DNA Microarray Platform Research Articles

Molecular Evidence for Increased Expression of Genes Related to Immune and Chaperone Function in the Prefrontal Cortex in Schizophrenia

Schizophrenia is characterized by complex gene expression changes. The transcriptome alterations in the prefrontal cortex have been the subject of several recent postmortem studies that yielded both convergent and divergent findings. To increase measurement precision, we used a custom-designed DNA microarray platform with long oligonucleotides and multiple probes with replicates. The platform was designed to assess the expression of > 1800 genes specifically chosen because of their hypothesized roles in the pathophysiology of schizophrenia. The gene expression differences in dorsolateral prefrontal cortex samples from 14 matched pairs of schizophrenia and control subjects were analyzed with two technical replicates and four data mining approaches. In addition to replicating many expression changes in synaptic, oligodendrocyte, and signal transduction genes, we uncovered and validated a robust immune/chaperone transcript upregulation in the schizophrenia samples. We speculate that the overexpression of SERPINA3, IFITM1, IFITM2, IFITM3, CHI3L1, MT2A, CD14, HSPB1, HSPA1B, and HSPA1A in schizophrenia subjects represents a long-lasting and correlated signature of an early environmental insult during development that actively contributes to the pathophysiology of prefrontal dysfunction.

Comparison of hybridization-based and sequencing-based gene expression technologies on biological replicates

BackgroundHigh-throughput systems for gene expression profiling have been developed and have matured rapidly through the past decade. Broadly, these can be divided into two categories: hybridization-based and sequencing-based approaches. With data from different technologies being accumulated, concerns and challenges are raised about the level of agreement across technologies. As part of an ongoing large-scale cross-platform data comparison framework, we report here a comparison based on identical samples between one-dye DNA microarray platforms and MPSS (Massively Parallel Signature Sequencing).ResultsThe DNA microarray platforms generally provided highly correlated data, while moderate correlations between microarrays and MPSS were obtained. Disagreements between the two types of technologies can be attributed to limitations inherent to both technologies. The variation found between pooled biological replicates underlines the importance of exercising caution in identification of differential expression, especially for the purposes of biomarker discovery.ConclusionBased on different principles, hybridization-based and sequencing-based technologies should be considered complementary to each other, rather than competitive alternatives for measuring gene expression, and currently, both are important tools for transcriptome profiling.

Surface-Enhanced Raman Scattering Based Nonfluorescent Probe for Multiplex DNA Detection

To provide rapid and accurate detection of DNA markers in a straightforward, inexpensive, and multiplex format, an alternative surface-enhanced Raman scattering based probe was designed and fabricated to covalently attach both DNA probing sequence and nonfluorescent Raman tags to the surface of gold nanoparticles (DNA-AuP-RTag). The intensity of Raman signal of the probes could be controlled through the surface coverage of the nonfluorescent Raman tags (RTags). Detection sensitivity of these probes could be optimized by fine-tuning the amount of DNA molecules and RTags on the probes. Long-term stability of the DNA-AuP-RTag probes was found to be good (over 3 months). Excellent multiplexing capability of the DNA-AuP-RTag scheme was demonstrated by simultaneous identification of up to eight probes in a mixture. Detection of hybridization of single-stranded DNA to its complementary targets was successfully accomplished with a long-term goal to use nonfluorescent RTags in a Raman-based DNA microarray platform.

Gene Expression Profiling of Breast Cancer

DNA microarray platforms for gene expression profiling were invented relatively recently, and breast cancer has been among the earliest and most intensely studied diseases using this technology. The molecular signatures so identified help reveal the biologic spectrum of breast cancers, provide diagnostic tools as well as prognostic and predictive gene signatures, and may identify new therapeutic targets. Data are best presented in an open access format to facilitate external validation, the most crucial step in identifying robust, reproducible gene signatures suitable for clinical translation. Clinically practical applications derived from full expression profile studies already in use include reduced versions of microarrays representing key discriminatory genes and therapeutic targets, quantitative polymerase chain reaction assays, or immunohistochemical surrogate panels (suitable for application to standard pathology blocks). Prospective trials are now underway to determine the value of such tools for clinical decision making in breast cancer; these efforts may serve as a model for using such approaches in other tumor types.

