PatentMatrix: an automated tool to survey patents related to large sets of genes or proteins

<p>Abstract</p> <p>Background</p> <p>The number of patents associated with genes and proteins and the amount of information contained in each patent often present a real obstacle to the rapid evaluation of the novelty of findings associated to genes from an intellectual property (IP) perspective. This assessment, normally carried out by expert patent professionals, can therefore become cumbersome and time consuming. Here we present PatentMatrix, a novel software tool for the automated analysis of patent sequence text entries.</p> <p>Methods and Results</p> <p>PatentMatrix is written in the Awk language and requires installation of the Derwent GENESEQ™ patent sequence database under the sequence retrieval system SRS.</p> <p>The software works by taking as input two files: i) a list of genes or proteins with the associated GENESEQ™ patent sequence accession numbers ii) a list of keywords describing the research context of interest (e.g. 'lung', 'cancer', 'therapeutics', 'diagnostics'). The GENESEQ™ database is interrogated through the SRS system and each patent entry of interest is screened for the occurrence of user-defined keywords. Moreover, the software extracts the basic information useful for a preliminary assessment of the IP coverage of each patent from the GENESEQ™ database. As output, two tab-delimited files are generated which provide the user with a detailed and an aggregated view of the results.</p> <p>An example is given where the IP position of five genes is evaluated in the context of 'development of antibodies for cancer treatment'</p> <p>Conclusion</p> <p>PatentMatrix allows a rapid survey of patents associated with genes or proteins in a particular area of interest as defined by keywords. It can be efficiently used to evaluate the IP-related novelty of scientific findings and to rank genes or proteins according to their IP position.</p

3dLOGO:a web server for the identification, analysis and use of conserved protein substructures

3dLOGO is a web server for the identification and analysis of conserved protein 3D substructures. Given a set of residues in a PDB (Protein Data Bank) chain, the server detects the matching substructure(s) in a set of user-provided protein structures, generates a multiple structure alignment centered on the input substructures and highlights other residues whose structural conservation becomes evident after the defined superposition. Conserved residues are proposed to the user for highlighting functional areas, deriving refined structural motifs or building sequence patterns. Residue structural conservation can be visualized through an expressly designed Java application, 3dProLogo, which is a 3D implementation of a sequence logo. The 3dLOGO server, with related documentation, is available at http://3dlogo.uniroma2.it

MicroRNAs: shortcuts in dealing with molecular complexity?

Recent studies from Clarke's group published in the journal Cell indicate that miRNAs may be the elusive universal stem cell markers that the field of cancer stem cell biology has been seeking. Distinct profiles of miRNAs appear to reflect the state of cell differentiation not only in breast cancer cells, but also in normal mammary epithelial cells. Moreover, they are conserved across tissues and species. The authors of this work also show evidence that downregulation of miRNA-200c in normal and malignant breast stem cells and in embryonal carcinoma cells has functional relevance, being responsible for the proliferative potential of these cells in vitro and in vivo

Comparative expression pathway analysis of human and canine mammary tumors

<p>Abstract</p> <p>Background</p> <p>Spontaneous tumors in dog have been demonstrated to share many features with their human counterparts, including relevant molecular targets, histological appearance, genetics, biological behavior and response to conventional treatments. Mammary tumors in dog therefore provide an attractive alternative to more classical mouse models, such as transgenics or xenografts, where the tumour is artificially induced. To assess the extent to which dog tumors represent clinically significant human phenotypes, we performed the first genome-wide comparative analysis of transcriptional changes occurring in mammary tumors of the two species, with particular focus on the molecular pathways involved.</p> <p>Results</p> <p>We analyzed human and dog gene expression data derived from both tumor and normal mammary samples. By analyzing the expression levels of about ten thousand dog/human orthologous genes we observed a significant overlap of genes deregulated in the mammary tumor samples, as compared to their normal counterparts. Pathway analysis of gene expression data revealed a great degree of similarity in the perturbation of many cancer-related pathways, including the 'PI3K/AKT', 'KRAS', 'PTEN', 'WNT-beta catenin' and 'MAPK cascade'. Moreover, we show that the transcriptional relationships between different gene signatures observed in human breast cancer are largely maintained in the canine model, suggesting a close interspecies similarity in the network of cancer signalling circuitries.</p> <p>Conclusion</p> <p>Our data confirm and further strengthen the value of the canine mammary cancer model and open up new perspectives for the evaluation of novel cancer therapeutics and the development of prognostic and diagnostic biomarkers to be used in clinical studies.</p

The integration of large-scale public data and network analysis uncovers molecular characteristics of psoriasis

In recent years, a growing interest in the characterization of the molecular basis of psoriasis has been observed. However, despite the availability of a large amount of molecular data, many pathogenic mechanisms of psoriasis are still poorly understood. In this study, we performed an integrated analysis of 23 public transcriptomic datasets encompassing both lesional and uninvolved skin samples from psoriasis patients. We defined comprehensive gene co-expression network models of psoriatic lesions and uninvolved skin. Moreover, we curated and exploited a wide range of functional information from multiple public sources in order to systematically annotate the inferred networks. The integrated analysis of transcriptomics data and co-expression networks highlighted genes that are frequently dysregulated and show aberrant patterns of connectivity in the psoriatic lesion compared with the unaffected skin. Our approach allowed us to also identify plausible, previously unknown, actors in the expression of the psoriasis phenotype. Finally, we characterized communities of co-expressed genes associated with relevant molecular functions and expression signatures of specific immune cell types associated with the psoriasis lesion. Overall, integrating experimental driven results with curated functional information from public repositories represents an efficient approach to empower knowledge generation about psoriasis and may be applicable to other complex diseases.Peer reviewe

