Originally published as JCO Early Release 10.1200/JCO.2005.05.5194 on September 11 2006

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MicroRNA Expression Abnormalities in Pancreatic Endocrine and Acinar Tumors Are Associated With Distinctive Pathologic Features and Clinical Behavior

Claudia Roldo, Edoardo Missiaglia, John P. Hagan, Massimo Falconi, Paola Capelli, Samantha Bersani, George Adrian Calin, Stefano Volinia, Chang-Gong Liu, Aldo Scarpa, Carlo M. Croce

From the Departments of Molecular Virology, Immunology and Medical Genetics and Comprehensive Cancer Center, Ohio State University, Columbus, OH; Departments of Pathology and Surgical and Gastroenterological Sciences, Università di Verona, Verona; and the Department of Morphology and Embryology, University of Ferrara, Ferrara, Italy

Address reprint requests in the United States to Carlo M. Croce, MD, Ohio State University, Comprehensive Cancer Center, Wiseman Hall Room 385K, 410 W 12th Ave, Columbus, OH; e-mail: Carlo.Croce{at}osumc.edu; and in Europe to Aldo Scarpa, MD, Verona University, strada Le grazie 8, 37134 Verona, Italy; e-mail: aldo.scarpa{at}univr.it

	ABSTRACT

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION Appendix Authors' Disclosures of... Author Contributions GLOSSARY REFERENCES

 
PURPOSE: We investigated the global microRNA expression patterns in normal pancreas, pancreatic endocrine tumors and acinar carcinomas to evaluate their involvement in transformation and malignant progression of these tumor types. MicroRNAs are small noncoding RNAs that regulate gene expression by targeting specific mRNAs for degradation or translation inhibition. Recent evidence indicates that microRNAs can contribute to tumor development and progression and may have diagnostic and prognostic value in several human malignancies.

MATERIALS AND METHODS: Using a custom microarray, we studied the global microRNA expression in 12 nontumor pancreas and 44 pancreatic primary tumors, including 12 insulinomas, 28 nonfunctioning endocrine tumors, and four acinar carcinomas.

RESULTS: Our data showed that a common pattern of microRNA expression distinguishes any tumor type from normal pancreas, suggesting that this set of microRNAs might be involved in pancreatic tumorigenesis; the expression of miR-103 and miR-107, associated with lack of expression of miR-155, discriminates tumors from normal; a set of 10 microRNAs distinguishes endocrine from acinar tumors and is possibly associated with either normal endocrine differentiation or endocrine tumorigenesis; miR-204 is primarily expressed in insulinomas and correlates with immunohistochemical expression of insulin; and the overexpression of miR-21 is strongly associated with both a high Ki67 proliferation index and presence of liver metastasis.

CONCLUSION: These results suggest that alteration in microRNA expression is related to endocrine and acinar neoplastic transformation and progression of malignancy, and might prove useful in distinguishing tumors with different clinical behavior.

	INTRODUCTION

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION Appendix Authors' Disclosures of... Author Contributions GLOSSARY REFERENCES

 
Pancreatic endocrine tumors (PETs) may occur sporadically or as part of multiple endocrine neoplasia type 1 syndrome.¹ These neoplasms are clinically classified as functioning (F-PET) or nonfunctioning (NF-PET), according to the presence of symptoms due to hormone hypersecretion. F-PETs are mainly represented by insulinomas. At diagnosis, metastatic disease is observed in only 10% of insulinomas but in up to 60% of NF-PETs, and most PET-related deaths are caused by liver metastasis.¹ The malignant potential among PETs varies greatly and cannot be predicted on the basis of histologic appearance. In fact, the vast majority of PETs are well-differentiated endocrine tumors (WDETs) and are defined as carcinoma (WDEC) only when invasion or metastases are identified.¹

Pancreatic acinar cell carcinoma (PACC) is an extremely rare tumor type distinct from ductal adenocarcinoma and PET, although some overlap with PET is testified by both the expression of neuroendocrine markers in one third of the cases and the existence of mixed acinar-endocrine carcinomas.² PACC is always malignant with a median survival of 18 months, which lies between that of pancreatic ductal adenocarcinoma and endocrine neoplasms (6 months and 40 months, respectively³).

