scholarly journals Protein Profiling of Microdissected Pancreas Carcinoma and Identification of HSP27 as a Potential Serum Marker

2007 ◽  
Vol 53 (4) ◽  
pp. 629-635 ◽  
Author(s):  
Christian Melle ◽  
Günther Ernst ◽  
Niko Escher ◽  
Daniel Hartmann ◽  
Bettina Schimmel ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Serum Marker ◽  
Pancreatic Tissue ◽  
Protein Profiling ◽  
Serum Samples ◽  
Pancreas Carcinoma ◽  
Tissue Samples ◽  
Potential Marker ◽  
Preoperative Serum ◽  
Surface Enhanced

Abstract Background: Patients with pancreatic adenocarcinomas have a poor prognosis because of late clinical manifestation and the tumor’s aggressive nature. We used proteomic techniques to search for markers of pancreatic carcinoma. Methods: We performed protein profiling of microdissected cryostat sections of 9 pancreatic adenocarcinomas and 10 healthy pancreatic tissue samples using ProteinChip technology (surface-enhanced laser desorption/ionization). We identified proteins by use of 2-dimensional gel electrophoresis, peptide fingerprint mapping, and immunodepletion and used immunohistochemistry for in situ localization of the proteins found. We used ELISA to quantify these proteins in preoperative serum samples from 35 patients with pancreatic cancer and 37 healthy individuals. Results: From among the differentially expressed signals that were detected by ProteinChip technology, we identified 2 proteins, DJ-1 and heat shock protein 27 (HSP27). We then detected HSP27 in sera of patients by use of ELISA, indicating a sensitivity of 100% and a specificity of 84% for the recognition of pancreatic cancer. Conclusions: The detection of DJ-1 and HSP27 in pure defined tissue and the retrieval of HSP27 in serum by antibody-based methods identifies a potential marker for pancreatic cancer.

scholarly journals NMR-based metabolic profiling of urine, serum, fecal, and pancreatic tissue samples from the Ptf1a-Cre; LSL-KrasG12D transgenic mouse model of pancreatic cancer

PLoS ONE ◽  
2018 ◽  
Vol 13 (7) ◽  
pp. e0200658 ◽  
Author(s):  
Michelle J. Schmahl ◽  
Daniel P. Regan ◽  
Adam C. Rivers ◽  
William C. Joesten ◽  
Michael A. Kennedy
Keyword(s):  
Pancreatic Cancer ◽  
Mouse Model ◽  
Transgenic Mouse ◽  
Metabolic Profiling ◽  
Transgenic Mouse Model ◽  
Pancreatic Tissue ◽  
Tissue Samples ◽  
Urine Serum

CRM1 expression in pancreatic carcinoma.

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. e15115-e15115 ◽  
Author(s):  
Amit Mahipal ◽  
Domenico Coppola ◽  
Shilpa Gupta ◽  
Barbara Centeno ◽  
Mokenge Peter Malafa
Keyword(s):  
Pancreatic Cancer ◽  
Pancreatic Carcinoma ◽  
Anticancer Agents ◽  
Normal Tissue ◽  
Tissue Sample ◽  
Pancreatic Tissue ◽  
Ductal Adenocarcinoma ◽  
Cancer Tissue ◽  
Tissue Samples ◽  
Paired Samples

e15115 Background: Increased expression of chromosomal region maintenance (CRM1) protein, also known as exportin 1, has been described in several human cancers. It is an important regulator of subcellular localization of tumor suppressor proteins and growth regulatory proteins. Direct inhibition of CRM1 blocks cell proliferation and induces apoptosis leading to the current evaluation of CRM1 inhibitors as anticancer agents in early phase clinical trials. There is a paucity of data regarding the prevalence of CRM1 expression in pancreatic cancer. Methods: We analyzed the expression of CRM1 by immunohistochemistry (IHC) in pancreatic tissue microarray (TMA) samples (malignant and non-malignant) obtained from patients who underwent potentially curative resection for pancreatic ductal adenocarcinoma. CRM1 antibody (Santa Cruz Biotechnology) was used for immunostaining the formalin fixed paraffin embedded core sections in the TMA samples. The intensity of staining and percentage of cells stained were graded on a scale of 0 to 3, with 3 being highest. The final IHC score was obtained using the product of immunostain intensity and percentage of cells stained (Range: 0-9). Low and high CRM1 expression was considered if the IHC score was 0 to 4 and 6 to 9 respectively. Results: Seventy nonmalignant and 91 pancreatic carcinoma samples were evaluated in this study. The median IHC score was 6 (range: 0-9) and 3 (range: 1-9) in malignant and nonmalignant pancreatic tissue samples respectively (P<0.0001). High CRM1 expression was found in 11% (8/70) of normal tissue samples and 69% (63/91) of tumor samples (P<0.0001). There were 48 paired samples of pancreatic cancer tissue and normal tissue obtained from same patient. Among these patients, 33 (69%) patients had higher CRM1 expression, 7 (15%) patients had similar expression and 8 (17%) patients had lower expression in malignant tissue sample as compared to their adjacent normal tissues. Conclusions: Higher CRM1 expression occurs frequently in pancreatic cancer as compared to nonmalignant pancreatic tissue, reinforcing its putative tumor oncogenic activity, and raising the value of targeting it for pancreatic cancer therapy.

