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Results for “Gene expression analysis”

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PubMed2003

Gene expression analysis on small numbers of invasive cells collected by chemotaxis from primary mammary tumors of the mouse.

BACKGROUND: cDNA microarrays have the potential to identify the genes involved in invasion and metastasis. However, when used with whole tumor tissue, the results average the expression patterns of different cell types. We have combined chemotaxis-based cell collection of the invasive subpopulation of cells within the primary tumor with array-based gene expression analysis to identify the genes necessary for the process of carcinoma cell invasion. RESULTS: Invasive cells were collected from live primary tumors using microneedles containing chemotactic growth factors to mimic chemotactic signals thought to be present in the primary tumor. When used with mammary tumors of rats and mice, carcinoma cells and macrophages constitute the invasive cell population. Microbeads conjugated with monoclonal anti-CD11b (Mac-1alpha) antibodies were used to separate macrophages from carcinoma cells. We utilized PCR-based cDNA amplification from small number of cells and compared it to the quality and complexity of conventionally generated cDNA to determine if amplified cDNA could be used with fidelity for array analysis of this cell population. These techniques showed a very high level of correlation indicating that the PCR based amplification technique yields a cDNA population that resembles, with high fidelity, the original template population present in the small number of cells used to prepare the cDNA for use with the chip. CONCLUSIONS: The specific collection of invasive cells from a primary tumor and the analysis of gene expression in these cells are is now possible. By further comparing the gene expression patterns of cells collected by invasion into microneedles with that of carcinoma cells obtained from the whole primary tumor, the blood, and whole metastatic tumors, genes that contribute to the invasive process in carcinoma cells may be identified.

Animals↗
PubMed2003

A high-throughput gene expression analysis technique using competitive PCR and matrix-assisted laser desorption ionization time-of-flight MS.

We report here an approach for gene expression analysis by combining competitive PCR and matrix-assisted laser desorption ionization time-of-flight MS. A DNA standard is designed with an artificial single nucleotide polymorphism in the gene of interest. The standard is added to the reverse transcription product before PCR. Subsequently, a base extension reaction is carried out at the single nucleotide polymorphism position, and the products are quantified by matrix-assisted laser desorption ionization time-of-flight MS. The approach is capable of relative and absolute quantification of gene expression; it is extremely sensitive (as few as five copies of DNA were quantified) and highly reproducible. It is also capable of simultaneous quantification of both alleles for heterozygotes and alternatively spliced genes. We have incorporated this technique with the homogeneous Mass Extension system (Sequenom) to create a high-throughput, automated gene expression analysis platform where a few hundred genes from 20-500 different samples can be accurately quantified per day.

Base Sequence↗
PubMed2003

Gene expression analysis using single molecule detection.

Recent developments of single molecule detection techniques and in particular the introduction of fluorescence correlation spectroscopy (FCS) led to a number of important applications in biological research. We present a unique approach for the gene expression analysis using dual-color cross-correlation. The expression assay is based on gene-specific hybridization of two dye-labeled DNA probes to a selected target gene. The counting of the dual-labeled molecules within the solution allows the quantification of the expressed gene copies in absolute numbers. As detection and analysis by FCS can be performed at the level of single molecules, there is no need for any type of amplification. We describe the gene expression assay and present data demonstrating the capacity of this novel technology. In order to prove the gene specificity, we performed experiments with gene-depleted total cDNA. The biological application was demonstrated by quantifying selected high, medium and low abundant genes in cDNA prepared from HL-60 cells.

Actins↗
PubMed2004

Gene expression analysis in Interleukin-12-induced suppression of mouse mammary carcinoma.

Interleukin-12 (IL-12) has potent antitumor activities via natural killer cells and cytotoxic T lymphocytes. However, the molecular mechanisms whereby IL-12 induces tumoricidal activities are poorly understood. Here, we report the genome-wide analysis of gene expression in a primary murine mammary carcinoma model that resembles human breast cancer, following the therapeutic application of recombinant IL-12, which restricted tumor growth and metastasis. IL-12 was able to curtail neovascularization in the tumor as well as enhance the number of tumor-infiltrating lymphocytes. Comprehensive examination of global gene expression revealed IL-12-induced molecular changes associated with tumor regression and reduced lung metastasis, thus providing a high-resolution snapshot of a host response against a developing malignancy and a rich source of potential targets for therapeutic intervention of breast cancer.

Animals↗
PubMed2000

High-throughput gene expression analysis for drug discovery.

