Learning from microarray interlaboratory studies: measures of precision for gene expression

<p>Abstract</p> <p>Background</p> <p>The ability to demonstrate the reproducibility of gene expression microarray results is a critical consideration for the use of microarray technology in clinical applications. While studies have asserted that microarray data can be "highly reproducible" under given conditions, there is little ability to quantitatively compare amongst the various metrics and terminology used to characterize and express measurement performance. Use of standardized conceptual tools can greatly facilitate communication among the user, developer, and regulator stakeholders of the microarray community. While shaped by less highly multiplexed systems, measurement science (metrology) is devoted to establishing a coherent and internationally recognized vocabulary and quantitative practice for the characterization of measurement processes.</p> <p>Results</p> <p>The two independent aspects of the metrological concept of "accuracy" are "trueness" (closeness of a measurement to an accepted reference value) and "precision" (the closeness of measurement results to each other). A carefully designed collaborative study enables estimation of a variety of gene expression measurement precision metrics: repeatability, several flavors of intermediate precision, and reproducibility. The three 2004 Expression Analysis Pilot Proficiency Test collaborative studies, each with 13 to 16 participants, provide triplicate microarray measurements on each of two reference RNA pools. Using and modestly extending the consensus ISO 5725 documentary standard, we evaluate the metrological precision figures of merit for individual microarray signal measurement, building from calculations appropriate to single measurement processes, such as technical replicate expression values for individual probes on a microarray, to the estimation and display of precision functions representing all of the probes in a given platform.</p> <p>Conclusion</p> <p>With only modest extensions, the established metrological framework can be fruitfully used to characterize the measurement performance of microarray and other highly multiplexed systems. Precision functions, summarizing routine precision metrics estimated from appropriately repeated measurements of one or more reference materials as functions of signal level, are demonstrated and merit further development for characterizing measurement platforms, monitoring changes in measurement system performance, and comparing performance among laboratories or analysts.</p

DNMT3b overexpression contributes to a hypermethylator phenotype in human breast cancer cell lines

<p>Abstract</p> <p>Background</p> <p>DNA hypermethylation events and other epimutations occur in many neoplasms, producing gene expression changes that contribute to neoplastic transformation, tumorigenesis, and tumor behavior. Some human cancers exhibit a hypermethylator phenotype, characterized by concurrent DNA methylation-dependent silencing of multiple genes. To determine if a hypermethylation defect occurs in breast cancer, the expression profile and promoter methylation status of methylation-sensitive genes were evaluated among breast cancer cell lines.</p> <p>Results</p> <p>The relationship between gene expression (assessed by RT-PCR and quantitative real-time PCR), promoter methylation (assessed by methylation-specific PCR, bisulfite sequencing, and 5-aza-2'deoxycytidine treatment), and the DNA methyltransferase machinery (total DNMT activity and expression of DNMT1, DNMT3a, and DNMT3b proteins) were examined in 12 breast cancer cell lines. Unsupervised cluster analysis of the expression of 64 methylation-sensitive genes revealed two groups of cell lines that possess distinct methylation signatures: (i) hypermethylator cell lines, and (ii) low-frequency methylator cell lines. The hypermethylator cell lines are characterized by high rates of concurrent methylation of six genes (<it>CDH1, CEACAM6, CST6, ESR1, LCN2, SCNN1A</it>), whereas the low-frequency methylator cell lines do not methylate these genes. Hypermethylator cell lines coordinately overexpress total DNMT activity and DNMT3b protein levels compared to normal breast epithelial cells. In contrast, most low-frequency methylator cell lines possess DNMT activity and protein levels that are indistinguishable from normal. Microarray data mining identified a strong cluster of primary breast tumors that express the hypermethylation signature defined by <it>CDH1</it>, <it>CEACAM6, CST6, ESR1, LCN2</it>, and <it>SCNN1A</it>. This subset of breast cancers represents 18/88 (20%) tumors in the dataset analyzed, and 100% of these tumors were classified as basal-like, suggesting that the hypermethylator defect cosegregates with poor prognosis breast cancers.</p> <p>Conclusion</p> <p>These observations combine to strongly suggest that: (a) a subset of breast cancer cell lines express a hypermethylator phenotype, (b) the hypermethylation defect in these breast cancer cell lines is related to aberrant overexpression of DNMT activity, (c) overexpression of DNMT3b protein significantly contributes to the elevated DNMT activity observed in tumor cells expressing this phenotype, and (d) the six-gene hypermethylator signature characterized in breast cancer cell lines defines a distinct cluster of primary basal-like breast cancers.</p

