Functional Expression of TWEAK and the Receptor Fn14 in Human Malignant Ovarian Tumors: Possible Implication for Ovarian Tumor Intervention

The aim of this current study was to investigate the expression of the tumor necrosis factor (TNF)-like weak inducer of apoptosis (TWEAK) and its receptor fibroblast growth factor-inducible 14 (Fn14) in human malignant ovarian tumors, and test TWEAK’s potential role on tumor progression in cell models in-vitro. Using immunohistochemistry (IHC), we found that TWEAK and its receptor Fn14 were expressed in human malignant ovarian tumors, but not in normal ovarian tissues or in borderline/benign epithelial ovarian tumors. High levels of TWEAK expression was detected in the majority of malignant tumors (36 out of 41, 87.80%). Similarly, 35 out of 41 (85.37%) malignant ovarian tumors were Fn14 positive. In these malignant ovarian tumors, however, TWEAK/Fn14 expression was not corrected with patients’ clinical subtype/stages or pathological features. In vitro, we demonstrated that TWEAK only inhibited ovarian cancer HO-8910PM cell proliferation in combination with tumor necrosis factor-α (TNF-α), whereas either TWEAK or TNF-α alone didn’t affect HO-8910PM cell growth. TWEAK promoted TNF-α production in cultured THP-1 macrophages. Meanwhile, conditioned media from TWEAK-activated macrophages inhibited cultured HO-8910PM cell proliferation and invasion. Further, TWEAK increased monocyte chemoattractant protein-1 (MCP-1) production in cultured HO-8910PM cells to possibly recruit macrophages. Our results suggest that TWEAK/Fn14, by activating macrophages, could be ovarian tumor suppressors. The unique expression of TWEAK/Fn14 in malignant tumors indicates that it might be detected as a malignant ovarian tumor marker.     

Proteins Related to the Type I Secretion System Are Associated with Secondary SecA_DEAD Domain Proteins in Some Species of Planctomycetes,Verrucomicrobia, Proteobacteria,Nitrospirae and Chlorobi

A number of bacteria belonging to the PVC (Planctomycetes-Verrucomicrobia-Chlamydiae) super-phylum contain unusual ribosome-bearing intracellular membranes. The evolutionary origins and functions of these membranes are unknown. Some proteins putatively associated with the presence of intracellular membranes in PVC bacteria contain signal peptides. Signal peptides mark proteins for translocation across the cytoplasmic membrane in prokaryotes, and the membrane of the endoplasmic reticulum in eukaryotes, by highly conserved Sec machinery. This suggests that proteins might be targeted to intracellular membranes in PVC bacteria via the Sec pathway. Here, we show that canonical signal peptides are significantly over-represented in proteins preferentially present in PVC bacteria possessing intracellular membranes, indicating involvement of Sec translocase in their cellular targeting. We also characterized Sec proteins using comparative genomics approaches, focusing on the PVC super-phylum. While we were unable to detect unique changes in Sec proteins conserved among membrane-bearing PVC species, we identified (1) SecA ATPase domain re-arrangements in some Planctomycetes, and (2) secondary SecA_DEAD domain proteins in the genomes of some Planctomycetes, Verrucomicrobia, Proteobacteria, Nitrospirae and Chlorobi. This is the first report of potentially duplicated SecA in Gram-negative bacteria. The phylogenetic distribution of secondary SecA_DEAD domain proteins suggests that the presence of these proteins is not related to the occurrence of PVC endomembranes. Further genomic analysis showed that secondary SecA_DEAD domain proteins are located within genomic neighborhoods that also encode three proteins possessing domains specific for the Type I secretion system.     

Using the Gene Ontology for Microarray Data Mining: A Comparison of Methods and Application to Age Effects in Human Prefrontal Cortex

One of the challenges in the analysis of gene expression data is placing the results in the context of other data available about genes and their relationships to each other. Here, we approach this problem in the study of gene expression changes associated with age in two areas of the human prefrontal cortex, comparing two computational methods. The first method, "overrepresentation analysis" (ORA), is based on statistically evaluating the fraction of genes in a particular gene ontology class found among the set of genes showing age-related changes in expression. The second method, "functional class scoring" (FCS), examines the statistical distribution of individual gene scores among all genes in the gene ontology class and does not involve an initial gene selection step. We find that FCS yields more consistent results than ORA, and the results of ORA depended strongly on the gene selection threshold. Our findings highlight the utility of functional class scoring for the analysis of complex expression data sets and emphasize the advantage of considering all available genomic information rather than sets of genes that pass a predetermined "threshold of significance."     