Little is known about the molecular pathogenesis of PETs.⁴ Inactivation of multiple endocrine neoplasia type 1 gene is the most frequent genetic event identified in sporadic PET,⁵ whereas mutations in genes typically involved in pancreatic adenocarcinoma are uncommon.⁵ Even less is known regarding the molecular anomalies of PACC.⁶ No gene expression profile data are available for PACC, and our understanding of gene expression changes that occur in PET is still at an initial phase.⁷

MicroRNAs are small (20 to 24 nucleotides) noncoding RNA gene products that serve critical roles in cell proliferation, apoptosis and developmental timing by negatively regulating the stability or translational efficiency of their target mRNAs.⁸ Currently, 462 unique mature human microRNAs are known (http://microrna.sanger.ac.uk). Aberrant expression of microRNAs has been linked to cancers,^9,10 and diagnostic/prognostic characteristics of specific cancer types can be distinguished based on their microRNA profiles.^11-19 Functional studies also have linked aberrant microRNA expression to carcinogenesis.^20-23

We investigated the global microRNA expression patterns in normal pancreas, primary pancreatic endocrine tumors and acinar carcinomas to evaluate their involvement in transformation and malignant progression of these tumor types.

	MATERIALS AND METHODS

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION Appendix Authors' Disclosures of... Author Contributions GLOSSARY REFERENCES

 
Patient Data, Neoplastic-Cell Enrichment, and RNA Extraction
All samples were from frozen primary tumors collected at the Department of Pathology, Verona University, Verona, Italy. All tumors were sporadic, as assessed by personal and family histories. PET were diagnosed and classified according to WHO criteria.¹ They included 28 nonfunctional and 12 functional tumors. The 28 NF-PET included 11 WDETs and 17 WDECs. The 12 F-PET were insulinomas, comprising 11 WDETs and one WDEC. Diagnosis of PACC was confirmed by immunohistochemical expression of lipase, amylase, and trypsin. As a control, normal pancreas was taken in 12 corresponding patient specimens.

A neoplastic cellularity higher than 90% was obtained by cryostat enrichment. RNA was extracted with Trizol (Invitrogen, Carlsbad, CA) from 10 20-µm thick cryostat sections, checking the cell composition of the sample every five sections. RNA integrity was confirmed using the Agilent 2100 Bioanalyzer (Agilent Technologies, Palo Alto, CA).

MicroRNA Microarray Hybridization and Quantification
MicroRNA labeling and hybridization were performed as described previously,²⁴ using 5 µg of total RNA. Our microRNA microarray (Ohio State University Comprehensive Cancer Center, version 2.0) contains probes for 460 mature microRNAs spotted in quadruplicate (235 homo sapiens, 222 mus musculus, and three Arabidopsis thaliana) with annotated active sites. Often, more than one probe set exists for a given mature microRNA. Additionally, there are quadruplicate probes corresponding to most precursor microRNA. Hybridization signals were detected with Streptavidin-Alexa647 conjugate and scanned images (Axon 4000B) were quantified using the Genepix 6.0 software (Axon Instruments, Sunnyvale, CA).

Computational Analysis of microRNA Microarray Data
Most of the analysis and graphics were generated using R software version 2.0.1 and Bioconductor version 1.6²⁵ packages. Sequentially, the blank and probe controls spots were removed from the data set of the 56 microRNA microarrays, and the local background was then subtracted from the median signal. Next, the data were normalized using a variance-stabilizing transformation stratified, within each array, by grid using the vsn package.²⁶ The data resulting from this transformation can be considered as equivalent to logarithmic transformed data.²⁶ Subsequently, the genefilter package was used to remove all the spots whose intensities were lower than 99th percentile of the intensities of blank spots in all the arrays. To select the differentially expressed genes between pairs of relevant sample categories, the data obtained were then analyzed by direct two-class unpaired comparison using the samr package. To increase stringency, we considered only the microRNA probes that had at least three significantly differentially expressed spots out of the four replicas contained in the array. The fold change reported in the tables is the median value of these spot replicas.

Hierarchical cluster analysis was performed using the aggregate values of replicate spots obtained applying Tukey's median polish algorithm. The analysis was done using the 200 probes containing the mature microRNA sequences with the highest interquartile range. The distance metrics used to cluster samples and genes were Pearson correlation and Euclidean distance, respectively. The agglomerative method was the complete-linkage. The output was visualized using Maple Tree (version 0.2.3.2, http://mapletree.sourceforge.net/). All data were submitted using MIAMExpress to the Array Express database (http://www.ebi.ac.uk/arrayexpress/).

