Alfredo Pulvirenti

miRandola: Extracellular Circulating MicroRNAs Database

MicroRNAs are small noncoding RNAs that play an important role in the regulation of various biological processes through their interaction with cellular messenger RNAs. They are frequently dysregulated in cancer and have shown great potential as tissue-based markers for cancer classification and prognostication. microRNAs are also present in extracellular human body fluids such as serum, plasma, saliva, and urine. Most of circulating microRNAs are present in human plasma and serum cofractionate with the Argonaute2 (Ago2) protein. However, circulating microRNAs have been also found in membrane-bound vesicles such as exosomes. Since microRNAs circulate in the bloodstream in a highly stable, extracellular form, they may be used as blood-based biomarkers for cancer and other diseases. A knowledge base of extracellular circulating miRNAs is a fundamental tool for biomedical research. In this work, we present miRandola, a comprehensive manually curated classification of extracellular circulating miRNAs. miRandola is connected to miRò, the miRNA knowledge base, allowing users to infer the potential biological functions of circulating miRNAs and their connections with phenotypes. The miRandola database contains 2132 entries, with 581 unique mature miRNAs and 21 types of samples. miRNAs are classified into four categories, based on their extracellular form: miRNA-Ago2 (173 entries), miRNA-exosome (856 entries), miRNA-HDL (20 entries) and miRNA-circulating (1083 entries). miRandola is available online at: http://atlas.dmi.unict.it/mirandola/index.html.

Integrated microRNA and mRNA signatures associated with survival in triple negative breast cancer.

Triple negative breast cancer (TNBC) is a heterogeneous disease at the molecular, pathologic and clinical levels. To stratify TNBCs, we determined microRNA (miRNA) expression profiles, as well as expression profiles of a cancer-focused mRNA panel, in tumor, adjacent non-tumor (normal) and lymph node metastatic lesion (mets) tissues, from 173 women with TNBCs; we linked specific miRNA signatures to patient survival and used miRNA/mRNA anti-correlations to identify clinically and genetically different TNBC subclasses. We also assessed miRNA signatures as potential regulators of TNBC subclass-specific gene expression networks defined by expression of canonical signal pathways. Tissue specific miRNAs and mRNAs were identified for normal vs tumor vs mets comparisons. miRNA signatures correlated with prognosis were identified and predicted anti-correlated targets within the mRNA profile were defined. Two miRNA signatures (miR-16, 155, 125b, 374a and miR-16, 125b, 374a, 374b, 421, 655, 497) predictive of overall survival (P = 0.05) and distant-disease free survival (P = 0.009), respectively, were identified for patients 50 yrs of age or younger. By multivariate analysis the risk signatures were independent predictors for overall survival and distant-disease free survival. mRNA expression profiling, using the cancer-focused mRNA panel, resulted in clustering of TNBCs into 4 molecular subclasses with different expression signatures anti-correlated with the prognostic miRNAs. Our findings suggest that miRNAs play a key role in triple negative breast cancer through their ability to regulate fundamental pathways such as: cellular growth and proliferation, cellular movement and migration, Extra Cellular Matrix degradation. The results define miRNA expression signatures that characterize and contribute to the phenotypic diversity of TNBC and its metastasis.

The neurology of coeliac disease in childhood: what is the evidence? A systematic review and meta‐analysis

Aim  The aim of this article was to review and conduct a meta‐analysis of the paediatric literature on the neurology of coeliac disease.

Cellular and molecular effects of protons: Apoptosis induction and potential implications for cancer therapy

