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Oral tongue cancer gene expression profiling: Identification of novel potential prognosticators by oligonucleotide microarray analysis
Cherry L Estilo, Pornchai O-charoenrat, Simon Talbot, Nicholas D Socci, Diane L Carlson, Ronald Ghossein, Tijaana Williams, Yoshihiro Yonekawa, Yegnanarayana Ramanathan, Jay O Boyle, Dennis H Kraus, Snehal Patel, Ashok R Shaha, Richard J Wong, Joseph M Huryn, Jatin P Shah, Bhuvanesh Singh
BMC Cancer , 2009, DOI: 10.1186/1471-2407-9-11
Abstract: The gene expression profile of patients (n=37) with oral tongue SCC were analyzed using Affymetrix HG_U95Av2 high-density oligonucleotide arrays. Patients (n=20) from which there were available tumor and matched normal mucosa were grouped into stage (early vs. late) and nodal disease (node positive vs. node negative) subgroups and genes differentially expressed in tumor vs. normal and between the subgroups were identified. Three genes, GLUT3, HSAL2, and PACE4, were selected for their potential biological significance in a larger cohort of 49 patients via quantitative real-time RT-PCR.Hierarchical clustering analyses failed to show significant segregation of patients. In patients (n=20) with available tumor and matched normal mucosa, 77 genes were found to be differentially expressed (P< 0.05) in the tongue tumor samples compared to their matched normal controls. Among the 45 over-expressed genes, MMP-1 encoding interstitial collagenase showed the highest level of increase (average: 34.18 folds). Using the criterion of two-fold or greater as overexpression, 30.6%, 24.5% and 26.5% of patients showed high levels of GLUT3, HSAL2 and PACE4, respectively. Univariate analyses demonstrated that GLUT3 over-expression correlated with depth of invasion (P<0.0001), tumor size (P=0.024), pathological stage (P=0.009) and recurrence (P=0.038). HSAL2 was positively associated with depth of invasion (P=0.015) and advanced T stage (P=0.047). In survival studies, only GLUT3 showed a prognostic value with disease-free (P=0.049), relapse-free (P=0.002) and overall survival (P=0.003). PACE4 mRNA expression failed to show correlation with any of the relevant parameters.The characterization of genes identified to be significant predictors of prognosis by oligonucleotide microarray and further validation by real-time RT-PCR offers a powerful strategy for identification of novel targets for prognostication and treatment of oral tongue carcinoma.Cancer arising from the oral cavity accounts fo
Three microarray platforms: an analysis of their concordance in profiling gene expression
David Petersen, GVR Chandramouli, Joel Geoghegan, Joanne Hilburn, Jonathon Paarlberg, Chang Kim, David Munroe, Lisa Gangi, Jing Han, Raj Puri, Lou Staudt, John Weinstein, J Carl Barrett, Jeffrey Green, Ernest S Kawasaki
BMC Genomics , 2005, DOI: 10.1186/1471-2164-6-63
Abstract: The three platforms had 6430 genes in common. In general, correlation of gene expression levels across the platforms was good when defined by concordance in the direction of expression difference (upregulation or downregulation), scatter plot analysis, principal component analysis, cell line correlation or quantitative RT-PCR. The overall correlations (r values) between platforms were in the range 0.7 to 0.8, as determined by analysis of scatter plots. When concordance was measured for expression ratios significant at p-values of <0.05 and at expression threshold levels of 1.5 and 2-fold, the agreement among the platforms was very high, ranging from 93% to 100%.Our results indicate that the long oligonucleotide platform is highly suitable for expression analysis and compares favorably with the cDNA and short oligonucleotide varieties. All three platforms can give similar and reproducible results if the criterion is the direction of change in gene expression and minimal emphasis is placed on the magnitude of change.Completion of the human genome sequence has made it possible to study expression of the entire complement of 20,000–30,000 genes in a single assay. The two most common array platforms are based on collections of cDNA clones [1] or short (25 base) oligonucleotides synthesized in situ by photolithographic methods (i.e., by Affymetrix, Inc.) [2]. Partly because they are easy to use, microarrays are the most extensively used technology for studying gene expression on a global scale [3,4]. Thousands of expression studies employ one or the other microarray platform, but comparison of results between platforms has been difficult because of inherent differences in the array technologies. The situation became more complex as investigators began using long oligonucleotide arrays for expression profiling [5-9].Because long oligonucleotide arrays for expression profiling are relatively new, we wished to validate them in relation to the cDNA and short oligonucleotide p
A strategy for oligonucleotide microarray probe reduction
Alena A Antipova, Pablo Tamayo, Todd R Golub
Genome Biology , 2002, DOI: 10.1186/gb-2002-3-12-research0073
