) 
 ≥5% 1/24 (4%) 5/15 (33%) 
Angioinvasion 4/24 (17%) 10/15 (67%) 
Location   
 Head of pancreas 12/24 (50%) 9/15 (60%) 
 Pancreatic tail 12/24 (50%) 6/15 (40%) 
Associated syndromes 1 FAP 2 MEN-1, 1 VHL 
Functional PENs 5/24 (21%) 3/15 (20%) 
 Insulinoma 
 Glucagonoma 
 Gastrinoma 
 VIPoma 
Nonmetastatic (n = 24)Metastatic (n = 15)
Mean age (y) 58 50 
Gender (male:female) 10:14 10:5 
Average diameter (cm) 4.8 5.5 
Diameter   
 ≥2 cm 17/24 (71%) 14/15 (93%) 
 ≥5 cm 6/24 (25%) 9/15 (60%) 
Ki67 index   
 ≥2% 4/24 (17%) 7/15 (47%) 
 ≥5% 1/24 (4%) 5/15 (33%) 
Angioinvasion 4/24 (17%) 10/15 (67%) 
Location   
 Head of pancreas 12/24 (50%) 9/15 (60%) 
 Pancreatic tail 12/24 (50%) 6/15 (40%) 
Associated syndromes 1 FAP 2 MEN-1, 1 VHL 
Functional PENs 5/24 (21%) 3/15 (20%) 
 Insulinoma 
 Glucagonoma 
 Gastrinoma 
 VIPoma 

NOTE. Functional PEN status was determined by clinical syndromes and elevated serum hormone levels.

Abbreviations: MEN-1, multiple endocrine neoplasia, type 1; VHL, von Hippel-Lindau syndrome; FAP, familial adenomatous polyposis syndrome.

Table 3

Expression of up-regulated genes in primary and metastatic pancreatic endocrine neoplasms