Arrays of Hope

A large study by the MAQC consortium has established that different DNA microarray platforms can generate reproducible lists of differentially expressed genes. Now scientists are grappling with the challenges of moving the technology toward the clinic.

Gene Expression Profiling Reveals Reproducible Human Lung Adenocarcinoma Subtypes in Multiple Independent Patient Cohorts

Published reports suggest that DNA microarrays identify clinically meaningful subtypes of lung adenocarcinomas not recognizable by other routine tests. This report is an investigation of the reproducibility of the reported tumor subtypes. Three independent cohorts of patients with lung cancer were evaluated using a variety of DNA microarray assays. Using the integrative correlations method, a subset of genes was selected, the reliability of which was acceptable across the different DNA microarray platforms. Tumor subtypes were selected using consensus clustering and genes distinguishing subtypes were identified using the weighted difference statistic. Gene lists were compared across cohorts using centroids and gene set enrichment analysis. Cohorts of 31, 72, and 128 adenocarcinomas were generated for a total of 231 microarrays, each with 2,553 reliable genes. Three adenocarcinoma subtypes were identified in each cohort. These were named bronchioid, squamoid, and magnoid according to their respective correlations with gene expression patterns from histologically defined bronchioalveolar carcinoma, squamous cell carcinoma, and large-cell carcinoma. Tumor subtypes were distinguishable by many hundreds of genes, and lists generated in one cohort were predictive of tumor subtypes in the two other cohorts. Tumor subtypes correlated with clinically relevant covariates, including stage-specific survival and metastatic pattern. Most notably, bronchioid tumors were correlated with improved survival in early-stage disease, whereas squamoid tumors were associated with better survival in advanced disease. DNA microarray analysis of lung adenocarcinomas identified reproducible tumor subtypes which differ significantly in clinically important behaviors such as stage-specific survival.

An improved gel‐based DNA microarray method for detecting single nucleotide mismatch

3-D polyacrylamide gel-based DNA microarray platforms provide a high capacity for nucleic acids immobilization and a solution-mimicking environment for hybridization. However, several technological bottlenecks still remain in these platforms, such as difficult microarray preparation and high fluorescent background, which limit their application. In this study, two new approaches have been developed to improve the convenience in microarray preparation and to reduce the background after hybridization. To control the polymerization process, solutions containing acrylamide-modified oligonucleotide, acrylamide, glycerol and ammonium persulfate are spotted onto a functionalized glass slide, and then the slide is transferred to a vacuum chamber with TEMED, so that TEMED is vaporized and diffused into the spots to induce polymerization. By applying an electric field across a hybridized microarray to remove the nonspecifically bound labeled targets, this approach can solve the problem of high fluorescent background of the gel-based microarray after hybridization. Experimental results show that our immobilization method can be used to construct high quality microarrays and exhibits good reproducibility. Moreover, the polymerization is not affected by PCR medium, so that PCR products can be used for microarray construction without being treated by commercial purification cartridges. Electrophoresis can improve the signal-to-noise significantly and has the ability to differentiate single nucleotide variation between two homozygotes and a heterozygote. Our results demonstrated that this is a reliable novel method for high-throughput mutation analysis and disease diagnosis.

Capturing genomic signatures of DNA sequence variation using a standard anonymous microarray platform

