SNPnexus: a web server for functional annotation of human genome sequence variation (2020 update).

SNPnexus is a web-based annotation tool for the analysis and interpretation of both known and novel sequencing variations. Since its last release, SNPnexus has received continual updates to expand the range and depth of annotations provided. SNPnexus has undergone a complete overhaul of the underlying infrastructure to accommodate faster computational times. The scope for data annotation has been substantially expanded to enhance biological interpretations of queried variants. This includes the addition of pathway analysis for the identification of enriched biological pathways and molecular processes. We have further expanded the range of user directed annotation fields available for the study of cancer sequencing data. These new additions facilitate investigations into cancer driver variants and targetable molecular alterations within input datasets. New user directed filtering options have been coupled with the addition of interactive graphical and visualization tools. These improvements streamline the analysis of variants derived from large sequencing datasets for the identification of biologically and clinically significant subsets in the data. SNPnexus is the most comprehensible web-based application currently available and these new set of updates ensures that it remains a state-of-the-art tool for researchers. SNPnexus is freely available at https://www.snp-nexus.org.

'Multi-omic' data analysis using O-miner.

Innovations in -omics technologies have driven advances in biomedical research. However, integrating and analysing the large volumes of data generated from different high-throughput -omics technologies remain a significant challenge to basic and clinical scientists without bioinformatics skills or access to bioinformatics support. To address this demand, we have significantly updated our previous O-miner analytical suite, to incorporate several new features and data types to provide an efficient and easy-to-use Web tool for the automated analysis of data from '-omics' technologies. Created from a biologist's perspective, this tool allows for the automated analysis of large and complex transcriptomic, genomic and methylomic data sets, together with biological/clinical information, to identify significantly altered pathways and prioritize novel biomarkers/targets for biological validation. Our resource can be used to analyse both in-house data and the huge amount of publicly available information from array and sequencing platforms. Multiple data sets can be easily combined, allowing for meta-analyses. Here, we describe the analytical pipelines currently available in O-miner and present examples of use to demonstrate its utility and relevance in maximizing research output. O-miner Web server is free to use and is available at http://www.o-miner.org.

Transient Inhibition of PI3Kδ Enhances the Therapeutic Effect of Intravenous Delivery of Oncolytic Vaccinia Virus.

Tumor-targeting oncolytic viruses such as vaccinia virus (VV) are attractive cancer therapeutic agents that act through multiple mechanisms to provoke both tumor lysis and anti-tumor immune responses. However, delivery of these agents remains restricted to intra-tumoral administration, which prevents effective targeting of inaccessible and disseminated tumor cells. In the present study we have identified transient pharmacological inhibition of the leukocyte-enriched phosphoinositide 3-kinase δ (PI3Kδ) as a novel mechanism to potentiate intravenous delivery of oncolytic VV to tumors. Pre-treatment of immunocompetent mice with the PI3Kδ-selective inhibitor IC87114 or the clinically approved idelalisib (CAL-101), prior to intravenous delivery of a tumor-tropic VV, dramatically improved viral delivery to tumors. This occurred via an inhibition of viral attachment to, but not internalization by, systemic macrophages through perturbation of signaling pathways involving RhoA/ROCK, AKT, and Rac. Pre-treatment using PI3Kδ-selective inhibitors prior to intravenous delivery of VV resulted in enhanced anti-tumor efficacy and significantly prolonged survival compared to delivery without PI3Kδ inhibition. These results indicate that effective intravenous delivery of oncolytic VV may be clinically achievable and could be useful in improving anti-tumor efficacy of oncolytic virotherapy.

SNPnexus: assessing the functional relevance of genetic variation to facilitate the promise of precision medicine.

Broader functional annotation of genetic variation is a valuable means for prioritising phenotypically-important variants in further disease studies and large-scale genotyping projects. We developed SNPnexus to meet this need by assessing the potential significance of known and novel SNPs on the major transcriptome, proteome, regulatory and structural variation models. Since its previous release in 2012, we have made significant improvements to the annotation categories and updated the query and data viewing systems. The most notable changes include broader functional annotation of noncoding variants and expanding annotations to the most recent human genome assembly GRCh38/hg38. SNPnexus has now integrated rich resources from ENCODE and Roadmap Epigenomics Consortium to map and annotate the noncoding variants onto different classes of regulatory regions and noncoding RNAs as well as providing their predicted functional impact from eight popular non-coding variant scoring algorithms and computational methods. A novel functionality offered now is the support for neo-epitope predictions from leading tools to facilitate its use in immunotherapeutic applications. These updates to SNPnexus are in preparation for its future expansion towards a fully comprehensive computational workflow for disease-associated variant prioritization from sequencing data, placing its users at the forefront of translational research. SNPnexus is freely available at http://www.snp-nexus.org.