Nonmetastatic primaryMetastatic primaryLymph node metastasesLiver metastases
IGFBP3 10/24 (42%) 12/15 (80%) 6/7 (86%) 9/9 (100%) 
MET 4/24 (17%) 5/15 (33%) 4/7 (57%) 5/9 (56%) 
Nonmetastatic primaryMetastatic primaryLymph node metastasesLiver metastases
IGFBP3 10/24 (42%) 12/15 (80%) 6/7 (86%) 9/9 (100%) 
MET 4/24 (17%) 5/15 (33%) 4/7 (57%) 5/9 (56%) 
1
Gumbs AA, Moore PS, Falconi M, et al Review of the clinical, histological, and molecular aspects of pancreatic endocrine neoplasms.
J Surg Oncol
2002
;
81
:
45
-53.discussion 54
2
Hochwald SN, Zee S, Conlon KC, et al Prognostic factors in pancreatic endocrine neoplasms: an analysis of 136 cases with a proposal for low-grade and intermediate-grade groups.
J Clin Oncol
2002
;
20
:
2633
-42.
3
Wang EH, Ebrahimi SA, Wu AY, Kashefi C, Passaro E, Jr, Sawicki MP Mutation of the MENIN gene in sporadic pancreatic endocrine tumors.
Cancer Res
1998
;
58
:
4417
-20.
4
Cupisti K, Hoppner W, Dotzenrath C, et al Lack of MEN1 gene mutations in 27 sporadic insulinomas.
Eur J Clin Investig
2000
;
30
:
325
-9.
5
Beghelli S, Pelosi G, Zamboni G, et al Pancreatic endocrine tumours: evidence for a tumour suppressor pathogenesis and for a tumour suppressor gene on chromosome 17p.
J Pathol
1998
;
186
:
41
-50.
6
Bartsch DK, Kersting M, Wild A, et al Low frequency of p16(INK4a) alterations in insulinomas.
Digestion
2000
;
62
:
171
-7.
7
Perren A, Komminoth P, Saremaslani P, et al Mutation and expression analyses reveal differential subcellular compartmentalization of PTEN in endocrine pancreatic tumors compared to normal islet cells.
Am J Pathol
2000
;
157
:
1097
-103.
8
Yashiro T, Fulton N, Hara H, et al Comparison of mutations of ras oncogene in human pancreatic exocrine and endocrine tumors.
Surgery (St. Louis)
1993
;
114
:
758
-63.
9
Missiaglia E, Moore PS, Williamson J, et al Sex chromosome anomalies in pancreatic endocrine tumors.
Int J Cancer
2002
;
98
:
532
-8.
10
Maitra A, Hansel DE, Argani P, et al Global expression analysis of well-differentiated pancreatic endocrine neoplasms using oligonucleotide microarrays.
Clin Cancer Res
2003
;
9
:
5988
-95.
11
Peghini PL, Iwamoto M, Raffeld M, et al Overexpression of epidermal growth factor and hepatocyte growth factor receptors in a proportion of gastrinomas correlates with aggressive growth and lower curability.
Clin Cancer Res
2002
;
8
:
2273
-85.
12
Maggiora P, Marchio S, Stella MC, et al Overexpression of the RON gene in human breast carcinoma.
Oncogene
1998
;
16
:
2927
-33.
13
Morello S, Olivero M, Aimetti M, et al MET receptor is overexpressed but not mutated in oral squamous cell carcinomas.
J Cell Physiol
2001
;
189
:
285
-90.
14
Kondoh N, Wakatsuki T, Ryo A, et al Identification and characterization of genes associated with human hepatocellular carcinogenesis.
Cancer Res
1999
;
59
:
4990
-96.
15
Ferry RJ, Jr, Cerri RW, Cohen P Insulin-like growth factor binding proteins: new proteins, new functions.
Horm Res
1999
;
51
:
53
-67.
16
Furstenberger G, Senn HJ Insulin-like growth factors and cancer.
Lancet Oncol
2002
;
3
:
298
-302.
17
Vadgama JV, Wu Y, Datta G, Khan H, Chillar R Plasma insulin-like growth factor I and serum IGF-binding protein 3 can be associated with the progression of breast cancer, and predict the risk of recurrence and the probability of survival in African-American and Hispanic women.
Oncology
1999
;
57
:
330
-40.
18
Goodwin PJ, Ennis M, Pritchard KI, et al Insulin-like growth factor binding proteins 1 and 3 and breast cancer outcomes.
Breast Cancer Res Treat
2002
;
74
:
65
-76.
19
Popovici RM, Lu M, Bhatia S, Faessen GH, Giaccia AJ, Giudice LC Hypoxia regulates insulin-like growth factor-binding protein 1 in human fetal hepatocytes in primary culture: suggestive molecular mechanisms for in utero fetal growth restriction caused by uteroplacental insufficiency.
J Clin Endocrinol Metab
2001
;
86
:
2653
-9.
20
Guvakova MA, Adams JC, Boettiger D Functional role of alpha-actinin, PI 3-kinase and MEK1/2 in insulin-like growth factor I receptor kinase regulated motility of human breast carcinoma cells.
J Cell Sci
2002
;
115
:
4149
-65.
21
Rotem-Yehudar R, Galperin E, Horowitz M Association of insulin-like growth factor 1 receptor with EHD1 and SNAP29.
J Biol Chem
2001
;
276
:
33054
-60.
22
Ma PC, Maulik G, Christensen J, Salgia R c-Met: structure, functions and potential for therapeutic inhibition.
Cancer Metastasis Rev
2003
;
22
:
309
-25.
23
Trusolino L, Comoglio PM Scatter-factor and semaphorin receptors: cell signalling for invasive growth.
Nat Rev Cancer
2002
;
2
:
289
-300.
24
Zhang YW, Van de Woude GF HGF/SF-met signaling in the control of branching morphogenesis and invasion.
J Cell Biochem
2003
;
88
:
408
-17.
25
Kitajima Y, Miyazaki K, Matsukura S, Tanaka M, Sekiguchi M Loss of expression of DNA repair enzymes MGMT, hMLH1, and hMSH2 during tumor progression in gastric cancer.
Gastric Cancer
2003
;
6
:
86
-95.
26
Pulling LC, Divine KK, Klinge DM, et al Promoter hypermethylation of the O6-methylguanine-DNA methyltransferase gene: more common in lung adenocarcinomas from never-smokers than smokers and associated with tumor progression.
Cancer Res
2003
;
63
:
4842
-8.
27
Alonso ME, Bello MJ, Gonzalez-Gomez P, et al Aberrant promoter methylation of multiple genes in oligodendrogliomas and ependymomas.
Cancer Genet Cytogenet
2003
;
144
:
134
-42.
28
Zhao H, Watkins JL, Piwnica-Worms H Disruption of the checkpoint kinase 1/cell division cycle 25A pathway abrogates ionizing radiation-induced S and G2 checkpoints.
Proc Natl Acad Sci USA
2002
;
99
:
14795
-800.
29
Prendergast GC CHK and MEK inhibitors team up to trigger cancer cell suicide.
Cancer Biol Ther
2002
;
1
:
254
-5.
30
Kunapuli P, Somerville R, Still IH, Cowell JK ZNF198 protein, involved in rearrangement in myeloproliferative disease, forms complexes with the DNA repair-associated HHR6A/6B and RAD18 proteins.
Oncogene
2003
;
22
:
3417
-23.
31
Chauhan NB Membrane dynamics, cholesterol homeostasis and Alzheimer’s disease.
J Lipid Res
2003
;
44
:
2019
-29.
32
Tosi MR, Bottura G, Lucchi P, Reggiani A, Trinchero A, Tugnoli V Cholesteryl esters in human malignant neoplasms.
Int J Mol Med
2003
;
11
:
95
-8.
33
Fujino T, Asaba H, Kang MJ, et al Low-density lipoprotein receptor-related protein 5 (LRP5) is essential for normal cholesterol metabolism and glucose-induced insulin secretion.
Proc Natl Acad Sci USA
2003
;
100
:
229
-34.
34
Schneider WJ, Nimpf J LDL receptor relatives at the crossroad of endocytosis and signaling.
Cell Mol Life Sci
2003
;
60
:
892
-903.
35
Stahl A A current review of fatty acid transport proteins (SLC27).
Pflugers Arch
2004
;
447
:
722
-7.
36
Davies JP, Levy B, Ioannou YA Evidence for a Niemann-pick C (NPC) gene family: identification and characterization of NPC1L1.
Genomics
2000
;
65
:
137
-45.