Validation of a blood protein signature for non-small cell lung cancer

Background: CT screening for lung cancer is effective in reducing mortality, but there are areas of concern, including a positive predictive value of 4% and development of interval cancers. A blood test that could manage these limitations would be useful, but development of such tests has been impaired by variations in blood collection that may lead to poor reproducibility across populations. Results: Blood-based proteomic profiles were generated with SOMAscan technology, which measured 1033 proteins. First, preanalytic variability was evaluated with Sample Mapping Vectors (SMV), which are panels of proteins that detect confounders in protein levels related to sample collection. A subset of well collected serum samples not influenced by preanalytic variability was selected for discovery of lung cancer biomarkers. The impact of sample collection variation on these candidate markers was tested in the subset of samples with higher SMV scores so that the most robust markers could be used to create disease classifiers. The discovery sample set (n = 363) was from a multi-center study of 94 non-small cell lung cancer (NSCLC) cases and 269 long-term smokers and benign pulmonary nodule controls. The analysis resulted in a 7-marker panel with an AUC of 0.85 for all cases (68% adenocarcinoma, 32% squamous) and an AUC of 0.93 for squamous cell carcinoma in particular. This panel was validated by making blinded predictions in two independent cohorts (n = 138 in the first validation and n = 135 in the second). The model was recalibrated for a panel format prior to unblinding the second cohort. The AUCs overall were 0.81 and 0.77, and for squamous cell tumors alone were 0.89 and 0.87. The estimated negative predictive value for a 15% disease prevalence was 93% overall and 99% for squamous lung tumors. The proteins in the classifier function in destruction of the extracellular matrix, metabolic homeostasis and inflammation. Conclusions: Selecting biomarkers resistant to sample processing variation led to robust lung cancer biomarkers that performed consistently in independent validations. They form a sensitive signature for detection of lung cancer, especially squamous cell histology. This non-invasive test could be used to improve the positive predictive value of CT screening, with the potential to avoid invasive evaluation of nonmalignant pulmonary nodules

The health workforce crisis in Bangladesh: shortage, inappropriate skill-mix and inequitable distribution

<p>Abstract</p> <p>Background</p> <p>Bangladesh is identified as one of the countries with severe health worker shortages. However, there is a lack of comprehensive data on human resources for health (HRH) in the formal and informal sectors in Bangladesh. This data is essential for developing an HRH policy and plan to meet the changing health needs of the population. This paper attempts to fill in this knowledge gap by using data from a nationally representative sample survey conducted in 2007.</p> <p>Methods</p> <p>The study population in this survey comprised all types of currently active health care providers (HCPs) in the formal and informal sectors. The survey used 60 unions/wards from both rural and urban areas (with a comparable average population of approximately 25 000) which were proportionally allocated based on a 'Probability Proportion to Size' sampling technique for the six divisions and distribution areas. A simple free listing was done to make an inventory of the practicing HCPs in each of the sampled areas and cross-checking with community was done for confirmation and to avoid duplication. This exercise yielded the required list of different HCPs by union/ward.</p> <p>Results</p> <p>HCP density was measured per 10 000 population. There were approximately five physicians and two nurses per 10 000, the ratio of nurse to physician being only 0.4. Substantial variation among different divisions was found, with gross imbalance in distribution favouring the urban areas. There were around 12 unqualified village doctors and 11 salespeople at drug retail outlets per 10 000, the latter being uniformly spread across the country. Also, there were twice as many community health workers (CHWs) from the non-governmental sector than the government sector and an overwhelming number of traditional birth attendants. The village doctors (predominantly males) and the CHWs (predominantly females) were mainly concentrated in the rural areas, while the paraprofessionals were concentrated in the urban areas. Other data revealed the number of faith/traditional healers, homeopaths (qualified and non-qualified) and basic care providers.</p> <p>Conclusions</p> <p>Bangladesh is suffering from a severe HRH crisis--in terms of a shortage of qualified providers, an inappropriate skills-mix and inequity in distribution--which requires immediate attention from policy makers.</p

Mouse Acetylcholinesterase Enhances Neurite Outgrowth of Rat R28 Cells Through Interaction With Laminin-1