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.

Anti-stromal treatment together with chemotherapy targets multiple signalling pathways in pancreatic adenocarcinoma.

Stromal targeting for pancreatic ductal adenocarcinoma (PDAC) is rapidly becoming an attractive option, due to the lack of efficacy of standard chemotherapy and increased knowledge about PDAC stroma. We postulated that the addition of stromal therapy may enhance the anti-tumour efficacy of chemotherapy. Gemcitabine and all-trans retinoic acid (ATRA) were combined in a clinically applicable regimen, to target cancer cells and pancreatic stellate cells (PSCs) respectively, in 3D organotypic culture models and genetically engineered mice (LSL-Kras(G12D) (/+) ;LSL-Trp53(R172H) (/+) ;Pdx-1-Cre: KPC mice) representing the spectrum of PDAC. In two distinct sets of organotypic models as well as KPC mice, we demonstrate a reduction in cancer cell proliferation and invasion together with enhanced cancer cell apoptosis when ATRA is combined with gemcitabine, compared to vehicle or either agent alone. Simultaneously, PSC activity (as measured by deposition of extracellular matrix proteins such as collagen and fibronectin) and PSC invasive ability were both diminished in response to combination therapy. These effects were mediated through a range of signalling cascades (Wnt, hedgehog, retinoid, and FGF) in cancer as well as stellate cells, affecting epithelial cellular functions such as epithelial-mesenchymal transition, cellular polarity, and lumen formation. At the tissue level, this resulted in enhanced tumour necrosis, increased vascularity, and diminished hypoxia. Consequently, there was an overall reduction in tumour size. The enhanced effect of stromal co-targeting (ATRA) alongside chemotherapy (gemcitabine) appears to be mediated by dampening multiple signalling cascades in the tumour-stroma cross-talk, rather than ablating stroma or targeting a single pathway. © 2016 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

The pancreatic expression database: recent extensions and updates.

The Pancreatic Expression Database (PED, http://www.pancreasexpression.org) is the only device currently available for mining of pancreatic cancer literature data. It brings together the largest collection of multidimensional pancreatic data from the literature including genomic, proteomic, microRNA, methylomic and transcriptomic profiles. PED allows the user to ask specific questions on the observed levels of deregulation among a broad range of specimen/experimental types including healthy/patient tissue and body fluid specimens, cell lines and murine models as well as related treatments/drugs data. Here we provide an update to PED, which has been previously featured in the Database issue of this journal. Briefly, PED data content has been substantially increased and expanded to cover methylomics studies. We introduced an extensive controlled vocabulary that records specific details on the samples and added data from large-scale meta-analysis studies. The web interface has been improved/redesigned with a quick search option to rapidly extract information about a gene/protein of interest and an upload option allowing users to add their own data to PED. We added a user guide and implemented integrated graphical tools to overlay and visualize retrieved information. Interoperability with biomart-compatible data sets was significantly improved to allow integrative queries with pancreatic cancer data.

STAT1 interaction with E3-14.7K in monocytes affects the efficacy of oncolytic adenovirus.

Oncolytic viruses based on adenovirus type 5 (Ad5) have been developed as a new class of therapeutic agents for cancers that are resistant to conventional therapies. Clinical experience shows that these agents are safe, but virotherapy alone has not achieved long-term cure in cancer patients. The vast majority of oncolytic adenoviruses used in clinical trials to date have deletion of the E3B genes. It has been demonstrated that the antitumor potency of the E3B-deleted mutant (dl309) is inferior to adenovirus with E3B genes intact. Tumors treated with dl309 show markedly greater macrophage infiltration than E3B-intact adenovirus. However, the functional mechanisms for this were not previously known. Here, we demonstrate that deletion of E3B genes increases production of chemokines by monocytes after adenovirus infection and increases monocyte migration. The E3B 14,700-Da protein (E3B-14.7K) inhibits STAT1 function by preventing its phosphorylation and nuclear translocation. The STAT1 inhibitor, fludarabine, rescues the effect of E3B-14.7K deletion by downregulating target chemokine expression in human and murine monocytes and results in an enhanced antitumor efficacy with dl309 in vivo. These findings have important implications for clinical use of E3B-deleted oncolytic adenovirus and other E3B-deleted adenovirus vector-based therapy.