Fronto-Central Theta Oscillations Are Related to Oscillations in Saccadic Response Times (SRT): An EEG and Behavioral Data Analysis

The phase reset hypothesis states that the phase of an ongoing neural oscillation, reflecting periodic fluctuations in neural activity between states of high and low excitability, can be shifted by the occurrence of a sensory stimulus so that the phase value become highly constant across trials (Schroeder et al., 2008). From EEG/MEG studies it has been hypothesized that coupled oscillatory activity in primary sensory cortices regulates multi sensory processing (Senkowski et al. 2008). We follow up on a study in which evidence of phase reset was found using a purely behavioral paradigm by including also EEG measures. In this paradigm, presentation of an auditory accessory stimulus was followed by a visual target with a stimulus-onset asynchrony (SOA) across a range from 0 to 404 ms in steps of 4 ms. This fine-grained stimulus presentation allowed us to do a spectral analysis on the mean SRT as a function of the SOA, which revealed distinct peak spectral components within a frequency range of 6 to 11 Hz with a modus of 7 Hz. The EEG analysis showed that the auditory stimulus caused a phase reset in 7-Hz brain oscillations in a widespread set of channels. Moreover, there was a significant difference in the average phase at which the visual target stimulus appeared between slow and fast SRT trials. This effect was evident in three different analyses, and occurred primarily in frontal and central electrodes.     

Issues Related to Chemical Analysis,Data Reporting,and Use: Implications for Human Health Risk Assessment of PCBs and PBDEs in Fish Tissue

Recent reports in the scientific literature and the media, related to elevated levels of polychlorinated biphenyls (PCBs) and polybrominated diethyl ethers (PBDEs) in farmed and wild salmon have had significant impacts on public opinion and consumer behavior, influencing the sales of farmed salmon in North America and Europe. The assessment of contaminants in fatty fish, an important source of omega-3 fatty acids, is therefore an exercise in balancing risks and benefits. Human health risk assessors and risk managers will benefit from an understanding of the level of uncertainty that is integrated into all aspects of evaluating risk in this context. Significant variability exists in the way in which analyses are conducted, how data are reported, and how they are used in risk assessments. We conducted an analytical review of PCB and PBDE data in farmed and wild salmon, and identified critical issues having implications on human health risk assessment from fish consumption. These issues include: analytical methodologies used, quantification issues, reporting of QA/QC information, tissue sampling, nature of tissue analyzed, and laboratory competence. This article reviews and outlines these issues, discusses their implications for human health risk assessment, and recommends the consistent application of analytical fish tissue data in human health risk assessment.     

Quantitative Imaging to Assess Tumor Response to Therapy: Common Themes of Measurement,Truth Data,and Error Sources

RATIONALE: Early detection of tumor response to therapy is a key goal. Finding measurement algorithms capable of early detection of tumor response could individualize therapy treatment as well as reduce the cost of bringing new drugs to market. On an individual basis, the urgency arises from the desire to prevent continued treatment of the patient with a high-cost and/or high-risk regimen with no demonstrated individual benefit and rapidly switch the patient to an alternative efficacious therapy for that patient. In the context of bringing new drugs to market, such algorithms could demonstrate efficacy in much smaller populations, which would allow phase 3 trials to achieve statistically significant decisions with fewer subjects in shorter trials. MATERIALS AND METHODS: This consensus-based article describes multiple, image modality-independent means to assess the relative performance of algorithms for measuring tumor change in response to therapy. In this setting, we describe specifically the example of measurement of tumor volume change from anatomic imaging as well as provide an overview of other promising generic analytic methods that can be used to assess change in heterogeneous tumors. To support assessment of the relative performance of algorithms for measuring small tumor change, data sources of truth are required. RESULTS: Very short interval clinical imaging examinations and phantom scans provide known truth for comparative evaluation of algorithms. CONCLUSIONS: For a given category of measurement methods, the algorithm that has the smallest measurement noise and least bias on average will perform best in early detection of true tumor change.     

