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 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 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 Prognostic Role of High-Grade Tumor Budding in Pancreatic Ductal Adenocarcinoma: A Systematic Review and Meta-Analysis with a Focus on Epithelial to Mesenchymal Transition

Cancers ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 113 ◽  
Author(s):  
Rita Lawlor ◽  
Nicola Veronese ◽  
Alessia Nottegar ◽  
Giuseppe Malleo ◽  
Lee Smith ◽  
...  
Keyword(s):  
Systematic Review ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Epithelial To Mesenchymal Transition ◽  
Meta Analysis ◽  
Tumor Budding ◽  
Ductal Adenocarcinoma ◽  
High Grade ◽  
Prognostic Role ◽  
Mesenchymal Transition

This study aims at clarifying the prognostic role of high-grade tumor budding (TB) in pancreatic ductal adenocarcinoma (PDAC) with the first systematic review and meta-analysis on this topic. Furthermore, we analyzed with a systematic review the relationship between TB and a recently suggested TB-associated mechanism: the epithelial to mesenchymal transition (EMT). Analyzing a total of 613 patients, 251 of them (40.9%) with high grade-TB, we found an increased risk of all-cause mortality (RR, 1.46; 95% CI, 1.13–1.88, p = 0.004; HR, 2.65; 95% CI, 1.79–3.91; p < 0.0001) and of recurrence (RR, 1.61; 95% CI, 1.05–2.47, p = 0.03) for PDAC patients with high-grade TB. Moreover, we found that EMT is a central process in determining the presence of TB in PDAC. Thanks to this meta-analysis, we demonstrate the potential clinical significance of high-grade TB for prognostic stratification of PDAC. TB also shows a clear association with the process of EMT. Based on the results of the present study, TB should be conveyed in pathology reports and taken into account by future oncologic staging systems.

MET overexpression as a hallmark of the epithelial-mesenchymal transition (EMT) phenotype in colorectal cancer.

2013 ◽  
Vol 31 (4_suppl) ◽  
pp. 334-334 ◽  
Author(s):  
Kanwal Pratap Singh Raghav ◽  
Wenting Wang ◽  
Michael J. Overman ◽  
Scott Kopetz
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Overall Survival ◽  
Protein Expression ◽  
Survival Data ◽  
Fold Increase ◽  
Clinicopathological Characteristics ◽  
Fisher Exact Test ◽  
Mesenchymal Transition ◽  
Emt Markers

334 Background: Dysregulation of the proto-oncogene MET (mesenchymal-epithelial transition factor gene) has been implicated in tumorigenesis and correlates with worse survival and chemo/radio-resistance in colorectal cancer (CRC). EMT has been identified as a dominant molecular characteristic of a subset of CRC tumors and represents a key feature in the developing colorectal taxonomy. The purpose of this study was to compare protein expression of MET with protein/gene expression of EMT markers and other clinicopathological characteristics, and to evaluate its impact on overall survival (OS). Methods: We performed an exploratory analysis of 590 CRC samples using data from The Cancer Genome Atlas. Fisher-exact test and Pearson’s method was used to determine the relationship between MET protein expression, clinicopathological characteristics and EMT marker protein expression by reverse-phase protein array (RPPA) and EMT-associated gene expression by RNA-sequencing. Regression tree method was applied to find the best cutoff point for MET using patients with available survival data. Overall survival (OS) was estimated non-parametrically using Kaplan-Meier curve and log-rank test was used to evaluate hazard ratio. Results: MET expression by RPPA did not correlate with traditional clinicopathologic characteristics. MET was overexpressed in 17% of CRC tumors and was significantly associated with OS (HR 2.92; 95% CI: 1.45 - 5.92). Correlation analysis of MET levels with gene expression of EMT markers AXL, CDH1, FGFR1, SNAIL, TWIST1/2, VIM, SLUG, ZEB1/2, FN1 demonstrated that the highest quartile of MET protein expression was associated with a 1.5 fold increase in ZEB1 (p = 0.002), a 1.4 fold increase in AXL (p = 0.005) and ZEB2 (p = 0.008), and a 1.3 fold increase in VIM (p = 0.02). MET expression also correlated strongly with protein expressions of SNAIL (transcription factor for EMT) (r = 0.96) and ERCC1 (r = 0.83) (a marker for oxaliplatin chemo-resistance). Conclusions: Increased MET protein expression is seen in 17% of CRC tumors and strongly correlates with a molecular EMT phenotype and poor survival in patients with CRC. MET protein expression may be a surrogate biomarker for this unique subset of CRC.

scholarly journals Systemic neoadjuvant chemotherapy in modern pancreatic cancer treatment: a systematic review and meta-analysis

2019 ◽  
Vol 101 (7) ◽  
pp. 453-462 ◽  
Author(s):  
K Rangarajan ◽  
PH Pucher ◽  
T Armstrong ◽  
A Bateman ◽  
ZZR Hamady
Keyword(s):  
Overall Survival ◽  
Neoadjuvant Chemotherapy ◽  
Adjuvant Therapy ◽  
Confidence Interval ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Neoadjuvant Therapy ◽  
Meta Analysis ◽  
Ductal Adenocarcinoma ◽  
Current Evidence ◽  
Surgery First

Background Pancreatic ductal adenocarcinoma remains a disease with a poor prognosis despite advances in surgery and systemic therapies. Neoadjuvant therapy strategies are a promising alternative to adjuvant chemotherapy. However, their role remains controversial. This meta-analysis aims to clarify the benefits of neoadjuvant therapy in resectable pancreatic ductal adenocarcinoma. Methods Eligible studies were identified from MEDLINE, Embase, Web of Science and the Cochrane Library. Studies comparing neoadjuvant therapy with a surgery first approach (with or without adjuvant therapy) in resectable pancreatic ductal adenocarcinoma were included. The primary outcome assessed was overall survival. A random-effects meta-analysis was performed, together with pooling of unadjusted Kaplan–Meier curve data. Results A total of 533 studies were identified that analysed the effect of neoadjuvant therapy in pancreatic ductal adenocarcinoma. Twenty-seven studies were included in the final data synthesis. Meta-analysis suggested beneficial effects of neoadjuvant therapy with prolonged survival compared with a surgery-first approach, (hazard ratio 0.72, 95% confidence interval 0.69–0.76). In addition, R0 resection rates were significantly higher in patients receiving neoadjuvant therapy (relative risk 0.51, 95% confidence interval 0.47–0.55). Individual patient data analysis suggested that overall survival was better for patients receiving neoadjuvant therapy (P = 0.008). Conclusions Current evidence suggests that neoadjuvant chemotherapy has a beneficial effect on overall survival in resectable pancreatic ductal adenocarcinoma in comparison with upfront surgery and adjuvant therapy. Further trials are needed to address the need for practice change.

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