Northern Blotting
Five micrograms of total RNAs prepared from samples derived from the same patients but different from those used in the microarray experiment were run on 15% Criterion polyacrylamide gel electrophoresis/Urea gels (Bio-Rad, Hercules, CA), transferred onto Hybond-N+ membranes (Amersham, Piscataway, NJ) and hybridized overnight with ³²P end-labeled probes at 37°C in ULTRAhyb-Oligo hybridization buffer (Ambion, Austin, TX). The probes were antisense oligonucleotides relative to the mature microRNAs and to 5S RNA as normalizer. Membranes were washed at 37°C twice for 30 minutes each with 2XSSC/0.5% sodium dodecyl sulfate (SDS), analyzed using a Typhoon 9410 phoshorimager (Amersham) and quantified using ImageQuant-TL (Amersham). Blots were stripped by boiling in 0.1% aqueous SDS for 5 minutes and were reprobed several times.

	RESULTS

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION Appendix Authors' Disclosures of... Author Contributions GLOSSARY REFERENCES

 
MicroRNA expression profiles were determined for 12 nontumor pancreas and 44 primary pancreatic tumors, including 40 PETs and four PACCs, using a custom microarray platform that was proven to give robust results, as validated by several studies.^12,17,19,24 The unsupervised hierarchical clustering, using the 200 most variable microRNAs, showed a common microRNA expression pattern distinguishing PET and PACC from normal pancreas (Fig 1). Notably, PACCs fell into a unique cluster that was part of the wider cluster including all PETs, whereas there was no distinctive pattern between insulinomas and NF-PET.

View larger version (76K): [in this window] [in a new window]   Fig 1. Unsupervised hierarchical clustering of 12 normal pancreas and 44 pancreatic tumors, including 22 well-differentiated pancreatic endocrine tumors (WDETs), 18 well-differentiated pancreatic endocrine carcinomas (WDECs) and four pancreatic acinar cell carcinomas (PACCs). WDET included 11 insulinomas (INS) and 11 NF-PET; WDEC included 1 INS and 17 NF-PET. (A, B) Some microRNAs upregulated in PET versus normal tissue (in red); (C) two microRNAs upregulated in INS versus NF-PET (in blue); (D) some microRNAs downregulated (in green).

View larger version (22K): [in this window] [in a new window]   Fig 2. Venn diagram illustrating the relationships between sets of microRNAs found differentially expressed using direct two class unpaired comparisons. Circles include the total number of differentially expressed microRNAs in the pairwise comparison indicated. The intersection areas identify the number of differentially expressed microRNAs in common between each comparison. Normal, nontumor; PET, pancreatic endocrine tumor; PACC, pancreatic acinar cell carcinoma.

Among the upregulated microRNAs in PET that are also common to PACC, seven were validated by Northern analysis. MiR-103 was the best discriminator for all pairwise comparisons of normal pancreas, acinar carcinomas, and endocrine tumors (Fig 3). The expression of miR-107 paralleled that of its highly homologous miR-103, and the significant overexpression in tumors versus normal of miR-23a, miR-26b, miR-192, and miR-342 was also confirmed (online only Fig 1).

View larger version (26K): [in this window] [in a new window]   Fig 3. The overexpression of miR-103 and lack of expression of miR-155 is peculiar to pancreatic insular and acinar tumors. Box-and-whiskers plots showing the expression levels of (A) miR-103 and (B) miR-155 measured by microarray analysis in 12 nontumor pancreas (normal) and 44 pancreatic tumors, including 22 well-differentiated pancreatic endocrine tumors (WDETs), 18 well-differentiated pancreatic endocrine carcinomas (WDECs) and four pancreatic acinar cell carcinomas (ACCs). Median intensity is highlighted by bold lines. (C) Northern blot analysis parallels the microarray expression data.

Limited Set of microRNA Distinguishes Pancreatic Endocrine From Acinar Tumors
The direct comparison of PET and PACC showed only 10 upregulated microRNAs, all of which were also overexpressed in PET versus normal tissue. In contrast, no microRNA was found to be specifically up- or downregulated in PACC.

