Approaches towards expression profiling the response to treatment

Over the past 8 years there has been a wealth of breast cancer gene expression studies. The majority of these studies have focused upon characterising a tumour at presentation, before treatment, rather than looking at the effects of treatment on the tumour. More recently, a number of groups have moved from predicting prognosis based upon long-term follow-up to alternative approaches of using expression profiling to measure the effect of treatment on breast tumours and potentially predict response to therapy using either post-treatment samples or both pre-treatment and post-treatment samples. Whilst this provides great potential to further our understanding of the mode of action of treatments and to more accurately select which patients will benefit from a particular treatment, serious issues of experimental design must be considered

Relative impact of key sources of systematic noise in Affymetrix and Illumina gene-expression microarray experiments

<p>Abstract</p> <p>Background</p> <p>Systematic processing noise, which includes batch effects, is very common in microarray experiments but is often ignored despite its potential to confound or compromise experimental results. Compromised results are most likely when re-analysing or integrating datasets from public repositories due to the different conditions under which each dataset is generated. To better understand the relative noise-contributions of various factors in experimental-design, we assessed several Illumina and Affymetrix datasets for technical variation between replicate hybridisations of Universal Human Reference (UHRR) and individual or pooled breast-tumour RNA.</p> <p>Results</p> <p>A varying degree of systematic noise was observed in each of the datasets, however in all cases the relative amount of variation between standard control RNA replicates was found to be greatest at earlier points in the sample-preparation workflow. For example, 40.6% of the total variation in reported expressions were attributed to replicate extractions, compared to 13.9% due to amplification/labelling and 10.8% between replicate hybridisations. Deliberate probe-wise batch-correction methods were effective in reducing the magnitude of this variation, although the level of improvement was dependent on the sources of noise included in the model. Systematic noise introduced at the chip, run, and experiment levels of a combined Illumina dataset were found to be highly dependant upon the experimental design. Both UHRR and pools of RNA, which were derived from the samples of interest, modelled technical variation well although the pools were significantly better correlated (4% average improvement) and better emulated the effects of systematic noise, over all probes, than the UHRRs. The effect of this noise was not uniform over all probes, with low GC-content probes found to be more vulnerable to batch variation than probes with a higher GC-content.</p> <p>Conclusions</p> <p>The magnitude of systematic processing noise in a microarray experiment is variable across probes and experiments, however it is generally the case that procedures earlier in the sample-preparation workflow are liable to introduce the most noise. Careful experimental design is important to protect against noise, detailed meta-data should always be provided, and diagnostic procedures should be routinely performed prior to downstream analyses for the detection of bias in microarray studies.</p

Direct integration of intensity-level data from Affymetrix and Illumina microarrays improves statistical power for robust reanalysis

<p>Abstract</p> <p>Background</p> <p>Affymetrix GeneChips and Illumina BeadArrays are the most widely used commercial single channel gene expression microarrays. Public data repositories are an extremely valuable resource, providing array-derived gene expression measurements from many thousands of experiments. Unfortunately many of these studies are underpowered and it is desirable to improve power by combining data from more than one study; we sought to determine whether platform-specific bias precludes direct integration of probe intensity signals for combined reanalysis.</p> <p>Results</p> <p>Using Affymetrix and Illumina data from the microarray quality control project, from our own clinical samples, and from additional publicly available datasets we evaluated several approaches to directly integrate intensity level expression data from the two platforms. After mapping probe sequences to Ensembl genes we demonstrate that, ComBat and cross platform normalisation (XPN), significantly outperform mean-centering and distance-weighted discrimination (DWD) in terms of minimising inter-platform variance. In particular we observed that DWD, a popular method used in a number of previous studies, removed systematic bias at the expense of genuine biological variability, potentially reducing legitimate biological differences from integrated datasets.</p> <p>Conclusion</p> <p>Normalised and batch-corrected intensity-level data from Affymetrix and Illumina microarrays can be directly combined to generate biologically meaningful results with improved statistical power for robust, integrated reanalysis.</p