Comparative genomics, using the model organism approach, has provided powerful insights into the structure and evolution of whole genomes. Unfortunately, only a small fraction of Earth's biodiversity will have its genome sequenced in the foreseeable future. Most wild organisms have radically different life histories and evolutionary genomics than current model systems. A novel technique is needed to expand comparative genomics to a wider range of organisms. Here, we describe a novel approach using an anonymous DNA microarray platform that gathers genomic samples of sequence variation from any organism. Oligonucleotide probe sequences placed on a custom 44 K array were 25 bp long and designed using a simple set of criteria to maximize their complexity and dispersion in sequence probability space. Using whole genomic samples from three known genomes (mouse, rat and human) and one unknown (Gonystylus bancanus), we demonstrate and validate its power, reliability, transitivity and sensitivity. Using two separate statistical analyses, a large numbers of genomic ‘indicator’ probes were discovered. The construction of a genomic signature database based upon this technique would allow virtual comparisons and simple queries could generate optimal subsets of markers to be used in large-scale assays, using simple downstream techniques. Biologists from a wide range of fields, studying almost any organism, could efficiently perform genomic comparisons, at potentially any phylogenetic level after performing a small number of standardized DNA microarray hybridizations. Possibilities for refining and expanding the approach are discussed.

DNA microarray analysis for the detection of mutations in hemophilia A.

Congenital deficiency of factor (F) VIII results in the inherited X-linked bleeding disorder hemophilia A. More than 900 different mutations are reported in the hemophilia A mutation database with the largest number of mutations being single nucleotide substitutions distributed throughout the gene. Complicating the molecular characterization of this disease is the complexity of the F8 gene, the mutational heterogeneity, and technical limitations of the current mutation detection techniques. Development of a DNA oligonucleotide microarray-based technique for F8 gene analysis to detect hemophilia A mutations. To construct the oligonucleotide DNA microarray system: a total of 720, one base pair overlapping, 25-mer perfect match probes were designed from six exons of the F8 gene. Twenty-two different F8 gene mutations previously identified by CSGE and DNA sequence analysis were tested by using a loss-of-signal analysis approach. Differentially labeled wild type and hemophilic samples were co-hybridized to the array. Sequence alterations were detected by quantifying relative losses of test sample hybridization signals to the perfectly matched probes. A total of 22 different F8 mutations were tested. To test the sensitivity of the system, a blinded study was performed on 16 of the samples. F8 gene mutations can be detected with 96% efficiency with this microarray system. This proof-of-principle study has demonstrated that a F8 DNA microarray platform is an alternative gene mutation analysis approach that has a high sensitivity, and reproducibility. The methodology is, however, expensive and time consuming, and with the reduction in sequencing costs, direct sequencing is now the most cost and time efficient strategy for hemophilia A mutation analysis.

Distinct molecular mechanisms underlying clinically relevant subtypes of breast cancer: gene expression analyses across three different platforms

BackgroundGene expression profiling has been used to define molecular phenotypes of complex diseases such as breast cancer. The luminal A and basal-like subtypes have been repeatedly identified and validated as the two main subtypes out of a total of five molecular subtypes of breast cancer. These two are associated with distinctly different gene expression patterns and more importantly, a significant difference in clinical outcome. To further validate and more thoroughly characterize these two subtypes at the molecular level in tumors at an early stage, we report a gene expression profiling study using three different DNA microarray platforms.ResultsExpression data from 20 tumor biopsies of early stage breast carcinomas were generated on three different DNA microarray platforms; Applied Biosystems Human Genome Survey Microarrays, Stanford cDNA Microarrays and Agilent's Whole Human Genome Oligo Microarrays, and the resulting gene expression patterns were analyzed. Both unsupervised and supervised analyses identified the different clinically relevant subtypes of breast tumours, and the results were consistent across all three platforms. Gene classification and biological pathway analyses of the genes differentially expressed between the two main subtypes revealed different molecular mechanisms descriptive of the two expression-based subtypes: Signature genes of the luminal A subtype were over-represented by genes involved in fatty acid metabolism and steroid hormone-mediated signaling pathways, in particular estrogen receptor signaling, while signature genes of the basal-like subtype were over-represented by genes involved in cell proliferation and differentiation, p21-mediated pathway, and G1-S checkpoint of cell cycle-signaling pathways. A minimal set of 54 genes that best discriminated the two subtypes was identified using the combined data sets generated from the three different array platforms. These predictor genes were further verified by TaqMan® Gene Expression assays.ConclusionWe have identified and validated the two main previously defined clinically relevant subtypes, luminal A and basal-like, in a small set of early stage breast carcinomas. Signature genes characterizing these two subtypes revealed that distinct molecular mechanisms might have been pre-programmed at an early stage in different subtypes of the disease. Our results provide further evidence that these breast tumor subtypes represent biologically distinct disease entities and may require different therapeutic strategies. Finally, validated by multiple gene expression platforms, including quantitative PCR, the set of 54 predictor genes identified in this study may define potential prognostic molecular markers for breast cancer.

