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Results for “Gene expression analysis”

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At least 163 records · Page 9Linked to original sources
PubMed2001

Genetic cancer syndromes and large-scale gene expression analysis: applications in surgical oncology.

The last decade of the 20th century was characterized by an explosion in genetic discoveries. The Human Genome Project and technical advances have made it possible to unravel many genetic abnormalities underlying cancer. Many genes responsible for inherited cancer syndromes have been identified and diagnostic tests are readily available. The clinical implications of these tests are currently under debate. Large-scale gene expression analysis enables simultaneous monitoring of expression of thousands of genes, in vitro and in vivo. The identification of high risk patients and drug responsiveness, can be studied within the framework of complex molecular networks. This article will focus on the possibilities for surgical oncology.

Breast Neoplasms↗
PubMed1997

Gene Expression Analysis during Conidial Germ Tube and Appressorium Development in Colletotrichum trifolii.

Preinfection development in Colletotrichum spp. exhibits three morphologies (conidia, germ tubes, and appressoria) and is directed by a complex interplay of environmental signals. Germ tube morphogenesis for Colletotrichum trifolii and the related fungus Colletotrichum gloeosporioides f. sp. aeschynomene was shown to be partially dependent on a balance between self-germination inhibitors and environmental nutrients or cutin. The degree of responsiveness to these environmental signals was strikingly different between the two fungal species. A solid contact surface stimulated germ tube morphogenesis and was the only apparent requirement for appressorium morphogenesis in both fungi. A population of C. trifolii conidia was incubated on a solid surface in the presence of cutin to stimulate nearly synchronous preinfection morphogenesis for gene expression analysis. RNA analysis of signal-transducing genes from C. trifolii, including genes for a serine-threonine kinase (TB3), calmodulin, and protein kinase C, showed that maximum transcription of all three genes occurred in conidia prior to or during germ tube morphogenesis. Transcription of melanin biosynthetic genes THR1 and SCD1 (Y. Kubo, Y. Takano, and I. Furusawa, Colletotrichum Newsl. II:5-10, 1996; N. S. Perpetua, Y. Kubo, N. Yasuda, Y. Takano, and I. Furusawa, Mol. Plant-Microbe Interact. 9:323-329, 1996) was highest prior to and during appressorium morphogenesis.

Journal Article↗
PubMed2004

Differentially expressed genes in pancreatic ductal adenocarcinomas identified through serial analysis of gene expression.

Serial analysis of gene expression (SAGE) is a powerful tool for the discovery of novel tumor markers. The publicly available online SAGE libraries of normal and neoplastic tissues (http://www.ncbi.nlm.nih.gov/SAGE/) have recently been expanded; in addition, a more complete annotation of the human genome and better biocomputational techniques have substantially improved the assignment of differentially expressed SAGE "tags" to human genes. These improvements have provided us with an opportunity to re-evaluate global gene expression in pancreatic cancer using existing SAGE libraries. SAGE libraries generated from six pancreatic cancers were compared to SAGE libraries generated from 11 non-neoplastic tissues. Compared to normal tissue libraries, we identified 453 SAGE tags as differentially expressed in pancreatic cancer, including 395 that mapped to known genes and 58 "uncharacterized" tags. Of the 395 SAGE tags assigned to known genes, 223 were overexpressed in pancreatic cancer, and 172 were underexpressed. In order to map the 58 uncharacterized differentially expressed SAGE tags to genes, we used a newly developed resource called TAGmapper (http://tagmapper.ibioinformatics.org), to identify 16 additional differentially expressed genes. The differential expression of seven genes, involved in multiple cellular processes such as signal transduction (MIC-1), differentiation (DMBT1 and Neugrin), immune response (CD74), inflammation (CXCL2), cell cycle (CEB1) and enzymatic activity (Kallikrein 6), was confirmed by either immunohistochemical labeling of tissue microarrays (Kallikrein 6, CD74 and DMBT1) or by RT-PCR (CEB1, Neugrin, MIC1 and CXCL2). Of note, Neugrin was one of the genes whose previously uncharacterized SAGE tag was correctly assigned using TAGmapper, validating the utility of this program. Novel differentially expressed genes in a cancer type can be identified by revisiting updated and expanded SAGE databases. TAGmapper should prove to be a powerful tool for the discovery of novel tumor markers through assignment of uncharacterized SAGE tags.

