Identification of early stage recurrence endometrial cancer biomarkers using bioinformatics tools.

Endometrial cancer (EC) is the sixth most common cancer in women worldwide. Early diagnosis is critical in recurrent EC management. The present study aimed to identify biomarkers of EC early recurrence using a workflow that combined text and data mining databases (DisGeNET, Gene Expression Omnibus), a prioritization algorithm to select a set of putative candidates (ToppGene), protein­protein interaction network analyses (Search Tool for the Retrieval of Interacting Genes, cytoHubba), association analysis of selected genes with clinicopathological parameters, and survival analysis (Kaplan­Meier and Cox proportional hazard ratio analyses) using a The Cancer Genome Atlas cohort. A total of 10 genes were identified, among which the targeting protein for Xklp2 (TPX2) was the most promising independent prognostic biomarker in stage I EC. TPX2 expression (mRNA and protein) was higher (P<0.0001 and P<0.001, respectively) in ETS variant transcription factor 5­overexpressing Hec1a and Ishikawa cells, a previously reported cell model of aggressive stage I EC. In EC biopsies, TPX2 mRNA expression levels were higher (P<0.05) in high grade tumors (grade 3) compared with grade 1­2 tumors (P<0.05), in tumors with deep myometrial invasion (>50% compared with <50%; P<0.01), and in intermediate­high recurrence risk tumors compared with low­risk tumors (P<0.05). Further validation studies in larger and independent EC cohorts will contribute to confirm the prognostic value of TPX2.

Identification of a Novel Human E-Cadherin Splice Variant and Assessment of Its Effects Upon EMT-Related Events.

Epithelial Cadherin (E-cadherin) is involved in calcium-dependent cell-cell adhesion and signal transduction. The E-cadherin decrease/loss is a hallmark of Epithelial to Mesenchymal Transition (EMT), a key event in tumor progression. The underlying molecular mechanisms that trigger E-cadherin loss and consequent EMT have not been completely elucidated. This study reports the identification of a novel human E-cadherin variant mRNA produced by alternative splicing. A bioinformatics evaluation of the novel mRNA sequence and biochemical verifications suggest its regulation by Nonsense-Mediated mRNA Decay (NMD). The novel E-cadherin variant was detected in 29/42 (69%) human tumor cell lines, expressed at variable levels (E-cadherin variant expression relative to the wild type mRNA = 0.05-11.6%). Stable transfection of the novel E-cadherin variant in MCF-7 cells (MCF7Ecadvar) resulted in downregulation of wild type E-cadherin expression (transcript/protein) and EMT-related changes, among them acquisition of a fibroblastic-like cell phenotype, increased expression of Twist, Snail, Zeb1, and Slug transcriptional repressors and decreased expression of ESRP1 and ESRP2 RNA binding proteins. Moreover, loss of cytokeratins and gain of vimentin, N-cadherin and Dysadherin/FXYD5 proteins was observed. Dramatic changes in cell behavior were found in MCF7Ecadvar, as judged by the decreased cell-cell adhesion (Hanging-drop assay), increased cell motility (Wound Healing) and increased cell migration (Transwell) and invasion (Transwell w/Matrigel). Some changes were found in MCF-7 cells incubated with culture medium supplemented with conditioned medium from HEK-293 cells transfected with the E-cadherin variant mRNA. Further characterization of the novel E-cadherin variant will help understanding the molecular basis of tumor progression and improve cancer diagnosis. J. Cell. Physiol. 232: 1368-1386, 2017. © 2016 Wiley Periodicals, Inc.

CDH1/E-cadherin and solid tumors. An updated gene-disease association analysis using bioinformatics tools.

Cancer is a group of diseases that causes millions of deaths worldwide. Among cancers, Solid Tumors (ST) stand-out due to their high incidence and mortality rates. Disruption of cell-cell adhesion is highly relevant during tumor progression. Epithelial-cadherin (protein: E-cadherin, gene: CDH1) is a key molecule in cell-cell adhesion and an abnormal expression or/and function(s) contributes to tumor progression and is altered in ST. A systematic study was carried out to gather and summarize current knowledge on CDH1/E-cadherin and ST using bioinformatics resources. The DisGeNET database was exploited to survey CDH1-associated diseases. Reported mutations in specific ST were obtained by interrogating COSMIC and IntOGen tools. CDH1 Single Nucleotide Polymorphisms (SNP) were retrieved from the dbSNP database. DisGeNET analysis identified 609 genes annotated to ST, among which CDH1 was listed. Using CDH1 as query term, 26 disease concepts were found, 21 of which were neoplasms-related terms. Using DisGeNET ALL Databases, 172 disease concepts were identified. Of those, 80 ST disease-related terms were subjected to manual curation and 75/80 (93.75%) associations were validated. On selected ST, 489 CDH1 somatic mutations were listed in COSMIC and IntOGen databases. Breast neoplasms had the highest CDH1-mutation rate. CDH1 was positioned among the 20 genes with highest mutation frequency and was confirmed as driver gene in breast cancer. Over 14,000 SNP for CDH1 were found in the dbSNP database. This report used DisGeNET to gather/compile current knowledge on gene-disease association for CDH1/E-cadherin and ST; data curation expanded the number of terms that relate them. An updated list of CDH1 somatic mutations was obtained with COSMIC and IntOGen databases and of SNP from dbSNP. This information can be used to further understand the role of CDH1/E-cadherin in health and disease.

