Prediction of alternatively skipped exons and splicing enhancers from exon junction arrays

<p>Abstract</p> <p>Background</p> <p>Alternative splicing of exons in a pre-mRNA transcript is an important mechanism which contributes to protein diversity in human. Arrays for detecting alternative splicing are available using several different probe designs, including those based on exon-junctions. In this work, we introduce a new method for predicting alternatively skipped exons from exon-junction arrays. Predictions based on our method are compared against controls and their sequences are analyzed to identify motifs important for regulating alternative splicing.</p> <p>Results</p> <p>Our comparison of several alternative methods shows that an exon-skipping score based on neighboring junctions best discriminates between positive and negative controls. Sequence analysis of our predicted exons confirms the presence of known splicing regulatory sequences. In addition, we also derive a set of development-related alternatively spliced genes based on fetal versus adult tissue comparisons and find that our predictions are consistent with their functional annotations. <it>Ab initio </it>motif finding algorithms are applied to identify several motifs that may be relevant for splicing during development.</p> <p>Conclusion</p> <p>This work describes a new method for analyzing exon-junction arrays, identifies sequence motifs that are specific for alternative and constitutive splicing and suggests a role for several known splicing factors and their motifs in developmental regulation.</p

Differential gene expression by integrin β7(+ )and β7(- )memory T helper cells

BACKGROUND: The cell adhesion molecule integrin α4β7 helps direct the migration of blood lymphocytes to the intestine and associated lymphoid tissues. We hypothesized that β7(+ )and β7(- )blood memory T helper cells differ in their expression of genes that play a role in the adhesion or migration of T cells. RESULTS: RNA was prepared from β7(+ )and β7(- )CD4(+ )CD45RA(- )blood T cells from nine normal human subjects and analyzed using oligonucleotide microarrays. Of 21357 genes represented on the arrays, 16 were more highly expressed in β7(+ )cells and 18 were more highly expressed in β7(- )cells (≥1.5 fold difference and adjusted P < 0.05). Several of the differentially expressed transcripts encode proteins with established or putative roles in lymphocyte adhesion and chemotaxis, including the chemokine receptors CCR9 and CCR10, the integrin α4 subunit, L-selectin, KLRB1 (CD161), NT5E (CD73), LGALS1 and LGALS2 (galectin-1 and -2), and RGS1. Flow cytometry was used to determine whether differences in levels of transcripts encoding cell surface proteins were associated with differential expression of those proteins. Using this approach, we found that surface expression of KLRB1, LAIR1, and NT5E proteins was higher on β7(+ )memory/effector T cells than on β7(- )cells. CONCLUSIONS: Memory/effector T cells that express integrin β7 have a distinct pattern of expression of a set of gene transcripts. Several of these molecules can affect cell adhesion or chemotaxis and are therefore likely to modulate the complex multistep process that regulates trafficking of CD4(+ )memory T cell subsets with different homing behaviors

The transcriptional response to oxidative stress is part of, but not sufficient for, insulin resistance in adipocytes.

Insulin resistance is a major risk factor for metabolic diseases such as Type 2 diabetes. Although the underlying mechanisms of insulin resistance remain elusive, oxidative stress is a unifying driver by which numerous extrinsic signals and cellular stresses trigger insulin resistance. Consequently, we sought to understand the cellular response to oxidative stress and its role in insulin resistance. Using cultured 3T3-L1 adipocytes, we established a model of physiologically-derived oxidative stress by inhibiting the cycling of glutathione and thioredoxin, which induced insulin resistance as measured by impaired insulin-stimulated 2-deoxyglucose uptake. Using time-resolved transcriptomics, we found > 2000 genes differentially-expressed over 24 hours, with specific metabolic and signalling pathways enriched at different times. We explored this coordination using a knowledge-based hierarchical-clustering approach to generate a temporal transcriptional cascade and identify key transcription factors responding to oxidative stress. This response shared many similarities with changes observed in distinct insulin resistance models. However, an anti-oxidant reversed insulin resistance phenotypically but not transcriptionally, implying that the transcriptional response to oxidative stress is insufficient for insulin resistance. This suggests that the primary site by which oxidative stress impairs insulin action occurs post-transcriptionally, warranting a multi-level 'trans-omic' approach when studying time-resolved responses to cellular perturbations