Overexpression of miR-204 Is Specific to Insulinomas and Correlates With Immunohistochemical Expression of Insulin
The comparison of insulinomas with NF-PET identified only three microRNAs that were significantly overexpressed in insulinomas, including miR-204, its homologous miR-211, and miR-203. Notably, the immunohistochemical expression of insulin correlated with miR-204 expression more strongly than with insulin mRNA expression (Fig 4). In fact, logistic regression analysis, based on negative or positive immunohistochemical staining, showed that the protein expression was predicted by both insulin mRNA and miR-204 expression (P < .001); however, in a multivariate model only miR-204 expression retained statistical significance (P < .001).

View larger version (37K): [in this window] [in a new window]   Fig 4. miR-204 overexpression is specific to insulinomas and correlates with immunohistochemical expression of insulin. (A) Box-and-whiskers plot showing the expression level of miR-204 measured by microarray analysis in 12 nontumor pancreas (normal), 12 insulinomas (INSs), 28 nonfunctioning pancreatic endocrine tumors (NF-PETs) and four pancreatic acinar cell carcinomas (ACCs). Median intensity is highlighted by bold lines. (B) Strong correlation observed between miR-204 expression and insulin staining assessed by immunohistochemistry. Significant correlation was found also between miR-204 expression and insulin mRNA expression (Pearson correlation = 0.42; 95% CI, 0.12 to 0.65; P = .008). (C, D) Northern blot analysis confirms the microarray expression data.

Expression of miR-21 Is Strongly Associated With the Proliferation Index and Presence of Liver Metastasis
The evaluation of expression profiles to identify microRNAs discriminating PETs based on either metastatic status or proliferation index identified only miR-21 as significant (Fig 5). This is not surprising, because these two tumor characteristics are interconnected. In fact, all metastatic PETs had a proliferation index more than 2%, whereas no tumor with a lower proliferation score was metastatic. Furthermore, miR-21 also distinguished between NF-PETs or WDECs with high (Ki67 > 2%) and low (Ki67 2%) proliferation index. Another interesting observation is that miR-21 was also overexpressed in PACCs versus nontumor pancreas.

View larger version (27K): [in this window] [in a new window]   Fig 5. Expression of miR-21 is strongly associated with presence of liver metastasis and tumoral proliferation index. The box-and-whiskers plots show the different expression level of miR-21, measured by microarray analysis, (A) between pancreatic endocrine tumors with (Meta+) or without (Meta–) liver metastasis, and (B) between tumors with a proliferation index more than 2% (high) or 2 (low), as measured by Ki67 immunohistochemistry. (C) Northern blot analysis confirms microarray expression data. WDEC, well-differentiated pancreatic endocrine carcinoma; WDET, well-differentiated pancreatic endocrine tumor.

View larger version (13K): [in this window] [in a new window]   Fig 6. Inverse correlation between the expression of miR-21 and its putative mRNA target PDCD4. The plot shows the expression of miR-21 and PDCD4 mRNA in normal pancreas (*), metastatic (), and nonmetastatic () PET. A robust locally weighted regression function has been used to fit a line among data points. Pearson correlation = –0.49 (95% CI, –0.68 to 0.23; P < .001).

	DISCUSSION

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION Appendix Authors' Disclosures of... Author Contributions GLOSSARY REFERENCES

Unsupervised hierarchical clustering of the expression profiles showed that both tumor types were separated from normal pancreas. Although PACCs fell into a unique cluster, this was part of the wider cluster including all PETs. Although we identified many more differentially expressed microRNAs in PET versus healthy than between PACC versus healthy, the vast majority of differentially expressed microRNAs in PACC were similarly altered in PET. It is worth noting that healthy pancreas is largely formed by acini and therefore represents the ideal normal counterpart for the analysis of acinar cell carcinomas, whereas pancreatic islet cells would represent the healthy counterpart for pancreatic endocrine tumors. Unfortunately, we had no preparations of these cells available. Nonetheless, the finding of a largely concordant pattern of differentially expressed microRNAs between acinar and insular tumors, including 28 upregulated and five downregulated genes, suggests that this set common to both tumor types might be related to pancreatic neoplastic transformation. Providing additional support for this assertion, several microRNAs differentially expressed in both our tumor types have been found differentially expressed also in breast,¹⁷ colon¹¹ and B-cell leukemia.¹² In addition, at least 20 of the differentially expressed microRNAs in our tumors have been identified as having either growth related or apoptotic effects in the lung A549 or cervical HeLa carcinoma cell lines.²⁸

