Characterizing genomic alterations in cancer by complementary functional associations.

Systematic efforts to sequence the cancer genome have identified large numbers of mutations and copy number alterations in human cancers. However, elucidating the functional consequences of these variants, and their interactions to drive or maintain oncogenic states, remains a challenge in cancer research. We developed REVEALER, a computational method that identifies combinations of mutually exclusive genomic alterations correlated with functional phenotypes, such as the activation or gene dependency of oncogenic pathways or sensitivity to a drug treatment. We used REVEALER to uncover complementary genomic alterations associated with the transcriptional activation of β-catenin and NRF2, MEK-inhibitor sensitivity, and KRAS dependency. REVEALER successfully identified both known and new associations, demonstrating the power of combining functional profiles with extensive characterization of genomic alterations in cancer genomes

Tumor innate immunity primed by specific interferon-stimulated endogenous retroviruses.

Mesenchymal tumor subpopulations secrete pro-tumorigenic cytokines and promote treatment resistance1-4. This phenomenon has been implicated in chemorefractory small cell lung cancer and resistance to targeted therapies5-8, but remains incompletely defined. Here, we identify a subclass of endogenous retroviruses (ERVs) that engages innate immune signaling in these cells. Stimulated 3 prime antisense retroviral coding sequences (SPARCS) are oriented inversely in 3' untranslated regions of specific genes enriched for regulation by STAT1 and EZH2. Derepression of these loci results in double-stranded RNA generation following IFN-γ exposure due to bi-directional transcription from the STAT1-activated gene promoter and the 5' long terminal repeat of the antisense ERV. Engagement of MAVS and STING activates downstream TBK1, IRF3, and STAT1 signaling, sustaining a positive feedback loop. SPARCS induction in human tumors is tightly associated with major histocompatibility complex class 1 expression, mesenchymal markers, and downregulation of chromatin modifying enzymes, including EZH2. Analysis of cell lines with high inducible SPARCS expression reveals strong association with an AXL/MET-positive mesenchymal cell state. While SPARCS-high tumors are immune infiltrated, they also exhibit multiple features of an immune-suppressed microenviroment. Together, these data unveil a subclass of ERVs whose derepression triggers pathologic innate immune signaling in cancer, with important implications for cancer immunotherapy

Unsupervised Analysis of Classical Biomedical Markers: Robustness and Medical Relevance of Patient Clustering Using Bioinformatics Tools

Motivation: It has been proposed that clustering clinical markers, such as blood test results, can be used to stratify patients. However, the robustness of clusters formed with this approach to data pre-processing and clustering algorithm choices has not been evaluated, nor has clustering reproducibility. Here, we made use of the NHANES survey to compare clusters generated with various combinations of pre-processing and clustering algorithms, and tested their reproducibility in two separate samples. Method: Values of 44 biomarkers and 19 health/life style traits were extracted from the National Health and Nutrition Examination Survey (NHANES). The 1999–2002 survey was used for training, while data from the 2003–2006 survey was tested as a validation set. Twelve combinations of pre-processing and clustering algorithms were applied to the training set. The quality of the resulting clusters was evaluated both by considering their properties and by comparative enrichment analysis. Cluster assignments were projected to the validation set (using an artificial neural network) and enrichment in health/life style traits in the resulting clusters was compared to the clusters generated from the original training set. Results: The clusters obtained with different pre-processing and clustering combinations differed both in terms of cluster quality measures and in terms of reproducibility of enrichment with health/life style properties. Z-score normalization, for example, dramatically improved cluster quality and enrichments, as compared to unprocessed data, regardless of the clustering algorithm used. Clustering diabetes patients revealed a group of patients enriched with retinopathies. This coul

A High-Throughput Screen Identifies a New Natural Product with Broad-Spectrum Antibacterial Activity

Due to the inexorable invasion of our hospitals and communities by drug-resistant bacteria, there is a pressing need for novel antibacterial agents. Here we report the development of a sensitive and robust but low-tech and inexpensive high-throughput metabolic screen for novel antibiotics. This screen is based on a colorimetric assay of pH that identifies inhibitors of bacterial sugar fermentation. After validation of the method, we screened over 39,000 crude extracts derived from organisms that grow in the diverse ecosystems of Costa Rica and identified 49 with reproducible antibacterial effects. An extract from an endophytic fungus was further characterized, and this led to the discovery of three novel natural products. One of these, which we named mirandamycin, has broad-spectrum antibacterial activity against Escherichia coli, Pseudomonas aeruginosa, Vibrio cholerae, methicillin-resistant Staphylococcus aureus, and Mycobacterium tuberculosis. This demonstrates the power of simple high throughput screens for rapid identification of new antibacterial agents from environmental samples