Understanding innovators' experiences of barriers and facilitators in implementation and diffusion of healthcare service innovations: A qualitative study

This article is made available through the Brunel Open Access Publishing Fund - Copyright @ 2011 Barnett et al.Background: Healthcare service innovations are considered to play a pivotal role in improving organisational efficiency and responding effectively to healthcare needs. Nevertheless, healthcare organisations encounter major difficulties in sustaining and diffusing innovations, especially those which concern the organisation and delivery of healthcare services. The purpose of the present study was to explore how healthcare innovators of process-based initiatives perceived and made sense of factors that either facilitated or obstructed the innovation implementation and diffusion. Methods: A qualitative study was designed. Fifteen primary and secondary healthcare organisations in the UK, which had received health service awards for successfully generating and implementing service innovations, were studied. In-depth, semi structured interviews were conducted with the organisational representatives who conceived and led the development process. The data were recorded, transcribed and thematically analysed. Results: Four main themes were identified in the analysis of the data: the role of evidence, the function of inter-organisational partnerships, the influence of human-based resources, and the impact of contextual factors. "Hard" evidence operated as a proof of effectiveness, a means of dissemination and a pre-requisite for the initiation of innovation. Inter-organisational partnerships and people-based resources, such as champions, were considered an integral part of the process of developing, establishing and diffusing the innovations. Finally, contextual influences, both intra-organisational and extra-organisational were seen as critical in either impeding or facilitating innovators' efforts. Conclusions: A range of factors of different combinations and co-occurrence were pointed out by the innovators as they were reflecting on their experiences of implementing, stabilising and diffusing novel service initiatives. Even though the innovations studied were of various contents and originated from diverse organisational contexts, innovators' accounts converged to the significant role of the evidential base of success, the inter-personal and inter-organisational networks, and the inner and outer context. The innovators, operating themselves as important champions and being often willing to lead constructive efforts of implementation to different contexts, can contribute to the promulgation and spread of the novelties significantly.This research was supported financially by the Multidisciplinary Assessment of Technology Centre for Healthcare (MATCH)

Dermatitis associated with exposure to a marine cyanobacterium during recreational water exposure

<p>Abstract</p> <p>Background</p> <p>Anecdotal evidence reported an outbreak of symptoms on Fraser Island during the late 1990s similar to those expected from exposure to dermotoxins found in the cyanobacterium <it>L. majuscula</it>. This coincided with the presence of a bloom of <it>L. majuscula</it>.</p> <p>Methods</p> <p>Records from the Fraser Island National Parks First aid station were examined. Information on cyanobacterial blooms at Fraser Island were obtained from Queensland National Parks rangers.</p> <p>Results</p> <p>Examination of first aid records from Fraser Island revealed an outbreak of symptoms predominantly in January and February 1998.</p> <p>Conclusion</p> <p>During a bloom of <it>L. majuscula </it>there were numerous reports of symptoms that could be attributed to dermotoxins found in <it>L. majuscula</it>. The other four years examined had no <it>L. majuscula </it>blooms and the number of <it>L. majuscula </it>symptoms was much reduced. These cases comprised a high percentage of the cases treated at the first aid station.</p

A requirement for astrocyte IP3R2 signaling for whisker experience-dependent depression and homeostatic upregulation in the mouse barrel cortex.