Infection Control and SARS Transmission among Healthcare Workers, Taiwan

This study found infrequent transmission of severe acute respiratory syndrome (SARS) coronavirus to healthcare workers involved in the care of the first five case-patients in Taiwan, despite a substantial number of unprotected exposures. Nonetheless, given that SARS has been highly transmissible on some occasions, we still recommend strict precautions

Prognostic Factors and Clinical Outcomes of High-Dose Chemotherapy followed by Autologous Stem Cell Transplantation in Patients with Peripheral T Cell Lymphoma, Unspecified: Complete Remission at Transplantation and the Prognostic Index of Peripheral T Cell Lymphoma Are the Major Factors Predictive of Outcome

AbstractHigh-dose chemotherapy followed by autologous stem cell transplantation (HDT/ASCT) offers a rescue option for T cell lymphoma patients with poor prognosis. However, the effectiveness of HDT/ASCT in patients with various peripheral T cell subtypes, optimal transplant timing, and the prognostic factors that predict better outcomes, have not been identified. We retrospectively investigated the clinical outcomes and prognostic factors for HDT/ASCT in 64 Korean patients with peripheral T cell lymphoma, unspecified (PTCL-U) between March 1995 and February 2007. The median age at transplantation was 44 years (range: 15-63 years). According to the age-adjusted International Prognostic Index (a-IPI) and the prognostic index of PTCL (PIT), 8 patients (12.5%) were in the high-risk group and 16 (26.6%) had the 2-3 PIT factors, respectively. After a median follow-up of 29.7 months, the 3-year overall survival (OS) and progression-free survival (PFS) rates were 53.0% ± 7.5% and 44.3% ± 7.0%, respectively. Univariate analysis showed that poor performance status, high lactate dehydrogenase (LDH) levels, high a-IPI score, high PIT classes, failure to achieve complete response (CR) at transplantation, and nonfrontline transplantation were associated with poor OS. Multivariate analysis showed that failure to achieve CR at transplantation (hazard ratio [HR] 2.23; 95% confidence interval [CI] 1.78-7.93) and 2-3 PIT factors (HR 3.76; 95% CI 1.02-5.42) were independent prognostic factors for OS. Failure to achieve CR at transplantation and high PIT are negative predictable factors for survival following HDT/ASCT in patients with PTCL-U

Comparison study of microarray meta-analysis methods

<p>Abstract</p> <p>Background</p> <p>Meta-analysis methods exist for combining multiple microarray datasets. However, there are a wide range of issues associated with microarray meta-analysis and a limited ability to compare the performance of different meta-analysis methods.</p> <p>Results</p> <p>We compare eight meta-analysis methods, five existing methods, two naive methods and a novel approach (mDEDS). Comparisons are performed using simulated data and two biological case studies with varying degrees of meta-analysis complexity. The performance of meta-analysis methods is assessed via ROC curves and prediction accuracy where applicable.</p> <p>Conclusions</p> <p>Existing meta-analysis methods vary in their ability to perform successful meta-analysis. This success is very dependent on the complexity of the data and type of analysis. Our proposed method, mDEDS, performs competitively as a meta-analysis tool even as complexity increases. Because of the varying abilities of compared meta-analysis methods, care should be taken when considering the meta-analysis method used for particular research.</p

Discriminating lymphomas and reactive lymphadenopathy in lymph node biopsies by gene expression profiling