The ability to rapidly survey and compare gene expression levels between reference and test samples is moving the drug discovery process towards a more genomic orientation. The success of the Human Genome Project and related private genomics initiatives, combined with new technologies to probe, image and access expression data, are responsible for this transformation. This article reviews the history, status and future direction of high-throughput gene expression analysis. It describes classical approaches, explains the development of methods such as differential display for discovering novel genes, and discusses how microarray technology is exploiting collections of known sequences to pinpoint drug targets.

Journal Article↗
PubMed2003

[DNA chips for gene expression analysis and their application in diagnostics].

Due to large genome projects more and more genetic information and more and more data about genetic background of various diseases can be obtained. By means of microarrays thousands to hundreds of thousands of molecular analysis can be performed at a time, rapidly, under identical conditions, hereby microarrays provide a solution to continuously increasing throughput demands from large genomic, pharmacogenetic and proteomic programmes. Microarrays offer unprecedented opportunities for qualitative and quantitative analysis of gene expression, understanding gene function and detection gene alterations, polimorphisms. Microarray expression profiles will define stages of different tumor types and new prognostic subgroups in cancer and other diseases. For individual patients, more precise diagnosis and risk assessment based on expression profiles are already achievable, leading to more accurate determination of prognosis and more individually tailored treatment. Microarrays will play an important role in diagnostics of infectious diseases and identification of novel diagnostic and therapeutic targets. Wide-spread application of microarrays in clinical practice is not typical today, but their production on an industrial scale and the increased information provided by microarrays should assure their entry into clinical practice as very powerful, sensitive, specific and rapid tools of diagnostics of various diseases.

Communicable Diseases↗
PubMed2002

Global gene expression analysis of developing neocortex using SAGE.

The mammalian brain is estimated to contain about a hundred billion neurons, making it the most complex biological structure on earth. Trying to understand the assembly and function of this elaborate organ is a formidable task. Yet the information to build a brain is encoded by no more than a subset of the 80,000 genes present in the genome, a more manageable number. This review describes the use of SAGE technology (Serial Analysis of Gene Expression) to decode the genetic repertoire of genes that are differentially expressed in time and in space during development of the neocortex, the part of the mammalian brain responsible for complex traits. We demonstrate that SAGE is not only powerful for generating comprehensive molecular portraits from the developing cortex but can also assist in discovering new genes.

Animals↗
PubMed2005

Compartment-specific quantitative gene expression analysis after laser microdissection from archival renal allograft biopsies.

BACKGROUND: Various immunological and non-immunological pathomechanisms are responsible for the cellular damage in renal allografts. Since the kidney is an anatomically complex organ with functional and morphological heterogeneous compartments (interstitium, tubuli, vessels, glomeruli), the local response to injury maybe variable, therefore, the identification of local pathomechanisms is important. AIM: To elucidate any discrepancies in quantitative mRNA expression profiles between a total specimen analysis and a cell-specific evaluation after laser microdissection. METHODS: Real-time RT-PCR was performed for complement component C3 and heme oxygenase-1 (HO-1) genes compared to the housekeeping gene beta-actin using whole section RNA extracted from formalin-fixed and paraffin-embedded archival material of 16 explanted, rejected renal allografts. Ten non-transplant nephrectomies served as controls. For five cases from each group, five different compartments of the organs (interstitium, proximal tubuli, distal tubuli, vessels, glomeruli) were microdissected and quantitative analysis for C3 and HO-1 was performed identically. RESULTS: Whole section mRNA expression analysis: the data showed a constant expression of the housekeeping gene beta-actin, a 7-fold increased expression of C3 and a 3-fold decreased expression of HO-1 in the allograft group as compared to the control group. mRNA expression results from microdissected compartments: in the control group, C3 and HO-1 expression could only be detected in the proximal tubuli of all cases whereas all five compartments analyzed from the rejecting kidneys showed expression of the two genes. In the allografts, expression levels of the investigated genes varied considerably not only among the different compartments but between individual cases as well. CONCLUSION: Laser microdissection combined with real-time RT-PCR is a feasible approach for retrospective quantitative gene expression analysis in formalin-fixed and paraffin-embedded renal allograft specimens. As shown for C3 and HO-1, cell-specific expression patterns ofpathogenetically relevant genes vary considerably between individual cases. A close correlation of morphology and cell-specific gene expression analysis will contribute to the elucidation of the complex pathogenesis of chronic renal allograft nephropathy.

Actins↗
PubMed2007

Gene expression analysis identifies a genetic signature potentially associated with response to alpha-IFN in chronic phase CML patients.