Translational profiling of hypocretin neurons identifies candidate molecules for sleep regulation

Hypocretin (orexin; Hcrt)-containing neurons of the hypothalamus are essential for the normal regulation of sleep and wake behaviors and have been implicated in feeding, anxiety, depression, and reward. The absence of these neurons causes narcolepsy in humans and model organisms. However, little is known about the molecular phenotype of these cells; previous attempts at comprehensive profiling had only limited sensitivity or were inaccurate. We generated a Hcrt translating ribosome affinity purification (bacTRAP) line for comprehensive translational profiling of all ribosome-bound transcripts in these neurons in vivo. From this profile, we identified >6000 transcripts detectably expressed above background and 188 transcripts that are highly enriched in these neurons, including all known markers of the cells. Blinded analysis of in situ hybridization databases suggests that ∼60% of these are expressed in a Hcrt marker-like pattern. Fifteen of these were confirmed with double labeling and microscopy, including the transcription factor Lhx9. Ablation of this gene results in a >30% loss specifically of Hcrt neurons, without a general disruption of hypothalamic development. Polysomnography and activity monitoring revealed a profound hypersomnolence in these mice. These data provide an in-depth and accurate profile of Hcrt neuron gene expression and suggest that Lhx9 may be important for specification or survival of a subset of these cells

Patients' constructions of disability in metastatic spinal cord compression

Metastatic spinal cord compression (MSCC) is characterised by poor prognosis and serious physical disability. Patients have complex rehabilitation needs, but the evidence on rehabilitation is sparse. This study aimed to ascertain the constructions placed upon disability by patients with MSCC. A series of nine process-tracing, longitudinal case studies, involving 58 interviews with 9 patients, 6 carers, and 29 staff in one NHS region. A context-mechanism-outcome configuration was adopted as a conceptual basis for data collection, together with a constant comparative method of data analysis. Patients’ orientation to disability incorporated two apparently inconsistent attitudes. Patients acknowledged that their situation had changed, and that their future plans would need to accommodate altered circumstances. However, they also resisted the idea of themselves as disabled, wanting to retain an image of themselves as resourceful and resilient. Patients used a number of strategies to reconcile the tension between these two positions. The illusions incorporated into the ‘failure to acknowledge’ pole of this orientation are self-protective and, like other positive illusions, have psychological benefits. Providing effective and acceptable support to patients living with disability relies on professional responses that are able to sustain patients’ sense of their own competence

The Reproducibility of Lists of Differentially Expressed Genes in Microarray Studies

Reproducibility is a fundamental requirement in scientific experiments and clinical contexts. Recent publications raise concerns about the reliability of microarray technology because of the apparent lack of agreement between lists of differentially expressed genes (DEGs). In this study we demonstrate that (1) such discordance may stem from ranking and selecting DEGs solely by statistical significance (P) derived from widely used simple t-tests; (2) when fold change (FC) is used as the ranking criterion, the lists become much more reproducible, especially when fewer genes are selected; and (3) the instability of short DEG lists based on P cutoffs is an expected mathematical consequence of the high variability of the t-values. We recommend the use of FC ranking plus a non-stringent P cutoff as a baseline practice in order to generate more reproducible DEG lists. The FC criterion enhances reproducibility while the P criterion balances sensitivity and specificity