Preventable hospitalization and access to primary health care in an area of Southern Italy

<p>Abstract</p> <p>Background</p> <p>Ambulatory care-sensitive conditions (ACSC), such as hypertension, diabetes, chronic heart failure, chronic obstructive pulmonary disease and asthma, are conditions that can be managed with timely and effective outpatient care reducing the need of hospitalization. Avoidable hospitalizations for ACSC have been used to assess access, quality and performance of the primary care delivery system. The aims of this study were to quantify the proportion of avoidable hospital admissions for ACSCs, to identify the related patient's socio-demographic profile and health conditions, to assess the relationship between the primary care access characteristics and preventable hospitalizations, and the usefulness of avoidable hospitalizations for ACSCs to monitor the effectiveness of primary health care.</p> <p>Methods</p> <p>A random sample of 520 medical records of patients admitted to medical wards (Cardiology, Internal Medicine, Pneumology, Geriatrics) of a non-teaching acute care 717-bed hospital located in Catanzaro (Italy) were reviewed.</p> <p>Results</p> <p>A total of 31.5% of the hospitalizations in the sample were judged to be preventable. Of these, 40% were for congestive heart failure, 23.2% for chronic obstructive pulmonary disease, 13.5% for angina without procedure, 8.4% for hypertension, and 7.1% for bacterial pneumonia. Preventable hospitalizations were significantly associated to age and sex since they were higher in older patients and in males. The proportion of patients who had a preventable hospitalization significantly increased with regard to the number of hospital admissions in the previous year and to the number of patients for each primary care physician (PCP), with lower number of PCP accesses and PCP medical visits in the previous year, with less satisfaction about PCP health services, and, finally, with worse self-reported health status and shorter length of hospital stay.</p> <p>Conclusion</p> <p>The findings from this study add to the evidence and the urgency of developing and implementing effective interventions to improve delivery of health care at the community level and provided support to the usefulness of avoidable hospitalizations for ACSCs to monitor this process.</p

Using Pre-existing Microarray Datasets to Increase Experimental Power: Application to Insulin Resistance

Although they have become a widely used experimental technique for identifying differentially expressed (DE) genes, DNA microarrays are notorious for generating noisy data. A common strategy for mitigating the effects of noise is to perform many experimental replicates. This approach is often costly and sometimes impossible given limited resources; thus, analytical methods are needed which increase accuracy at no additional cost. One inexpensive source of microarray replicates comes from prior work: to date, data from hundreds of thousands of microarray experiments are in the public domain. Although these data assay a wide range of conditions, they cannot be used directly to inform any particular experiment and are thus ignored by most DE gene methods. We present the SVD Augmented Gene expression Analysis Tool (SAGAT), a mathematically principled, data-driven approach for identifying DE genes. SAGAT increases the power of a microarray experiment by using observed coexpression relationships from publicly available microarray datasets to reduce uncertainty in individual genes' expression measurements. We tested the method on three well-replicated human microarray datasets and demonstrate that use of SAGAT increased effective sample sizes by as many as 2.72 arrays. We applied SAGAT to unpublished data from a microarray study investigating transcriptional responses to insulin resistance, resulting in a 50% increase in the number of significant genes detected. We evaluated 11 (58%) of these genes experimentally using qPCR, confirming the directions of expression change for all 11 and statistical significance for three. Use of SAGAT revealed coherent biological changes in three pathways: inflammation, differentiation, and fatty acid synthesis, furthering our molecular understanding of a type 2 diabetes risk factor. We envision SAGAT as a means to maximize the potential for biological discovery from subtle transcriptional responses, and we provide it as a freely available software package that is immediately applicable to any human microarray study

Alternative Oxidase Mediates Pathogen Resistance in Paracoccidioides brasiliensis Infection

