BASE - 2nd generation software for microarray data management and analysis

<p>Abstract</p> <p>Background</p> <p>Microarray experiments are increasing in size and samples are collected asynchronously over long time. Available data are re-analysed as more samples are hybridized. Systematic use of collected data requires tracking of biomaterials, array information, raw data, and assembly of annotations. To meet the information tracking and data analysis challenges in microarray experiments we reimplemented and improved BASE version 1.2.</p> <p>Results</p> <p>The new BASE presented in this report is a comprehensive annotable local microarray data repository and analysis application providing researchers with an efficient information management and analysis tool. The information management system tracks all material from biosource, via sample and through extraction and labelling to raw data and analysis. All items in BASE can be annotated and the annotations can be used as experimental factors in downstream analysis. BASE stores all microarray experiment related data regardless if analysis tools for specific techniques or data formats are readily available. The BASE team is committed to continue improving and extending BASE to make it usable for even more experimental setups and techniques, and we encourage other groups to target their specific needs leveraging on the infrastructure provided by BASE.</p> <p>Conclusion</p> <p>BASE is a comprehensive management application for information, data, and analysis of microarray experiments, available as free open source software at <url>http://base.thep.lu.se</url> under the terms of the GPLv3 license.</p

Normalization of array-CGH data: influence of copy number imbalances

<p>Abstract</p> <p>Background</p> <p>High-resolution microarray-based comparative genomic hybridization (CGH) techniques have successfully been applied to study copy number imbalances in a number of settings such as the analysis of cancer genomes. For normalization of array-CGH data, methods initially developed for gene expression microarray analysis have, in general, been directly adopted and used. However, these methods are designed to work under assumptions that may not be valid for array-CGH data when copy number imbalances are present. We therefore sought to investigate the effect on normalization imposed by copy number imbalances.</p> <p>Results</p> <p>Here we demonstrate that copy number imbalances correlate with intensity in array-CGH data thereby causing problems for conventional normalization methods. We propose a strategy to circumvent these problems by taking copy number imbalances into account during normalization, and we test the proposed strategy using several data sets from the analysis of cancer genomes. In addition, we show how the strategy can be applied to conveniently define adaptive sample-specific boundaries between balanced copy number, losses, and gains to facilitate management of variation in tissue heterogeneity when calling copy number changes.</p> <p>Conclusion</p> <p>We highlight the importance of considering copy number imbalances during normalization of array-CGH data, and show how failure to do so can deleteriously affect data and hamper interpretation.</p

Tasquinimod (ABR-215050), a quinoline-3-carboxamide anti-angiogenic agent, modulates the expression of thrombospondin-1 in human prostate tumors

<p>Abstract</p> <p>Background</p> <p>The orally active quinoline-3-carboxamide tasquinimod [ABR-215050; CAS number 254964-60-8), which currently is in a phase II-clinical trial in patients against metastatic prostate cancer, exhibits anti-tumor activity via inhibition of tumor angiogenesis in human and rodent tumors. To further explore the mode of action of tasquinimod, <it>in vitro </it>and <it>in vivo </it>experiments with gene microarray analysis were performed using LNCaP prostate tumor cells. The array data were validated by real-time semiquantitative reversed transcriptase polymerase chain reaction (sqRT-PCR) and protein expression techniques.</p> <p>Results</p> <p>One of the most significant differentially expressed genes both <it>in vitro </it>and <it>in vivo </it>after exposure to tasquinimod, was thrombospondin-1 (TSP1). The up-regulation of TSP1 mRNA in LNCaP tumor cells both <it>in vitro </it>and <it>in vivo </it>correlated with an increased expression and extra cellular secretion of TSP1 protein. When nude mice bearing CWR-22RH human prostate tumors were treated with oral tasquinimod, there was a profound growth inhibition, associated with an up-regulation of TSP1 and a down- regulation of HIF-1 alpha protein, androgen receptor protein (AR) and glucose transporter-1 protein within the tumor tissue. Changes in TSP1 expression were paralleled by an anti-angiogenic response, as documented by decreased or unchanged tumor tissue levels of VEGF (a HIF-1 alpha down stream target) in the tumors from tasquinimod treated mice.</p> <p>Conclusions</p> <p>We conclude that tasquinimod-induced up-regulation of TSP1 is part of a mechanism involving down-regulation of HIF1α and VEGF, which in turn leads to reduced angiogenesis via inhibition of the "angiogenic switch", that could explain tasquinimods therapeutic potential.</p

Non-coding antisense transcription detected by conventional and single-stranded cDNA microarray

<p>Abstract</p> <p>Background</p> <p>Recent studies revealed that many mammalian protein-coding genes also transcribe their complementary strands. This phenomenon raises questions regarding the validity of data obtained from double-stranded cDNA microarrays since hybridization to both strands may occur. Here, we wanted to analyze experimentally the incidence of antisense transcription in human cells and to estimate their influence on protein coding expression patterns obtained by double-stranded microarrays. Therefore, we profiled transcription of sense and antisense independently by using strand-specific cDNA microarrays.</p> <p>Results</p> <p>Up to 88% of expressed protein coding loci displayed concurrent expression from the complementary strand. Antisense transcription is cell specific and showed a strong tendency to be positively correlated to the expression of the sense counterparts. Even if their expression is wide-spread, detected antisense signals seem to have a limited distorting effect on sense profiles obtained with double-stranded probes.</p> <p>Conclusion</p> <p>Antisense transcription in humans can be far more common than previously estimated. However, it has limited influence on expression profiles obtained with conventional cDNA probes. This can be explained by a biological phenomena and a bias of the technique: a) a co-ordinate sense and antisense expression variation and b) a bias for sense-hybridization to occur with more efficiency, presumably due to variable exonic overlap between antisense transcripts.</p