Abstract: The methodology has been tested on a dataset comprising 317 Affymetrix HuGeneFL GeneChips. The performance of the original and reduced probe sets was compared in four cancer-classification problems. The results of these comparisons show that reduction of the probe set by 95% does not dramatically affect performance, and thus illustrate the feasibility of substantially reducing probe numbers without significantly compromising sensitivity and specificity of detection.The strategy described here is potentially useful for designing small, limited-probe genome-wide arrays for screening applications.DNA microarrays have become commonplace for the genome-wide measurement of mRNA expression levels. The first described microarray for this purpose, the cDNA microarray, involves the mechanical deposition of cDNA clones on glass slides [1]. Although this strategy has proved highly effective, it has two limitations: cross-hybridization can occur between mRNAs and non-unique or repetitive portions of the cDNA clone; and the maintenance and quality control of large, arrayed cDNA libraries can be challenging. For these reasons, oligonucleotide microarrays have at least theoretical advantages. Short probes (25 nucleotides or longer) can be selected on the basis of their sequence specificity, and either synthesized in situ (by photolithography or inkjet technology) on a solid surface or conventionally synthesized and then robotically deposited.The first oligonucleotide microarrays contained hundreds of distinct probes per gene in order to maximize sensitivity and specificity of detection [2]. Over the past few years, the number of probes per gene has decreased as increasing amounts of sequence information have become available, probe-selection algorithms have improved, feature sizes have decreased and researchers have wanted to maximize the number of genes assayable on a single microarray. Nevertheless, no single array representing the entire human genome has been described. Furtherm
Microarray Generation of Thousand-Member Oligonucleotide Libraries  [PDF]
Nina Svensen, Juan José Díaz-Mochón, Mark Bradley
PLOS ONE , 2011, DOI: 10.1371/journal.pone.0024906
Abstract: The ability to efficiently and economically generate libraries of defined pieces of DNA would have a myriad of applications, not least in the area of defined or directed sequencing and synthetic biology, but also in applications associated with encoding and tagging. In this manuscript DNA microarrays were used to allow the linear amplification of immobilized DNA sequences from the array followed by PCR amplification. Arrays of increasing sophistication (1, 10, 3,875, 10,000 defined sequences) were used to validate the process, with sequences verified by selective hybridization to a complementary DNA microarray and DNA sequencing, which demonstrated a PCR error rate of 9.7×10?3/site/duplication. This technique offers an economical and efficient way of producing specific DNA libraries of hundreds to thousands of members with the DNA-arrays being used as “factories” allowing specific DNA oligonucleotide pools to be generated. We also found substantial variance observed between the sequence frequencies found via Solexa sequencing and microarray analysis, highlighting the care needed in the interpretation of profiling data.
Construction and validation of a first-generation Bordetella bronchiseptica long-oligonucleotide microarray by transcriptional profiling the Bvg regulon
Tracy L Nicholson
BMC Genomics , 2007, DOI: 10.1186/1471-2164-8-220
Abstract: Based on the genomic sequence and using the freely available software ArrayOligoSelector, a long oligonucleotide B. bronchiseptica microarray was designed and assembled. This long-oligonucleotide microarray was subsequently tested and validated by comparing changes in the global expression profiles between B. bronchiseptica RB50 and its Bvg- phase-locked derivative, RB54. Data from this microarray analysis revealed 1,668 Bvg-regulated genes, which greatly expands the BvgAS regulon defined in previous reports. For previously reported Bvg-regulated transcripts, the gene expression data presented here is congruent with prior findings. Additionally, quantitative real-time PCR data provided an independent verification of the microarray expression values.The results presented here provide a comprehensive, genome-wide portrait of transcripts encompassing the BvgAS regulon, while also providing data validating the long-oligonucleotide microarray described here for studying gene expression in Bordetella bronchiseptica.Bordetellae are Gram negative bacterial respiratory pathogens. Bordetella pertussis and Bordetella parapertussishu, the causative agents of whooping cough, are human-adapted variants of Bordetella bronchiseptica, which naturally infects a broad range of mammals causing chronic and often asymptomatic infections [1]. The majority of gene expression in Bordetella is regulated by a two-component sensory transduction system encoded by the bvg locus. The bvg locus comprises a histidine kinase sensor protein, BvgS, and a DNA-binding response-regulator protein, BvgA. In response to environmental cues, BvgAS controls expression of a spectrum of phenotypic phases transitioning between a virulent (Bvg+) phase and a non-virulent (Bvg-) phase. During the virulent Bvg+ phase, the BvgAS system is fully active and many of the known virulence factors are expressed, such as filamentous hemagglutinin (FHA), pertactin, fimbriae, adenylate cyclase-hemolysin toxin, and dermonecrotic