CrossHybDetector: detection of cross-hybridization events in DNA microarray experiments

Background\ud DNA microarrays contain thousands of different probe sequences represented on their surface. These are designed in such a way that potential cross-hybridization reactions with non-target sequences are minimized. However, given the large number of probes, the occurrence of cross hybridization events cannot be excluded. This problem can dramatically affect the data quality and cause false positive/false negative results.\ud \ud Results\ud CrossHybDetector is a software package aimed at the identification of cross-hybridization events occurred during individual array hybridization, by using the probe sequences and the array intensity values. As output, the software provides the user with a list of array spots potentially &apos;corrupted&apos; and their associated p-values calculated by Monte Carlo simulations. Graphical plots are also generated, which provide a visual and global overview of the quality of the microarray experiment with respect to cross-hybridization issues.\ud \ud Conclusion\ud CrossHybDetector is implemented as a package for the statistical computing environment R and is freely available under the LGPL license within the CRAN project

Blood and islet phenotypes indicate immunological heterogeneity in type 1 diabetes

This is an author-created, uncopyedited electronic version of an article accepted for publication in Diabetes. The American Diabetes Association (ADA), publisher of Diabetes, is not responsible for any errors or omissions in this version of the manuscript or any version derived from it by third parties. The definitive publisher-authenticated version is available in Diabetes in print and online at http://diabetes.diabetesjournals.orgThe erratum to this article is available in ORE at http://hdl.handle.net/10871/40335Studies in type 1 diabetes indicate potential disease heterogeneity, notably in the rate of β-cell loss, responsiveness to immunotherapies, and, in limited studies, islet pathology. We sought evidence for different immunological phenotypes using two approaches. First, we defined blood autoimmune response phenotypes by combinatorial, multiparameter analysis of autoantibodies and autoreactive T-cell responses in 33 children/adolescents with newly diagnosed diabetes. Multidimensional cluster analysis showed two equal-sized patient agglomerations characterized by proinflammatory (interferon-γ-positive, multiautoantibody-positive) and partially regulated (interleukin-10-positive, pauci-autoantibody-positive) responses. Multiautoantibody-positive nondiabetic siblings at high risk of disease progression showed similar clustering. Additionally, pancreas samples obtained post mortem from a separate cohort of 21 children/adolescents with recently diagnosed type 1 diabetes were examined immunohistologically. This revealed two distinct types of insulitic lesions distinguishable by the degree of cellular infiltrate and presence of B cells that we termed "hyper-immune CD20Hi" and "pauci-immune CD20Lo." Of note, subjects had only one infiltration phenotype and were partitioned by this into two equal-sized groups that differed significantly by age at diagnosis, with hyper-immune CD20Hi subjects being 5 years younger. These data indicate potentially related islet and blood autoimmune response phenotypes that coincide with and precede disease. We conclude that different immunopathological processes (endotypes) may underlie type 1 diabetes, carrying important implications for treatment and prevention strategies.JDRFNational Institute for Health Research (NIHR) Biomedical Research Centre based at Guy’s and St Thomas’ NHS Foundation Trust and King’s College LondonEuropean Union (EU FP7) award - Persistent Virus Infection in Diabetes Network Study Group (PEVNET)EU FP7 Large-Scale Focused Collaborative Research Project on Natural Immunomodulators as Novel Immunotherapies for Type 1 Diabetes (NAIMIT)EU FP7 Large-Scale Focused Collaborative Research Project on β-cell preservation through antigen-specific immunotherapy in Type 1 Diabetes: Enhanced Epidermal Antigen Delivery Systems (EE-ASI)National Institutes of Health (NIH)National Institute of Diabetes and Digestive and Kidney DiseasesNational Institute of Allergy and Infectious DiseasesEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Center for Research ResourcesGeneral Clinical Research CenterAmerican Diabetes Association (ADA

Deep-phenotyping of Tregs identifies an immune signature for idiopathic aplastic anemia and predicts response to treatment

Idiopathic aplastic anemia (AA) is an immune-mediated and serious form of bone marrow failure. Akin to other autoimmune diseases, we have previously shown that in AA regulatory T-cells (Tregs) are reduced in number and function. The aim of this study was to further characterize Treg subpopulations in AA and investigate the potential correlation between specific Treg subsets and response to immunosuppressive therapy (IST) as well as their in-vitro expandability for potential clinical use. Using mass cytometry (CyTOF) and an unbiased multidimensional analytical approach, we identified two specific human Treg subpopulations (Treg A and Treg B) with distinct phenotypes, gene-expression, expandability and function. Treg subpopulation B, predominates in IST responder patients, has a memory/activated phenotype (with higher expression of CD95, CCR4 and CD45RO within FOXP3hi, CD127lo Tregs), expresses the IL- 2/STAT5 pathway and cell-cycle commitment genes. Furthermore, in-vitro expanded Tregs become functional and with the characteristics of Treg subpopulation B. Collectively, this study identifies human Treg subpopulations that can be used as predictive biomarkers for response to IST in AA and potentially other autoimmune diseases. We also show that Tregs from AA patients are IL-2 sensitive and expandable in-vitro, suggesting novel therapeutic approaches such as low dose IL-2 therapy and/or expanded autologous Tregs and meriting further exploration