AmpliChip CYP450 Test: personalized medicine has arrived in psychiatry

The US FDA has granted market approval for the first pharmacogenetic test using a DNA microarray, the AmpliChip CYP450, which genotypes cytochrome P450 (CYP)2D6 and CYP2C19. The test uses software to predict phenotypes and tests for 27 CYP2D6 alleles, including the deletions and duplications, and three CYP2C19 alleles. Other DNA microarray platforms are being developed for CYP testing, but none have been completely developed or approved by the FDA to date. The differences between an implementation of pharmacogenetic tests centered on the individual and implementation using a public health approach are discussed. In this review, the major obstacles to the wide implementation of pharmacogenetic testing in the clinical environment are summarized.

DNA microarrays for pathogen detection and characterisation

DNA microarrays have three main potential diagnostic uses in clinical microbiology: detection of known pathogens, pathogen typing and novel pathogen discovery. Although DNA microarray platforms offer the ability to screen for a large number of agents in parallel, sensitivity is dependent on the ability to obtain adequate amounts of pathogen nucleic acids from collected samples. In general, high levels of sensitivity require a PCR amplification step using specific primer sets, subsequently reducing the overall scope of the microarray assay. At present, relatively high costs, restricted sample throughput capabilities and validation difficulties are also major factors limiting the implementation of DNA microarray assays in diagnostic microbiology laboratories.

Array-CGH and Gene Expression Profiling Based Molecular Characterization of Myeloid Leukemia Cell Lines.

Myeloid leukemias are characterized by cytogenetic and molecular-genetic aberrations resulting in altered gene expression. Nevertheless, so far still little is known regarding the underlying mechanisms of leukemogenesis. To model and investigate the different aspects of leukemia pathogenesis a widely accepted approach is to use immortalized leukemia cell lines. While these provide powerful tools for the investigation of gene function, the dissection of signal transduction pathways and the analysis of drug effects, to our knowledge only few studies have addressed the question whether hematopoietic cell lines represent reliable model systems.In order to improve the molecular characterization of these model systems we therefore analyzed 18 myeloid leukemia cell lines using DNA microarray technology. To determine the secondary aberrations acquired in addition to their characteristic primary cytogenetic aberrations during numerous passages in vitro, we first analyzed all cell lines by array-CGH (comparative genomic hybridization). Using a BAC/PAC platform with an average resolution of ~ 1.5 Mb across the entire genome we identified recurrent losses and gains, as well as high level amplifications like e.g. an amplification in 4q12 (Kasumi1) and in 8q24 (HL60). The parallel analysis of gene expression using a whole genome cDNA microarray platform helped to further delineate potential candidate genes in the affected regions (e.g. overexpression of KIT in the 4q12 and MYC in the 8q24 amplicon). Furthermore, unsupervised hierarchical cluster analysis revealed distinct gene signatures pointing towards dysregulated transcriptional networks. Comparison of our findings with acute myeloid leukemia patient data (Bullinger et al. 2004) showed the signatures underlying characteristic cytogenetic aberrations like e.g. t(15;17) were conserved in cell lines. Interestingly, these signatures were also quite robust as they displayed a highly significant correlation with published cell line data profiled on a different DNA microarray platform in a different laboratory.Thus, our analyses demonstrate that cell lines exhibit conserved signatures correlating with the primary balanced cytogenetic aberrations, and that most cell lines even when grown and analyzed under different conditions provide highly robust signatures. Therefore, our refined molecular characterization of myeloid cell lines supports the utility of cell lines as powerful model systems and provides additional insights into the molecular mechanisms of leukemogenesis.