Oligonucleotide microarray for the identification of potential mycotoxigenic fungi
Sabine Lezar, Eugenia Barros
BMC Microbiology , 2010, DOI: 10.1186/1471-2180-10-87
Abstract: A total of 40 potentially mycotoxigenic fungi isolated from different food commodities, as well as the genes that are involved in the mycotoxin synthetic pathways, were analyzed. For fungal identification, oligonucleotide probes were designed by exploiting the sequence variations of the elongation factor 1-alpha (EF-1 α) coding regions and the internal transcribed spacer (ITS) regions of the rRNA gene cassette. For the detection of fungi able to produce mycotoxins, oligonucleotide probes directed towards genes leading to toxin production from different fungal strains were identified in data available in the public domain. The probes selected for fungal identification and the probes specific for toxin producing genes were spotted onto microarray slides.The diagnostic microarray developed can be used to identify single pure strains or cultures of potentially mycotoxigenic fungi as well as genes leading to toxin production in both laboratory samples and maize-derived foods offering an interesting potential for microbiological laboratories.Mycotoxins are fungal toxins which pose a threat to human, animal and plant health. These toxins can cause acute or chronic toxicity in humans and animals that eat contaminated foods or crops, depending on the quantities produced and consumed [1]. It is estimated that 25% of all food commodities produced on earth are contaminated with mycotoxins due to the fact that fungi develop on these commodities [2]. A study done in South Africa by Rabie et al. [3] showed that mycotoxins such as aflatoxins, beauvericin, deoxynivalenol, moniliformin, trichothecene and zearalenone are contaminants of food commodities. The most known and studied group of mycotoxins in South Africa are fumonisins which have been associated with oesophageal cancer in humans and the cause of leucoencephalomalacia (LEM) in horses, mules and donkeys [4]. It is thus necessary to eliminate or reduce the presence of mycotoxins in the food chain.An important step in controll
Microarray oligonucleotide probe designer: a Web service
Viren C Patel, Kajari Mondal, Amol Carl Shetty, et al
Open Access Bioinformatics , 2010, DOI: http://dx.doi.org/10.2147/OAB.S13741
Abstract: roarray oligonucleotide probe designer: a Web service Methodology (3251) Total Article Views Authors: Viren C Patel, Kajari Mondal, Amol Carl Shetty, et al Published Date November 2010 Volume 2010:2 Pages 145 - 155 DOI: http://dx.doi.org/10.2147/OAB.S13741 Viren C Patel1*, Kajari Mondal1*, Amol Carl Shetty1*, Vanessa L Horner1, Jirair K Bedoyan2, Donna Martin2,3, Tamara Caspary1, David J Cutler1, Michael E Zwick1 1Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA; 2Department of Pediatrics, 3Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA; *These authors contributed equally to this work. Abstract: Methods of genomic selection that combine high-density oligonucleotide microarrays with next-generation DNA sequencing allow investigators to characterize genomic variation in selected portions of complex eukaryotic genomes. However, choosing the specific oligonucleotides to be used can pose a major technical challenge. To address this issue, we have developed a software package called MOPeD (microarray oligonucleotide probe designer), which automates the process of designing genomic selection microarrays. This Web-based software allows individual investigators to design custom genomic selection microarrays optimized for synthesis with Roche NimbleGen’s maskless photolithography. Design parameters include uniqueness of the probe sequences, melting temperature, hairpin formation, and the presence of single-nucleotide polymorphisms. We generated probe databases for the human, mouse, and rhesus macaque genomes and conducted experimental validation of MOPeDdesigned microarrays in human samples by sequencing the human X chromosome exome, where relevant sequence metrics indicated superior performance relative to a microarray designed by the Roche NimbleGen proprietary algorithm. We also performed validation in the mouse to identify known mutations contained within a 487-kb region from mouse chromosome 16, the mouse chromosome 16 exome (1.7 Mb), and the mouse chromosome 12 exome (3.3 Mb). Our results suggest that the open source MOPeD software package and Web site (http://moped.genetics.emory.edu/) will make a valuable resource for investigators in their sequence-based studies of complex eukaryotic genomes.
