Examination of Apoptosis Signaling in Pancreatic Cancer by Computational Signal Transduction Analysis

Abstract

BackgroundPancreatic ductal adenocarcinoma (PDAC) remains an important cause of cancer death. Changes in apoptosis signaling in pancreatic cancer result in chemotherapy resistance and aggressive growth and metastasizing. The aim of this study was to characterize the apoptosis pathway in pancreatic cancer computationally by evaluation of experimental data from high-throughput technologies and public data bases. Therefore, gene expression analysis of microdissected pancreatic tumor tissue was implemented in a model of the apoptosis pathway obtained by computational protein interaction prediction.Methodology/Principal FindingsApoptosis pathway related genes were assembled from electronic databases. To assess expression of these genes we constructed a virtual subarray from a whole genome analysis from microdissected native tumor tissue. To obtain a model of the apoptosis pathway, interactions of members of the apoptosis pathway were analysed using public databases and computational prediction of protein interactions. Gene expression data were implemented in the apoptosis pathway model. 19 genes were found differentially expressed and 12 genes had an already known pathophysiological role in PDAC, such as Survivin/BIRC5, BNIP3 and TNF-R1. Furthermore we validated differential expression of IL1R2 and Livin/BIRC7 by RT-PCR and immunohistochemistry. Implementation of the gene expression data in the apoptosis pathway map suggested two higher level defects of the pathway at the level of cell death receptors and within the intrinsic signaling cascade consistent with references on apoptosis in PDAC. Protein interaction prediction further showed possible new interactions between the single pathway members, which demonstrate the complexity of the apoptosis pathway.Conclusions/SignificanceOur data shows that by computational evaluation of public accessible data an acceptable virtual image of the apoptosis pathway might be given. By this approach we could identify two higher level defects of the apoptosis pathway in PDAC. We could further for the first time identify IL1R2 as possible candidate gene in PDAC.

Long noncoding intronic RNAs are differentially expressed in primary and metastatic pancreatic cancer

“…IPA analysis also highlighted the prevalence of genes related to cell death within the metastasis-signature. It comprised 42 protein-coding mRNAs related to apoptosis (19 down-regulated and 23 up-regulated), in line with the notion that perturbation of the normal programmed cell death is involved in the metastatic phenotype in pancreatic cancer [6,55]. Interestingly, we found 6 intronic lncRNAs mapped to locus of apoptosis-related genes among those present in the metastasis signature ( ATF2 , TGFβR2 , MAP2K5 , MAP3K1 , DAPK1 and PTEN ).…”

Identifying Driver Genes of Breast Cancer by Integrated Analysis of Methylation and Expression Data in Paired Disease-Normal Samples of Patients

“…Secondly, in addition to the known cancer genes collected in the F-census database, some driver genes have been suggested to be cancer genes in previous studies. For instance, IL1R2 has been identified as a driver gene with promoter hypomethylation, in accordance with a previous report that this gene is a possible cancer gene [12].…”

Five Primary Human Pancreatic Adenocarcinoma Cell Lines Established by the Outgrowth Method

“…Dysregulation of genes associated with the intrinsic apoptotic pathway seem to play an important role in mediating this resistance to apoptosis [24,25]. We, therefore, evaluated the expression of several important anti-apoptotic genes of the intrinsic apoptosis pathway in our PaCaDD cell lines and in the established cell lines as controls.…”