Computed Tomography Assessment of Response to Therapy: Tumor Volume Change Measurement,Truth Data,and Error

RATIONALE AND OBJECTIVES: This article describes issues and methods that are specific to the measurement of change in tumor volume as measured from computed tomographic (CT) images and how these would relate to the establishment of CT tumor volumetrics as a biomarker of patient response to therapy. The primary focus is on the measurement of lung tumors, but the approach should be generalizable to other anatomic regions. MATERIALS AND METHODS: The first issues addressed are the various sources of bias and variance in the measurement of tumor volumes, which are discussed in the context of measurement variation and its impact on the early detection of response to therapy. RESULTS AND RESOURCES: Research that seeks to identify the magnitude of some of these sources of error is ongoing, and several of these efforts are described herein. In addition, several resources for these investigations are being made available through the National Institutes of Health-funded Reference Image Database to Evaluate Response to therapy in cancer project, and these are described as well. Other measures derived from CT image data that might be predictive of patient response are described briefly, as well as the additional issues that each of these metrics may encounter in real-life applications. CONCLUSIONS: The article concludes with a brief discussion of moving from the assessment of measurement variation to the steps necessary to establish the efficacy of a metric as a biomarker for response.     

PET/CT Assessment of Response to Therapy: Tumor Change Measurement,Truth Data,and Error

We describe methods and issues that are relevant to the measurement of change in tumor uptake of ¹⁸F-fluorodeoxyglucose (FDG) or other radiotracers, as measured from positron emission tomography/computed tomography (PET/CT) images, and how this would relate to the establishment of PET/CT tumor imaging as a biomarker of patient response to therapy. The primary focus is on the uptake of FDG by lung tumors, but the approach can be applied to diseases other than lung cancer and to tracers other than FDG. The first issue addressed is the sources of bias and variance in the measurement of tumor uptake of FDG, and where there are still gaps in our knowledge. These are discussed in the context of measurement variation and how these would relate to the early detection of response to therapy. Some of the research efforts currently underway to identify the magnitude of some of these sources of error are described. In addition, we describe resources for these investigations that are being made available through the Reference Image Database for the Evaluation of Response project. Measures derived from PET image data that might be predictive of patient response as well as the additional issues that each of these metrics may encounter are described briefly. The relationship between individual patient response to therapy and utility for multicenter trials is discussed. We conclude with a discussion of moving from assessing measurement variation to the steps necessary to establish the efficacy of PET/CT imaging as a biomarker for response.     

Magnetic Resonance Assessment of Response to Therapy: Tumor Change Measurement,Truth Data and Error Sources

This article describes methods and issues that are specific to the assessment of change in tumor characteristics as measured using quantitative magnetic resonance (MR) techniques and how this relates to the establishment of quantitative MR imaging (MRI) biomarkers of patient response to therapy. The initial focus is on the various sources of bias and variance in the measurement of microvascular parameters and diffusion parameters as such parameters are being used relatively commonly as secondary or exploratory end points in current phase 1/2 clinical trails of conventional and targeted therapies. Several ongoing initiatives that seek to identify the magnitude of some of the sources of measurement variations are then discussed. Finally, resources being made available through the National Cancer Institute Reference Image Database to Evaluate Response (RIDER) project that might be of use in investigations of quantitative MRI biomarker change analysis are described. These resources include 1) data from phantom-based assessment of system response, including short-term (1 hour) and moderate-term (1 week) contrast response and relaxation time measurement, 2) data obtained from repeated dynamic contrast agent-enhanced MRI studies in intracranial tumors, and 3) data obtained from repeated diffusion MRI studies in both breast and brain. A concluding section briefly discusses issues that must be addressed to allow the transition of MR-based imaging biomarker measures from their current role as secondary/exploratory end points in clinical trials to primary/surrogate markers of response and, ultimately, in clinical application.     

Expression of Peripheral Benzodiazepine Receptor (PBR) in Human Tumors: Relationship to Breast,Colorectal, and Prostate Tumor Progression

Abstract

High levels of peripheral‐type benzodiazepine receptor (PBR), the alternative‐binding site for diazepam, are part of the aggressive human breast cancer cell phenotype in vitro. We examined PBR levels and distribution in normal tissue and tumors from multiple cancer types by immunohistochemistry. Among normal breast tissues, fibroadenomas, primary and metastatic adenocarcinomas, there is a progressive increase in PBR levels parallel to the invasive and metastatic ability of the tumor (p < 0.0001). In colorectal and prostate carcinomas, PBR levels were also higher in tumor than in the corresponding non‐tumoral tissues and benign lesions (p < 0.0001). In contrast, PBR was highly concentrated in normal adrenal cortical cells and hepatocytes, whereas in adrenocortical tumors and hepatomas PBR levels were decreased. Moreover, malignant skin tumors showed decreased PBR expression compared with normal skin. These results indicate that elevated PBR expression is not a common feature of aggressive tumors, but rather may be limited to certain cancers, such as those of breast, colon‐rectum and prostate tissues, where elevated PBR expression is associated with tumor progression. Thus, we propose that PBR overexpression could serve as a novel prognostic indicator of an aggressive phenotype in breast, colorectal and prostate cancers.     

