Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Oligonucleotide Array Sequence Analysis”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 937 records · Page 52Linked to original sources
PubMed2005

Analysis of significance patterns identifies ubiquitous and disease-specific gene-expression signatures in patient peripheral blood leukocytes.

The utilization of gene-expression microarrays in patient-based research creates new prospects for the discovery of diagnostic biomarkers and the identification of genes or pathways linked to pathogenesis. Gene-expression signatures in peripheral blood mononuclear cells isolated from over one hundred patients with conditions presenting a strong immunological component (patient with autoimmune, graft versus host and infectious diseases, as well as immunosuppressed transplant recipients) were generated. This dataset provides the opportunity to carry out comparative analyses and define disease signatures in a broader context. Transcriptional changes of 22,283 probe sets were evaluated through statistical group comparison performed systematically for seven diseases versus their respective healthy control group. Patterns of significance were generated by hierarchical clustering of P-values. This approach led to the identification of a SLE-specific "diagnostic signature," formed by genes that did not change compared to healthy subjects in the other six diseases. Conversely, a "sentinel signature" that was common to all seven diseases was characterized. These findings bring new perspectives for the application of blood leukocyte expression signatures for diagnosis and early disease detection.

Adult↗
PubMed2005

Genomic and protein expression profiling identifies CDK6 as novel independent prognostic marker in medulloblastoma.

PURPOSE: Medulloblastoma is the most common malignant brain tumor in children. Despite multimodal aggressive treatment, nearly half of the patients die as a result of this tumor. Identification of molecular markers for prognosis and development of novel pathogenesis-based therapies depends crucially on a better understanding of medulloblastoma pathomechanisms. PATIENTS AND METHODS: We performed genome-wide analysis of DNA copy number imbalances in 47 medulloblastomas using comparative genomic hybridization to large insert DNA microarrays (matrix-CGH). The expression of selected candidate genes identified by matrix-CGH was analyzed immunohistochemically on tissue microarrays representing medulloblastomas from 189 clinically well-documented patients. To identify novel prognostic markers, genomic findings and protein expression data were correlated to patient survival. RESULTS: Matrix-CGH analysis revealed frequent DNA copy number alterations of several novel candidate regions. Among these, gains at 17q23.2-qter (P < .01) and losses at 17p13.1 to 17p13.3 (P = .04) were significantly correlated to poor prognosis. Within 17q23.2-qter and 7q21.2, two of the most frequently gained chromosomal regions, confined amplicons were identified that contained the PPM1D and CDK6 genes, respectively. Immunohistochemistry revealed strong expression of PPM1D in 148 (88%) of 168 and CDK6 in 50 (30%) of 169 medulloblastomas. Overexpression of CDK6 correlated significantly with poor prognosis (P < .01) and represented an independent prognostic marker of overall survival on multivariate analysis (P = .02). CONCLUSION: We identified CDK6 as a novel molecular marker that can be determined by immunohistochemistry on routinely processed tissue specimens and may facilitate the prognostic assessment of medulloblastoma patients. Furthermore, increased protein-levels of PPM1D and CDK6 may link the TP53 and RB1 tumor suppressor pathways to medulloblastoma pathomechanisms.

Biomarkers, Tumor↗
PubMed2005

Tissue microarrays: bridging the gap between research and the clinic.

Tissue microarrays are a high-throughput method for the investigation of biomarkers in multiple tissue specimens at once. This technique allows for the analysis of up to 500 tissue samples in a single experiment using immunohistochemistry and in situ hybridization. Recently, cell lines and xenografts have been reduced to a tissue microarray format and are being applied to preclinical drug development. In clinical research, tissue microarrays are applied at multiple levels: comprehensive analysis of samples in the context of a clinical trial or across a population. Tissue microarrays play a central role in translational research, facilitating the discovery of molecules that have potential roles in the diagnosis, prognosis and prediction of response to therapy.

Animals↗
PubMed2001

Exploring relationships in gene expressions: a partial least squares approach.