Microarray-based gene expression analysis was performed on diagnostic chronic phase CML patient samples prior to interferon treatment. Fifteen patient samples corresponding to six cytogenetic responders and nine non-responders were included. Genes differentially expressed between responder and non-responder patients were listed and a subsequent leave-one-out cross validation (LOOV) procedure showed that the top 20 genes allowed the highest prediction accuracy. The relevant genes were quantified by real-time PCR that supported the microarray results. We conclude that it might be possible to use gene expression analysis to predict future response to interferon in CML diagnostic samples.

Adult↗
PubMed2003

Gene expression analysis of thymocyte selection in vivo.

Self versus non-self discrimination is a key feature of immunorecognition. Through TCR-activated apoptotic mechanisms, autoreactive thymocytes are purged at the CD4(+)CD8(+) double-positive (DP) precursor stage prior to maturation to CD4(+) or CD8(+) single-positive (SP) thymocytes. To investigate this selection process in vivo, gene expression analysis by oligonucleotide array was performed in TCR transgenic mice. In total, 244 differentially expressed DP thymocyte genes induced or repressed by TCR triggering in vivo were identified. Genes involved in the biological processes of apoptosis, DNA recombination, antigen processing and adhesion are coordinately engaged. Moreover, analysis of gene expression in thymocyte subsets revealed that TCR ligand-induced expression profiles vary according to their developmental stage, with 48 genes showing DP preference and nine showing SP thymocyte preference. Finally, our data suggest that both the extrinsic and the intrinsic apoptosis pathways are operating in thymic selection.

Animals↗
PubMed2006

Gene expression analysis of glycosylation-related genes by real-time polymerase chain reaction.

Glycan molecules covalently linked to proteins or lipids control vital properties of cells, such as signaling, adherence, and migration through the body. The biosynthesis of such glycans depends on the concerted action of many endoplasmic reticulum and Golgi enzymes, a process that is tightly ordered and regulated. To understand the function of glycoconjugates in cellular interactions, it is crucial to investigate the regulation of expression of the genes encoding the "glycosylation-related" genes, encompassing large families of glycosyltransferases, glycosidases, and sulfotransferases. This chapter describes an easy, flexible, and reliable method of quantitative real-time polymerase chain reaction to measure the expression levels of 80 human glycosylation-related genes that primarily encode common enzymes involved in N- and O-linked protein glycosylation and/or glycolipids. Designing and including additional primer sets to detect more genes can easily extend the system. In order to allow the normalization of gene expression data obtained by real-time polymerase chain reaction within different cells, tissues, or under different experimental conditions, a protocol is included to detect genes suitable for use as endogenous reference genes.

Animals↗
PubMed2001

Gene expression analysis with the parametric bootstrap.

Recent developments in microarray technology make it possible to capture the gene expression profiles for thousands of genes at once. With this data researchers are tackling problems ranging from the identification of 'cancer genes' to the formidable task of adding functional annotations to our rapidly growing gene databases. Specific research questions suggest patterns of gene expression that are interesting and informative: for instance, genes with large variance or groups of genes that are highly correlated. Cluster analysis and related techniques are proving to be very useful. However, such exploratory methods alone do not provide the opportunity to engage in statistical inference. Given the high dimensionality (thousands of genes) and small sample sizes (often <30) encountered in these datasets, an honest assessment of sampling variability is crucial and can prevent the over-interpretation of spurious results. We describe a statistical framework that encompasses many of the analytical goals in gene expression analysis; our framework is completely compatible with many of the current approaches and, in fact, can increase their utility. We propose the use of a deterministic rule, applied to the parameters of the gene expression distribution, to select a target subset of genes that are of biological interest. In addition to subset membership, the target subset can include information about relationships between genes, such as clustering. This target subset presents an interesting parameter that we can estimate by applying the rule to the sample statistics of microarray data. The parametric bootstrap, based on a multivariate normal model, is used to estimate the distribution of these estimated subsets and relevant summary measures of this sampling distribution are proposed. We focus on rules that operate on the mean and covariance. Using Bernstein's Inequality, we obtain consistency of the subset estimates, under the assumption that the sample size converges faster to infinity than the logarithm of the number of genes. We also provide a conservative sample size formula guaranteeing that the sample mean and sample covariance matrix are uniformly within a distance epsilon > 0 of the population mean and covariance. The practical performance of the method using a cluster-based subset rule is illustrated with a simulation study. The method is illustrated with an analysis of a publicly available leukemia data set.

Journal Article↗
PubMed2002

Gene expression analysis of osteoblastic cells contacted by orthopedic implant particles.