Furthermore, both PACC and PET showed the coordinate overexpression of miR-17, miR-20 and miR-92-1, which are contained in a polycistronic cluster. This miR-17-92 cluster has been described to act as an oncogene in association with MYC gene.²² Notably, overexpression of MYC has been reported in PET and also in hyperplastic islets, suggesting its involvement in the early phases of insular tumorigenesis.²⁹ In addition, induction of MYC in islet or acinar cells of mouse in vitro or in vivo models produces endocrine tumors^30,31 or mixed acinar/ductal adenocarcinomas,³² respectively, while suppression of MYC-induced apoptosis leads to islet cell carcinoma.³³

The expression of the two highly homologous miR-103 and miR-107 together with the lack of expression of miR-155 was distinctive of tumors versus nontumor tissue. Interestingly, miR-103/107 have been found to be overexpressed in several tumor types.³⁴ The finding that miR-155 was expressed in healthy pancreas and lacking in both PET and PACC is rather interesting as overexpression of miR-155 has been observed in lymphomas^16,35,36 and breast cancer,¹⁷ finding that have led to the speculation that miR-155 may be an oncogenic microRNA.¹⁰ This may not be unexpected, as microRNAs expressed in adults are tissue specific³⁷ and the consequences of microRNA misexpression is highly dependent on the cell-specific expression pattern of mRNAs that are microRNA regulated.²⁸

Ten microRNAs were peculiarly overexpressed in PET and differentiated this tumor from both PACC and normal pancreas. These included miR-99a, 99b, 100, 125a, 125b-1, 125b-2, 129-2, 130a, 132, and 342. These microRNAs may be characteristic of either normal pancreatic endocrine differentiation or endocrine tumorigenesis. Conversely, no microRNA was found to be specifically up- or downregulated in PACC, though the limited number of PACC samples may have affected the power of the analysis.

Although the microRNA profiles were almost indistinguishable between insulinomas and nonfunctioning endocrine tumors, the overexpression of the two closely related miR-204 and miR-211 was restricted to insulinomas. Notably, miR-204 expression correlated with the immunohistochemical expression of insulin. In this respect, miR-375 has been recently reported to be specifically expressed in mouse pancreatic islets and to function as a negative regulator of insulin exocytosis.²⁷ Our data showed that this microRNA is expressed in human normal pancreas as well as in acinar and endocrine tumors. However, no difference was found in its expression level between insulinomas and nonfunctioning endocrine tumors.

We also determined whether microRNA expression was correlated with the clinical characteristics of PETs. Our results showed that miR-21 overexpression is associated with both enhanced Ki67 proliferation index and liver metastasis. MiR-21 overexpression has been observed in several cancers, including glioblastoma, breast, lung and colon cancers.^9,10,15,17 A cancer-related function of miR-21 is also supported by knockdown experiments in glioblastoma cells showing that this microRNA has an antiapoptotic function.²⁰ In this respect, the programmed cell death 4 (PDCD4) gene, putatively targeted by miR-21, was found significantly downregulated in our metastatic and high proliferative PET, and showed an inverse correlation with the expression of miR-21. This gene has been reported to act as a tumor suppressor implied in cellular invasion and metastasis.³⁸ Furthermore, PDCD4 expression is lost in progressed carcinomas of lung, breast, colon, and prostate,³⁹ and a tumor suppressor role for PDCD4 has been also reported in neuroendocrine tumor cells.⁴⁰

MicroRNAs exert their biologic effects by targeting specific mRNAs for degradation or translational inhibition. To get insights into the biologic implications of the most interesting microRNAs showing altered expression in pancreatic tumors (ie, miR-103/miR-107, miR-155, miR-204/miR-211, and miR-21), we searched predicted targets that were in common among those identified by three different algorithms, discussed in Results. Then, to evaluate whether there was a correlation between the expression of microRNAs and that of their predicted targets, we took advantage of the microarry expression profiles of the same tumor and normal samples (Missiaglia et al, manuscript in preparation). Among the selected targets that were contained in our microarray, we found several up- and downregulated genes. Interestingly, the predicted target genes of miR-103/107 were overexpressed more frequently than expected. This finding parallels that of Babak et al, ³⁷ who reported a low correlation between microRNA expression and their predicted mRNA targets in a set of 17 different mouse tissues. This supports the currently favored model that most microRNAs act more likely through translational inhibition without mRNA degradation.⁴¹

In conclusion, our study suggests that alteration in microRNA expression is related to endocrine and acinar neoplastic transformation and progression of malignancy.

