IQRray, a new method for Affymetrix microarray quality control, and the homologous organ conservation score, a new benchmark method for quality control metrics.

MOTIVATION: Microarray results accumulated in public repositories are widely reused in meta-analytical studies and secondary databases. The quality of the data obtained with this technology varies from experiment to experiment, and an efficient method for quality assessment is necessary to ensure their reliability. RESULTS: The lack of a good benchmark has hampered evaluation of existing methods for quality control. In this study, we propose a new independent quality metric that is based on evolutionary conservation of expression profiles. We show, using 11 large organ-specific datasets, that IQRray, a new quality metrics developed by us, exhibits the highest correlation with this reference metric, among 14 metrics tested. IQRray outperforms other methods in identification of poor quality arrays in datasets composed of arrays from many independent experiments. In contrast, the performance of methods designed for detecting outliers in a single experiment like Normalized Unscaled Standard Error and Relative Log Expression was low because of the inability of these methods to detect datasets containing only low-quality arrays and because the scores cannot be directly compared between experiments. AVAILABILITY AND IMPLEMENTATION: The R implementation of IQRray is available at: ftp://lausanne.isb-sib.ch/pub/databases/Bgee/general/IQRray.R. CONTACT: Marta.Rosikiewicz@unil.ch SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Protein-Binding Microarray Analysis of Tumor Suppressor AP2α Target Gene Specificity.

Cheap and massively parallel methods to assess the DNA-binding specificity of transcription factors are actively sought, given their prominent regulatory role in cellular processes and diseases. Here we evaluated the use of protein-binding microarrays (PBM) to probe the association of the tumor suppressor AP2α with 6000 human genomic DNA regulatory sequences. We show that the PBM provides accurate relative binding affinities when compared to quantitative surface plasmon resonance assays. A PBM-based study of human healthy and breast tumor tissue extracts allowed the identification of previously unknown AP2α target genes and it revealed genes whose direct or indirect interactions with AP2α are affected in the diseased tissues. AP2α binding and regulation was confirmed experimentally in human carcinoma cells for novel target genes involved in tumor progression and resistance to chemotherapeutics, providing a molecular interpretation of AP2α role in cancer chemoresistance. Overall, we conclude that this approach provides quantitative and accurate assays of the specificity and activity of tumor suppressor and oncogenic proteins in clinical samples, interfacing genomic and proteomic assays.

Selecting control genes for RT-QPCR using public microarray data.

Background: Gene expression analysis has emerged as a major biological research area, with real-time quantitative reverse transcription PCR (RT-QPCR) being one of the most accurate and widely used techniques for expression profiling of selected genes. In order to obtain results that are comparable across assays, a stable normalization strategy is required. In general, the normalization of PCR measurements between different samples uses one to several control genes (e. g. housekeeping genes), from which a baseline reference level is constructed. Thus, the choice of the control genes is of utmost importance, yet there is not a generally accepted standard technique for screening a large number of candidates and identifying the best ones. Results: We propose a novel approach for scoring and ranking candidate genes for their suitability as control genes. Our approach relies on publicly available microarray data and allows the combination of multiple data sets originating from different platforms and/or representing different pathologies. The use of microarray data allows the screening of tens of thousands of genes, producing very comprehensive lists of candidates. We also provide two lists of candidate control genes: one which is breast cancer-specific and one with more general applicability. Two genes from the breast cancer list which had not been previously used as control genes are identified and validated by RT-QPCR. Open source R functions are available at http://www.isrec.isb-sib.ch/similar to vpopovic/research/ Conclusion: We proposed a new method for identifying candidate control genes for RT-QPCR which was able to rank thousands of genes according to some predefined suitability criteria and we applied it to the case of breast cancer. We also empirically showed that translating the results from microarray to PCR platform was achievable.

Impact of normalization on miRNA microarray expression profiling.