Changes to sensory experience result in plasticity of synapses in the cortex. This experience-dependent plasticity (EDP) is a fundamental property of the brain. Yet, while much is known about neuronal roles in EDP, very little is known about the role of astrocytes. To address this issue, we used the well-described mouse whiskers-to-barrel cortex system, which expresses a number of forms of EDP. We found that all-whisker deprivation induced characteristic experience-dependent Hebbian depression (EDHD) followed by homeostatic upregulation in L2/3 barrel cortex of wild type mice. However, these changes were not seen in mutant animals (IP3R2-/-) that lack the astrocyte-expressed IP3 receptor subtype. A separate paradigm, the single-whisker experience, induced potentiation of whisker-induced response in both wild-type (WT) mice and IP3R2-/- mice. Recordings in ex vivo barrel cortex slices reflected the in vivo results so that long-term depression (LTD) could not be elicited in slices from IP3R2-/- mice, but long-term potentiation (LTP) could. Interestingly, 1 Hz stimulation inducing LTD in WT paradoxically resulted in NMDAR-dependent LTP in slices from IP3R2-/- animals. The LTD to LTP switch was mimicked by acute buffering astrocytic [Ca2+] i in WT slices. Both WT LTD and IP3R2-/- 1 Hz LTP were mediated by non-ionotropic NMDAR signaling, but only WT LTD was P38 MAPK dependent, indicating an underlying mechanistic switch. These results demonstrate a critical role for astrocytic [Ca2+] i in several EDP mechanisms in neocortex

Socioeconomic differentials in the immediate mortality effects of the national Irish smoking ban

This article has been made available through the Brunel Open Access Publishing Fund.Background: Consistent evidence has demonstrated that smoking ban policies save lives, but impacts on health inequalities are uncertain as few studies have assessed post-ban effects by socioeconomic status (SES) and findings have been inconsistent. The aim of this study was to assess the effects of the national Irish smoking ban on ischemic heart disease (IHD), stroke, and chronic obstructive pulmonary disease (COPD) mortality by discrete and composite SES indicators to determine impacts on inequalities. Methods: Census data were used to assign frequencies of structural and material SES indicators to 34 local authorities across Ireland with a 2000–2010 study period. Discrete indicators were jointly analysed through principal component analysis to generate a composite index, with sensitivity analyses conducted by varying the included indicators. Poisson regression with interrupted time-series analysis was conducted to examine monthly age and gender-standardised mortality rates in the Irish population, ages ≥35 years, stratified by tertiles of SES indicators. All models were adjusted for time trend, season, influenza, and smoking prevalence. Results: Post-ban mortality reductions by structural SES indicators were concentrated in the most deprived tertile for all causes of death, while reductions by material SES indicators were more equitable across SES tertiles. The composite indices mirrored the results of the discrete indicators, demonstrating that post-ban mortality decreases were either greater or similar in the most deprived when compared to the least deprived for all causes of death. Conclusions: Overall findings indicated that the national Irish smoking ban reduced inequalities in smoking-related mortality. Due to the higher rates of smoking-related mortality in the most deprived group, even equitable reductions across SES tertiles resulted in decreases in inequalities. The choice of SES indicator was influential in the measurement of effects, underscoring that a differentiated analytical approach aided in understanding the complexities in which structural and material factors influence mortality

Unlocking the potential of publicly available microarray data using inSilicoDb and inSilicoMerging R/Bioconductor packages

BACKGROUND: With an abundant amount of microarray gene expression data sets available through public repositories, new possibilities lie in combining multiple existing data sets. In this new context, analysis itself is no longer the problem, but retrieving and consistently integrating all this data before delivering it to the wide variety of existing analysis tools becomes the new bottleneck. RESULTS: We present the newly released inSilicoMerging R/Bioconductor package which, together with the earlier released inSilicoDb R/Bioconductor package, allows consistent retrieval, integration and analysis of publicly available microarray gene expression data sets. Inside the inSilicoMerging package a set of five visual and six quantitative validation measures are available as well. CONCLUSIONS: By providing (i) access to uniformly curated and preprocessed data, (ii) a collection of techniques to remove the batch effects between data sets from different sources, and (iii) several validation tools enabling the inspection of the integration process, these packages enable researchers to fully explore the potential of combining gene expression data for downstream analysis. The power of using both packages is demonstrated by programmatically retrieving and integrating gene expression studies from the InSilico DB repository [https://insilicodb.org/app/]

Evaluation of the current knowledge limitations in breast cancer research: a gap analysis