scholarly journals Characterising cis-regulatory variation in the transcriptome of histologically normal and tumour-derived pancreatic tissues

Gut ◽  
2017 ◽  
Vol 67 (3) ◽  
pp. 521-533 ◽  
Author(s):  
Mingfeng Zhang ◽  
Soren Lykke-Andersen ◽  
Bin Zhu ◽  
Wenming Xiao ◽  
Jason W Hoskins ◽  
...  
Keyword(s):  
Gene Expression ◽  
Pancreatic Cancer ◽  
Cancer Risk ◽  
Regulatory Element ◽  
Pancreatic Tissue ◽  
The Cancer Genome Atlas ◽  
Eqtl Analysis ◽  
Data Set ◽  
Tissue Samples ◽  
Pancreatic Cancer Risk

ObjectiveTo elucidate the genetic architecture of gene expression in pancreatic tissues.DesignWe performed expression quantitative trait locus (eQTL) analysis in histologically normal pancreatic tissue samples (n=95) using RNA sequencing and the corresponding 1000 genomes imputed germline genotypes. Data from pancreatic tumour-derived tissue samples (n=115) from The Cancer Genome Atlas were included for comparison.ResultsWe identified 38 615 cis-eQTLs (in 484 genes) in histologically normal tissues and 39 713 cis-eQTL (in 237 genes) in tumour-derived tissues (false discovery rate <0.1), with the strongest effects seen near transcriptional start sites. Approximately 23% and 42% of genes with significant cis-eQTLs appeared to be specific for tumour-derived and normal-derived tissues, respectively. Significant enrichment of cis-eQTL variants was noted in non-coding regulatory regions, in particular for pancreatic tissues (1.53-fold to 3.12-fold, p≤0.0001), indicating tissue-specific functional relevance. A common pancreatic cancer risk locus on 9q34.2 (rs687289) was associated with ABO expression in histologically normal (p=5.8×10−8) and tumour-derived (p=8.3×10−5) tissues. The high linkage disequilibrium between this variant and the O blood group generating deletion variant in ABO (exon 6) suggested that nonsense-mediated decay (NMD) of the ‘O’ mRNA might explain this finding. However, knockdown of crucial NMD regulators did not influence decay of the ABO ‘O’ mRNA, indicating that a gene regulatory element influenced by pancreatic cancer risk alleles may underlie the eQTL.ConclusionsWe have identified cis-eQTLs representing potential functional regulatory variants in the pancreas and generated a rich data set for further studies on gene expression and its regulation in pancreatic tissues.

scholarly journals Deep learning-based gene selection in comprehensive gene analysis in pancreatic cancer

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yasukuni Mori ◽  
Hajime Yokota ◽  
Isamu Hoshino ◽  
Yosuke Iwatate ◽  
Kohei Wakamatsu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Pancreatic Cancer ◽  
Deep Learning ◽  
Gene Selection ◽  
Pancreatic Tissue ◽  
Expression Data ◽  
Tissue Samples ◽  
Normal Pancreatic Tissue ◽  
Model Training ◽  
Selection Of

AbstractThe selection of genes that are important for obtaining gene expression data is challenging. Here, we developed a deep learning-based feature selection method suitable for gene selection. Our novel deep learning model includes an additional feature-selection layer. After model training, the units in this layer with high weights correspond to the genes that worked effectively in the processing of the networks. Cancer tissue samples and adjacent normal pancreatic tissue samples were collected from 13 patients with pancreatic ductal adenocarcinoma during surgery and subsequently frozen. After processing, gene expression data were extracted from the specimens using RNA sequencing. Task 1 for the model training was to discriminate between cancerous and normal pancreatic tissue in six patients. Task 2 was to discriminate between patients with pancreatic cancer (n = 13) who survived for more than one year after surgery. The most frequently selected genes were ACACB, ADAMTS6, NCAM1, and CADPS in Task 1, and CD1D, PLA2G16, DACH1, and SOWAHA in Task 2. According to The Cancer Genome Atlas dataset, these genes are all prognostic factors for pancreatic cancer. Thus, the feasibility of using our deep learning-based method for the selection of genes associated with pancreatic cancer development and prognosis was confirmed.

scholarly journals Quantitative Proteomics Analysis by Isobaric Tags for Relative and Absolute Quantitation Identified Lumican as a Potential Marker for Acute Aortic Dissection