Profiling miRNA levels in cells with miRNA microarrays is becoming a widely used technique. Although normalization methods for mRNA gene expression arrays are well established, miRNA array normalization has so far not been investigated in detail. In this study we investigate the impact of normalization on data generated with the Agilent miRNA array platform. We have developed a method to select nonchanging miRNAs (invariants) and use them to compute linear regression normalization coefficients or variance stabilizing normalization (VSN) parameters. We compared the invariants normalization to normalization by scaling, quantile, and VSN with default parameters as well as to no normalization using samples with strong differential expression of miRNAs (heart-brain comparison) and samples where only a few miRNAs are affected (by p53 overexpression in squamous carcinoma cells versus control). All normalization methods performed better than no normalization. Normalization procedures based on the set of invariants and quantile were the most robust over all experimental conditions tested. Our method of invariant selection and normalization is not limited to Agilent miRNA arrays and can be applied to other data sets including those from one color miRNA microarray platforms, focused gene expression arrays, and gene expression analysis using quantitative PCR.

Effects of mitotane on gene expression in the adrenocortical cell line NCI-H295R: a microarray study.

Aim: The adrenolytic agent mitotane is widely used in the treatment of adrenocortical cancer; however, its mechanism of action is poorly elucidated. We have studied mitotane-induced mRNA expression changes in the NCI-H295R adrenocortical cancer cell line. Materials & methods: Cell viability and hormone assays were used to select the optimal mitotane concentration effectively inhibiting hormone secretion without affecting cell viability. RNA isolated from cultures treated for 48 and 72 h was subjected to Agilent 4×44K microarray platforms. Microarray results were validated by quantitative reverse-transcription PCR. Results: Altogether, 117 significantly differentially expressed genes were detected at 48 h and 72 h (p < 0.05) in mitotane-treated samples relative to controls. Three significantly underexpressed genes involved in steroid hormone biosynthesis (HSD3B1, HSD3B2 and CYP21A2) and four significantly overexpressed genes (GDF15, ALDH1L2, TRIB3 and SERPINE2) have been validated. Conclusion: Gene-expression changes might be involved in the adrenal action of mitotane and in the inhibition of hormone secretion. Original submitted 20 January 2012; Revision submitted 17 May 2012.

Puce a ADN: pourquoi et pour qui [Array CGH: why and to whom]

Structural genomic abnormalities play a key role in the pathogenesis of human disorders and represent one of the first causes of mental impairment, complex syndromes and tumors. In order to detect these chromosomal abnormalities, many methodologies have been developed with limits. The new ARRAY based Comparative Genomic Hybridization (ARRAY CGH) is a revolutionary approach which allows to characterize very small genetic abnormalities undetectable by the standard approaches and in the absence of any associated clinical information. The aim of this article is to describe why the application of a new array CGH methodology is necessary in the etiological search for genetic diseases, what the limits of the standard approaches are and to whom arrayCGH analyses can be applied in a pediatric environment. Examples of our practice will be presented.

Tissue microarray and immunohistochemistry as tools for evaluation of antibodies against Chlamydia-like bacteria.

Tissue microarray technology was used to establish immunohistochemistry protocols and to determine the specificity of new antisera against various Chlamydia-like bacteria for future use on formalin-fixed and paraffin-embedded tissues. The antisera exhibited strong reactivity against autologous antigen and closely related heterologous antigen, but no cross-reactivity with distantly related species.

The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models.

Gene expression data from microarrays are being applied to predict preclinical and clinical endpoints, but the reliability of these predictions has not been established. In the MAQC-II project, 36 independent teams analyzed six microarray data sets to generate predictive models for classifying a sample with respect to one of 13 endpoints indicative of lung or liver toxicity in rodents, or of breast cancer, multiple myeloma or neuroblastoma in humans. In total, >30,000 models were built using many combinations of analytical methods. The teams generated predictive models without knowing the biological meaning of some of the endpoints and, to mimic clinical reality, tested the models on data that had not been used for training. We found that model performance depended largely on the endpoint and team proficiency and that different approaches generated models of similar performance. The conclusions and recommendations from MAQC-II should be useful for regulatory agencies, study committees and independent investigators that evaluate methods for global gene expression analysis.

Identification of molecular apocrine breast tumours by microarray analysis.