Due to their ballistic precision, apoptosis induction by protons could be a strategy to specifically eliminate neoplastic cells. To characterize the cellular and molecular effects of these hadrons, we performed dose-response and time-course experiments by exposing different cell lines (PC3, Ca301D, MCF7) to increasing doses of protons and examining them with FACS, RT-PCR, and electron spin resonance (ESR). Irradiation with a dose of 10 Gy of a 26,7 Mev proton beam altered cell structures such as membranes, caused DNA double strand breaks, and significantly increased intracellular levels of hydroxyl ions, are active oxygen species (ROS). This modified the transcriptome of irradiated cells, activated the mitochondrial (intrinsic) pathway of apoptosis, and resulted in cycle arrest at the G2/M boundary. The number of necrotic cells within the irradiated cell population did not significantly increase with respect to the controls. The effects of irradiation with 20 Gy were qualitatively as well as quantitatively similar, but exposure to 40 Gy caused massive necrosis. Similar experiments with photons demonstrated that they induce apoptosis in a significantly lower number of cells and in a temporally delayed manner. These data advance our knowledge on the cellular and molecular effects of proton irradiation and could be useful for improving current hadrontherapy protocols.

SIGMA: A SET-COVER-BASED INEXACT GRAPH MATCHING ALGORITHM ∗

Network querying is a growing domain with vast applications ranging from screening compounds against a database of known molecules to matching sub-networks across species. Graph indexing is a powerful method for searching a large database of graphs. Most graph indexing methods to date tackle the exact matching (isomorphism) problem, limiting their applicability to specific instances in which such matches exist. Here we provide a novel graph indexing method to cope with the more general, inexact matching problem. Our method, SIGMA, builds on approximating a variant of the set-cover problem that concerns overlapping multi-sets. We extensively test our method and compare it to a baseline method and to the state-of-the-art Grafil. We show that SIGMA outperforms both, providing higher pruning power in all the tested scenarios.

Variability in the Incidence of miRNAs and Genes in Fragile Sites and the Role of Repeats and CpG Islands in the Distribution of Genetic Material

Background Chromosomal fragile sites are heritable specific loci especially prone to breakage. Some of them are associated with human genetic disorders and several studies have demonstrated their importance in genome instability in cancer. MicroRNAs (miRNAs) are small non-coding RNAs responsible of post-transcriptional gene regulation and their involvement in several diseases such as cancer has been widely demonstrated. The altered expression of miRNAs is sometimes due to chromosomal rearrangements and epigenetic events, thus it is essential to study miRNAs in the context of their genomic locations, in order to find significant correlations between their aberrant expression and the phenotype. Principal Findings Here we use statistical models to study the incidence of human miRNA genes on fragile sites and their association with cancer-specific translocation breakpoints, repetitive elements, and CpG islands. Our results show that, on average, fragile sites are denser in miRNAs and also in protein coding genes. However, the distribution of miRNAs and protein coding genes in fragile versus non-fragile sites depends on chromosome. We find also a positive correlation between fragility and repeats, and between miRNAs and CpG islands. Conclusion Our results show that the relationship between site fragility and miRNA density is far more complex than previously thought. For example, we find that protein coding genes seem to be following similar patterns as miRNAs, if considered their overall distribution. However, once we allow for differences at the chromosome level in our statistical analysis, we find that distribution of miRNA and protein coding genes in fragile sites is very different from that of miRNA. This is a novel result that we believe may help discover new potential correlations between the localization of miRNAs and their crucial role in biological processes and in the development of diseases.

Tools and collaborative environments for bioinformatics research

Advanced research requires intensive interaction among a multitude of actors, often possessing different expertise and usually working at a distance from each other. The field of collaborative research aims to establish suitable models and technologies to properly support these interactions. In this article, we first present the reasons for an interest of Bioinformatics in this context by also suggesting some research domains that could benefit from collaborative research. We then review the principles and some of the most relevant applications of social networking, with a special attention to networks supporting scientific collaboration, by also highlighting some critical issues, such as identification of users and standardization of formats. We then introduce some systems for collaborative document creation, including wiki systems and tools for ontology development, and review some of the most interesting biological wikis. We also review the principles of Collaborative Development Environments for software and show some examples in Bioinformatics. Finally, we present the principles and some examples of Learning Management Systems. In conclusion, we try to devise some of the goals to be achieved in the short term for the exploitation of these technologies.

