Genome Wide DNA Copy Number Analysis of Serous Type Ovarian Carcinomas Identifies Genetic Markers Predictive of Clinical Outcome

Ovarian cancer is the fifth leading cause of cancer death in women. Ovarian cancers display a high degree of complex genetic alterations involving many oncogenes and tumor suppressor genes. Analysis of the association between genetic alterations and clinical endpoints such as survival will lead to improved patient management via genetic stratification of patients into clinically relevant subgroups. In this study, we aim to define subgroups of high-grade serous ovarian carcinomas that differ with respect to prognosis and overall survival. Genome-wide DNA copy number alterations (CNAs) were measured in 72 clinically annotated, high-grade serous tumors using high-resolution oligonucleotide arrays. Two clinically annotated, independent cohorts were used for validation. Unsupervised hierarchical clustering of copy number data derived from the 72 patient cohort resulted in two clusters with significant difference in progression free survival (PFS) and a marginal difference in overall survival (OS). GISTIC analysis of the two clusters identified altered regions unique to each cluster. Supervised clustering of two independent large cohorts of high-grade serous tumors using the classification scheme derived from the two initial clusters validated our results and identified 8 genomic regions that are distinctly different among the subgroups. These 8 regions map to 8p21.3, 8p23.2, 12p12.1, 17p11.2, 17p12, 19q12, 20q11.21 and 20q13.12; and harbor potential oncogenes and tumor suppressor genes that are likely to be involved in the pathogenesis of ovarian carcinoma. We have identified a set of genetic alterations that could be used for stratification of high-grade serous tumors into clinically relevant treatment subgroups

Parallels between Pathogens and Gluten Peptides in Celiac Sprue

Pathogens are exogenous agents capable of causing disease in susceptible organisms. In celiac sprue, a disease triggered by partially hydrolyzed gluten peptides in the small intestine, the offending immunotoxins cannot replicate, but otherwise have many hallmarks of classical pathogens. First, dietary gluten and its peptide metabolites are ubiquitous components of the modern diet, yet only a small, genetically susceptible fraction of the human population contracts celiac sprue. Second, immunotoxic gluten peptides have certain unusual structural features that allow them to survive the harsh proteolytic conditions of the gastrointestinal tract and thereby interact extensively with the mucosal lining of the small intestine. Third, they invade across epithelial barriers intact to access the underlying gut-associated lymphoid tissue. Fourth, they possess recognition sequences for selective modification by an endogenous enzyme, transglutaminase 2, allowing for in situ activation to a more immunotoxic form via host subversion. Fifth, they precipitate a T cell–mediated immune reaction comprising both innate and adaptive responses that causes chronic inflammation of the small intestine. Sixth, complete elimination of immunotoxic gluten peptides from the celiac diet results in remission, whereas reintroduction of gluten in the diet causes relapse. Therefore, in analogy with antibiotics, orally administered proteases that reduce the host's exposure to the immunotoxin by accelerating gluten peptide destruction have considerable therapeutic potential. Last but not least, notwithstanding the power of in vitro methods to reconstitute the essence of the immune response to gluten in a celiac patient, animal models for the disease, while elusive, are likely to yield fundamentally new systems-level insights

ViromeScan: a new tool for metagenomic viral community profiling

BACKGROUND: Bioinformatics tools available for metagenomic sequencing analysis are principally devoted to the identification of microorganisms populating an ecological niche, but they usually do not consider viruses. Only some software have been designed to profile the viral sequences, however they are not efficient in the characterization of viruses in the context of complex communities, like the intestinal microbiota, containing bacteria, archeabacteria, eukaryotic microorganisms and viruses. In any case, a comprehensive description of the host-microbiota interactions can not ignore the profile of eukaryotic viruses within the virome, as viruses are definitely critical for the regulation of the host immunophenotype. RESULTS: ViromeScan is an innovative metagenomic analysis tool that characterizes the taxonomy of the virome directly from raw data of next-generation sequencing. The tool uses hierarchical databases for eukaryotic viruses to unambiguously assign reads to viral species more accurately and >1000 fold faster than other existing approaches. We validated ViromeScan on synthetic microbial communities and applied it on metagenomic samples of the Human Microbiome Project, providing a sensitive eukaryotic virome profiling of different human body sites. CONCLUSIONS: ViromeScan allows the user to explore and taxonomically characterize the virome from metagenomic reads, efficiently denoising samples from reads of other microorganisms. This implies that users can fully characterize the microbiome, including bacteria and viruses, by shotgun metagenomic sequencing followed by different bioinformatic pipelines. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-016-2446-3) contains supplementary material, which is available to authorized users