Adenocarcinoma↗
PubMed2002

Quantitative gene expression analysis in renal biopsies: a novel protocol for a high-throughput multicenter application.

BACKGROUND: Recent advances in gene expression analysis may add the quantification of mRNA species in renal biopsies to routine diagnostic procedures in nephrology. METHODS: A systematic evaluation was performed on the relevant steps required to efficiently obtain cDNA from renal biopsies for high-throughput reverse transcription-polymerase chain reaction (RT-PCR) based mRNA quantification. RESULTS: The protocol preserves mRNA integrity by a novel RNase inhibitor and allows meticulous microdissection followed by maximal RNA recovery from tissue samples. Reverse transcription was optimized to give the best yield from minimal starting material. RNA quantity and quality were systematically investigated by real-time RT-PCR and electrophoresis on a microfluidic system, respectively. The reported procedure offers high RNA preservation and increases the yield of cDNA significantly compared to former protocols. CONCLUSION: The simplicity of biopsy material acquisition combined with the centrally performed processing makes this protocol suitable for a wide spectrum of expression analysis in diverse clinical settings.

Biopsy↗
PubMed2005

Identification of novel biomarkers for Niemann-Pick disease using gene expression analysis of acid sphingomyelinase knockout mice.

Although several therapies are available or being developed for lysosomal storage disorders (LSDs), assessment of therapeutic efficacy is challenged by the lack of markers to assess disease progression and severity. This is particularly true for rare diseases such as LSDs, since natural history data from human populations are often lacking. Herein we describe the use of gene expression analysis in the acid sphingomyelinase-deficient mouse model (ASMKO) of Types A and B Niemann-Pick disease (NPD) to identify novel serum biomarkers. We used microarray and real-time PCR analyses to compare mRNA expression in ASMKO and normal mice in two important sites of pathology, lung and brain, and from these data identified and validated several potential biomarkers. The cytokine MIP-1alpha was markedly elevated in ASMKO mouse serum, and following enzyme replacement therapy (ERT) it was reduced to normal levels. Total iron levels were similarly elevated in ASMKO mice, reflective of the elevated ferritin light chain transcript, and decreased to normal after ERT. Serum growth hormone levels were also elevated in ASMKO mice and were reduced to normal after brain-directed gene therapy, but not ERT. These studies illustrate the value of gene expression analysis for the identification of biomarkers, and provide new insight into the pathobiology of NPD.

Animals↗
PubMed2001

Quantitative gene expression analysis in microdissected archival formalin-fixed and paraffin-embedded tumor tissue.

Formalin-fixed, paraffin-embedded tissue is the most widely available material for retrospective clinical studies. In combination with the potential of genomics, these tissues represent an invaluable resource for the elucidation of disease mechanisms and validation of differentially expressed genes as novel therapeutic targets or prognostic indicators. We describe here an approach that, in combination with laser-assisted microdissection allows quantitative gene expression analysis in formalin-fixed, paraffin-embedded archival tissue. Using an optimized RNA microscale extraction procedure in conjunction with real-time quantitative reverse transcriptase-polymerase chain reaction based on fluorogenic TaqMan methodology, we analyzed the expression of a panel of cancer-relevant genes, EGF-R, HER-2/neu, FGF-R4, p21/WAF1/Cip1, MDM2, and HPRT and PGK as controls. We demonstrate that expression level determinations from formalin-fixed, paraffin-embedded tissues are accurate and reproducible. Measurements were comparable to those obtained with matching fresh-frozen tissue and neither fixation grade nor time significantly affected the results. Laser microdissection studies with 5-microm thick sections and defined numbers of tumor cells demonstrated that reproducible quantitation of specific mRNAs can be achieved with only 50 cells. We applied our approach to HER-2/neu quantitative gene expression analysis in 54 microdissected tumor and nonneoplastic archival samples from patients with Barrett's esophageal adenocarcinoma and showed that the results matched those obtained in parallel by fluorescence in situ hybridization and immunohistochemistry. Thus, the combination of laser-assisted microdissection and real-time TaqMan reverse transcriptase-polymerase chain reaction opens new avenues for the investigation and clinical validation of gene expression changes in archival tissue specimens.

Animals↗
PubMed2002

Isolating vessels from the mouse brain for gene expression analysis using laser capture microdissection.

