Pancreatic Expression database: a generic model for the organization, integration and mining of complex cancer datasets

<p>Abstract</p> <p>Background</p> <p>Pancreatic cancer is the 5th leading cause of cancer death in both males and females. In recent years, a wealth of gene and protein expression studies have been published broadening our understanding of pancreatic cancer biology. Due to the explosive growth in publicly available data from multiple different sources it is becoming increasingly difficult for individual researchers to integrate these into their current research programmes. The Pancreatic Expression database, a generic web-based system, is aiming to close this gap by providing the research community with an open access tool, not only to mine currently available pancreatic cancer data sets but also to include their own data in the database.</p> <p>Description</p> <p>Currently, the database holds 32 datasets comprising 7636 gene expression measurements extracted from 20 different published gene or protein expression studies from various pancreatic cancer types, pancreatic precursor lesions (PanINs) and chronic pancreatitis. The pancreatic data are stored in a data management system based on the BioMart technology alongside the human genome gene and protein annotations, sequence, homologue, SNP and antibody data. Interrogation of the database can be achieved through both a web-based query interface and through web services using combined criteria from pancreatic (disease stages, regulation, differential expression, expression, platform technology, publication) and/or public data (antibodies, genomic region, gene-related accessions, ontology, expression patterns, multi-species comparisons, protein data, SNPs). Thus, our database enables connections between otherwise disparate data sources and allows relatively simple navigation between all data types and annotations.</p> <p>Conclusion</p> <p>The database structure and content provides a powerful and high-speed data-mining tool for cancer research. It can be used for target discovery i.e. of biomarkers from body fluids, identification and analysis of genes associated with the progression of cancer, cross-platform meta-analysis, SNP selection for pancreatic cancer association studies, cancer gene promoter analysis as well as mining cancer ontology information. The data model is generic and can be easily extended and applied to other types of cancer. The database is available online with no restrictions for the scientific community at <url>http://www.pancreasexpression.org/</url>.</p

p21 promotes oncolytic adenoviral activity in ovarian cancer and is a potential biomarker

The oncolytic adenovirus dl922-947 replicates selectively within and lyses cells with a dysregulated Rb pathway, a finding seen in > 90% human cancers. dl922-947 is more potent than wild type adenovirus and the E1B-deletion mutant dl1520 (Onyx-015). We wished to determine which host cell factors influence cytotoxicity. SV40 large T-transformed MRC5-VA cells are 3-logs more sensitive to dl922-947 than isogenic parental MRC5 cells, confirming that an abnormal G1/S checkpoint increases viral efficacy. The sensitivity of ovarian cancer cells to dl922-947 varied widely: IC50 values ranged from 51 (SKOV3ip1) to 0.03 pfu/cell (TOV21G). Cells sensitive to dl922-947 had higher S phase populations and supported earlier E1A expression. Cytotoxicity correlated poorly with both infectivity and replication, but well with expression of p21 by microarray and western blot analyses. Matched p21+/+ and -/- Hct116 cells confirmed that p21 influences dl922-947 activity in vitro and in vivo. siRNA-mediated p21 knockdown in sensitive TOV21G cells decreases E1A expression and viral cytotoxicity, whilst expression of p21 in resistant A2780CP cells increases virus activity in vitro and in intraperitoneal xenografts. These results highlight that host cell factors beyond simple infectivity can influence the efficacy of oncolytic adenoviruses. p21 expression may be an important biomarker of response in clinical trials

A global insight into a cancer transcriptional space using pancreatic data: importance, findings and flaws

Despite the increasing wealth of available data, the structure of cancer transcriptional space remains largely unknown. Analysis of this space would provide novel insights into the complexity of cancer, assess relative implications in complex biological processes and responses, evaluate the effectiveness of cancer models and help uncover vital facets of cancer biology not apparent from current small-scale studies. We conducted a comprehensive analysis of pancreatic cancer-expression space by integrating data from otherwise disparate studies. We found (i) a clear separation of profiles based on experimental type, with patient tissue samples, cell lines and xenograft models forming distinct groups; (ii) three subgroups within the normal samples adjacent to cancer showing disruptions to biofunctions previously linked to cancer; and (iii) that ectopic subcutaneous xenografts and cell line models do not effectively represent changes occurring in pancreatic cancer. All findings are available from our online resource for independent interrogation. Currently, the most comprehensive analysis of pancreatic cancer to date, our study primarily serves to highlight limitations inherent with a lack of raw data availability, insufficient clinical/histopathological information and ambiguous data processing. It stresses the importance of a global-systems approach to assess and maximise findings from expression profiling of malignant and non-malignant diseases

The Pancreatic Expression Database: 2018 update.

