scholarly journals Meta-analysis of 1,200 transcriptomic profiles identifies a prognostic model for pancreatic ductal adenocarcinoma

2018 ◽  
Author(s):  
Vandana Sandhu ◽  
Knut Jorgen Labori ◽  
Ayelet Borgida ◽  
Ilinca Lungu ◽  
John Bartlett ◽  
...  
Keyword(s):  
Gene Expression ◽  
Pancreatic Cancer ◽  
Overall Survival ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Prognostic Model ◽  
Meta Analysis ◽  
Early Death ◽  
Receiver Operating Curve ◽  
Ductal Adenocarcinoma ◽  
Survival Predictor

ABSTRACTBackgroundWith a dismal 8% median 5-year overall survival (OS), pancreatic ductal adenocarcinoma (PDAC) is highly lethal. Only 10-20% of patients are eligible for surgery, and over 50% of these will die within a year of surgery. Identify molecular predictors of early death would enable the selection of PDAC patients at high risk.MethodsWe developed the Pancreatic Cancer Overall Survival Predictor (PCOSP), a prognostic model built from a unique set of 89 PDAC tumors where gene expression was profiled using both microarray and sequencing platforms. We used a meta-analysis framework based on the binary gene pair method to create gene expression barcodes robust to biases arising from heterogeneous profiling platforms and batch effects. Leveraging the largest compendium of PDAC transcriptomic datasets to date, we show that PCOSP is a robust single-sample predictor of early death (≤1 yr) after surgery in a subset of 823 samples with available transcriptomics and survival data.ResultsThe PCOSP model was strongly and significantly prognostic with a meta-estimate of the area under the receiver operating curve (AUROC) of 0.70 (P=1.9e-18) and hazard ratio (HR) of 1.95(1.6-2.3) (P=2.6e-16) for binary and survival predictions, respectively. The prognostic value of PCOSP was independent of clinicopathological parameters and molecular subtypes. Over-representation analysis of the PCOSP 2619 gene-pairs (1070 unique genes) unveiled pathways associated with Hedgehog signalling, epithelial mesenchymal transition (EMT) and extracellular matrix (ECM) signalling.ConclusionPCOSP could improve treatment decision by identifying patients who will not benefit from standard surgery/chemotherapy and may benefit from alternate approaches.AbbreviationsAUROCArea under the receiver operating curveGOGene annotationOSOverall survivalPCOSPPancreatic cancer overall survival predictorPDACPancreatic ductal adenocarcinomaTSPTop scoring pairs.

scholarly journals Meta-Analysis of 1,200 Transcriptomic Profiles Identifies a Prognostic Model for Pancreatic Ductal Adenocarcinoma

2019 ◽  
pp. 1-16 ◽  
Author(s):  
Vandana Sandhu ◽  
Knut Jorgen Labori ◽  
Ayelet Borgida ◽  
Ilinca Lungu ◽  
John Bartlett ◽  
...  
Keyword(s):  
Gene Expression ◽  
Overall Survival ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Survival Data ◽  
Prognostic Model ◽  
Meta Analysis ◽  
Early Death ◽  
Receiver Operating Curve ◽  
Ductal Adenocarcinoma ◽  
Mesenchymal Transition

PURPOSE With a dismal 8% median 5-year overall survival, pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy. Only 10% to 20% of patients are eligible for surgery, and more than 50% of these patients will die within 1 year of surgery. Building a molecular predictor of early death would enable the selection of patients with PDAC who are at high risk. MATERIALS AND METHODS We developed the Pancreatic Cancer Overall Survival Predictor (PCOSP), a prognostic model built from a unique set of 89 PDAC tumors in which gene expression was profiled using both microarray and sequencing platforms. We used a meta-analysis framework that was based on the binary gene pair method to create gene expression barcodes that were robust to biases arising from heterogeneous profiling platforms and batch effects. Leveraging the largest compendium of PDAC transcriptomic data sets to date, we show that PCOSP is a robust single-sample predictor of early death—1 year or less—after surgery in a subset of 823 samples with available transcriptomics and survival data. RESULTS The PCOSP model was strongly and significantly prognostic, with a meta-estimate of the area under the receiver operating curve of 0.70 ( P = 2.6E−22) and d-index (robust hazard ratio) of 1.9 (range, 1.6 to 2.3; ( = 1.4E−04) for binary and survival predictions, respectively. The prognostic value of PCOSP was independent of clinicopathologic parameters and molecular subtypes. Over-representation analysis of the PCOSP 2,619 gene pairs—1,070 unique genes—unveiled pathways associated with Hedgehog signaling, epithelial–mesenchymal transition, and extracellular matrix signaling. CONCLUSION PCOSP could improve treatment decisions by identifying patients who will not benefit from standard surgery/chemotherapy but who may benefit from a more aggressive treatment approach or enrollment in a clinical trial.