Mining the modular structure of protein interaction networks.

BACKGROUND: Cluster-based descriptions of biological networks have received much attention in recent years fostered by accumulated evidence of the existence of meaningful correlations between topological network clusters and biological functional modules. Several well-performing clustering algorithms exist to infer topological network partitions. However, due to respective technical idiosyncrasies they might produce dissimilar modular decompositions of a given network. In this contribution, we aimed to analyze how alternative modular descriptions could condition the outcome of follow-up network biology analysis. METHODOLOGY: We considered a human protein interaction network and two paradigmatic cluster recognition algorithms, namely: the Clauset-Newman-Moore and the infomap procedures. We analyzed to what extent both methodologies yielded different results in terms of granularity and biological congruency. In addition, taking into account Guimera's cartographic role characterization of network nodes, we explored how the adoption of a given clustering methodology impinged on the ability to highlight relevant network meso-scale connectivity patterns. RESULTS: As a case study we considered a set of aging related proteins and showed that only the high-resolution modular description provided by infomap, could unveil statistically significant associations between them and inter/intra modular cartographic features. Besides reporting novel biological insights that could be gained from the discovered associations, our contribution warns against possible technical concerns that might affect the tools used to mine for interaction patterns in network biology studies. In particular our results suggested that sub-optimal partitions from the strict point of view of their modularity levels might still be worth being analyzed when meso-scale features were to be explored in connection with external source of biological knowledge.

Gathering and exploring scientific knowledge in pharmacovigilance.

Pharmacovigilance plays a key role in the healthcare domain through the assessment, monitoring and discovery of interactions amongst drugs and their effects in the human organism. However, technological advances in this field have been slowing down over the last decade due to miscellaneous legal, ethical and methodological constraints. Pharmaceutical companies started to realize that collaborative and integrative approaches boost current drug research and development processes. Hence, new strategies are required to connect researchers, datasets, biomedical knowledge and analysis algorithms, allowing them to fully exploit the true value behind state-of-the-art pharmacovigilance efforts. This manuscript introduces a new platform directed towards pharmacovigilance knowledge providers. This system, based on a service-oriented architecture, adopts a plugin-based approach to solve fundamental pharmacovigilance software challenges. With the wealth of collected clinical and pharmaceutical data, it is now possible to connect knowledge providers' analysis and exploration algorithms with real data. As a result, new strategies allow a faster identification of high-risk interactions between marketed drugs and adverse events, and enable the automated uncovering of scientific evidence behind them. With this architecture, the pharmacovigilance field has a new platform to coordinate large-scale drug evaluation efforts in a unique ecosystem, publicly available at http://bioinformatics.ua.pt/euadr/.

OSIRIS: a tool for retrieving literature about sequence variants.

UNLABELLED: Sequence variants, in particular single nucleotide polymorphisms (SNPs), are key elements for the identification of genes associated with complex diseases and with particular drug responses. The search for literature about sequence variation is hampered by the large number of allelic variants reported for many genes and by the variability in both gene and sequence variants nomenclatures. We describe OSIRIS, a search tool that integrates different sources of information with the aim to retrieve literature about sequence variation of a gene. In addition, it provides a method to link a dbSNP entry with the articles referring to it. AVAILABILITY: OSIRIS is available for public use at http://ibi.imim.es/

Evaluation of the proacrosin/acrosin system and its mechanism of activation in human sperm extracts.

Acrosin is an acrosomal protease synthesized as a proenzyme and activated into beta-acrosin during the acrosome reaction. In the present study, a set of sensitive assays was developed to identify the proacrosin/acrosin system and to evaluate its activation pattern in human sperm extracts. Immunocytochemical analysis with monoclonal antibody (Mab) AcrC5F10 showed specific staining on the acrosome of permeabilized ejaculated and capacitated spermatozoa. Acrosome reaction was associated with a decrease in staining. AcrC5F10 specifically recognized a 55-kDa band (proacrosin) in Western immunoblots. Activation studies showed enzymatically active intermediates of 39 and 35 kDa after zymography. Immunoreactive bands of 52, 43, 34, 21-26 and 16 kDa were identified in the activation patterns developed with AcrC5F10. Activation was completely inhibited in the presence of 9 mM CaCl(2) or 100 mM benzamidine. A multiple sequence alignment revealed partial conservation of putative cleavage sites in the proacrosin sequence. The tests described allow the detection of human proacrosin in spermatozoa and sperm protein extracts, as well as the evaluation of the proenzyme activation pattern. They can be used to study the effect of inhibitors upon proenzyme activation. In addition, alterations in proacrosin activation in semen samples with abnormal acrosin enzymatic activity can be analyzed using these assays.