The enzyme acetylcholinesterase (AChE) terminates synaptic transmission at cholinergic synapses by hydrolyzing the neurotransmitter acetylcholine, but can also exert ‘non-classical’, morpho-regulatory effects on developing neurons such as stimulation of neurite outgrowth. Here, we investigated the role of AChE binding to laminin-1 on the regulation of neurite outgrowth by using cell culture, immunocytochemistry, and molecular biological approaches. To explore the role of AChE, we examined fiber growth of cells overexpressing different forms of AChE, and/or during their growth on laminin-1. A significant increase of neuritic growth as compared with controls was observed for neurons over-expressing AChE. Accordingly, addition of globular AChE to the medium increased total length of neurites. Co-transfection with PRIMA, a membrane anchor of AChE, led to an increase in fiber length similar to AChE overexpressing cells. Transfection with an AChE mutant that leads to the retention of AChE within cells had no stimulatory effect on neurite length. Noticeably, the longest neurites were produced by neurons overexpressing AChE and growing on laminin-1, suggesting that the AChE/laminin interaction is involved in regulating neurite outgrowth. Our findings demonstrate that binding of AChE to laminin-1 alters AChE activity and leads to increased neurite growth in culture. A possible mechanism of the AChE effect on neurite outgrowth is proposed due to the interaction of AChE with laminin-1

Syndromics: A Bioinformatics Approach for Neurotrauma Research

Substantial scientific progress has been made in the past 50 years in delineating many of the biological mechanisms involved in the primary and secondary injuries following trauma to the spinal cord and brain. These advances have highlighted numerous potential therapeutic approaches that may help restore function after injury. Despite these advances, bench-to-bedside translation has remained elusive. Translational testing of novel therapies requires standardized measures of function for comparison across different laboratories, paradigms, and species. Although numerous functional assessments have been developed in animal models, it remains unclear how to best integrate this information to describe the complete translational “syndrome” produced by neurotrauma. The present paper describes a multivariate statistical framework for integrating diverse neurotrauma data and reviews the few papers to date that have taken an information-intensive approach for basic neurotrauma research. We argue that these papers can be described as the seminal works of a new field that we call “syndromics”, which aim to apply informatics tools to disease models to characterize the full set of mechanistic inter-relationships from multi-scale data. In the future, centralized databases of raw neurotrauma data will enable better syndromic approaches and aid future translational research, leading to more efficient testing regimens and more clinically relevant findings

Criteria for the use of omics-based predictors in clinical trials: Explanation and elaboration

High-throughput 'omics' technologies that generate molecular profiles for biospecimens have been extensively used in preclinical studies to reveal molecular subtypes and elucidate the biological mechanisms of disease, and in retrospective studies on clinical specimens to develop mathematical models to predict clinical endpoints. Nevertheless, the translation of these technologies into clinical tests that are useful for guiding management decisions for patients has been relatively slow. It can be difficult to determine when the body of evidence for an omics-based test is sufficiently comprehensive and reliable to support claims that it is ready for clinical use, or even that it is ready for definitive evaluation in a clinical trial in which it may be used to direct patient therapy. Reasons for this difficulty include the exploratory and retrospective nature of many of these studies, the complexity of these assays and their application to clinical specimens, and the many potential pitfalls inherent in the development of mathematical predictor models from the very high-dimensional data generated by these omics technologies. Here we present a checklist of criteria to consider when evaluating the body of evidence supporting the clinical use of a predictor to guide patient therapy. Included are issues pertaining to specimen and assay requirements, the soundness of the process for developing predictor models, expectations regarding clinical study design and conduct, and attention to regulatory, ethical, and legal issues. The proposed checklist should serve as a useful guide to investigators preparing proposals for studies involving the use of omics-based tests. The US National Cancer Institute plans to refer to these guidelines for review of proposals for studies involving omics tests, and it is hoped that other sponsors will adopt the checklist as well. © 2013 McShane et al.; licensee BioMed Central Ltd

Effectiveness of a Household Environmental Health Intervention Delivered by Rural Public Health Nurses

Objectives. Parents need meaningful and actionable information if they are to reduce household environmental health risks to their children. To address this issue, we tested the effectiveness of a multi-risk social/cognitive intervention on rural low-income parents' (1) environmental health self-efficacy and (2) stage of environmental health precautionary adoption. Methods. Biomarker (lead, cotinine) and household samples (carbon monoxide, radon, mold/mildew, and drinking water contaminants) were collected from 235 families (399 adults, 441 children) in Montana and Washington states. Families were randomly assigned to intervention or control groups; intervention families received 4 visits from public health nurses who provided tailored information and guidance to parents; controls received usual and customary public health services. Results. At 3 months, the intervention group had significantly higher scores on (1) all 6 risk-specific self-efficacy subscales (P < .01), (2) general environmental health self-efficacy (P < .001), (3) 5 of 6 risk-specific precaution adoption subscales (P < .05), and (4) general environmental health precaution adoption (P < .001). Conclusions. The intervention yielded significant improvements in both outcomes. This evidence supported the need for a policy discussion addressing the added value that broadbased public health nurse interventions might bring to children's environmental health