Studies of gene expression often examine a pool of RNA extracted from the diverse cell types making up a tissue. We have developed a method for isolating vessels from the brain in order to understand the changes occurring in the vessels during the pathogenesis of cerebral malaria. Vessels were visualised by incubating sections of mouse brain with a substrate for alkaline phosphatase. Vessels were collected by laser capture microdissection and the specificity was monitored by measuring the expression of cell-specific markers. RNA from the captured vessels was highly enriched in mRNA for genes associated with endothelial cells and pericytes. Measurement of indoleamine 2,3-dioxygenase mRNA indicated it was possible to detect changes in gene expression, due to malaria infection, occurring specifically within the vessels. Laser capture microdissection can be used to study changes in gene expression occurring at the blood-brain barrier.

Alkaline Phosphatase↗
PubMedDate not supplied

Gene expression analysis of human tissue from patients with cardiomyopathies: a new tool for guiding therapies in the future?

The complete sequencing of the human genome led to the development of a number of new molecular technologies. DNA microarrays represent an exciting new tool for gene expression analysis in human tissue. Measurements of the expressions of many thousands of genes in parallel is possible now. Microarrays may be used for various applications in medicine. They can be used to find novel prognostic and predictive markers as well as new disease classifications into clinically relevant subgroups. While there has been great progress in cancer research in this field, there are significantly less expression data available concerning the heart. In order to identify genes and pathways involved in the pathogenesis of cardiomyopathies, we have looked recently for alterations at cellular and molecular levels in heart tissue from cardiomyopathy patients. We showed that a special group of genes is differentially regulated in dilated cardiomyopathy. The first results in hypertrophic cardiomyopathy also showed similar findings. The surgeon's role in the clinical application of gene expression profiling is crucial. He provides a link between the patient and the laboratory scientists playing a significant role in focusing research on the clinically relevant problems. Gene expression profiles may help to better characterize the course and prognosis of the individual patient in the future. The long-term goal is to find a tool that will help to guide medical and surgical therapies in cardiomyopathies and other heart diseases.

Cardiomyopathies↗
PubMed2003

Feasibility of global gene expression analysis in testicular biopsies from infertile men.

Numerous studies have documented the use of microarray analysis to identify patterns of global gene expression that distinguish normal development from that of the diseased state. Yet, there are no reports that compare global gene expression in the fertile and infertile human testis. Here, we report an initial study of global gene expression in testicular biopsies from several men with different infertility phenotypes. We found that microarray analysis of small biopsy samples was suitable for profiling expression of genes known to function in germ cell development and also identified expression of novel genes. Since it is now common for infertile men with spermatogenic failure to use intracytoplasmic sperm injection (ICSI) to achieve biological paternity, we hypothesize that molecular screening of testicular biopsies with microarrays may be suitable: (1) to categorize the molecular phenoytpes of infertile testes in a manner similar to standard morphologic analysis and (2) to initiate larger studies of gene expression in the infertile testes that may identify genetic signatures from biopsies that allow prediction of outcomes.

Biopsy↗
PubMed2005

Differentiating mechanisms of toxicity using global gene expression analysis in Saccharomyces cerevisiae.

Genotoxic stress triggers a variety of biological responses including the transcriptional activation of genes regulating DNA repair, cell survival and cell death. Genomic approaches, which monitor gene expressions across large numbers of genes, can serve as a powerful tool for exploring mechanisms of toxicity. Here, using five different agents, we investigated whether the analysis of genome-wide expression profiles in Saccharomyces cerevisiae could provide insights into mechanisms of genotoxicity versus cytotoxicity. To differentiate the genotoxic stress-associated expression signatures from that of a general cytotoxic stress, we compared gene expression profiles following the treatment with DNA-reactive (cisplatin, MMS, bleomycin) and DNA non-reactive (ethanol and sodium chloride) compounds. Although each of the tested chemicals produced a distinct gene expression profile, we were able to identify a gene expression signature consisting of a relatively small number of biologically relevant genes capable of differentiating genotoxic and cytotoxic stress. The gene set includes such upregulated genes as HUG1, ECM4 and previously uncharacterized gene, YLR297W in the genotoxic and GAP1, CGR1 in the cytotoxic group. Our results indicate the potential of gene expression profile analysis for elucidating mechanism of action of genotoxic agents.

Alkylating Agents↗
PubMed2003

Liquid-based pap smears as a source of RNA for gene expression analysis.