Particles generated from orthopedic implants through years of wear play an essential role in the aseptic loosening of a prosthesis. We have investigated the biocompatibility of these orthopedic particles on different osteoblast-like cells representative of different stages of osteoblast maturation. We found the particles induced a caspase-dependent apoptosis of osteoblasts, with less mature osteoblasts being the most susceptible. An analysis of gene expression was performed on the less mature osteoblasts, which were in contact with the particles. We found that the particles had a profound impact on genes that code for inflammatory cytokines and genes involved in controlling the nuclear architecture. Results from this study suggest that the peri-implant osteolysis after a total joint replacement can be due in part to a decrease of bone formation and not solely to an overstimulation of bone resorption as is generally proposed. Development of new drugs that promote normal bone formation and osteoblast survival would possibly control peri-implant osteolysis, resulting in a better prognosis for patients with orthopedic implants.

Animals↗
PubMed2002

Long oligonucleotide arrays on nylon for large-scale gene expression analysis.

To date, most studies of multigenic expression patterns by long DNA array have used DNA fragments as probes. These probes are usually obtained as PCR products, and this represents a time-consuming and error-prone approach, requiring strict quality control. The present study examines the use of 40- and 70-mer synthetic oligonucleotides as probes for DNA array analysis with radioactive labeled targets. Design, spotting onto nylon filters, and hybridization conditions were determined and optimized. In this approach, the sensitivity and the specificity of the hybridization appear comparable to the conventional long DNA probes assay, permitting the analysis of small samples of approximately 1 microg total RNA. The long oligonucleotide array thus provides a very convenient method for the analysis of gene expression patterns in biological specimens and in clinical research.

Arabidopsis↗
PubMed2006

Automated target preparation for microarray-based gene expression analysis.

DNA microarrays have rapidly evolved toward a platform for massively paralleled gene expression analysis. Despite its widespread use, the technology has been criticized to be vulnerable to technical variability. Addressing this issue, recent comparative, interplatform, and interlaboratory studies have revealed that, given defined procedures for "wet lab" experiments and data processing, a satisfactory reproducibility and little experimental variability can be achieved. In view of these advances in standardization, the requirement for uniform sample preparation becomes evident, especially if a microarray platform is used as a facility, i.e., by different users working in the laboratory. While one option to reduce technical variability is to dedicate one laboratory technician to all microarray studies, we have decided to automate the entire RNA sample preparation implementing a liquid handling system coupled to a thermocycler and a microtiter plate reader. Indeed, automated RNA sample preparation prior to chip analysis enables (1) the reduction of experimentally caused result variability, (2) the separation of (important) biological variability from (undesired) experimental variation, and (3) interstudy comparison of gene expression results. Our robotic platform can process up to 24 samples in parallel, using an automated sample preparation method that produces high-quality biotin-labeled cRNA ready to be hybridized on Affymetrix GeneChips. The results show that the technical interexperiment variation is less pronounced than with manually prepared samples. Moreover, experiments using the same starting material showed that the automated process yields a good reproducibility between samples.

Animals↗
PubMed1999

Comparative gene-expression analysis.

The study of differences in gene-expression patterns is one of the most promising approaches for understanding mechanisms of differentiation and development. In addition, the identification of disease-related target molecules opens new avenues for rational pharmaceutical intervention. Recent technical advances and improvements are accelerating the analysis of gene-expression profiles at the transcript level. The knowledge and comprehension of currently applied methods is one of the central criteria for an efficient and successful gene-screening approach.

Expressed Sequence Tags↗
PubMed2007

Gene expression analysis of TFII-I modulated genes in mouse embryonic fibroblasts.

TFII-I is a founding member of a family of helix-loop-helix transcription factors involved in modulation of genes through interaction with various nuclear factors and chromatin remodeling complexes. Recent studies indicate that TFII-I performs important function in cell physiology and mouse embryogenesis. In order to understand its molecular role, TFII-I was overexpressed in primary mouse embryonic fibroblasts (MEFs) and alterations in gene expression were monitored with a mouse 16 K oligonucleotide microarray. These studies allowed us to identify genes that lie downstream of TFII-I-dependent pathways. Among the modulated candidates were genes involved in the immunity response, catalytic activity, signaling pathways and transcriptional regulation. Expression of several candidates including those for the interferon-stimulated protein (G1p2), small inducible cytokine A7 (Ccl7), ubiquitin-conjugating enzyme 8 (Ube2l6), cysteine-rich protein (Csrp2) and Drosophila delta-like 1 homolog (Dlk1) were confirmed by real-time PCR. The obtained results suggest that TFII-I participates in multiple signaling and regulatory pathways in MEFs.

Animals↗