Characterizing disease states from topological properties of transcriptional regulatory networks

BACKGROUND: High throughput gene expression experiments yield large amounts of data that can augment our understanding of disease processes, in addition to classifying samples. Here we present new paradigms of data Separation based on construction of transcriptional regulatory networks for normal and abnormal cells using sequence predictions, literature based data and gene expression studies. We analyzed expression datasets from a number of diseased and normal cells, including different types of acute leukemia, and breast cancer with variable clinical outcome. RESULTS: We constructed sample-specific regulatory networks to identify links between transcription factors (TFs) and regulated genes that differentiate between healthy and diseased states. This approach carries the advantage of identifying key transcription factor-gene pairs with differential activity between healthy and diseased states rather than merely using gene expression profiles, thus alluding to processes that may be involved in gene deregulation. We then generalized this approach by studying simultaneous changes in functionality of multiple regulatory links pointing to a regulated gene or emanating from one TF (or changes in gene centrality defined by its in-degree or out-degree measures, respectively). We found that samples can often be separated based on these measures of gene centrality more robustly than using individual links. We examined distributions of distances (the number of links needed to traverse the path between each pair of genes) in the transcriptional networks for gene subsets whose collective expression profiles could best separate each dataset into predefined groups. We found that genes that optimally classify samples are concentrated in neighborhoods in the gene regulatory networks. This suggests that genes that are deregulated in diseased states exhibit a remarkable degree of connectivity. CONCLUSION: Transcription factor-regulated gene links and centrality of genes on transcriptional networks can be used to differentiate between cell types. Transcriptional network blueprints can be used as a basis for further research into gene deregulation in diseased states

Quantitative Assessment of Tissue Biomarkers and Construction of a Model to Predict Outcome in Breast Cancer Using Multiple Imputation

Missing data pose one of the greatest challenges in the rigorous evaluation of biomarkers. The limited availability of specimens with complete clinical annotation and quality biomaterial often leads to underpowered studies. Tissue microarray studies, for example, may be further handicapped by the loss of data points because of unevaluable staining, core loss, or the lack of tumor in the histospot. This paper presents a novel approach to these common problems in the context of a tissue protein biomarker analysis in a cohort of patients with breast cancer. Our analysis develops techniques based on multiple imputation to address the missing value problem. We first select markers using a training cohort, identifying a small subset of protein expression levels that are most useful in predicting patient survival. The best model is obtained by including both protein markers (including COX6C, GATA3, NAT1, and ESR1) and lymph node status. The use of either lymph node status or the four protein expression levels provides similar improvements in goodness-of-fit, with both significantly better than a baseline clinical model. Using the same multiple imputation strategy, we then validate the results out-of-sample on a larger independent cohort. Our approach of integrating multiple imputation with each stage of the analysis serves as an example that may be replicated or adapted in future studies with missing values

Monitoring of Collapsed Built-Up Areas with High Resolution SAR Images

A 16-year-old male with cystic fibrosis (CF) was admitted to hospital with a severe infective exacerbation. Despite standard management, including conventionally selected intravenous antibiotics for Pseudomonas aeruginosa chest physiotherapy, and institution of noninvasive ventilation (NIV) for progressive hypercapneic respiratory failure, he continued to deteriorate. Direct sputum sensitivity testing (DSST) revealed a novel combination of antibiotics that resulted in a rapid and remarkable clinical improvement. DSST is a form of "whole" sputum sensitivity testing that provides information on antibiotic synergy, and may more accurately reflect in vivo antibiotic sensitivity patterns in cystic fibrosis.</p

Rationale and design of the randomized, controlled early valve replacement guided by biomarkers of left ventricular decompensation in asymptomatic patients with severe aortic stenosis (EVOLVED) trial

Background: The optimal timing of aortic valve replacement in asymptomatic patients with aortic stenosis is uncertain. Replacement fibrosis, as assessed by midwall (nonischemic) late gadolinium enhancement (LGE) on cardiac magnetic resonance (CMR) imaging, is an irreversible marker of left ventricular decompensation in aortic stenosis. Once established, it progresses rapidly and is associated with poor long-term prognosis in a dose-dependent manner. // Trial design: The objective of this multicenter prospective randomized controlled trial is to determine whether early aortic valve replacement in asymptomatic patients with severe aortic stenosis can improve the adverse prognosis associated with midwall LGE. Patients will be screened for likelihood of having LGE with electrocardiography or high-sensitivity troponin I. Those at high risk will proceed to CMR imaging. Approximately 400 patients with midwall LGE will be randomized 1:1 to early valve replacement or routine care. Those who do not exhibit midwall LGE will continue with routine care and be randomized to a study registry or no further follow-up. Follow-up will be annual for approximately 3 years until the number of required outcome events is achieved. The primary endpoint is a composite of all-cause mortality and unplanned aortic stenosis–related hospitalization. The expected event rate is 25.0% in the routine care arm and 13.4% in the early intervention arm over the first 2 years; 88 observed primary outcome events will give 90% power at 5% significance level. Key secondary endpoints include all-cause mortality, sudden cardiac death, stroke, and symptomatic status. // Conclusion: The EVOLVED trial is the first multicenter randomized controlled trial to compare early aortic valve replacement to routine care in asymptomatic patients with severe aortic stenosis and midwall LGE

Role of the Placental Vitamin D Receptor in Modulating Feto-Placental Growth in Fetal Growth Restriction and Preeclampsia-Affected Pregnancies