A practical guide for the functional annotation of genetic variations using SNPnexus.

Broader functional annotation of known as well as putative genetic variations is a valuable mean for prioritizing targets in disease studies and large-scale genotyping projects. In this article, we present a practical guide to SNPnexus, a web-based tool that provides an aggregate set of functional annotations for genomic variation data by characterizing related consequences at the transcriptome/proteome levels with in-depth analysis of potential deleterious effects, inferring physical and cytogenetic mapping, reporting related HapMap data, finding overlaps with potential regulatory, structural as well as conserved elements and retrieving links with previously reported genetic disease studies. We focus on the SNPnexus query system, its annotation categories and the biological interpretation of results.

Vascular endothelial growth factor A promotes vaccinia virus entry into host cells via activation of the Akt pathway.

Vaccinia virus (VV) is an enveloped DNA virus from the poxvirus family and has played a crucial role in the eradication of smallpox. It continues to be used in immunotherapy for the prevention of infectious diseases and treatment of cancer. However, the mechanisms of poxvirus entry, the host factors that affect viral virulence, and the reasons for its natural tropism for tumor cells are incompletely understood. By studying the effect of hypoxia on VV infection, we found that vascular endothelial growth factor A (VEGF-A) augments oncolytic VV cytotoxicity. VEGF derived from tumor cells acts to increase VV internalization, resulting in increased replication and cytotoxicity in an AKT-dependent manner in both tumor cells and normal respiratory epithelial cells. Overexpression of VEGF also enhances VV infection within tumor tissue in vivo after systemic delivery. These results highlight the importance of VEGF expression in VV infection and have potential implications for the design of new strategies to prevent poxvirus infection and the development of future generations of oncolytic VV in combination with conventional or biological therapies.

SNPnexus: a web server for functional annotation of novel and publicly known genetic variants (2012 update).

Broader functional annotation of single nucleotide variations is a valuable mean for prioritizing targets in further disease studies and large-scale genotyping projects. We originally developed SNPnexus to assess the potential significance of known and novel SNPs on the major transcriptome, proteome, regulatory and structural variation models in order to identify the phenotypically important variants. Being committed to providing continuous support to the scientific community, we have substantially improved SNPnexus over time by incorporating a broader range of variations such as insertions/deletions, block substitutions, IUPAC codes submission and region-based analysis, expanding the query size limit, and most importantly including additional categories for the assessment of functional impact. SNPnexus provides a comprehensive set of annotations for genomic variation data by characterizing related functional consequences at the transcriptome/proteome levels of seven major annotation systems with in-depth analysis of potential deleterious effects, inferring physical and cytogenetic mapping, reporting information on HapMap genotype/allele data, finding overlaps with potential regulatory elements, structural variations and conserved elements, and retrieving links with previously reported genetic disease studies. SNPnexus has a user-friendly web interface with an improved query structure, enhanced functional annotation categories and flexible output presentation making it practically useful for biologists. SNPnexus is freely available at http://www.snp-nexus.org.

O-miner: an integrative platform for automated analysis and mining of -omics data.

High-throughput profiling has generated massive amounts of data across basic, clinical and translational research fields. However, open source comprehensive web tools for analysing data obtained from different platforms and technologies are still lacking. To fill this gap and the unmet computational needs of ongoing research projects, we developed O-miner, a rapid, comprehensive, efficient web tool that covers all the steps required for the analysis of both transcriptomic and genomic data starting from raw image files through in-depth bioinformatics analysis and annotation to biological knowledge extraction. O-miner was developed from a biologist end-user perspective. Hence, it is as simple to use as possible within the confines of the complexity of the data being analysed. It provides a strong analytical suite able to overlay and harness large, complicated, raw and heterogeneous sets of profiles with biological/clinical data. Biologists can use O-miner to analyse and integrate different types of data and annotations to build knowledge of relevant altered mechanisms and pathways in order to identify and prioritize novel targets for further biological validation. Here we describe the analytical workflows currently available using O-miner and present examples of use. O-miner is freely available at www.o-miner.org.

Online resources of cancer data: barriers, benefits and lessons.

With advances in high-throughput techniques, the volume of data generated has resulted in the creation of a plethora of resources for the cancer research community. However, a key factor in the utility, sustainability and future use of a novel resource lies in its ability to allow for data sharing and to be interoperable with major international cancer research efforts. This article will introduce some of these efforts, the interoperable cancer data-mining resources and repositories, from a user-perspective. Some of the considerations to be addressed when building interoperable, sustainable cancer resources will be discussed with case studies-hoping this will prove useful for researchers designing their own cancer databases.