Microarray technology has revolutionized the way gene functions are monitored. Analysis of microarray data is a fast growing research area that interfaces various disciplines such as biology, biochemistry, computer science, and statistics. While various clustering and classification techniques have been successfully employed to group genes based on the similarity of their expression patterns, much is yet to be learned about the interrelationship of the expression levels among various genes. We approach this problem with a statistical technique called partial least squares that is capable of modeling a large number of variables each with relatively few observations. This property of the partial least squares methodology appears to be attractive for application to microarray data sets where the simultaneous expression levels of many genes are collected each at a few time points (or individuals). We use it to analyze publicly available microarray data on sporulation of budding yeast (Saccharomyces cerevisiae). We investigate a number of representative genes, one from each temporal group (based on the time of first induction) of positively expressed genes and show that in each case most of the variability was explained by only two partial regression terms based on all remaining genes. Moreover, the predicted expression levels of the representative genes from partial least squares fit very well on the average with the true expression levels over time. Finally, we compare the biological functions of the genes with largest coefficients with those of the predicted genes. In many cases, the genes are involved in similar or related biological functions including negative relationships. We show that this method can identify established gene relationships; we argue that it can be an exploratory tool for identifying potential gene relationships requiring further biological investigation.

Gene Expression Profiling↗
PubMed2002

How well do we understand the clusters found in microarray data?

We wished to quantify the state-of-the-art of our understanding of clusters in microarray data. To do this we systematically compared the clusters produced on sets of microarray data using a representative set of clustering algorithms (hierarchical, k-means, and a modified version of QT_CLUST) with the annotation schemes MIPS, GeneOntology and GenProtEC. We assumed that if a cluster reflected known biology its members would share related ontological annotations. This assumption is the basis of "guilt-by-association" and is commonly used to assign the putative function of proteins. To statistically measure the relationship between cluster and annotation we developed a new predictive discriminatory measure. We found that the clusters found in microarray data do not in general agree with functional annotation classes. Although many statistically significant relationships can be found, the majority of clusters are not related to known biology (as described in annotation ontologies). This implies that use of guilt-by-association is not supported by annotation ontologies. Depending on the estimate of the amount of noise in the data, our results suggest that bioinformatics has only codified a small proportion of the biological knowledge required to understand microarray data.

Algorithms↗
PubMed2003

Classification and identification of genes associated with oral cancer based on gene expression profiles. A preliminary study.

Oral squamous cell carcinoma (OSCC) is an aggressive malignancy. The five-year survival rate remains largely unchanged for the past 40 years. Early diagnosis has been shown to correlate with increased survival, based on cytologic changes. In order to improve our current treatment strategies for OSCC, it is necessary to understand the genetic and molecular networks underlying this disease. In this preliminary study, we illustrate the application of DNA microarrays to study OSCC. Using computational and statistical algorithms, we were able to differentiate (or classify) "cancer" and "normal" samples based on the behavior of the gene expression profiles. We found 651 genes to be associated with cancer. This article describes a preliminary study of current developments from the Human Genome Project (HGP) and its application to OSCC.

Carcinoma, Squamous Cell↗
PubMed2004

Analysis of regenerated amine-reactive polymer microarray slides.

Reactive polymer-coated microarray substrates based on N-hydroxyl succinimide (NHS) chemistry lose their bio-immobilization reactivity to probe nucleophiles over time, both in use and in storage, due to their intrinsic hydrolytic instability. Poor DNA and protein probe immobilization efficiency is often observed with routine microarray printing conditions, with accompanying reliability and stability issues for assay. We report a one-step reaction to regenerate NHS-reactive chemistry in situ on these microarray polymer surfaces with simple, straightforward reaction chemistry. Surfaces regenerated with this method perform equal to or better than freshly prepared slides in print-immobilization of oligonucleotide probes functionalized with primary amine reactive groups. DNA probe specific and non-specific surface binding as well as target hybridization were analyzed using both fresh and regenerated slides. Commercial microarray substrates appear to retain DNA probes with both substantial covalent immobilization and some non-specific adsorption to the surface.