The Papanicolaou smear has contributed to a decrease in cervical cancer rates in populations that receive regular screening. However, treatment of women with mildly abnormal cells is problematic because the majority of these women do not develop neoplasia. Thus, new techniques for identification of truly precancerous cells are needed. Characterization of cellular gene expression patterns is now possible through microarray techniques that survey the expression of large numbers of genes simultaneously. Here we have assessed the feasibility of combining new microscopic and molecular technologies to determine gene expression patterns in cervical intraepithelial neoplasia grade 3 cells recovered from liquid cytology-based Papanicolaou smear slides. Laser capture microdissection was used to retrieve cervical cells from ThinPrep prepared slides. The quality of RNA recovered from these cells proved suitable for reverse transcription polymerase chain reaction and for T7 RNA polymerase-based linear amplification of messenger RNA. We developed an optimized RNA amplification protocol that permitted microarray gene expression profiling in samples of as few as 20 cervical cells. This approach combining laser capture microdissection, linear RNA amplification, and microarray gene expression analysis will enable comparison of gene expression patterns between cytologically abnormal and normal cells taken from a single slide and may assist in the differential diagnosis of histologically difficult cases.

Biomarkers↗
PubMed2001

Global gene expression analysis reveals a role for the alpha 1 integrin in renal pathogenesis.

Kidney fibrosis is the hallmark of most types of progressive kidney disease, including the genetic disorder Alport's syndrome. We undertook gene expression analysis in Alport's syndrome mouse kidneys using microchip arrays to characterize the development of fibrosis. In addition to matrix and matrix-remodeling genes, consistent with interstitial fibrosis, macrophage-related genes show elevated expression levels in Alport's syndrome kidneys. Immunohistochemical analysis of kidney sections illustrated that macrophages as well as myofibroblasts accumulate in the tubular interstitium. Deletion of alpha(1) integrin results in decreased accumulation of both myofibroblasts and macrophages in the tubular interstitium in Alport's syndrome mice and delays disease progression. Transforming growth factor beta antagonism, although reducing interstitial fibrosis, does not limit macrophage accumulation in the tubular interstitium and disease progression. In this study, we identified previously overlooked inflammatory events that occur in the tubulointerstitial region. We propose that in addition to the previously suggested role for the alpha(1)beta(1) integrin in mesangial expansion and abnormal laminin deposition, this integrin may be critical for monocyte accumulation that, in turn, may lead directly to renal failure. Our gene expression and immunohistochemical data indicate that macrophage accumulation is dependent on alpha(1) integrin expression on the macrophage cell surface and that anti-alpha(1) integrin strategies may be employed as therapeutics in the treatment of chronic inflammatory and fibrotic diseases.

Animals↗
PubMed2002

Differential gene expression analysis during porcine hepatocyte spheroid formation.

Primary porcine hepatocytes cultured in suspension self-assemble into multicellular aggregates or spheroids that display enhanced liver-specific functional capability and remain viable for an extended period of time in vitro. The molecular events underlying the process of spheroid formation were explored by differential gene expression analysis. Critical time points in spheroid formation were first identified by reverse transcriptase-polymerase chain reaction (RT-PCR) analysis of stress-related gene expression levels at different stages of spheroid formation. Suppression subtractive hybridization was used to identify transcripts up- or down-regulated at different stages of spheroid formation. Subsequently, three sets of reciprocal subtractions, comparing freshly isolated hepatocytes, spheroid-forming hepatocytes, and mature spheroids were carried out, and differentially expressed transcripts were isolated, cloned, sequenced, and annotated. A total of 65 genes and 14 novel transcripts were identified as differentially expressed, and very high sequence conservation between pig and human transcripts was observed. The resultant expressed sequence tags (ESTs) revealed a rapid decrease in the transcript levels of a subset of liver-specific genes, cytochrome P450s, and enzymes involved in heme biosynthesis, as well as up-regulation of genes involved in calcium-dependent vesicle trafficking and a number of acute-phase proteins in mature spheroids. Previous morphological and functional data on hepatocyte spheroid formation support cellular polarization of the hepatocyte into apical and basolateral domains in spheroids. This is important for the re-emergence of differentiated functions in vitro and is reflected by differences in gene expression patterns.

Animals↗
PubMed2004

Minimum entropy clustering and applications to gene expression analysis.

