Gene expression meta-analysis supports existence of molecular apocrine breast cancer with a role for androgen receptor and implies interactions with ErbB family

<p>Abstract</p> <p>Background</p> <p>Pathway discovery from gene expression data can provide important insight into the relationship between signaling networks and cancer biology. Oncogenic signaling pathways are commonly inferred by comparison with signatures derived from cell lines. We use the Molecular Apocrine subtype of breast cancer to demonstrate our ability to infer pathways directly from patients' gene expression data with pattern analysis algorithms.</p> <p>Methods</p> <p>We combine data from two studies that propose the existence of the Molecular Apocrine phenotype. We use quantile normalization and XPN to minimize institutional bias in the data. We use hierarchical clustering, principal components analysis, and comparison of gene signatures derived from Significance Analysis of Microarrays to establish the existence of the Molecular Apocrine subtype and the equivalence of its molecular phenotype across both institutions. Statistical significance was computed using the Fasano & Franceschini test for separation of principal components and the hypergeometric probability formula for significance of overlap in gene signatures. We perform pathway analysis using LeFEminer and Backward Chaining Rule Induction to identify a signaling network that differentiates the subset. We identify a larger cohort of samples in the public domain, and use Gene Shaving and Robust Bayesian Network Analysis to detect pathways that interact with the defining signal.</p> <p>Results</p> <p>We demonstrate that the two separately introduced ER^-breast cancer subsets represent the same tumor type, called Molecular Apocrine breast cancer. LeFEminer and Backward Chaining Rule Induction support a role for AR signaling as a pathway that differentiates this subset from others. Gene Shaving and Robust Bayesian Network Analysis detect interactions between the AR pathway, EGFR trafficking signals, and ErbB2.</p> <p>Conclusion</p> <p>We propose criteria for meta-analysis that are able to demonstrate statistical significance in establishing molecular equivalence of subsets across institutions. Data mining strategies used here provide an alternative method to comparison with cell lines for discovering seminal pathways and interactions between signaling networks. Analysis of Molecular Apocrine breast cancer implies that therapies targeting AR might be hampered if interactions with ErbB family members are not addressed.</p

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency–Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research

Colloidal crystal order and structure revealed by tabletop extreme ultraviolet scattering and coherent diffractive imaging

Colloidal crystals with specific electronic, optical, magnetic, vibrational properties, can be rationally designed by controlling fundamental parameters such as chemical composition, scale, periodicity and lattice symmetry. In particular, silica nanospheres -which assemble to form colloidal crystals- are ideal for this purpose, because of the ability to infiltrate their templates with semiconductors or metals. However characterization of these crystals is often limited to techniques such as grazing incidence small-angle scattering that provide only global structural information and also often require synchrotron sources. Here we demonstrate small-angle Bragg scattering from nanostructured materials using a tabletop-scale setup based on high-harmonic generation, to reveal important information about the local order of nanosphere grains, separated by grain boundaries and discontinuities. We also apply full-field quantitative ptychographic imaging to visualize the extended structure of a silica close-packed nanosphere multilayer, with thickness information encoded in the phase. These combined techniques allow us to simultaneously characterize the silica nanospheres size, their symmetry and distribution within single colloidal crystal grains, the local arrangement of nearest-neighbor grains, as well as to quantitatively determine the number of layers within the sample. Key to this advance is the good match between the high harmonic wavelength used (13.5nm) and the high transmission, high scattering efficiency, and low sample damage of the silica colloidal crystal at this wavelength. As a result, the relevant distances in the sample - namely, the interparticle distance (≈124nm) and the colloidal grains local arrangement (≈1μm) - can be investigated with Bragg coherent EUV scatterometry and ptychographic imaging within the same experiment simply by tuning the EUV spot size at the sample plane (5μm and 15μm respectively). In addition, the high spatial coherence of high harmonics light, combined with advances in imaging techniques, makes it possible to image near-periodic structures quantitatively and nondestructively, and enables the observation of the extended order of quasi-periodic colloidal crystals, with a spatial resolution better than 20nm. In the future, by harnessing the high time-resolution of tabletop high harmonics, this technique can be extended to dynamically image the three-dimensional electronic, magnetic, and transport properties of functional nanosystems

Russian vaccines against especially dangerous bacterial pathogens

In response to the epidemiological situation, live attenuated or killed vaccines against anthrax, brucellosis, cholera, glanders, plague and tularemia were developed and used for immunization of at-risk populations in the Former Soviet Union. Certain of these vaccines have been updated and currently they are used on a selective basis, mainly for high risk occupations, in the Russian Federation. Except for anthrax and cholera these vaccines currently are the only licensed products available for protection against the most dangerous bacterial pathogens. Development of improved formulations and new products is ongoing

A meta-analysis of gene expression quantitative trait loci in brain

Current catalogs of brain expression quantitative trait loci (eQTL) are incomplete and the findings do not replicate well across studies. All existing cortical eQTL studies are small and emphasize the need for a meta-analysis. We performed a meta-analysis of 424 brain samples across five studies to identify regulatory variants influencing gene expression in human cortex. We identified 3584 genes in autosomes and chromosome X with false discovery rate q<0.05 whose expression was significantly associated with DNA sequence variation. Consistent with previous eQTL studies, local regulatory variants tended to occur symmetrically around transcription start sites and the effect was more evident in studies with large sample sizes. In contrast to random SNPs, we observed that significant eQTLs were more likely to be near 5'-untranslated regions and intersect with regulatory features. Permutation-based enrichment analysis revealed that SNPs associated with schizophrenia and bipolar disorder were enriched among brain eQTLs. Genes with significant eQTL evidence were also strongly associated with diseases from OMIM (Online Mendelian Inheritance in Man) and the NHGRI (National Human Genome Research Institute) genome-wide association study catalog. Surprisingly, we found that a large proportion (28%) of ~1000 autosomal genes encoding proteins needed for mitochondrial structure or function were eQTLs (enrichment P-value=1.3 × 10(−)(9)), suggesting a potential role for common genetic variation influencing the robustness of energy supply in brain and a possible role in the etiology of some psychiatric disorders. These systematically generated eQTL information should be a valuable resource in determining the functional mechanisms of brain gene expression and the underlying biology of associations with psychiatric disorders