Amines↗
PubMed2005

Expression of transcription factor Yin Yang 1 in prostate cancer.

The transcription repressor Yin Yang 1 (YY1) is expressed in several human cancer cell lines and its expression correlates with resistance to immune-mediated apoptosis. This study used tissue microarrays to investigate the expression and localization of YY1 in 1364 representative tissue samples from 246 hormone naive prostate cancer patients who underwent radical prostatectomy. Staining intensity and frequency measures for both YY1 nuclear and cytoplasmic expression were higher in neoplastic tissues and in PIN samples compared to matched benign cells (p < 0.0001 for all comparisons). Expression of YY1 is predominantly elevated in early malignancy (PIN), as well as in tumors of intermediate to high morphologic grade (Gleason's grade 3-5). Using multivariate Cox proportional hazards analysis, we observed that low nuclear YY1 staining is an independent predictor of a shorter time to recurrence (p = 0.012). Based on these results, we hypothesize that YY1 may play a role in prostate cancer development; however, decreased YY1 may give metastatic cells a survival advantage. These results may also implicate YY1 as a useful diagnostic and prognostic marker.

Aged↗
PubMed2003

Degenerate primer design via clustering.

This paper describes a new strategy for designing degenerate primers for a given multiple alignment of amino acid sequences. Degenerate primers are useful for amplifying homologous genes. However, when a large collection of sequences is considered, no consensus region may exist in the multiple alignment, making it impossible to design a single pair of primers for the collection. In such cases, manual methods are used to find smaller groups from the input collection so that primers can be designed for individual groups. Our strategy proposes an automatic grouping of the input sequences by using clustering techniques. Conserved regions are then detected for each individual group. Conserved regions are scored using a BlockSimilarity score, a novel alignment scoring scheme that is appropriate for this application. Degenerate primers are then designed by reverse translating the conserved amino acid sequences to the corresponding nucleotide sequences. Our program, DePiCt, was written in BioPerl and was tested on the Toll-Interleukin Receptor (TIR)and the non-TIR family of plant resistance genes. Existing programs for degenerate primer design were unable to find primers for these data sets.

Algorithms↗
PubMed2006

Estimating the number of clusters in DNA microarray data.

OBJECTIVES: The main objective of the research is an application of the clustering and cluster validity methods to estimate the number of clusters in cancer tumor datasets. A weighed voting technique is going to be used to improve the prediction of the number of clusters based on different data mining techniques. These tools may be used for the identification of new tumour classes using DNA microarray datasets. This estimation approach may perform a useful tool to support biological and biomedical knowledge discovery. METHODS: Three clustering and two validation algorithms were applied to two cancer tumor datasets. Recent studies confirm that there is no universal pattern recognition and clustering model to predict molecular profiles across different datasets. Thus, it is useful not to rely on one single clustering or validation method, but to apply a variety of approaches. Therefore, combination of these methods may be successfully used for the estimation of the number of clusters. RESULTS: The methods implemented in this research may contribute to the validation of clustering results and the estimation of the number of clusters. The results show that this estimation approach may represent an effective tool to support biomedical knowledge discovery and healthcare applications. CONCLUSION: The methods implemented in this research may be successfully used for the estimation of the number of clusters. The methods implemented in this research may contribute to the validation of clustering results and the estimation of the number of clusters. These tools may be used for the identification of new tumour classes using gene expression profiles.

Central Nervous System Neoplasms↗
PubMed2006

DNA immobilization and SAW response in ZnO nanotips grown on LiNbO3 substrates.