scholarly journals An Integrated Meta-Analysis of Secretome and Proteome Identify Potential Biomarkers of Pancreatic Ductal Adenocarcinoma

Cancers ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 716
Author(s):  
Grasieli de Oliveira ◽  
Paula Paccielli Freire ◽  
Sarah Santiloni Cury ◽  
Diogo de Moraes ◽  
Jakeline Santos Oliveira ◽  
...  
Keyword(s):  
Gene Expression ◽  
Pancreatic Cancer ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Prognostic Value ◽  
Meta Analysis ◽  
The Cancer Genome Atlas ◽  
Secreted Proteins ◽  
Ductal Adenocarcinoma ◽  
Public Data ◽  
Potential Biomarkers

Pancreatic ductal adenocarcinoma (PDAC) is extremely aggressive, has an unfavorable prognosis, and there are no biomarkers for early detection of the disease or identification of individuals at high risk for morbidity or mortality. The cellular and molecular complexity of PDAC leads to inconsistences in clinical validations of many proteins that have been evaluated as prognostic biomarkers of the disease. The tumor secretome, a potential source of biomarkers in PDAC, plays a crucial role in cell proliferation and metastasis, as well as in resistance to treatments, which together contribute to a worse clinical outcome. The massive amount of proteomic data from pancreatic cancer that has been generated from previous studies can be integrated and explored to uncover secreted proteins relevant to the diagnosis and prognosis of the disease. The present study aimed to perform an integrated meta-analysis of PDAC proteome and secretome public data to identify potential biomarkers of the disease. Our meta-analysis combined mass spectrometry data obtained from two systematic reviews of the pancreatic cancer literature, which independently selected 20 studies of the secretome and 35 of the proteome. Next, we predicted the secreted proteins using seven in silico tools or databases, which identified 39 secreted proteins shared between the secretome and proteome data. Notably, the expression of 31 genes of these secretome-related proteins was upregulated in PDAC samples from The Cancer Genome Atlas (TCGA) when compared to control samples from TCGA and The Genotype-Tissue Expression (GTEx). The prognostic value of these 39 secreted proteins in predicting survival outcome was confirmed using gene expression data from four PDAC datasets (validation set). The gene expression of these secreted proteins was able to distinguish high- and low-survival patients in nine additional tumor types from TCGA, demonstrating that deregulation of these secreted proteins may also contribute to the prognosis in multiple cancers types. Finally, we compared the prognostic value of the identified secreted proteins in PDAC biomarkers studies from the literature. This analysis revealed that our gene signature performed equally well or better than the signatures from these previous studies. In conclusion, our integrated meta-analysis of PDAC proteome and secretome identified 39 secreted proteins as potential biomarkers, and the tumor gene expression profile of these proteins in patients with PDAC is associated with worse overall survival.

Precursors of pancreatic cancer in background of chronic opisthorchiasis

2021 ◽  
Vol 22 (1) ◽  
pp. 118-121
Author(s):  
V. U. Rayn ◽  
◽  
M. A. Persidskiy ◽  
E. V. Malakhova ◽  
I. V. Anuchina ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Overall Survival ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Disease Free Survival ◽  
Morphological Data ◽  
Small Samples ◽  
Ductal Adenocarcinoma ◽  
Preneoplastic Lesions ◽  
Opisthorchis Felineus ◽  
Disease Free

Aim. To establish the association between pancreatic cancer precursor lesions and chronic opisthorchiasis. Materials and methods. A single center case-control study was conducted at a low-volume pancreatic surgery center in Khanty-Mansiysk. We retrospectively collected morphological data from 47 pancreatoduodenectomies performed for pancreatic ductal adenocarcinoma. The study group included 23 cases of pancreatic ductal adenocarcinoma with concomitant chronic Opisthorchis felineus invasion which were compared to 24 controls consisting of “pure” cancer. Qualitative analysis was performed using χ2 Pearson criterion. Exact Fisher test was used for small samples. Time to progression and overall survival rates were calculated using Kaplan-Meier survival analysis. Data were collected and analyzed in Statistica 7.0. Results. PanINs were seen in 41,7% pancreata resected for ductal adenocarcinoma of the head and in 95,7% cases of pancreatic cancer in background of chronic opisthorchiasis (р = 0,000; 95% CI 3,5-268). PanIN high grade were observed only in opisthorchiasis group. In mixed pathology invasive cancer component tended to be more dedifferentiated and advanced when compared to pure cancer group (p = 0,029). Median disease free survival was 9 mo. in both groups and overall survival was 13 mo. in non-opisthorchiasis group and 15,3 mo. in opisthorchiasis group (р = 0,437). Conclusion. Chronic opisthorchiasis is associated with pancreatic intraepithelial neoplasia. Pancreatic ductal adenocarcinoma in background of opisthorchiasis with preneoplastic lesions tend to be more advanced in stage and poorly differentiated. Disease free and overall survival have no statistically significant differences in patients with and without Opisthorchis felineus invasion.