Correction of scaling mismatches in oligonucleotide microarray data
Martino Barenco, Jaroslav Stark, Daniel Brewer, Daniela Tomescu, Robin Callard, Michael Hubank
BMC Bioinformatics , 2006, DOI: 10.1186/1471-2105-7-251
Abstract: We explain how scaling mismatches occur in data summarized by the popular MAS5 (GCOS; Affymetrix) algorithm, and propose a simple recursive algorithm to correct them. Its principle is to identify a set of constant genes and to use this set to rescale the microarray signals. We study the properties of the algorithm using artificially generated data and apply it to experimental data. We show that the set of constant genes it generates can be used to rescale data from other experiments, provided that the underlying system is similar to the original. We also demonstrate, using a simple example, that the method can successfully correct existing imbalancesin the data.The set of constant genes obtained for a given experiment can be applied to other experiments, provided the systems studied are sufficiently similar. This type of rescaling is especially relevant in systems biology applications using microarray data.Gene expression profiling using microarrays has become a popular technique in modern biochemical research. One of the commonest microarray platforms in use is the high-density oligonucleotide array introduced by Affymetrix (Santa Clara, CA). In the Affymetrix system, biotinylated cRNA generated from the sample of interest is hybridised to the array and detected using fluorescently-labelled streptavidin. A number of different expression summary algorithms are available to derive the concentration of each transcript from the intensity of fluorescence. These include MAS5 (Affymetrix) [1], RMA [2], MBEI [3,4].It is important to use the most accurate and precise methods for calculating gene expression levels from microarray data. MAS5, RMA and MBEI offer different solutions to this problem. On Affymetrix arrays, transcripts are represented by multiple (typically 11) pairs of 25-mer oligonucleotides termed a probeset. One of each pair is a perfect match (PM) for the target and the other is a mismatch control (MM). In MAS5, signal values from MM oligonucleotides are subt
Evaluation of methods for oligonucleotide array data via quantitative real-time PCR
Li-Xuan Qin, Richard P Beyer, Francesca N Hudson, Nancy J Linford, Daryl E Morris, Kathleen F Kerr
BMC Bioinformatics , 2006, DOI: 10.1186/1471-2105-7-23
Abstract: Quantitative reverse-transcription polymerase chain reaction (qRT-PCR) is generally considered the "gold-standard" assay for measuring gene expression by biologists and is often used to confirm findings from microarray data. Here we use qRT-PCR measurements to validate methods for the components of processing oligo array data: background adjustment, normalization, mismatch adjustment, and probeset summary. An advantage of our approach over spike-in studies is that methods are validated on a real dataset that was collected to address a scientific question.We initially identify three of six popular methods that consistently produced the best agreement between oligo array and RT-PCR data for medium- and high-intensity genes. The three methods are generally known as MAS5, gcRMA, and the dChip mismatch mode. For medium- and high-intensity genes, we identified use of data from mismatch probes (as in MAS5 and dChip mismatch) and a sequence-based method of background adjustment (as in gcRMA) as the most important factors in methods' performances. However, we found poor reliability for methods using mismatch probes for low-intensity genes, which is in agreement with previous studies.We advocate use of sequence-based background adjustment in lieu of mismatch adjustment to achieve the best results across the intensity spectrum. No method of normalization or probeset summary showed any consistent advantages.Affymetrix GeneChip? oligonucleotide arrays are a popular platform for the high-throughput analysis of gene expression in mRNA. Nguyen et al [1] give an introduction to the technology for quantitative scientists. Briefly, an oligonucleotide array contains 11–20 probe pairs for each gene. Probe pairs consist of an oligonucleotide that is a "perfect match" (PM) to a subsequence of the mRNA transcript for a gene and a corresponding "mismatch" (MM) oligo that differs from it in one base in the middle. These MM probes are meant to provide information on cross-hybridization.Quanti
A meta-analysis of kidney microarray datasets: investigation of cytokine gene detection and correlation with rt-PCR and detection thresholds
Walter D Park, Mark D Stegall
BMC Genomics , 2007, DOI: 10.1186/1471-2164-8-88
Abstract: Using both publicly available and our own microarray datasets we analyzed the detection p-value and detection call values for 81 human kidney samples run on the U133A or U133Plus2.0 Affymetrix microarrays (Affymetrix, Santa Clara, CA). For the cytokine genes, the frequency of detection in each sample group (normal, transplant and renal cell carcinoma) was examined and revealed that a majority of cytokine related genes are not detectable in human kidney by microarray. Using a subset of 29 Mayo transplant samples, a group of seven transplant-related cytokines and eight non-cytokine genes were evaluated by real-time PCR (rt-PCR). For these 15 genes we compared the impact of decreasing microarray detection frequency with the changes in gene expression observed by both microarray and rt-PCR. We found that as microarray detection frequency decreased the correlation between microarray and rt-PCR data also decreased.We conclude that, when analyzing microarray data from human kidney samples, genes generally expressed at low abundance (i.e. cytokines) should be evaluated with more sensitive approaches such as rt-PCR. In addition, our data suggest that the use of detection frequency cutoffs for inclusion or exclusion of microarray data may be appropriate when comparing microarray and rt-PCR gene expression data and p-value calculations.The recent completion of the human genome project, improvements in gene level annotation and microarray technology have led to a rapid increase in the number of whole genome microarray based studies for researchers interested in understanding the underlying etiology of various human conditions. However, there remain several significant questions to answer with regard to microarray data acquisition and analyses, including the accurate determination of signal intensity, development of optimal analytical strategies and detection limit thresholds.The most common oligonucleotide microarray platform is made by Affymetrix Inc. and uses 25-mer probes to
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