Thermally dimorphic pathogenic fungi are responsible for potentially life-threatening diseases of immunocompetent and immunocompromised individuals. These microorganisms grow as conidia-producing mycelia in the environment, which when inhaled by the host convert to the pathogenic yeast form at 37°C. During adaptation and growth, fungi interact with host immune cells and must cope with defense mechanisms such as imposed-oxidative stress (e.g., reactive oxygen species; ROS). Alternative oxidase (AOX) is an enzyme recently implicated in the reduction of ROS production by the mitochondria when triggered by external stimuli, such as temperature and ROS. During this work we have evaluated the relevance of AOX during infection with Paracoccidioides brasiliensis, the etiological agent of one of the most prevalent mycoses in Latin America, paracoccidioidomycosis. We show that PbAOX gene expression is stimulated after interaction with alveolar macrophages or in the presence of H2O2 and is essential for survival against fungicidal activity of both the immune cells and the ROS compound. Moreover, decreasing PbAOX gene expression in P. brasiliensis led to increased survival of infected mice. Altogether, our data supports a relevant role for AOX in the virulence of P. brasiliensis

Necdin, a p53-Target Gene, Is an Inhibitor of p53-Mediated Growth Arrest

In vitro, cellular immortalization and transformation define a model for multistep carcinogenesis and current ongoing challenges include the identification of specific molecular events associated with steps along this oncogenic pathway. Here, using NIH3T3 cells, we identified transcriptionally related events associated with the expression of Polyomavirus Large-T antigen (PyLT), a potent viral oncogene. We propose that a subset of these alterations in gene expression may be related to the early events that contribute to carcinogenesis. The proposed tumor suppressor Necdin, known to be regulated by p53, was within a group of genes that was consistently upregulated in the presence of PyLT. While Necdin is induced following p53 activation with different genotoxic stresses, Necdin induction by PyLT did not involve p53 activation or the Rb-binding site of PyLT. Necdin depletion by shRNA conferred a proliferative advantage to NIH3T3 and PyLT-expressing NIH3T3 (NIHLT) cells. In contrast, our results demonstrate that although overexpression of Necdin induced a growth arrest in NIH3T3 and NIHLT cells, a growing population rapidly emerged from these arrested cells. This population no longer showed significant proliferation defects despite high Necdin expression. Moreover, we established that Necdin is a negative regulator of p53-mediated growth arrest induced by nutlin-3, suggesting that Necdin upregulation could contribute to the bypass of a p53-response in p53 wild type tumors. To support this, we characterized Necdin expression in low malignant potential ovarian cancer (LMP) where p53 mutations rarely occur. Elevated levels of Necdin expression were observed in LMP when compared to aggressive serous ovarian cancers. We propose that in some contexts, the constitutive expression of Necdin could contribute to cancer promotion by delaying appropriate p53 responses and potentially promote genomic instability

Planetary Rings

Planetary rings are the only nearby astrophysical disks, and the only disks that have been investigated by spacecraft. Although there are significant differences between rings and other disks, chiefly the large planet/ring mass ratio that greatly enhances the flatness of rings (aspect ratios as small as 1e-7), understanding of disks in general can be enhanced by understanding the dynamical processes observed at close-range and in real-time in planetary rings. We review the known ring systems of the four giant planets, as well as the prospects for ring systems yet to be discovered. We then review planetary rings by type. The main rings of Saturn comprise our system's only dense broad disk and host many phenomena of general application to disks including spiral waves, gap formation, self-gravity wakes, viscous overstability and normal modes, impact clouds, and orbital evolution of embedded moons. Dense narrow rings are the primary natural laboratory for understanding shepherding and self-stability. Narrow dusty rings, likely generated by embedded source bodies, are surprisingly found to sport azimuthally-confined arcs. Finally, every known ring system includes a substantial component of diffuse dusty rings. Planetary rings have shown themselves to be useful as detectors of planetary processes around them, including the planetary magnetic field and interplanetary impactors as well as the gravity of nearby perturbing moons. Experimental rings science has made great progress in recent decades, especially numerical simulations of self-gravity wakes and other processes but also laboratory investigations of coefficient of restitution and spectroscopic ground truth. The age of self-sustained ring systems is a matter of debate; formation scenarios are most plausible in the context of the early solar system, while signs of youthfulness indicate at least that rings have never been static phenomena.Comment: 82 pages, 34 figures. Final revision of general review to be published in "Planets, Stars and Stellar Systems", P. Kalas and L. French (eds.), Springer (http://refworks.springer.com/sss