DNA immobilization enhancement is demonstrated in a structure consisting of ZnO nanotips on 128 degrees Y-cut LiNbO3. The ZnO nanotips are grown by metalorganic chemical vapor deposition (MOCVD) on the top of a SiO2 layer that is deposited and patterned on the LiNbO3 SAW delay path. The effects of ZnO nanotips on the SAW response are investigated. X-ray diffraction and scanning electron microscopy are used to analyze the ZnO nanotips, which are of single crystalline quality, and they are uniformly aligned with their c-axis perpendicular to the substrate surface. The photoluminescence (PL) spectrum of the ZnO nanotips shows strong near bandedge transition with insignificant deep level emission, confirming their good optical property. DNA immobilization enhancement is experimentally validated by radioactive labeling tests and SAW response changes. The ZnO nanotips enhance the DNA immobilization by a factor of 200 compared to ZnO film with flat surface. DNA hybridization with complementary and noncomplementary second strand DNA oligonucleotides is used to study the selective binding of the structure. This device structure possesses the advantages of both traditional SAW sensors and ZnO nanostructures.

Biosensing Techniques↗
PubMed2006

Gene expression profile of multiple myeloma cell line treated by realgar.

In order to elucidate the molecular mechanism of Realgar treatment for multiple myeloma (MM), cDNA microaaray was used to compare the gene expression profiles of MM cell line RPMI8226 at 72 hrs pre- and post-Realgar treatment on three separate days. 54 up-regulated and 60 down-regulated genes were identified by cDNA microarray. Further analysis screened out 17 up-regulated and 3 down-regulated genes with Z-score greater than 2 or less than -2, which can be considered the significantly altered genes after Realgar treatment in this study. CCL2, CCL3, BTG1,TNFAIP3, TNFAIP8, SLC38A2, IGFBP4 were important up-regulated genes and they were associated with a variety of cell life functions such as cell growth, cell-cell signaling, regulation of apoptosis and cell homeostasis based on biological process of gene. There are only 3 significantly down-regulated genes (Z-score <-2.0) involved in muscle contract. Several of these genes have been previously identified in relation to MM in published papers. Subsequent validation of selected genes (CCL2, TNFAIP3 and BTG1) by reverse transcription polymerase chain reaction was consistent with our microarray analysis. CCL2 may be involved in MM pathobiology by tumor growth suppression. BTG1 could be used as a potential treatment-related biomarker for monitoring the therapy effect and the remission status of leukemia patients.

Arsenicals↗
PubMed2005

Gene expression profiling of experimental traumatic spinal cord injury as a function of distance from impact site and injury severity.

Changes in gene expression contribute to pathophysiological alterations following spinal cord injury (SCI). We examined gene expression over time (4 h, 24 h, 7 days) at the impact site, as well as rostral and caudal regions, following mild, moderate, or severe contusion SCI in rats. High-density oligonucleotide microarrays were used that included approximately 27,000 genes/ESTs (Affymetrix RG-U34; A, B and C arrays), together with multiple analyses (MAS 5.0, dChip). Alterations after mild injury were relatively rapid (4 and 24 h), whereas they were delayed and prolonged after severe injury (24 h and 7 days). The number and magnitude of gene expression changes were greatest at the injury site after moderate injury and increased in rostral and caudal regions as a function of injury severity. Sham surgery resulted in expression changes that were similar to mild injury, suggesting the importance of using time-linked surgical controls as well as naive animals for these kinds of studies. Expression of many genes and ESTs was altered; these were classified functionally based on ontology. Overall representation of these functional classes varied with distance from the site of injury and injury severity, as did the individual genes that contributed to each functional class. Different clustering approaches were used to identify changes in neuronal-specific genes and several transcription factors that have not previously been associated with SCI. This study represents the most comprehensive evaluation of gene expression changes after SCI to date. The results underscore the power of microarray approaches to reveal global genomic responses as well as changes in particular gene clusters and/or families that may be important in the secondary injury cascade.

Algorithms↗
PubMed2004

Microarray-based AMASE as a novel approach for mutation detection.