BioArray Software Environment (BASE): a platform for comprehensive management and analysis of microarray data

The microarray technique requires the organization and analysis of vast amounts of data. These data include information about the samples hybridized, the hybridization images and their extracted data matrices, and information about the physical array, the features and reporter molecules. We present a web-based customizable bioinformatics solution called BioArray Software Environment (BASE) for the management and analysis of all areas of microarray experimentation. All software necessary to run a local server is freely available

Normalization of Illumina Infinium whole-genome SNP data improves copy number estimates and allelic intensity ratios

<p>Abstract</p> <p>Background</p> <p>Illumina Infinium whole genome genotyping (WGG) arrays are increasingly being applied in cancer genomics to study gene copy number alterations and allele-specific aberrations such as loss-of-heterozygosity (LOH). Methods developed for normalization of WGG arrays have mostly focused on diploid, normal samples. However, for cancer samples genomic aberrations may confound normalization and data interpretation. Therefore, we examined the effects of the conventionally used normalization method for Illumina Infinium arrays when applied to cancer samples.</p> <p>Results</p> <p>We demonstrate an asymmetry in the detection of the two alleles for each SNP, which deleteriously influences both allelic proportions and copy number estimates. The asymmetry is caused by a remaining bias between the two dyes used in the Infinium II assay after using the normalization method in Illumina's proprietary software (BeadStudio). We propose a quantile normalization strategy for correction of this dye bias. We tested the normalization strategy using 535 individual hybridizations from 10 data sets from the analysis of cancer genomes and normal blood samples generated on Illumina Infinium II 300 k version 1 and 2, 370 k and 550 k BeadChips. We show that the proposed normalization strategy successfully removes asymmetry in estimates of both allelic proportions and copy numbers. Additionally, the normalization strategy reduces the technical variation for copy number estimates while retaining the response to copy number alterations.</p> <p>Conclusion</p> <p>The proposed normalization strategy represents a valuable tool that improves the quality of data obtained from Illumina Infinium arrays, in particular when used for LOH and copy number variation studies.</p

Segmentation-based detection of allelic imbalance and loss-of-heterozygosity in cancer cells using whole genome SNP arrays

A strategy is presented for detection of loss-of-heterozygosity and allelic imbalance in cancer cells from whole genome SNP genotyping data

RNA sequencing-based single sample predictors of molecular subtype and risk of recurrence for clinical assessment of early-stage breast cancer

BackgroundMultigene expression assays for molecular subtypes and biomarkers can aid clinical management of early invasive breast cancer. Based on RNA-sequencing we aimed to develop single-sample predictor (SSP) models for conventional clinical markers, molecular intrinsic subtype and risk of recurrence (ROR).MethodsA uniformly accrued breast cancer cohort of 7743 patients with RNA-sequencing data from fresh tissue was divided into a training set and a reserved test set. We trained SSPs for PAM50 molecular subtypes and ROR assigned by nearest-centroid (NC) and SSPs for conventional clinical markers from histopathology data. Additionally, SSP classifications were compared with Prosigna® in two external cohorts. Prognostic value was assessed using distant recurrence-free interval.ResultsIn the test set, agreement between SSP and NC classifications for PAM50 (five subtypes) and Subtype (four subtypes) was high (85%, Kappa=0.78) and very high (90%, Kappa=0.84) respectively. Accuracy for ROR risk category was high (84%, Kappa=0.75, weighted Kappa=0.90). The prognostic value for SSP and NC was assessed as equivalent. Agreement for SSP and histopathology was very high or high for receptor status, while moderate and poor for Ki67 status and Nottingham histological grade, respectively. SSP concordance with Prosigna® was high for subtype and moderate and high for ROR risk category. In pooled analysis, concordance between SSP and Prosigna® for emulated treatment recommendation for chemotherapy (yes vs. no) was high (85%, Kappa=0.66). In postmenopausal ER+/HER2-/N0 patients SSP application suggested changed treatment recommendations for up to 17% of patients, with nearly balanced escalation and de-escalation of chemotherapy.ConclusionsSSP models for histopathological variables, PAM50, and ROR classifications can be derived from RNA-sequencing that closely matches clinical tests. Agreement and outcome analyses suggest that NC and SSP models are interchangeable on a group-level and nearly so on a patient level. Retrospective evaluation in postmenopausal ER+/HER2-/N0 patients suggested that molecular testing could lead to a changed therapy recommendation for almost one-fifth of patients

graph2tab, a library to convert experimental workflow graphs into tabular formats

Motivations: Spreadsheet-like tabular formats are ever more popular in the biomedical field as a mean for experimental reporting. The problem of converting the graph of an experimental workflow into a table-based representation occurs in many such formats and is not easy to solve