The Pancreatic Expression Database (PED, http://www.pancreasexpression.org) continues to be a major resource for mining pancreatic -omics data a decade after its initial release. Here, we present recent updates to PED and describe its evolution into a comprehensive resource for extracting, analysing and integrating publicly available multi-omics datasets. A new analytical module has been implemented to run in parallel with the existing literature mining functions. This analytical module has been created using rich data content derived from pancreas-related specimens available through the major data repositories (GEO, ArrayExpress) and international initiatives (TCGA, GENIE, CCLE). Researchers have access to a host of functions to tailor analyses to meet their needs. Results are presented using interactive graphics that allow the molecular data to be visualized in a user-friendly manner. Furthermore, researchers are provided with the means to superimpose layers of molecular information to gain greater insight into alterations and the relationships between them. The literature-mining module has been improved with a redesigned web appearance, restructured query platforms and updated annotations. These updates to PED are in preparation for its integration with the Pancreatic Cancer Research Fund Tissue Bank (PCRFTB), a vital resource of pancreas cancer tissue for researchers to support and promote cutting-edge research.Pancreatic Cancer Research Fund [Tissue Bank grant]; Cancer Research UK [Grant A12008]; Breast Cancer Campaign [Tissue Bank Bioinformatics grant TB2016BIF]

The integrin αvβ6 drives pancreatic cancer through diverse mechanisms and represents an effective target for therapy

Pancreatic ductal adenocarcinoma (PDAC) has a five‐year survival rate of &lt;4% and desperately needs novel effective therapeutics. Integrin αvβ6 has been linked with poor prognosis in cancer but its potential as a target in PDAC remains unclear. We report that transcriptional expression analysis revealed high levels of β6 mRNA correlated strongly with significantly poorer survival (n=491 cases, p= 3.17x10‐8). In two separate cohorts we showed that over 80% of PDAC expressed αvβ6 protein and that paired metastases retained αvβ6 expression. In vitro, integrin αvβ6 promoted PDAC cell growth, survival, migration and invasion. Treatment of both αvβ6‐positive human PDAC xenografts and transgenic mice bearing αvβ6‐positive PDAC with the αvβ6 blocking antibody 264RAD, combined with gemcitabine, significantly reduced tumour growth (p&lt;0.0001) and increased survival (Log‐rank test, p&lt;0.05). Antibody therapy was associated with suppression of both tumour cell activity (suppression of pErk growth signals, increased apoptosis seen as activated Caspase 3) and suppression of the pro‐tumourigenic microenvironment (suppression of TGFβ signalling, fewer αSMA‐positive myofibroblasts, decreased blood vessel density). These data show that αvβ6 promotes PDAC growth through both tumour cell and tumour microenvironment mechanisms and represents a valuable target for PDAC therapy

A multi-gene signature predicts outcome in patients with pancreatic ductal adenocarcinoma.

© 2014 Haider et al.; licensee BioMed Central. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Improved usage of the repertoires of pancreatic ductal adenocarcinoma (PDAC) profiles is crucially needed to guide the development of predictive and prognostic tools that could inform the selection of treatment options

Molecular Analysis of Precursor Lesions in Familial Pancreatic Cancer

PMCID: PMC3553106This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Deconstruction of a Metastatic Tumor Microenvironment Reveals a Common Matrix Response in Human Cancers.

We have profiled, for the first time, an evolving human metastatic microenvironment by measuring gene expression, matrisome proteomics, cytokine and chemokine levels, cellularity, extracellular matrix organization, and biomechanical properties, all on the same sample. Using biopsies of high-grade serous ovarian cancer metastases that ranged from minimal to extensive disease, we show how nonmalignant cell densities and cytokine networks evolve with disease progression. Multivariate integration of the different components allowed us to define, for the first time, gene and protein profiles that predict extent of disease and tissue stiffness, while also revealing the complexity and dynamic nature of matrisome remodeling during development of metastases. Although we studied a single metastatic site from one human malignancy, a pattern of expression of 22 matrisome genes distinguished patients with a shorter overall survival in ovarian and 12 other primary solid cancers, suggesting that there may be a common matrix response to human cancer.Significance: Conducting multilevel analysis with data integration on biopsies with a range of disease involvement identifies important features of the evolving tumor microenvironment. The data suggest that despite the large spectrum of genomic alterations, some human malignancies may have a common and potentially targetable matrix response that influences the course of disease. Cancer Discov; 8(3); 304-19. ©2017 AACR.This article is highlighted in the In This Issue feature, p. 253

Inactivation of TGFβ receptors in stem cells drives cutaneous squamous cell carcinoma

Melanoma patients treated with oncogenic BRAF inhibitors can develop cutaneous squamous cell carcinoma (cSCC) within weeks of treatment, driven by paradoxical RAS/RAF MAPK pathway activation. Here, we identify frequent TGFBR1 and TGFBR2 mutations in human vemurafenib-induced skin lesions and in sporadic cSCC. Functional analysis reveals these mutations ablate canonical TGFb Smad signaling which is localised to bulge stem cells in both normal human and murine skin. MAPK pathway hyperactivation (through BRafV600E or KRASG12D knockin) and TGFb signaling ablation (through Tgfbr1 deletion) in Lgr5+ve stem cells enables rapid cSCC development in the mouse. Mutation of TP53 (which is commonly mutated in sporadic cSCC) coupled with TGFbR1 deletion in Lgr5+ve cells also results in cSCC development. These findings indicate that Lgr5+ve stem cells can act as a cell of origin for cSCC and that RAS-RAF-MAPK pathway hyperactivation or TP53 mutation, coupled with loss of TGFb signaling, are driving events of skin tumorigenesis

IW-Scoring: an Integrative Weighted Scoring framework for annotating and prioritizing genetic variations in the noncoding genome

Cancer Research UK Centre of Excellence Award to Barts Cancer Centre [C16420/A18066]; Barts and The London Charity Grant [MGU0344]; D.U. is funded by Pancreatic Cancer Research Fund Tissue Bank Grant. Funding for open access charge: Charity Open Access Fund (COAF) award