Previous microarray studies on breast cancer identified multiple tumour classes, of which the most prominent, named luminal and basal, differ in expression of the oestrogen receptor alpha gene (ER). We report here the identification of a group of breast tumours with increased androgen signalling and a 'molecular apocrine' gene expression profile. Tumour samples from 49 patients with large operable or locally advanced breast cancers were tested on Affymetrix U133A gene expression microarrays. Principal components analysis and hierarchical clustering split the tumours into three groups: basal, luminal and a group we call molecular apocrine. All of the molecular apocrine tumours have strong apocrine features on histological examination (P=0.0002). The molecular apocrine group is androgen receptor (AR) positive and contains all of the ER-negative tumours outside the basal group. Kolmogorov-Smirnov testing indicates that oestrogen signalling is most active in the luminal group, and androgen signalling is most active in the molecular apocrine group. ERBB2 amplification is commoner in the molecular apocrine than the other groups. Genes that best split the three groups were identified by Wilcoxon test. Correlation of the average expression profile of these genes in our data with the expression profile of individual tumours in four published breast cancer studies suggest that molecular apocrine tumours represent 8-14% of tumours in these studies. Our data show that it is possible with microarray data to divide mammary tumour cells into three groups based on steroid receptor activity: luminal (ER+ AR+), basal (ER- AR-) and molecular apocrine (ER- AR+).

Microarray and RNAi Analysis of P450s in Anopheles gambiae Male and Female Steroidogenic Tissues: CYP307A1 Is Required for Ecdysteroid Synthesis.

In insects, the steroid hormone 20-hydroxyecdysone (20E) coordinates major developmental transitions. While the first and the final steps of 20E biosynthesis are characterized, the pathway from 7-dehydrocholesterol to 5β-ketodiol, commonly referred as the "black box", remains hypothetical and whether there are still unidentified enzymes is unknown. The black box would include some oxidative steps, which are believed to be mediated by P450 enzymes. To identify new enzyme(s) involved in steroid synthesis, we analyzed by small-scale microarray the expression of all the genes encoding P450 enzymes of the malaria mosquito Anopheles gambiae in active steroidogenic organs of adults, ovaries from blood-fed females and male reproductive tracts, compared to inactive steroidogenic organs, ovaries from non-blood-fed females. Some genes encoding P450 enzymes were specifically overexpressed in female ovaries after a blood-meal or in male reproductive tracts but only three genes were found to be overexpressed in active steroidogenic organs of both females and males: cyp307a1, cyp4g16 and cyp6n1. Among these genes, only cyp307a1 has an expression pattern similar to other mosquito steroidogenic genes. Moreover, loss-of-function by transient RNAi targeting cyp307a1 disrupted ecdysteroid production demonstrating that this gene is required for ecdysteroid biosynthesis in Anopheles gambiae.

Test of four colon cancer risk-scores in formalin fixed paraffin embedded microarray gene expression data.

BACKGROUND: Prognosis prediction for resected primary colon cancer is based on the T-stage Node Metastasis (TNM) staging system. We investigated if four well-documented gene expression risk scores can improve patient stratification. METHODS: Microarray-based versions of risk-scores were applied to a large independent cohort of 688 stage II/III tumors from the PETACC-3 trial. Prognostic value for relapse-free survival (RFS), survival after relapse (SAR), and overall survival (OS) was assessed by regression analysis. To assess improvement over a reference, prognostic model was assessed with the area under curve (AUC) of receiver operating characteristic (ROC) curves. All statistical tests were two-sided, except the AUC increase. RESULTS: All four risk scores (RSs) showed a statistically significant association (single-test, P < .0167) with OS or RFS in univariate models, but with HRs below 1.38 per interquartile range. Three scores were predictors of shorter RFS, one of shorter SAR. Each RS could only marginally improve an RFS or OS model with the known factors T-stage, N-stage, and microsatellite instability (MSI) status (AUC gains < 0.025 units). The pairwise interscore discordance was never high (maximal Spearman correlation = 0.563) A combined score showed a trend to higher prognostic value and higher AUC increase for OS (HR = 1.74, 95% confidence interval [CI] = 1.44 to 2.10, P < .001, AUC from 0.6918 to 0.7321) and RFS (HR = 1.56, 95% CI = 1.33 to 1.84, P < .001, AUC from 0.6723 to 0.6945) than any single score. CONCLUSIONS: The four tested gene expression-based risk scores provide prognostic information but contribute only marginally to improving models based on established risk factors. A combination of the risk scores might provide more robust information. Predictors of RFS and SAR might need to be different.

Proof of concept for microarray-based detection of DNA-binding oncogenes in cell extracts.