Gene Expression Profiling Identifies Distinct Subclasses in Core Binding Factor Acute Myeloid Leukemia.

Recurrent cytogenetic aberrations have been shown to constitute markers of diagnostic and prognostic value in acute myeloid leukemia (AML). However, even within well-defined cytogenetic AML subgroups with an inv(16) or a t(8;21) we see substantial biological and clinical heterogeneity which is not fully reflected by the current classification system. Therefore, we profiled gene expression in a large series of adult AML patients with core binding factor (CBF) leukemia [inv(16) n=55, t(8;21) n=38] using a whole genome DNA microarray platform in order to better characterize this disease on the molecular level. By unsupervised hierarchical clustering based on 8556 filtered genes we observed that our CBF leukemia samples separated primarily into three different subgroups. While two of the subgroups were characterized by inv(16) and t(8;21) cases, respectively, the third subgroup contained a mixture of both cytogenetic groups. There was no obvious correlation with known secondary aberrations or molecular marker like FLT3-ITD, NRAS and KIT mutations between the cases in the mixed subgroup and the others. However, the newly defined inv(16)/t(8;21)-subgroup (n=35) was characterized by distinct clinical behavior with shorter overall survival times (P=0.029; log rank test) compared to the other two groups. Unsupervised analyses within the inv(16) and t(8;21) cases also revealed corresponding inv(16) and t(8;21) subgroups with a strong trend towards inferior outcome (P=0.11 and P=0.09, respectively; log rank test). Since the primary translocation/inversion events themselves are not sufficient for leukemogenesis, distinct patterns of gene expression found within each of these cytogenetic groups may suggest alternative cooperating mutations and deregulated pathways leading to transformation. Therefore, we performed a supervised analysis to determine the characteristic gene expression patterns underlying the cluster-defined subgroups. We identified 528 genes significantly differentially expressed between the newly defined inv(16)/t(8;21)-subgroup and the other CBF cases (significance analysis of microarrays, false discovery rate < 0.001). Potential candidates for cooperating pathways characterizing the mixed inv(16)/t(8;21)-subgroup included e.g. AVO3, a member of the mTOR pathway, oncogene homologs like LYN and BRAF, as well as FOXO1A and IL6ST which have been previously identified to correlate with outcome in AML (Bullinger et al., N Engl J Med 350:1605, 2004). In conclusion, while the observed signatures remain to be validated for their functional relevance, both supervised and unsupervised methods provide numerous insights into the pathogenesis of CBF AML, identifying clinically significant patterns of gene expression, as well as candidate target genes involved in leukemogenesis.

MeSHer: identifying biological concepts in microarray assays based on PubMed references and MeSH terms

MeSHer uses a simple statistical approach to identify biological concepts in the form of Medical Subject Headings (MeSH terms) obtained from the PubMed database that are significantly overrepresented within the identified gene set relative to those associated with the overall collection of genes on the underlying DNA microarray platform. As a demonstration, we apply this approach to gene lists acquired from a published study of the effects of angiotensin II (Ang II) treatment on cardiac gene expression and demonstrate that this approach can aid in the interpretation of the resulting 'significant' gene set. The software is available at http://www.tm4.org. Results from the analysis of significant genes from the published Ang II study.

Development of a protein microarray using sequence-specific DNA binding domain on DNA chip surface

A protein microarray based on DNA microarray platform was developed to identify protein–protein interactions in vitro. The conventional DNA chip surface by 156-bp PCR product was prepared for a substrate of protein microarray. High-affinity sequence-specific DNA binding domain, GAL4 DNA binding domain, was introduced to the protein microarray as fusion partner of a target model protein, enhanced green fluorescent protein. The target protein was oriented immobilized directly on the DNA chip surface. Finally, monoclonal antibody of the target protein was used to identify the immobilized protein on the surface. This study shows that the conventional DNA chip can be used to make a protein microarray directly, and this novel protein microarray can be applicable as a tool for identifying protein–protein interactions.