Modification of the early gene enhancer-promoter improves the oncolytic potency of adenovirus 11.

Oncolytic adenoviruses based on serotype 5 (Ad5) have several shortcomings, including the downregulation of its receptor in cancer cells, high prevalence of neutralizing antibodies and hepatotoxicity. Another adenoviral serotype, Ad11, could overcome these obstacles. Here, we show that human cancer cell lines express higher levels of the Ad11 receptor CD46, resulting in much better infectivity than Ad5. Surprisingly, only 36% (9/25) of the cell lines were more sensitive to Ad11- than to Ad5-mediated cytotoxicity. Investigations revealed that it was the transcription of Ad11 E1A, not CD46 expression or virus infectivity, which determined the cell's sensitivity to Ad11 killing. Ad11 E1A mRNA levels have an effect on viral DNA replication, structural protein synthesis and infectious particle production. To test the hypothesis that increased E1A transcription would lead to improved Ad11 replication in Ad5-sensitive (but Ad11-less sensitive) cells, two Ad11 mutants (Ad11-Ad5-P and Ad11-Ad5-EP) were constructed where either the E1A promoter or enhancer-promoter, respectively, was replaced by that of Ad5. Ad11-Ad5-EP demonstrated increased E1A mRNA levels and replication, together with enhanced oncolytic potency in vitro and in vivo. This effect was found in both the Ad5-sensitive and Ad11-sensitive cancer cells, broadening the range of tumors that could be effectively killed by Ad11-Ad5-EP.

The Pancreatic Expression database: 2011 update.

The Pancreatic Expression database (PED, http://www.pancreasexpression.org) has established itself as the main repository for pancreatic-derived -omics data. For the past 3 years, its data content and access have increased substantially. Here we describe several of its new and improved features, such as data content, which now includes over 60,000 measurements derived from transcriptomics, proteomics, genomics and miRNA profiles from various pancreas-centred reports on a broad range of specimen and experimental types. We also illustrate the capabilities of its interface, which allows integrative queries that can combine PED data with a growing number of biological resources such as NCBI, Ensembl, UniProt and Reactome. Thus, PED is capable of retrieving and integrating different types of -omics, annotations and clinical data. We also focus on the importance of data sharing and interoperability in the cancer field, and the integration of PED into the International Cancer Genome Consortium (ICGC) data portal.

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.

Oncolytic vaccinia virus and cancer immunotherapy.

Oncolytic virotherapy (OVT) is a promising form of cancer treatment that uses genetically engineered viruses to replicate within cancer cells and trigger anti-tumor immune response. In addition to killing cancer cells, oncolytic viruses can also remodel the tumor microenvironment and stimulate a long-term anti-tumor immune response. Despite achieving positive results in cellular and organismal studies, there are currently only a few approved oncolytic viruses for clinical use. Vaccinia virus (VACV) has emerged as a potential candidate due to its ability to infect a wide range of cancer cells. This review discusses the mechanisms, benefits, and clinical trials of oncolytic VACVs. The safety and efficacy of different viral backbones are explored, as well as the effects of oncolytic VACVs on the tumor microenvironment. The potential combination of oncolytic VACVs with immunotherapy or traditional therapies is also highlighted. The review concludes by addressing prospects and challenges in the field of oncolytic VACVs, with the aim of promoting further research and application in cancer therapy.

Syrian hamster as an ideal animal model for evaluation of cancer immunotherapy.

Cancer immunotherapy (CIT) has emerged as an exciting new pillar of cancer treatment. Although benefits have been achieved in individual patients, the overall response rate is still not satisfactory. To address this, an ideal preclinical animal model for evaluating CIT is urgently needed. Syrian hamsters present similar features to humans with regard to their anatomy, physiology, and pathology. Notably, the histological features and pathological progression of tumors and the complexity of the tumor microenvironment are equivalent to the human scenario. This article reviews the current tumor models in Syrian hamster and the latest progress in their application to development of tumor treatments including immune checkpoint inhibitors, cytokines, adoptive cell therapy, cancer vaccines, and oncolytic viruses. This progress strongly advocates Syrian hamster as an ideal animal model for development and assessment of CIT for human cancer treatments. Additionally, the challenges of the Syrian hamster as an animal model for CIT are also discussed.