Fetal growth restriction (FGR) is a common pregnancy complication that affects up to 5% of pregnancies worldwide. Recent studies demonstrate that Vitamin D deficiency is implicated in reduced fetal growth, which may be rescued by supplementation of Vitamin D. Despite this, the pathway(s) by which Vitamin D modulate fetal growth remains to be investigated. Our own studies demonstrate that the Vitamin D receptor (VDR) is significantly decreased in placentae from human pregnancies complicated by FGR and contributes to abnormal placental trophoblast apoptosis and differentiation and regulation of cell-cycle genes in vitro. Thus, Vitamin D signaling is important for normal placental function and fetal growth. This review discusses the association of Vitamin D with fetal growth, the function of Vitamin D and its receptor in pregnancy, as well as the functional significance of a placental source of Vitamin D in FGR. Additionally, we propose that for Vitamin D to be clinically effective to prevent and manage FGR, the molecular mechanisms of Vitamin D and its receptor in modulating fetal growth requires further investigation

A Soluble ‘Ba(Ni-ett)’ (ett = 1,1,2,2-Ethenetetrathiolate) Derived Thermoelectric Material

We describe the synthesis and characterisation of the first of a new class of soluble ladder oligomeric thermoelectric material based on previously unutilised ethene-1,1,2,2-tetrasulfonic acid. Reaction of Ba(OH)2 and propionic acid at a 1:1 stoichiometry leads to the formation of the previously unrecognised soluble [Ba(OH)(O2CEt)]⋅H2O. The latter when used to hydrolyse 1,3,4,6-tetrathiapentalene-2,5-dione (TPD), in the presence of NiCl2, forms a new material whose elemental composition is in accord with the formula [(EtCO2Ba)4Ni8{(O3S)2C = C(SO3)2}5]⋅22H2O (4). Compound 4 can be pressed into pellets, drop-cast as DMSO solutions or ink-jet printed (down to sub-mm resolutions). While its room temperature thermoelectric properties are modest (σmax 0.04 S cm−1 and Seebeck coefficient, αmax − 25.8 μV K−1) we introduce a versatile new oligomeric material that opens new possible synthetic routes for n-type thermoelectrics

Identifying the science and technology dimensions of emerging public policy issues through horizon scanning

Public policy requires public support, which in turn implies a need to enable the public not just to understand policy but also to be engaged in its development. Where complex science and technology issues are involved in policy making, this takes time, so it is important to identify emerging issues of this type and prepare engagement plans. In our horizon scanning exercise, we used a modified Delphi technique [1]. A wide group of people with interests in the science and policy interface (drawn from policy makers, policy adviser, practitioners, the private sector and academics) elicited a long list of emergent policy issues in which science and technology would feature strongly and which would also necessitate public engagement as policies are developed. This was then refined to a short list of top priorities for policy makers. Thirty issues were identified within broad areas of business and technology; energy and environment; government, politics and education; health, healthcare, population and aging; information, communication, infrastructure and transport; and public safety and national security.Public policy requires public support, which in turn implies a need to enable the public not just to understand policy but also to be engaged in its development. Where complex science and technology issues are involved in policy making, this takes time, so it is important to identify emerging issues of this type and prepare engagement plans. In our horizon scanning exercise, we used a modified Delphi technique [1]. A wide group of people with interests in the science and policy interface (drawn from policy makers, policy adviser, practitioners, the private sector and academics) elicited a long list of emergent policy issues in which science and technology would feature strongly and which would also necessitate public engagement as policies are developed. This was then refined to a short list of top priorities for policy makers. Thirty issues were identified within broad areas of business and technology; energy and environment; government, politics and education; health, healthcare, population and aging; information, communication, infrastructure and transport; and public safety and national security

PAM50 proliferation score as a predictor of weekly paclitaxel benefit in breast cancer

To identify a group of patients who might benefit from the addition of weekly paclitaxel to conventional anthracycline-containing chemotherapy as adjuvant therapy of node-positive operable breast cancer. The predictive value of PAM50 subtypes and the 11-gene proliferation score contained within the PAM50 assay were evaluated in 820 patients from the GEICAM/9906 randomized phase III trial comparing adjuvant FEC to FEC followed by weekly paclitaxel (FEC-P). Multivariable Cox regression analyses of the secondary endpoint of overall survival (OS) were performed to determine the significance of the interaction between treatment and the (1) PAM50 subtypes, (2) PAM50 proliferation score, and (3) clinical and pathological variables. Similar OS analyses were performed in 222 patients treated with weekly paclitaxel versus paclitaxel every 3 weeks in the CALGB/9342 and 9840 metastatic clinical trials. In GEICAM/9906, with a median follow up of 8.7 years, OS of the FEC-P arm was significantly superior compared to the FEC arm (unadjusted HR = 0.693, p = 0.013). A benefit from paclitaxel was only observed in the group of patients with a low PAM50 proliferation score (unadjusted HR = 0.23, p < 0.001; and interaction test, p = 0.006). No significant interactions between treatment and the PAM50 subtypes or the various clinical–pathological variables, including Ki-67 and histologic grade, were identified. Finally, similar OS results were obtained in the CALGB data set, although the interaction test did not reach statistical significance (p = 0.109). The PAM50 proliferation score identifies a subset of patients with a low proliferation status that may derive a larger benefit from weekly paclitaxel. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10549-013-2416-2) contains supplementary material, which is available to authorized users