Clustering is a common methodology for analyzing the gene expression data. In this paper, we present a new clustering algorithm from an information-theoretic point of view. First, we propose the minimum entropy (measured on a posteriori probabilities) criterion, which is the conditional entropy of clusters given the observations. Fano's inequality indicates that it could be a good criterion for clustering. We generalize the criterion by replacing Shannon's entropy with Havrda-Charvat's structural alpha-entropy. Interestingly, the minimum entropy criterion based on structural alpha-entropy is equal to the probability error of the nearest neighbor method when alpha = 2. This is another evidence that the proposed criterion is good for clustering. With a non-parametric approach for estimating a posteriori probabilities, an efficient iterative algorithm is then established to minimize the entropy. The experimental results show that the clustering algorithm performs significantly better than k-means/medians, hierarchical clustering, SOM, and EM in terms of adjusted Rand index. Particularly, our algorithm performs very well even when the correct number of clusters is unknown. In addition, most clustering algorithms produce poor partitions in presence of outliers while our method can correctly reveal the structure of data and effectively identify outliers simultaneously.

Algorithms↗
PubMed2000

A natural history of melanoma: serial gene expression analysis.

Ena Wang and Francesco Marincola propose a novel strategy whereby tumor-host interactions are studied within the melanoma microenvironment by serial gene expression analysis. Methodological constraints and ways to circumvent them are discussed. This approach might improve our understanding of the molecular basis of tumor regression in response to immune manipulation.

Alleles↗
PubMed2004

Functional gene expression analysis of clonal plasma cells identifies a unique molecular profile for light chain amyloidosis.

Immunoglobulin light chain amyloidosis (AL) is characterized by a clonal expansion of plasma cells within the bone marrow. Gene expression analysis was used to identify a unique molecular profile for AL using enriched plasma cells (CD138+) from the bone marrow of 24 patients with AL and 28 patients with multiple myeloma (MM) and 6 healthy controls. Class prediction analysis (PAM) revealed a subset of 12 genes, which included TNFRSF7 (CD27), SDF-1, and PSMA2, that distinguished between these 2 groups with an estimated and observed accuracy of classification of 92%. This model was validated with an independent dataset of 11 patients with AL and 12 patients with MM with 87% accuracy. Differential expression for the most discriminant genes in the 12-gene subset was validated using quantitative real-time polymerase chain reaction and protein expression analysis, which upheld the observations from the micro-array expression data. Functional analyses using a novel network mapping software revealed a number of potentially significant pathways that were dysregulated in patients with AL, with those regulating proliferation, apoptosis, cell signaling, chemotaxis, and migration being substantially represented. This study provides new insight into the molecular profile of clonal plasma cells and its functional relevance in the pathogenesis of light chain amyloidosis.

Aged↗
PubMed2004

Use of beta-glucuronidase reporter gene for gene expression analysis in turfgrasses.

The beta-glucuronidase (GUS) gene has been successfully used as a reporter gene in innumerable number of plant species. The functional GUS gene produces blue coloration in plants upon integration into the plant genome. Because of the ease it provides to analyze the gene expression (as no expensive equipment is needed), GUS gene is surely plant biotechnologist's first choice as a reporter gene. The turfgrass family contains the world's most economically important horticultural crops. There is a world-wide drive for genetic modification of grasses due to its huge economic importance. GUS gene can be transiently or stably expressed in grasses for the purpose of promoter analysis and to study tissue-specific and developmental gene expression. This paper summarizes the use of GUS gene for transient and stable expression studies in various turfgrass species.

Gene Expression Profiling↗
PubMed2000

CLICK: a clustering algorithm with applications to gene expression analysis.

Novel DNA microarray technologies enable the monitoring of expression levels of thousands of genes simultaneously. This allows a global view on the transcription levels of many (or all) genes when the cell undergoes specific conditions or processes. Analyzing gene expression data requires the clustering of genes into groups with similar expression patterns. We have developed a novel clustering algorithm, called CLICK, which is applicable to gene expression analysis as well as to other biological applications. No prior assumptions are made on the structure or the number of the clusters. The algorithm utilizes graph-theoretic and statistical techniques to identify tight groups of highly similar elements (kernels), which are likely to belong to the same true cluster. Several heuristic procedures are then used to expand the kernels into the full clustering. CLICK has been implemented and tested on a variety of biological datasets, ranging from gene expression, cDNA oligo-fingerprinting to protein sequence similarity. In all those applications it outperformed extant algorithms according to several common figures of merit. CLICK is also very fast, allowing clustering of thousands of elements in minutes, and over 100,000 elements in a couple of hours on a regular workstation.

Algorithms↗