Acute Disseminated Encephalomyelitis: A Long-Term Prospective Study and Meta-Analysis

BACKGROUND There are only a few series in the literature on acute disseminated encephalomyelitis (ADEM) in children. OBJECTIVES AND METHODS the aims of this study were to perform (i) a prospective clinical/imaging study (1992-2009) on ADEM in children consecutively referred to our institution in Catania, Italy, and (ii) to undertake a systematic review and meta-analysis of published ADEM pediatric cohorts (>10 cases). RESULTS We identified 17 patients with ADEM (incidence <10 years of age=1.1 per 100 000 person-years). 15 previously published cohorts were compared with our cohort: (i) systematically reviewed (750 cases); and (ii) meta-analyzed (492/750 cases). The 17 patients had the following characteristics: (a) male-to-female ratio, 1.4 (vs. 1.2-1.3 in previous cohorts); (b) mean age at presentation, 3.6 years (vs. 7.1 years in previous cohorts); (c) specific preceding triggering factor, 88% (vs. 69-79% in previous cohorts); (d) the most common initial signs were ataxia, seizures, headache, and thalamic syndrome; (e) brain imaging revealed >3 lesions in 100% (vs. 92% in previous cohorts); (f) the outcome was good in 94% (vs. 70-75% in previous cohorts); and (g) 12% relapsed once (vs. 18% in previous cohorts). CONCLUSIONS ADEM is generally a benign condition that mosly affects boys more than girls and rarely recurs.

Prevalence and Natural History of Potential Celiac Disease in At-Family-Risk Infants Prospectively Investigated from Birth

OBJECTIVE To evaluate the frequency and the natural history of potential (serology positive/Marsh 0-1 histology) celiac disease (CD) in children with a family risk of CD and factors associated with potential instead of overt (serology positive/Marsh 2-3 histology) CD expression. STUDY DESIGN Two-year follow-up study of 96 children (57 females; mean age: 29 ± 12 months) prospectively investigated from birth with: (1) a CD-affected first-degree relative; (2) positivity of serum IgA anti-tissue transglutaminase (tTG) or IgG antigliadin and IgA deficiency; and (3) the results of small intestinal biopsy. Children with potential CD were advised to remain on a gluten containing diet, repeat the celiac antibodies every 6 months, and to have an intestinal biopsy performed in case of persistently high anti-tTG level. Factors discriminating between potential and overt CD were analyzed by decision tree analysis based on the C4.5 algorithm. RESULTS Twenty-four children had potential and 72 overt CD. The stronger predictors of potential CD were lack of symptoms, anti-tTG level lower than 11-fold the upper normal limit, age lower than 24 months, and breastfeeding longer than 8 months. Eighteen out of 21 (86%) patients with potential CD continuing a gluten-containing diet became antibody negative, 1/21 (5%) developed overt CD, and 2/21 (9%) had fluctuating antibodies levels after 2 years. CONCLUSIONS The prevalence of potential CD and the percentage of short-term loss of CD-related-antibodies are high in infants at-family-risk for CD. In symptomless children with a positive celiac serology, the decision of performing an intestinal biopsy should be preceded by a period of repeated serological testing.

SING: Subgraph search In Non-homogeneous Graphs

BackgroundFinding the subgraphs of a graph database that are isomorphic to a given query graph has practical applications in several fields, from cheminformatics to image understanding. Since subgraph isomorphism is a computationally hard problem, indexing techniques have been intensively exploited to speed up the process. Such systems filter out those graphs which cannot contain the query, and apply a subgraph isomorphism algorithm to each residual candidate graph. The applicability of such systems is limited to databases of small graphs, because their filtering power degrades on large graphs.ResultsIn this paper, SING (Subgraph search In Non-homogeneous Graphs), a novel indexing system able to cope with large graphs, is presented. The method uses the notion of feature, which can be a small subgraph, subtree or path. Each graph in the database is annotated with the set of all its features. The key point is to make use of feature locality information. This idea is used to both improve the filtering performance and speed up the subgraph isomorphism task.ConclusionsExtensive tests on chemical compounds, biological networks and synthetic graphs show that the proposed system outperforms the most popular systems in query time over databases of medium and large graphs. Other specific tests show that the proposed system is effective for single large graphs.