Structural Differences between the Avian and Human H7N9 Hemagglutinin Proteins Are Attributable to Modifications in Salt Bridge Formation: A Computational Study with Implications in Viral Evolution

Influenza A hemagglutinin (HA) is a homotrimeric glycoprotein composed of a fibrous globular stem supporting a globular head containing three sialic acid binding sites responsible for infection. The H7N9 strain has consistently infected an avian host, however, the novel 2013 strain is now capable of infecting a human host which would imply that the HA in both strains structurally differ. A better understanding of the structural differences between the avian and human H7N9 strains may shed light into viral evolution and transmissibility. In this study, we elucidated the structural differences between the avian and human H7N9 strains. Throughout the study, we generated HA homology models, verified the quality of each model, superimposed HA homology models to determine structural differences, and, likewise, elucidated the probable cause for these structural differences. We detected two different types of structural differences between the novel H7N9 human and representative avian strains, wherein, one type (Pattern-1) showed three non-overlapping regions while the other type (Pattern-2) showed only one non-overlapping region. In addition, we found that superimposed HA homology models exhibiting Pattern-1 contain three non-overlapping regions designated as: Region-1 (S157₁-A160₁); Region-3 (R262₁-S265₁); and Region-4 (S270₁-D281₁), whereas, superimposed HA homology models showing Pattern-2 only contain one non-overlapping region designated as Region-2 (S137₁-S145₁). We attributed the two patterns we observed to either the presence of salt bridges involving the E114₁ residue or absence of the R141₁:D77₁ salt bridge. Interestingly, comparison between the human H7N7 and H7N9 HA homology models showed high structural similarity. We propose that the putative absence of the R141₁:D77₁ salt bridge coupled with the putative presence of the E114₁:R262₁ and E114₁:K264₁ salt bridges found in the 2013 H7N9 HA homology model is associated to human-type receptor binding. This highlights the possible significance of HA salt bridge formation modifications in viral infectivity, immune escape, transmissibility and evolution.     

From Tumor Necrosis Factor Receptor to RANK, from the Selectins and Link Proteins to CD44: New Molecular Models of Cell Surface Receptors and Analysis of Specificity Determinants

Modeling and structure-function studies on two cell surface proteins are presented, which are implicated in the regulation of immune responses and cell adhesion. In the first part, model building of RANK, a new member of the tumor necrosis factor receptor (TNFR) superfamily (TNFRSF), is reported. The model is analyzed in light of structural studies on the TNFR-ligand complex and molecular model-based mutagenesis analyses of CD40-ligand and Fas-ligand interactions. The study makes it possible to predict residues important for ligand binding to RANK and further rationalizes differences in specificity between TNFR-like cell surface receptors. In the second part, recent investigations on the structure and carbohydrate binding site of CD44, a member of the link protein family, are discussed. The binding site in CD44 is compared to calcium-dependent (C-type) lectins, which include the selectins, another family of cell adhesion molecules. The studies on TNFRSF members and link proteins reported herein complement a recent review article in this journal, which focused on modeling and binding site analysis of immune cell surface proteins.Electronic Supplementary Material available.     

Moving from Data on Deaths to Public Health Policy in Agincourt,South Africa: Approaches to Analysing and Understanding Verbal Autopsy Findings

Background

Cause of death data are an essential source for public health planning, but their availability and quality are lacking in many parts of the world. Interviewing family and friends after a death has occurred (a procedure known as verbal autopsy) provides a source of data where deaths otherwise go unregistered; but sound methods for interpreting and analysing the ensuing data are essential. Two main approaches are commonly used: either physicians review individual interview material to arrive at probable cause of death, or probabilistic models process the data into likely cause(s). Here we compare and contrast these approaches as applied to a series of 6,153 deaths which occurred in a rural South African population from 1992 to 2005. We do not attempt to validate either approach in absolute terms.