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The balance of reproducibility, sensitivity, and specificity of lists of differentially expressed genes in microarray studies

<p>Abstract</p> <p>Background</p> <p>Reproducibility is a fundamental requirement in scientific experiments. Some recent publications have claimed that microarrays are unreliable because lists of differentially expressed genes (DEGs) are not reproducible in similar experiments. Meanwhile, new statistical methods for identifying DEGs continue to appear in the scientific literature. The resultant variety of existing and emerging methods exacerbates confusion and continuing debate in the microarray community on the appropriate choice of methods for identifying reliable DEG lists.</p> <p>Results</p> <p>Using the data sets generated by the MicroArray Quality Control (MAQC) project, we investigated the impact on the reproducibility of DEG lists of a few widely used gene selection procedures. We present comprehensive results from inter-site comparisons using the same microarray platform, cross-platform comparisons using multiple microarray platforms, and comparisons between microarray results and those from TaqMan – the widely regarded "standard" gene expression platform. Our results demonstrate that (1) previously reported discordance between DEG lists could simply result from ranking and selecting DEGs solely by statistical significance (<it>P</it>) derived from widely used simple <it>t</it>-tests; (2) when fold change (FC) is used as the ranking criterion with a non-stringent <it>P</it>-value cutoff filtering, the DEG lists become much more reproducible, especially when fewer genes are selected as differentially expressed, as is the case in most microarray studies; and (3) the instability of short DEG lists solely based on <it>P</it>-value ranking is an expected mathematical consequence of the high variability of the <it>t</it>-values; the more stringent the <it>P</it>-value threshold, the less reproducible the DEG list is. These observations are also consistent with results from extensive simulation calculations.</p> <p>Conclusion</p> <p>We recommend the use of FC-ranking plus a non-stringent <it>P </it>cutoff as a straightforward and baseline practice in order to generate more reproducible DEG lists. Specifically, the <it>P</it>-value cutoff should not be stringent (too small) and FC should be as large as possible. Our results provide practical guidance to choose the appropriate FC and <it>P</it>-value cutoffs when selecting a given number of DEGs. The FC criterion enhances reproducibility, whereas the <it>P </it>criterion balances sensitivity and specificity.</p

The 2010 Interim Report of the Long-Baseline Neutrino Experiment Collaboration Physics Working Groups

Corresponding author R.J.Wilson ([email protected]); 113 pages, 90 figuresCorresponding author R.J.Wilson ([email protected]); 113 pages, 90 figuresIn early 2010, the Long-Baseline Neutrino Experiment (LBNE) science collaboration initiated a study to investigate the physics potential of the experiment with a broad set of different beam, near- and far-detector configurations. Nine initial topics were identified as scientific areas that motivate construction of a long-baseline neutrino experiment with a very large far detector. We summarize the scientific justification for each topic and the estimated performance for a set of far detector reference configurations. We report also on a study of optimized beam parameters and the physics capability of proposed Near Detector configurations. This document was presented to the collaboration in fall 2010 and updated with minor modifications in early 2011

The 2010 Interim Report of the Long-Baseline Neutrino Experiment Collaboration Physics Working Groups

In early 2010, the Long-Baseline Neutrino Experiment (LBNE) science collaboration initiated a study to investigate the physics potential of the experiment with a broad set of different beam, near- and far-detector configurations. Nine initial topics were identified as scientific areas that motivate construction of a long-baseline neutrino experiment with a very large far detector. We summarize the scientific justification for each topic and the estimated performance for a set of far detector reference configurations. We report also on a study of optimized beam parameters and the physics capability of proposed Near Detector configurations. This document was presented to the collaboration in fall 2010 and updated with minor modifications in early 2011.Comment: Corresponding author R.J.Wilson ([email protected]); 113 pages, 90 figure