	Appendix

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION Appendix Authors' Disclosures of... Author Contributions GLOSSARY REFERENCES

 

View larger version (34K): [in this window] [in a new window]   Fig A1. Validation of microarray data for a set of overexpressed microRNAs. The Northern blot analysis shown in (A) and (B) demonstrate the overexpression of miR-23a, miR-26b, miR-107, and miR-342 in all the pancreatic insulinomas and nonfunctioning endocrine tumors tested (NF-PET). Northern hybridization in (C) shows the overexpression of miR-192 in four of eight well-differentiated endocrine tumors (WDET), in all four well-differentiated endocrine carcinomas (WDEC), and one acinar cell carcinoma (ACC).

View larger version (32K): [in this window] [in a new window]   Fig A2. Mir-375 expression is specific of normal pancreas and is common in pancreatic insular and acinar tumors. The Northern blot in (A) shows that miR-375 is a pancreas specific miR, and its expression is a feature of pancreatic endocrine and acinar tumors (B and C), irrespective of the presence (insulinomas or absence (NF-PET and ACC) of clinically evident insulin oversecretion. NF-PET, nonfunctioning pancreatic endocrine tumors; ACC, acinar cell carcinoma.

	Authors' Disclosures of Potential Conflicts of Interest

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION Appendix Authors' Disclosures of... Author Contributions GLOSSARY REFERENCES

	Author Contributions

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION Appendix Authors' Disclosures of... Author Contributions GLOSSARY REFERENCES

 

Conception and design: Aldo Scarpa, Carlo M. Croce Financial support: Aldo Scarpa, Carlo M. Croce Provision of study materials or patients: Massimo Falconi, Paola Capelli, Samantha Bersani, Aldo Scarpa Collection and assembly of data: Claudia Roldo, Massimo Falconi, Paola Capelli, Aldo Scarpa Data analysis and interpretation: Claudia Roldo, Edoardo Missiaglia, John P. Hagan, Massimo Falconi, Paola Capelli, George Adrian Calin, Stefano Volinia, Chang-gong Liu, Aldo Scarpa, Carlo M. Croce Manuscript writing: Claudia Roldo, Edoardo Missiaglia, George Adrian Calin, Aldo Scarpa Final approval of manuscript: Carlo M. Croce

 

	GLOSSARY

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION Appendix Authors' Disclosures of... Author Contributions GLOSSARY REFERENCES

 

MicroRNA profiles:

The study of the global expression of microRNAs in tissues.

MicroRNAs:

Endogenous noncoding RNAs approximately 22 nucleotides long that regulate gene silencing by post-transcriptional mechanisms such as cleavage or translational repression.

	ACKNOWLEDGMENTS

 
We thank Stefano Barbi, PhD, for critically reviewing the bioinformatic sections.

	NOTES

 
published online ahead of print at www.jco.org on September 11, 2006.

Supported by Program Project Grants No. P01CA76259 and P01CA81534 from the National Cancer Institute (C.M.C.), by a Kimmel Scholar award (G.A.C.), Associazione Italiana Ricerca Cancro (AIRC; A.S.), Milan, Italy; Fondazione Cassa di Risparmio di Verona (Bando 2005), Italy; Ministeri Università e Salute, Rome, Italy; European Community Grant No. PL018771; and Fondazione Giorgio Zanotto, Verona, Italy.

C.R. and E.M. contributed equally to this work. A.S. and C.M.C. contributed equally to this work.

Terms in blue are defined in the glossary, found at the end of this article and online at www.jco.org.

Authors' disclosures of potential conflicts of interest and author contributions are found at the end of this article.

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Submitted December 28, 2005; accepted June 29, 2006.

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