Platform influence on DNA microarray data in postmortem brain research

In addition to the substantial biological diversity among humans, our limited ability to reliably measure expression changes of small magnitude significantly reduces our capacity to obtain convergent sets of transcriptome data in postmortem brain. In particular, differences in the structure and sensitivity/reproducibility of microarray platforms, and in the variety of tools used to analyze microarray data, strongly influence experimental outcome. In order to better understand the sensitivity, dynamic range, and reproducibility of three common DNA microarray platforms, we compared two human postmortem samples on cDNA microarrays with dual-fluorescence, oligonucleotide GeneChips (Affymetrix), and single-color gel matrix deposited CodeLink oligonucleotide arrays. All three microarray platforms reported a good dynamic range and high correlation in replicate experiments, but they failed to consistently identify the same genes as differentially expressed between the same samples. Given their reproducibility and proven accuracy, different microarray platforms appear to be measuring different things by nature of their design and function. This needs to be taken into account when comparing data across studies.

"Lineage Addiction" in Human Cancer: Lessons from Integrated Genomics

Genome-era advances in the field of oncology endorse the notion that many tumors may prove vulnerable to targeted therapeutic avenues once their salient molecular alterations are elucidated. Accomplishing this requires both detailed genomic characterization and the ability to identify in situ the critical dependencies operant within individual tumors. To this end, DNA microarray platforms such as high-density single-nucleotide polymorphism (SNP) arrays enable large-scale cancer genome characterization, including copy number and loss-of-heterozygosity analyses at high resolution. Clustering analyses of SNP array data from a large collection of tumor samples and cell lines suggest that certain copy number alterations correlate strongly with the tissue of origin. Such lineage-restricted alterations may harbor novel cancer genes directing genesis or progression of tumors from distinct tissue types. We have explored this notion through combined analysis of genome-scale data sets from the NCI60 cancer cell line collection. Here, several melanoma cell lines clustered on the basis of increased dosage at a region of chromosome 3p containing the master melanocyte regulator MITF. Combined analysis of gene expression data and additional functional studies established MITF as an amplified oncogene in melanoma. MITF may therefore represent a nodal point within a critical lineage survival pathway operant in a subset of melanomas. These findings suggest that, like oncogene addiction, "lineage addiction" may represent a fundamental tumor survival mechanism with important therapeutic implications.

Genome-scale identification of conditionally essential genes in E. coli by DNA microarrays

Identifying the genes required for the growth or viability of an organism under a given condition is an important step toward understanding the roles these genes play in the physiology of the organism. Currently, the combination of global transposon mutagenesis with PCR-based mapping of transposon insertion sites is the most common method for determining conditional gene essentiality. In order to accelerate the detection of essential gene products, here we test the utility and reliability of a DNA microarray technology-based method for the identification of conditionally essential genes of the bacterium, Escherichia coli, grown in rich medium under aerobic or anaerobic growth conditions using two different DNA microarray platforms. Identification and experimental verification of five hypothetical E. coli genes essential for anaerobic growth directly demonstrated the utility of the method. However, the two different DNA microarray platforms yielded largely non-overlapping results after a two standard deviations cutoff and were subjected to high false positive background levels. Thus, further methodological improvements are needed prior to the use of DNA microarrays to reliably identify conditionally essential genes on genome-scale.

Three-dimensional microarray platform applied to single nucleotide polymorphism analysis.

Bio-Strand, Inc., has developed a novel DNA microarray platform utilizing a three-dimensional (3D) DNA format. DNA probes or polymerase chain reaction (PCR) products are spotted onto a thread-like scaffold, which is then wound onto a cylindrical core. By wrapping the thread around the core, high efficiencies are achieved in sample analysis. Using allele-specific oligo (ASO) competitive hybridization (with Cy5 fluorescently labeled sequences), hybridized arrays are visualized using a helium-neon (HeNe) laser and quantitated/scored. The method can readily detect single nucleotide differences. We demonstrate the use of this Bio-Strand 3D array in the analysis of a single nucleotide polymorphism (SNP).