Gene expression profiles of microdissected pancreatic ductal adenocarcinoma

Grützmann, Robert; Foerder, Melanie; Alldinger, Ingo; Staub, Eike; Brümmendorf, Thomas; Röpcke, Stefan; Li, Xinzhong; Kristiansen, Glen; Jesnowski, Ralf; Sipos, Bence; Löhr, Matthias; Lüttges, Jutta; Ockert, D.; Klöppel, Günter; Saeger, H. D.; Pilarsky, Christian

doi:10.1007/s00428-003-0884-1

Cited by 93 publications

(31 citation statements)

References 48 publications

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“…To interpret our results in a general context, we analysed the data already published on the 568 genes using all published data sets on pancreatic cancer, including the four studies used here (Han et al, 2002;Iacobuzio-Donahue et al, 2002CrnogoracJurcevic et al, 2003;Friess et al, 2003;Grutzmann et al, 2003;Logsdon et al, 2003;Tan et al, 2003;Nakamura et al, 2004) (Table 2). Of the set of 568 genes, 189 were found in these 10 publications.…”

Section: Resultsmentioning

confidence: 99%

“…A total of 10 individual studies on gene expression in pancreatic cancer have been published so far (Han et al, 2002;Iacobuzio-Donahue et al, 2002Crnogorac-Jurcevic et al, 2003;Friess et al, 2003;Grutzmann et al, 2003;Logsdon et al, 2003;Tan et al, 2003;Nakamura et al, 2004). But, the concordance of these studies is rather low, with 86 genes described in at least two independent studies of 548 genes published in eight of these studies.…”

Section: Discussionmentioning

confidence: 99%

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Meta-analysis of microarray data on pancreatic cancer defines a set of commonly dysregulated genes

Boriss²,

et al. 2005

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Pancreatic ductal adenocarcinoma is the eighth most common cancer with the lowest overall 5-year relative survival rate of any tumor type today. Expression profiling using microarrays has been widely used to identify genes associated with pancreatic cancer development. To extract maximum value from the available gene expression data, we applied a meta-analysis to search for commonly differentially expressed genes in pancreatic ductal adenocarcinoma. We obtained data sets from four different gene expression studies on pancreatic cancer. We selected a consensus set of 2984 genes measured in all four studies and applied a meta-analysis approach to evaluate the combined data. Of the genes identified as differentially expressed, several were validated using RT-PCR and immunohistochemistry. Additionally, we used a class discovery algorithm to identify a gene expression signature. Our meta-analysis revealed that the pancreatic cancer gene expression data sets shared a significant number of up-and downregulated genes, independent of the technology used. This interstudy crossvalidation approach generated a set of 568 genes that were consistently and significantly dysregulated in pancreatic cancer. Of these, 364 (64.1%) were upregulated and 204 (35.9%) were downregulated in pancreatic cancer. Only 127 (22%) were described in the published individual analyses. Functional annotation of the genes revealed that genes presumably associated with the cell adhesionmediated drug resistance pathway are frequently overexpressed in pancreatic cancer. Meta-analysis is an important tool for the identification and validation of differentially expressed genes. These could represent good candidates for novel diagnostic and therapeutic approaches to pancreatic cancer.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Meta-analysis of microarray data on pancreatic cancer defines a set of commonly dysregulated genes

Boriss²,

et al. 2005

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“…High-throughput screening analyses have identified a multitude of differences between malignant and benign processes in the pancreas, as well as between different malignant tumor entities, on the genome [16][17][18][19], transcriptome [20][21][22][23][24][25][26][27][28][29][30][31][32][33], proteome [34][35][36][37][38], and epigenome [39][40][41][42] levels. Based on these results, a growing number of studies report on the use of one or several of these molecular markers in pre-operative diagnostic analysis of serum, pancreatic juice, brush cytologies, or FNABs.…”

Section: Discussionmentioning

confidence: 99%

Differentiation of multiple types of pancreatico-biliary tumors by molecular analysis of clinical specimens

et al. 2011

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Timely and accurate diagnosis of pancreatic ductal adenocarcinoma (PDAC) is critical in order to provide adequate treatment to patients. However, the clinical signs and symptoms of PDAC are shared by several types of malignant or benign tumors which may be difficult to differentiate from PDAC with conventional diagnostic procedures. Among others, these include ampullary cancers, solid pseudopapillary tumors, and adenocarcinomas of the distant bile duct, as well as inflammatory masses developing in chronic pancreatitis. Here, we report an approach to accurately differentiate between these different types of pancreatic masses based on molecular analysis of biopsy material. A total of 156 bulk tissue and fine needle aspiration biopsy samples were analyzed using a dedicated diagnostic cDNA array and a composite classification algorithm developed based on linear support vector machines. All five histological subtypes of pancreatic masses were clearly separable with 100% accuracy when using all 156 individual samples for classification. Generalized performance of the classification system was tested by 10 × 10-fold cross validation (100 test runs). Correct classification into the five diagnostic groups was demonstrated for 81.5% of 1,560 test set predictions. Performance increased to 85.3% accuracy when PDAC and distant bile duct carcinomas were combined in a single diagnostic class. Importantly, overall sensitivity of detection of malignant disease was 92.2%. The molecular diagnostic approach presented here is suitable to significantly aid in the differential diagnosis of undetermined pancreatic masses. To our knowledge, this is the first study reporting accurate differentiation between several types of pancreatico-biliary tumors in a single molecular analytical procedure.

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“…Here, we report the case of an unusual pancreatic tumor with tubulopapillary and microcystic features, which could not be assigned to any of the known pancreatic tumor types. The histological and immunohistochemical data and the results of a molecular analysis, which included the use of the increasingly employed microarray technology [11], all suggest that this tumor represents a new entity, not previously described in the pancreas.…”

Section: Introductionmentioning

confidence: 98%

Microcystic tubulopapillary carcinoma of the pancreas: a new tumor entity?

et al. 2004

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An unusual pancreatic tumor with microcystic and tubulopapillary features was observed in a 53-year-old woman. The tumor presented as a large, focally cystic mass in the head of the pancreas, which compressed the surrounding structures. The histological and immunohistochemical analysis revealed a neoplasm that could not be assigned to any of the known pancreatic tumor types. At the molecular level, the tumor showed inactivation of the DPC4/SMAD4 gene, deletion of exon 1 of the p16(INK4A) gene and a point mutation at codon 34 (GGA>AGA) of beta-catenin. Transcriptional profiling analyses and subsequent correspondence cluster analysis demonstrated that the transcriptional profile of the tumor differed distinctly from that of ductal adenocarcinomas, pancreatic cystic tumors and normal pancreatic tissues. These data suggest that the neoplasm most likely represents a new pancreatic tumor entity, which we would like to refer to as microcystic tubulopapillary tumor.

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Gene expression profiles of microdissected pancreatic ductal adenocarcinoma

Cited by 93 publications

References 48 publications

Meta-analysis of microarray data on pancreatic cancer defines a set of commonly dysregulated genes

Meta-analysis of microarray data on pancreatic cancer defines a set of commonly dysregulated genes

Differentiation of multiple types of pancreatico-biliary tumors by molecular analysis of clinical specimens

Microcystic tubulopapillary carcinoma of the pancreas: a new tumor entity?

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