BACKGROUND A gap analysis was conducted to determine which areas of breast cancer research, if targeted by researchers and funding bodies, could produce the greatest impact on patients. METHODS Fifty-six Breast Cancer Campaign grant holders and prominent UK breast cancer researchers participated in a gap analysis of current breast cancer research. Before, during and following the meeting, groups in seven key research areas participated in cycles of presentation, literature review and discussion. Summary papers were prepared by each group and collated into this position paper highlighting the research gaps, with recommendations for action. RESULTS Gaps were identified in all seven themes. General barriers to progress were lack of financial and practical resources, and poor collaboration between disciplines. Critical gaps in each theme included: (1) genetics (knowledge of genetic changes, their effects and interactions); (2) initiation of breast cancer (how developmental signalling pathways cause ductal elongation and branching at the cellular level and influence stem cell dynamics, and how their disruption initiates tumour formation); (3) progression of breast cancer (deciphering the intracellular and extracellular regulators of early progression, tumour growth, angiogenesis and metastasis); (4) therapies and targets (understanding who develops advanced disease); (5) disease markers (incorporating intelligent trial design into all studies to ensure new treatments are tested in patient groups stratified using biomarkers); (6) prevention (strategies to prevent oestrogen-receptor negative tumours and the long-term effects of chemoprevention for oestrogen-receptor positive tumours); (7) psychosocial aspects of cancer (the use of appropriate psychosocial interventions, and the personal impact of all stages of the disease among patients from a range of ethnic and demographic backgrounds). CONCLUSION Through recommendations to address these gaps with future research, the long-term benefits to patients will include: better estimation of risk in families with breast cancer and strategies to reduce risk; better prediction of drug response and patient prognosis; improved tailoring of treatments to patient subgroups and development of new therapeutic approaches; earlier initiation of treatment; more effective use of resources for screening populations; and an enhanced experience for people with or at risk of breast cancer and their families. The challenge to funding bodies and researchers in all disciplines is to focus on these gaps and to drive advances in knowledge into improvements in patient care

Agalsidase beta treatment is associated with improved quality of life in patients with Fabry disease: Findings from the Fabry Registry

Purpose: To evaluate the effect of agalsidase beta on longitudinal health-related quality of life in patients with Fabry disease. Methods: the SF-36 (R) Health Survey was used to measure health-related quality of life in Fabry Registry patients. Seventy-one men and 59 women who were treated with agalsidase beta (median dose: 1.0 mg/kg/2 weeks) and who had baseline and at least 2 yearly posttreatment health-related quality of life measurements were included in these analyses. A repeated measures model was used to analyze change in score from baseline. Results: Men improved in the physical component summary and in all eight scales of the SF-36 after 1 and 2 years and in the mental component summary after 1 year of agalsidase beta treatment (P < 0.05). Women improved in the mental component summary and in six of the eight scales after 1 and/or 2 years of treatment. Patients whose baseline SF-36 scores were below the median showed the greatest improvements. These responses were comparable with or greater than the published effects of various treatments for multiple sclerosis, rheumatoid arthritis, central neuropathic pain, and Gaucher disease. Conclusion: Long-term treatment with agalsidase beta resulted in substantial improvements in health-related quality of life in both men and women; the effect was more pronounced in men. Genet Med 2010:12(11):703 712.Genzyme CorporationGenzymeNatl Univ Hosp, Dept Endocrinol, DK-2100 Copenhagen, DenmarkSan Bassano Hosp, Dept Neurol, Bassano Del Grappa, ItalyUniv Padua, Dept Neurosci, Padua, ItalyUniv Wurzburg, Dept Med, Wurzburg, GermanyColumbia Univ, Dept Pediat, Div Clin Genet, Coll Phys & Surg, New York, NY 10027 USACincinnati Childrens Hosp, Div Human Genet, Cincinnati, OH USAUniversidade Federal de São Paulo, Inatos Metab CREIM, São Paulo, BrazilMassachusetts Gen Hosp, Dept Neurol, Boston, MA 02114 USAGenzyme Corp, Dept Biomed Data Sci & Informat, Cambridge, MA USAUniversidade Federal de São Paulo, Inatos Metab CREIM, São Paulo, BrazilWeb of Scienc