Alterations in the p53 tumor suppressor gene are important events in many cases of human cancers. We have developed a novel microarray based approach for re-sequencing and mutation detection of the p53 gene. The method facilitates rapid and simple scanning of the target gene sequence and could be expanded to include other candidate cancer genes. The methodology employs the previously described apyrase-mediated allele-specific extension reaction (AMASE). In order to re-sequence the selected region, four extension oligonucleotides with different 3'-termini were used for each base position and they were covalently attached to the glass slide's surface. The amplified single-stranded DNA templates were then hybridized to the array followed by in situ extension with fluorescently labeled dNTPs in the presence of apyrase. The model system used was based on analysis of a 15 bp stretch in exon 5 of the p53 gene. Mutations were scored as allelic fractions calculated as (wt)/(wt + mut) signals. When apyrase was included in the extension reactions of wild type templates, the mean allelic fraction was 0.96. When apyrase was excluded with the same wild type templates, significantly lower allelic fractions were obtained. Two 60-mer synthetic oligonucleotides were used to establish the detectable amount of mutations with AMASE and a clear distinction between all the points could be made. Several samples from different stages of skin malignancies were also analyzed. The results from this study imply the possibility to efficiently and accurately re-sequence the entire p53 gene with AMASE technology.

Alleles↗
PubMed2000

Application of polymer-embedded proteins to fabrication of DNA array.

A plasma-polymerized film (PPF) of hexamethyldisiloxane [HMDS; (CH(3))(3)SiOSi(CH(3))(3)] was used to immobilize streptavidin on a glass substrate. Another layer of HMDS-PPF was also applied to the protein, which was first adsorbed to an underlayer of the same kind of film. As the result, the streptavidin was "embedded" between the two layers of HMDS, whereby biotinylated molecules could be efficiently captured. The second layer of approximately 30 to 45 A PPF was sufficient to allow the binding of biotinylated molecules, whereas thicknesses of >90 A significantly hindered the streptavidin-biotin interactions. Fluorescence analysis revealed that the absence of an HMDS plasma-polymer (HMDS-PP) layer on either side of the streptavidin film resulted in a decrease in biotin binding. This immobilization technique was used to bind biotinylated oligonucleotides in sequence-specific DNA-DNA interactions. The hydrophobic properties of the plasma-polymerized HMDS thin film acted to minimize nonspecific DNA binding to the glass substrate. A DNA array was fabricated using this procedure and showed greatly decreased nonspecific DNA binding compared with a poly-L-lysine coated substrate.

Adsorption↗
PubMed2004

Three-dimensional microarray compared with PCR-single-strand conformation polymorphism analysis/DNA sequencing for mutation analysis of K-ras codons 12 and 13.

BACKGROUND: We developed a rapid, precise, and accurate microarray-based method that uses a three-dimensional platform for detection of mutations. METHODS: We used the PamChip microarray to detect mutations in codons 12 and 13 of K-ras in 15 cell lines and 81 gastric or colorectal cancer tissues. Fluorescein isothiocyanate-labeled PCR products were analyzed with the microarray. We confirmed the microarray results with PCR-single-strand conformation polymorphism (SSCP) analysis and DNA sequencing. RESULTS: We could correctly identify wild-type, heterozygous, and homozygous mutant genotypes with the PamChip microarray in <3.5 h. The array data were consistent with those of PCR-SSCP analysis and DNA sequencing. All 15 cell lines and 80 of 81 clinical cancer specimens (98.8%; 95% confidence interval, 96.4-100%) were genotyped accurately with the microarray, a rate better than that of direct DNA sequencing (38.9%) or SSCP (93.8%). Only one clinical specimen was misdiagnosed as homozygous for the wild-type allele. Densitometric analysis of SSCP bands indicated that the content of the mutant allele in the specimen was approximately 16%. The PamChip microarray could detect mutant alleles representing more than 25% of the SSCP band proportions. Therefore, the limit for detection of mutant alleles by the PamChip microarray was estimated to be 16-25% of the total DNA. CONCLUSIONS: The PamChip microarray is a novel three-dimensional microarray system and can be used to analyze K-ras mutations quickly and accurately. The mutation detection rate was nearly 100% and was similar to that of PCR-SSCP together with sequencing analysis, but the microarray analysis was faster and easier.

Cell Line, Tumor↗