2011 ◽  
Vol 2011 ◽  
pp. 1-10 ◽  
Author(s):  
Guorong Gu ◽  
Weizhong Cheng ◽  
Chenling Yao ◽  
Jun Yin ◽  
Chaoyang Tong ◽  
...  
Keyword(s):  
Aortic Dissection ◽  
Quantitative Proteomics ◽  
Acute Aortic Dissection ◽  
Serum Marker ◽  
Serum Biomarkers ◽  
Serum Samples ◽  
Absolute Quantitation ◽  
Itraq Analysis ◽  
Potential Marker ◽  
Isobaric Tags

Acute aortic dissection (AAD) is a serious vascular disease. Currently the diagnosis relies on clinical and radiological means whereas serum biomarkers are lacking. The purpose of this study was to identify potential serum biomarkers for AAD using isobaric tags for relative and absolute quantitation (iTRAQ) approach. A total of 120 serum samples were collected from three groups: AAD patients (n=60), patients with acute myocardial infarction (AMI,n=30), and healthy volunteers (n=30), whereas the first 10 samples from each group were used for iTRAQ analysis. Using iTRAQ approach, a total of 174 proteins were identified as significantly different between AAD patients and healthy subjects. Among them, forty-six proteins increased more than twofold, full-scale analysis using serum sample for the entire 120 subjects demonstrated that Lumican level was significantly increased relative to control and AMI samples. Further, Lumican level correlated with time from onset to admission in AAD but not AMI samples. Using iTRAQ approach, our study showed that Lumican may be a potential AAD-related serum marker that may assist the diagnosis of AAD.

scholarly journals Analysis of K-ras gene codon 12 mutation in pancreatic tissue of patients with pancreatic cancer

2009 ◽  
Vol 61 (4) ◽  
pp. 623-629 ◽  
Author(s):  
Aleksandra Nikolic ◽  
S. Knezevic ◽  
Mila Krsmanovic ◽  
M. Micev ◽  
M. Ristanovic ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
High Frequency ◽  
Fragment Length Polymorphism ◽  
Pancreatic Tissue ◽  
Ras Gene ◽  
Tissue Samples ◽  
Ras Mutation ◽  
Pcr Rflp ◽  
Polymerase Chain ◽  
The Given

The aim of this study was to analyze K-ras codon 12 mutation in the pancreatic tissue of Serbian patients with pancreatic cancer and assess whether the given mutation can be used as a molecular marker for this disease. The study was performed on pancreatic tissue samples obtained from 40 patients with clinical diagnosis of pancreatic cancer. The presence of K-ras codon 12 mutation was analyzed by the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method. Our study showed that K-ras mutation is present with a high frequency (66%) in the pancreatic tissue of patients with pancretic cancer.

scholarly journals CEACAM6’s Role as a Chemoresistance and Prognostic Biomarker for Pancreatic Cancer: A Comparison of CEACAM6’s Diagnostic and Prognostic Capabilities with Those of CA19-9 and CEA

Life ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 542
Author(s):  
Benediktas Kurlinkus ◽  
Marija Ger ◽  
Algirdas Kaupinis ◽  
Eugenijus Jasiunas ◽  
Mindaugas Valius ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Overall Survival ◽  
Blood Serum ◽  
Carcinoembryonic Antigen ◽  
Disease Free Survival ◽  
Pancreatic Tissue ◽  
Serum Concentrations ◽  
High Definition ◽  
Tissue Samples ◽  
Cancer Management

Survival rates from pancreatic cancer have remained stagnant for decades due to the heterogenic nature of the disease. This study aimed to find a new advanced biomarker and evaluate its clinical capabilities, thus enabling more individualised pancreatic cancer management. Between 2013 and 2020, 267 patients were included in the study. Surgically collected pancreatic tissue samples were analysed via high-definition mass spectrometry. Carcinoembryonic antigen-related cell adhesion molecule 6 (CEACAM6) was discovered as a possible promising pancreatic cancer biomarker. The predominance of CEACAM6 to pancreatic cancer was validated using antibodies in tissue samples. CEACAM6, carbohydrate antigen 19-9 (CA19-9), and carcinoembryonic antigen (CEA) blood serum concentrations were evaluated for clinical evaluation and comparison. Kaplan–Meier survival analyses were used to evaluate disease-free survival (DFS) and overall survival (OS). Poorer overall survival was significantly dependent on increased CEACAM6 blood serum concentrations (17.0 vs. 12.6 months, p = 0.017) in pancreatic cancer patients after radical treatment and adjuvant chemotherapy. Increased CEA and CA19-9 concentrations showed no significant dependencies with survival. Thus, CEACAM6 is a promising new biomarker with significant prognostic value and prediction of chemoresistance properties, enabling the improvement of individualised approaches to patients with pancreatic cancer.

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