scholarly journals Desmogleins as prognostic biomarkers in resected pancreatic ductal adenocarcinoma

2015 ◽  
Vol 113 (10) ◽  
pp. 1460-1466 ◽  
Author(s):  
Steffen Ormanns ◽  
Annelore Altendorf-Hofmann ◽  
Rene Jackstadt ◽  
David Horst ◽  
Gerald Assmann ◽  
...  
2017 ◽  
Vol 5 (1) ◽  
Author(s):  
Dan Calatayud ◽  
Christian Dehlendorff ◽  
Mogens K. Boisen ◽  
Jane Preuss Hasselby ◽  
Nicolai Aagaard Schultz ◽  
...  

2015 ◽  
Vol 10 (1) ◽  
Author(s):  
Petra Vychytilova-Faltejskova ◽  
Igor Kiss ◽  
Sona Klusova ◽  
Jan Hlavsa ◽  
Vladimir Prochazka ◽  
...  

HPB ◽  
2016 ◽  
Vol 18 (8) ◽  
pp. 652-663 ◽  
Author(s):  
Wilson Petrushnko ◽  
Justin S. Gundara ◽  
Philip R. De Reuver ◽  
Greg O'Grady ◽  
Jaswinder S. Samra ◽  
...  

2018 ◽  
Vol 9 (21) ◽  
pp. 3991-3999 ◽  
Author(s):  
Qiang Su ◽  
Emily C Zhu ◽  
Yao-long Qu ◽  
Di-ya Wang ◽  
Wei-wei Qu ◽  
...  

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e10141
Author(s):  
Sevcan Atay

A comprehensive meta-analysis of publicly available gene expression microarray data obtained from human-derived pancreatic ductal adenocarcinoma (PDAC) tissues and their histologically matched adjacent tissue samples was performed to provide diagnostic and prognostic biomarkers, and molecular targets for PDAC. An integrative meta-analysis of four submissions (GSE62452, GSE15471, GSE62165, and GSE56560) containing 105 eligible tumor-adjacent tissue pairs revealed 344 differentially over-expressed and 168 repressed genes in PDAC compared to the adjacent-to-tumor samples. The validation analysis using TCGA combined GTEx data confirmed 98.24% of the identified up-regulated and 73.88% of the down-regulated protein-coding genes in PDAC. Pathway enrichment analysis showed that “ECM-receptor interaction”, “PI3K-Akt signaling pathway”, and “focal adhesion” are the most enriched KEGG pathways in PDAC. Protein-protein interaction analysis identified FN1, TIMP1, and MSLN as the most highly ranked hub genes among the DEGs. Transcription factor enrichment analysis revealed that TCF7, CTNNB1, SMAD3, and JUN are significantly activated in PDAC, while SMAD7 is inhibited. The prognostic significance of the identified and validated differentially expressed genes in PDAC was evaluated via survival analysis of TCGA Pan-Cancer pancreatic ductal adenocarcinoma data. The identified candidate prognostic biomarkers were then validated in four external validation datasets (GSE21501, GSE50827, GSE57495, and GSE71729) to further improve reliability. A total of 28 up-regulated genes were found to be significantly correlated with worse overall survival in patients with PDAC. Twenty-one of the identified prognostic genes (ITGB6, LAMC2, KRT7, SERPINB5, IGF2BP3, IL1RN, MPZL2, SFTA2, MET, LAMA3, ARNTL2, SLC2A1, LAMB3, COL17A1, EPSTI1, IL1RAP, AK4, ANXA2, S100A16, KRT19, and GPRC5A) were also found to be significantly correlated with the pathological stages of the disease. The results of this study provided promising prognostic biomarkers that have the potential to differentiate PDAC from both healthy and adjacent-to-tumor pancreatic tissues. Several novel dysregulated genes merit further study as potentially promising candidates for the development of more effective treatment strategies for PDAC.


PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e10419
Author(s):  
Jingyi Ding ◽  
Yanxi Liu ◽  
Yu Lai

Background Pancreatic ductal adenocarcinoma (PDAC) is a fatal malignant neoplasm. It is necessary to improve the understanding of the underlying molecular mechanisms and identify the key genes and signaling pathways involved in PDAC. Methods The microarray datasets GSE28735, GSE62165, and GSE91035 were downloaded from the Gene Expression Omnibus. Differentially expressed genes (DEGs) were identified by integrated bioinformatics analysis, including protein–protein interaction (PPI) network, Gene Ontology (GO) enrichment, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. The PPI network was established using the Search Tool for the Retrieval of Interacting Genes (STRING) and Cytoscape software. GO functional annotation and KEGG pathway analyses were performed using the Database for Annotation, Visualization, and Integrated Discovery. Hub genes were validated via the Gene Expression Profiling Interactive Analysis tool (GEPIA) and the Human Protein Atlas (HPA) website. Results A total of 263 DEGs (167 upregulated and 96 downregulated) were common to the three datasets. We used STRING and Cytoscape software to establish the PPI network and then identified key modules. From the PPI network, 225 nodes and 803 edges were selected. The most significant module, which comprised 11 DEGs, was identified using the Molecular Complex Detection plugin. The top 20 hub genes, which were filtered by the CytoHubba plugin, comprised FN1, COL1A1, COL3A1, BGN, POSTN, FBN1, COL5A2, COL12A1, THBS2, COL6A3, VCAN, CDH11, MMP14, LTBP1, IGFBP5, ALB, CXCL12, FAP, MATN3, and COL8A1. These genes were validated using The Cancer Genome Atlas (TCGA) and Genotype–Tissue Expression (GTEx) databases, and the encoded proteins were subsequently validated using the HPA website. The GO analysis results showed that the most significantly enriched biological process, cellular component, and molecular function terms among the 20 hub genes were cell adhesion, proteinaceous extracellular matrix, and calcium ion binding, respectively. The KEGG pathway analysis showed that the 20 hub genes were mainly enriched in ECM–receptor interaction, focal adhesion, PI3K-Akt signaling pathway, and protein digestion and absorption. These findings indicated that FBN1 and COL8A1 appear to be involved in the progression of PDAC. Moreover, patient survival analysis performed via the GEPIA using TCGA and GTEx databases demonstrated that the expression levels of COL12A1 and MMP14 were correlated with a poor prognosis in PDAC patients (p < 0.05). Conclusions The results demonstrated that upregulation of MMP14 and COL12A1 is associated with poor overall survival, and these might be a combination of prognostic biomarkers in PDAC.


2015 ◽  
Vol 10 ◽  
pp. BMI.S27679 ◽  
Author(s):  
Bárbara Alemar ◽  
Cleandra Gregório ◽  
Patricia Ashton-Prolla

Pancreatic ductal adenocarcinoma (PDAC), a rare but lethal tumor, is difficult to diagnose without performing an invasive procedure. miRNAs are known to be deregulated in PDAC patients, and recent studies have shown that they can be used as diagnostic and prognostic of the disease. The detection of miRNAs in samples acquired through minimally or noninvasive procedures, such as serum, plasma, and saliva, can have a positive impact on the clinical management of these patients. This article is a comprehensive review of the major studies that have evaluated the expression of miRNAs as biomarkers in pancreatic cancer and its premalignant lesions.


Sign in / Sign up

Export Citation Format

Share Document