The Role of Nanoliposomal Irinotecan Plus Fluorouracil and Folinic Acid as Second-Line Treatment Option in Patients With Metastatic Pancreatic Ductal Adenocarcinoma

2021 ◽  
Author(s):  
Se Jun Park ◽  
Hyunho Kim ◽  
Kabsoo Shin ◽  
Tae Ho Hong ◽  
Ja Hee Suh ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Overall Survival ◽  
Adverse Events ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Real World ◽  
Median Overall Survival ◽  
Ductal Adenocarcinoma ◽  
Nanoliposomal Irinotecan ◽  
Previously Treated ◽  
Grade 3

Abstract BackgroundAccording to the NAPOLI-1 trial, nanoliposomal irinotecan (nal-IRI) plus 5-fluorouracil/leucovorin (5-FU/LV) showed improved overall survival compared to fluorouracil alone for patients with metastatic pancreatic cancer who previously treated gemcitabine-based therapy. In that trial, Asian patients had frequent dose modification due to hematological toxicity. There has been limited information on the clinical benefit and toxicity of this regimen in a real-world setting. Herein, we assessed real-world experience of nal-IRI plus 5-FU/LV in patients with advanced pancreatic cancer after gemcitabine failure.MethodsWe conducted a single institution retrospective analysis of response, survival and safety in patients who had been treated with nal-IRI with 5-FU/LV. Patients with metastatic pancreatic ductal adenocarcinoma previously treated with gemcitabine-based therapy received nal-IRI (80mg/m2) with 5-FU/LV every 2 weeks. ResultsFifty-one patients received nal-IRI plus 5-FU/LV between January 2015 and December 2020. The median age was 67 years, and males were 58.8%. A total of 40 (78.4%) and 11 (21.6%) patients had received one and two lines of prior chemotherapy before enrollment, respectively. Median progression-free survival was 2.8 months (95% confidence interval [CI] 1.8-3.7) and median overall survival was 7.0 months (95% CI 6.0-7.9). Chemotherapy doses were reduced or delayed in 33 (64.7%) patients during the first 6 weeks and median relative dose intensity was 0.87. Thirty-six (70.6%) patients experienced any grade 3 or 4 adverse events. Most common grade 3 or 4 adverse event was neutropenia (58.8%) and most non-hematologic adverse events were under grade 2. Since the start of first-line chemotherapy, median overall survival was 16.3 months (95% CI 14.1-18.4).ConclusionsNal-IRI plus 5-FU/LV seems to be effective, with manageable toxicities, after gemcitabine-based treatment in patients with metastatic pancreatic ductal adenocarcinoma. Trial registration Retrospectively registered

Clinical Characteristics and Overall Survival in Patients with Anaplastic Pancreatic Cancer

2014 ◽  
Vol 80 (2) ◽  
pp. 117-123 ◽  
Author(s):  
Clancy J. Clark ◽  
Janani S. Arun ◽  
Rondell P. Graham ◽  
Lizhi Zhang ◽  
Michael Farnell ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Overall Survival ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Tumor Stage ◽  
Ductal Adenocarcinoma ◽  
Rank Test ◽  
Poor Overall Survival ◽  
Perioperative Morbidity ◽  
Log Rank Test ◽  
Kaplan Meier

Anaplastic pancreatic cancer (APC) is a rare undifferentiated variant of pancreatic ductal adenocarcinoma with poor overall survival (OS). The aim of this study was to evaluate the clinical outcomes of APC compared with differentiated pancreatic ductal adenocarcinoma. We conducted a retrospective review of all patients treated at the Mayo Clinic with pathologically confirmed APC from 1987 to 2011. After matching with control subjects with pancreatic ductal adenocarcinoma, OS was evaluated using Kaplan-Meier estimates and log-rank test. Sixteen patients were identified with APC (56.3% male, median age 57 years). Ten patients underwent exploration of whom eight underwent pancreatectomy. Perioperative morbidity was 60 per cent with no mortality. The median OS was 12.8 months. However, patients with APC who underwent resection had longer OS compared with those who were not resected, 34.1 versus 3.3 months ( P = 0.001). After matching age, sex, tumor stage, and year of operation, the median OS was similar between patients with APC and those with ductal adenocarcinoma treated with pancreatic resection, 44.1 versus 39.9 months, ( P = 0.763). Overall survival for APC is poor; however, when resected, survival is similar to differentiated pancreatic ductal adenocarcinoma.