<p>Abstract</p> <p>Background</p> <p>Diagnostic accuracy of lymphoma, a heterogeneous cancer, is essential for patient management. Several ancillary tests including immunophenotyping, and sometimes cytogenetics and PCR are required to aid histological diagnosis. In this proof of principle study, gene expression microarray was evaluated as a single platform test in the differential diagnosis of common lymphoma subtypes and reactive lymphadenopathy (RL) in lymph node biopsies.</p> <p>Methods</p> <p>116 lymph node biopsies diagnosed as RL, classical Hodgkin lymphoma (cHL), diffuse large B cell lymphoma (DLBCL) or follicular lymphoma (FL) were assayed by mRNA microarray. Three supervised classification strategies (global multi-class, local binary-class and global binary-class classifications) using diagonal linear discriminant analysis was performed on training sets of array data and the classification error rates calculated by leave one out cross-validation. The independent error rate was then evaluated by testing the identified gene classifiers on an independent (test) set of array data.</p> <p>Results</p> <p>The binary classifications provided prediction accuracies, between a subtype of interest and the remaining samples, of 88.5%, 82.8%, 82.8% and 80.0% for FL, cHL, DLBCL, and RL respectively. Identified gene classifiers include LIM domain only-2 (<it>LMO2</it>), Chemokine (C-C motif) ligand 22 (<it>CCL22</it>) and Cyclin-dependent kinase inhibitor-3 (<it>CDK3</it>) specifically for FL, cHL and DLBCL subtypes respectively.</p> <p>Conclusions</p> <p>This study highlights the ability of gene expression profiling to distinguish lymphoma from reactive conditions and classify the major subtypes of lymphoma in a diagnostic setting. A cost-effective single platform "mini-chip" assay could, in principle, be developed to aid the quick diagnosis of lymph node biopsies with the potential to incorporate other pathological entities into such an assay.</p

Evasion of anti-growth signaling: a key step in tumorigenesis and potential target for treatment and prophylaxis by natural compounds

The evasion of anti-growth signaling is an important characteristic of cancer cells. In order to continue to proliferate, cancer cells must somehow uncouple themselves from the many signals that exist to slow down cell growth. Here, we define the anti-growth signaling process, and review several important pathways involved in growth signaling: p53, phosphatase and tensin homolog (PTEN), retinoblastoma protein (Rb), Hippo, growth differentiation factor 15 (GDF15), AT-rich interactive domain 1A (ARID1A), Notch, insulin-like growth factor (IGF), and Krüppel-like factor 5 (KLF5) pathways. Aberrations in these processes in cancer cells involve mutations and thus the suppression of genes that prevent growth, as well as mutation and activation of genes involved in driving cell growth. Using these pathways as examples, we prioritize molecular targets that might be leveraged to promote anti-growth signaling in cancer cells. Interestingly, naturally-occurring phytochemicals found in human diets (either singly or as mixtures) may promote anti-growth signaling, and do so without the potentially adverse effects associated with synthetic chemicals. We review examples of naturally-occurring phytochemicals that may be applied to prevent cancer by antagonizing growth signaling, and propose one phytochemical for each pathway. These are: epigallocatechin-3-gallate (EGCG) for the Rb pathway, luteolin for p53, curcumin for PTEN, porphyrins for Hippo, genistein for GDF15, resveratrol for ARID1A, withaferin A for Notch and diguelin for the IGF1-receptor pathway. The coordination of anti-growth signaling and natural compound studies will provide insight into the future application of these compounds in the clinical setting

Measures of Association for Identifying MicroRNA-mRNA Pairs of Biological Interest

MicroRNAs are a class of small non-protein coding RNAs that play an important role in the regulation of gene expression. Most studies on the identification of microRNA-mRNA pairs utilize the correlation coefficient as a measure of association. The use of correlation coefficient is appropriate if the expression data are available for several conditions and, for a given condition, both microRNA and mRNA expression profiles are obtained from the same set of individuals. However, there are many instances where one of the requirements is not satisfied. Therefore, there is a need for new measures of association to identify the microRNA-mRNA pairs of interest and we present two such measures. The first measure requires expression data for multiple conditions but, for a given condition, the microRNA and mRNA expression may be obtained from different individuals. The new measure, unlike the correlation coefficient, is suitable for analyzing large data sets which are obtained by combining several independent studies on microRNAs and mRNAs. Our second measure is able to handle expression data that correspond to just two conditions but, for a given condition, the microRNA and mRNA expression must be obtained from the same set of individuals. This measure, unlike the correlation coefficient, is appropriate for analyzing data sets with a small number of conditions. We apply our new measures of association to multiple myeloma data sets, which cannot be analyzed using the correlation coefficient, and identify several microRNA-mRNA pairs involved in apoptosis and cell proliferation