The function of DNA-binding proteins is controlled not just by their abundance, but mainly at the level of their activity in terms of their interactions with DNA and protein targets. Moreover, the affinity of such transcription factors to their target sequences is often controlled by co-factors and/or modifications that are not easily assessed from biological samples. Here, we describe a scalable method for monitoring protein-DNA interactions on a microarray surface. This approach was designed to determine the DNA-binding activity of proteins in crude cell extracts, complementing conventional expression profiling arrays. Enzymatic labeling of DNA enables direct normalization of the protein binding to the microarray, allowing the estimation of relative binding affinities. Using DNA sequences covering a range of affinities, we show that the new microarray-based method yields binding strength estimates similar to low-throughput gel mobility-shift assays. The microarray is also of high sensitivity, as it allows the detection of a rare DNA-binding protein from breast cancer cells, the human tumor suppressor AP-2. This approach thus mediates precise and robust assessment of the activity of DNA-binding proteins and takes present DNA-binding assays to a high throughput level.

Monitoring of malaria parasite resistance to chloroquine and sulphadoxine-pyrimethamine in the Solomon Islands by DNA microarray technology.

BACKGROUND: Little information is available on resistance to anti-malarial drugs in the Solomon Islands (SI). The analysis of single nucleotide polymorphisms (SNPs) in drug resistance associated parasite genes is a potential alternative to classical time- and resource-consuming in vivo studies to monitor drug resistance. Mutations in pfmdr1 and pfcrt were shown to indicate chloroquine (CQ) resistance, mutations in pfdhfr and pfdhps indicate sulphadoxine-pyrimethamine (SP) resistance, and mutations in pfATPase6 indicate resistance to artemisinin derivatives. METHODS: The relationship between the rate of treatment failure among 25 symptomatic Plasmodium falciparum-infected patients presenting at the clinic and the pattern of resistance-associated SNPs in P. falciparum infecting 76 asymptomatic individuals from the surrounding population was investigated. The study was conducted in the SI in 2004. Patients presenting at a local clinic with microscopically confirmed P. falciparum malaria were recruited and treated with CQ+SP. Rates of treatment failure were estimated during a 28-day follow-up period. In parallel, a DNA microarray technology was used to analyse mutations associated with CQ, SP, and artemisinin derivative resistance among samples from the asymptomatic community. Mutation and haplotype frequencies were determined, as well as the multiplicity of infection. RESULTS: The in vivo study showed an efficacy of 88% for CQ+SP to treat P. falciparum infections. DNA microarray analyses indicated a low diversity in the parasite population with one major haplotype present in 98.7% of the cases. It was composed of fixed mutations at position 86 in pfmdr1, positions 72, 75, 76, 220, 326 and 356 in pfcrt, and positions 59 and 108 in pfdhfr. No mutation was observed in pfdhps or in pfATPase6. The mean multiplicity of infection was 1.39. CONCLUSION: This work provides the first insight into drug resistance markers of P. falciparum in the SI. The obtained results indicated the presence of a very homogenous P. falciparum population circulating in the community. Although CQ+SP could still clear most infections, seven fixed mutations associated with CQ resistance and two fixed mutations related to SP resistance were observed. Whether the absence of mutations in pfATPase6 indicates the efficacy of artemisinin derivatives remains to be proven.

A simple, robust and rapid approach to detect carbapenemases in Gram-negative isolates by MALDI-TOF mass spectrometry: validation with triple quadripole tandem mass spectrometry, microarray and PCR.

Carbapenemases should be accurately and rapidly detected, given their possible epidemiological spread and their impact on treatment options. Here, we developed a simple, easy and rapid matrix-assisted laser desorption ionization-time of flight (MALDI-TOF)-based assay to detect carbapenemases and compared this innovative test with four other diagnostic approaches on 47 clinical isolates. Tandem mass spectrometry (MS-MS) was also used to determine accurately the amount of antibiotic present in the supernatant after 1 h of incubation and both MALDI-TOF and MS-MS approaches exhibited a 100% sensitivity and a 100% specificity. By comparison, molecular genetic techniques (Check-MDR Carba PCR and Check-MDR CT103 microarray) showed a 90.5% sensitivity and a 100% specificity, as two strains of Aeromonas were not detected because their chromosomal carbapenemase is not targeted by probes used in both kits. Altogether, this innovative MALDI-TOF-based approach that uses a stable 10-μg disk of ertapenem was highly efficient in detecting carbapenemase, with a sensitivity higher than that of PCR and microarray.