scholarly journals PDAC-ANN: an artificial neural network to predict Pancreatic Ductal Adenocarcinoma based on gene expression

2019 ◽  
Author(s):  
Palloma Porto Almeida ◽  
Cristina Padre Cardoso ◽  
Leandro Martins de Freitas
Keyword(s):  
Neural Network ◽  
Gene Expression ◽  
Artificial Neural Network ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Drug Targets ◽  
Meta Analysis ◽  
Human Protein ◽  
Ductal Adenocarcinoma ◽  
Human Protein Atlas ◽  
Artificial Neural

AbstractBackgroundAlthough the pancreatic ductal adenocarcinoma (PDAC) presents high mortality and metastatic potential, there is a lack of effective therapies and a low survival rate for this disease. This PDAC scenario urges new strategies for diagnosis, drug targets, and treatment.MethodsWe performed a gene expression microarray meta-analysis of the tumor against healthy tissues in order to identify differentially expressed genes shared among all datasets, named core-genes (CG). We confirmed the pancreatic expressed proteins of the CG through The Human Protein Atlas. The five most expressed proteins in the tumor group were selected to train an artificial neural network to classify samples.ResultsThis microarray included 110 tumor and 77 healthy samples. We identified a CG composed of 60 genes, 58 upregulated and two downregulated. The upregulated CG included proteins and extracellular matrix receptors linked to actin cytoskeleton reorganization. With the Human Protein Atlas, we verified that thirteen genes of the CG are translated, with high or medium expression in most of the pancreatic tumor samples. To train our artificial neural network, we used the five most expressed genes (KRT19, LAMC2, MELK, MET, TOP2A). The artificial neural network model (PDAC-ANN) classified the train samples with sensitivity of 0.95, specificity of 0.9, and f1-score of 0.93. The PDAC-ANN could classify the test samples with a sensitivity of 0.97, specificity of 0.88, and f1-score 0.94.ConclusionThe gene expression meta-analysis and confirmation of the protein expression allow us to select five genes highly expressed PDAC samples. We could build a python script to classify the samples based on mRNA expression. This software can be useful in the PDAC diagnosis.

scholarly journals Identify key genes and pathways in pancreatic ductal adenocarcinoma via bioinformatics analysis

2020 ◽  
Author(s):  
Huatian Luo ◽  
Da-qiu Chen ◽  
Jing-jing Pan ◽  
Zhang-wei Wu ◽  
Can Yang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Pancreatic Cancer ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Bioinformatics Analysis ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Gene Expression Omnibus ◽  
Ductal Adenocarcinoma ◽  
Hub Genes ◽  
Expression Levels

Abstract Background: Pancreatic cancer has many pathologic types, among which pancreatic ductal adenocarcinoma (PDAC) is the most common one. Bioinformatics has become a very common tool for the selection of potentially pathogenic genes. Methods: Three data sets containing the gene expression profiles of PDAC were downloaded from the gene expression omnibus (GEO) database. The limma package of R language was utilized to explore the differentially expressed genes (DEGs). To analyze functions and signaling pathways, the Database Visualization and Integrated Discovery (DAVID) was used. To visualize the protein-protein interaction (PPI) of the DEGs ,Cytoscape was performed under the utilization of Search Tool for the Retrieval of Interacting Genes (STRING). With the usage of the plug-in cytoHubba in cytoscape software, the hub genes were found out. To verify the expression levels of hub genes, Gene Expression Profiling Interactive Analysis (GEPIA) was performed. Last but not least, UALCAN analysis online tool was implemented to analyze the overall survival. Results: The 376 DEGs were highly enriched in biological processes including signal transduction, apoptotic process and several pathways, mainly associated with Protein digestion and absorption and Pancreatic secretion pathway. The expression levels of nucleolar and spindle associated protein 1 (NUSAP1) and SHC binding and spindle associated 1 (SHCBP1) were discovered highly expressed in pancreatic ductal adenocarcinoma tissues. NUSAP1 and SHCBP1 had a high correlation with prognosis. Conclusions: The findings of this bioinformatics analysis indicate that NUSAP1 and SHCBP1 may be key factors in the prognosis and treatment of pancreatic cancer.

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