Methods and Findings

The InterVA probabilistic model was applied to a series of 6,153 deaths which had previously been reviewed by physicians. Physicians used a total of 250 cause-of-death codes, many of which occurred very rarely, while the model used 33. Cause-specific mortality fractions, overall and for population subgroups, were derived from the model''s output, and the physician causes coded into comparable categories. The ten highest-ranking causes accounted for 83% and 88% of all deaths by physician interpretation and probabilistic modelling respectively, and eight of the highest ten causes were common to both approaches. Top-ranking causes of death were classified by population subgroup and period, as done previously for the physician-interpreted material. Uncertainty around the cause(s) of individual deaths was recognised as an important concept that should be reflected in overall analyses. One notably discrepant group involved pulmonary tuberculosis as a cause of death in adults aged over 65, and these cases are discussed in more detail, but the group only accounted for 3.5% of overall deaths.

Conclusions

There were no differences between physician interpretation and probabilistic modelling that might have led to substantially different public health policy conclusions at the population level. Physician interpretation was more nuanced than the model, for example in identifying cancers at particular sites, but did not capture the uncertainty associated with individual cases. Probabilistic modelling was substantially cheaper and faster, and completely internally consistent. Both approaches characterised the rise of HIV-related mortality in this population during the period observed, and reached similar findings on other major causes of mortality. For many purposes probabilistic modelling appears to be the best available means of moving from data on deaths to public health actions. Please see later in the article for the Editors'' Summary     

PhyreRisk: A Dynamic Web Application to Bridge Genomics,Proteomics and 3D Structural Data to Guide Interpretation of Human Genetic Variants

PhyreRisk is an open-access, publicly accessible web application for interactively bridging genomic, proteomic and structural data facilitating the mapping of human variants onto protein structures. A major advance over other tools for sequence-structure variant mapping is that PhyreRisk provides information on 20,214 human canonical proteins and an additional 22,271 alternative protein sequences (isoforms). Specifically, PhyreRisk provides structural coverage (partial or complete) for 70% (14,035 of 20,214 canonical proteins) of the human proteome, by storing 18,874 experimental structures and 84,818 pre-built models of canonical proteins and their isoforms generated using our in house Phyre2. PhyreRisk reports 55,732 experimentally, multi-validated protein interactions from IntAct and 24,260 experimental structures of protein complexes.Another major feature of PhyreRisk is that, rather than presenting a limited set of precomputed variant-structure mapping of known genetic variants, it allows the user to explore novel variants using, as input, genomic coordinates formats (Ensembl, VCF, reference SNP ID and HGVS notations) and Human Build GRCh37 and GRCh38. PhyreRisk also supports mapping variants using amino acid coordinates and searching for genes or proteins of interest.PhyreRisk is designed to empower researchers to translate genetic data into protein structural information, thereby providing a more comprehensive appreciation of the functional impact of variants. PhyreRisk is freely available at http://phyrerisk.bc.ic.ac.uk     

New Oral Anticoagulants Are Not Superior to Warfarin in Secondary Prevention of Stroke or Transient Ischemic Attacks,but Lower the Risk of Intracranial Bleeding: Insights from a Meta-Analysis and Indirect Treatment Comparisons

Purpose

Patients with Atrial Fibrillation (AF) and prior stroke are classified as high risk in all risk stratification schemes. A systematic review and meta-analysis was performed to compare the efficacy and safety of New Oral Anticoagulants (NOACs) to warfarin in patients with AF and previous stroke or transient ischemic attack (TIA).

Methods

Three randomized controlled trials (RCTs), including total 14527 patients, comparing NOACs (apixaban, dabigatran and rivaroxaban) with warfarin were included in the analysis. Primary efficacy endpoint was ischemic stroke, and primary safety endpoint was intracranial bleeding. Random-effects models were used to pool efficacy and safety data across RCTs. RevMan and Stata software were used for direct and indirect comparisons, respectively.

Results

In patients with AF and previous stroke or TIA, effects of NOACs were not statistically different from that of warfarin, in reduction of stroke (Odds Ratio [OR] 0.86, 95% confidence interval [CI] 0.73- 1.01), disabling and fatal stroke (OR 0.85, 95% CI 0.71-1.04), and all-cause mortality (OR 0.90, 95% CI 0.79 -1.02). Randomization to NOACs was associated with a significantly lower risk of intracranial bleeding (OR 0.42, 95% CI 0.25-0.70). There were no major differences in efficacy between apixaban, dabigatran (110 mg BID and 150 mg BID) and rivaroxaban. Major bleeding was significantly lower with apixaban and dabigatran (110 mg BID) compared with dabigatran (150 mg BID) and rivaroxaban.

Conclusion

NOACs may not be more effective than warfarin in the secondary prevention of ischemic stroke in patients with a prior history of cerebrovascular ischemia, but have a lower risk of intracranial bleeding.