974 resultados para microarray analysis


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To define specific pathways important in the multistep transformation process of normal plasma cells (PCs) to monoclonal gammopathy of uncertain significance (MGUS) and multiple myeloma (MM), we have applied microarray analysis to PCs from 5 healthy donors (N), 7 patients with MGUS, and 24 patients with newly diagnosed MM. Unsupervised hierarchical clustering using 125 genes with a large variation across all samples defined 2 groups: N and MGUS/MM. Supervised analysis identified 263 genes differentially expressed between N and MGUS and 380 genes differentially expressed between N and MM, 197 of which were also differentially regulated between N and MGUS. Only 74 genes were differentially expressed between MGUS and MM samples, indicating that the differences between MGUS and MM are smaller than those between N and MM or N and MGUS. Differentially expressed genes included oncogenes/tumor-suppressor genes (LAF4, RB1, and disabled homolog 2), cell-signaling genes (RAS family members, B-cell signaling and NF-kappaB genes), DNA-binding and transcription-factor genes (XBP1, zinc finger proteins, forkhead box, and ring finger proteins), and developmental genes (WNT and SHH pathways). Understanding the molecular pathogenesis of MM by gene expression profiling has demonstrated sequential genetic changes from N to malignant PCs and highlighted important pathways involved in the transformation of MGUS to MM.

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BACKGROUND: Stromal signalling increases the lateral cell adhesions of prostate epithelial cells grown in 3D culture. The aim of this study was to use microarray analysis to identify significant epithelial signalling pathways and genes in this process. METHODS: Microarray analysis was used to identify genes that were differentially expressed when epithelial cells were grown in 3D Matrigel culture with stromal co-culture compared to without stroma. Two culture models were employed: primary epithelial cells (ten samples) and an epithelial cell line (three experiments). A separate microarray analysis was performed on each model system and then compared to identify tissue-relevant genes in a cell line model. RESULTS: TGF beta signalling was significantly ranked for both model systems and in both models the TGF beta signalling gene SOX4 was significantly down regulated. Analysis of all differentially expressed genes to identify genes that were common to both models found several morphology related gene clusters; actin binding (DIAPH2, FHOD3, ABLIM1, TMOD4, MYH10), GTPase activator activity (BCR, MYH10), cytoskeleton (MAP2, MYH10, TMOD4, FHOD3), protein binding (ITGA6, CD44), proteinaceous extracellular matrix (NID2, CILP2), ion channel/ ion transporter activity (CACNA1C, CACNB2, KCNH2, SLC8A1, SLC39A9) and genes associated with developmental pathways (POFUT1, FZD2, HOXA5, IRX2, FGF11, SOX4, SMARCC1). CONCLUSIONS: In 3D prostate cultures, stromal cells increase lateral epithelial cell adhesions. We show that this morphological effect is associated with gene expression changes to TGF beta signalling, cytoskeleton and anion activity.

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OBJECTIVE: This study explored gene expression differences in predicting response to chemoradiotherapy in esophageal cancer. PURPOSE:: A major pathological response to neoadjuvant chemoradiation is observed in about 40% of esophageal cancer patients and is associated with favorable outcomes. However, patients with tumors of similar histology, differentiation, and stage can have vastly different responses to the same neoadjuvant therapy. This dichotomy may be due to differences in the molecular genetic environment of the tumor cells. BACKGROUND DATA: Diagnostic biopsies were obtained from a training cohort of esophageal cancer patients (13), and extracted RNA was hybridized to genome expression microarrays. The resulting gene expression data was verified by qRT-PCR. In a larger, independent validation cohort (27), we examined differential gene expression by qRT-PCR. The ability of differentially-regulated genes to predict response to therapy was assessed in a multivariate leave-one-out cross-validation model. RESULTS: Although 411 genes were differentially expressed between normal and tumor tissue, only 103 genes were altered between responder and non-responder tumor; and 67 genes differentially expressed >2-fold. These included genes previously reported in esophageal cancer and a number of novel genes. In the validation cohort, 8 of 12 selected genes were significantly different between the response groups. In the predictive model, 5 of 8 genes could predict response to therapy with 95% accuracy in a subset (74%) of patients. CONCLUSIONS: This study has identified a gene microarray pattern and a set of genes associated with response to neoadjuvant chemoradiation in esophageal cancer. The potential of these genes as biomarkers of response to treatment warrants further investigation. Copyright © 2009 by Lippincott Williams & Wilkins.

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Cancer can be defined as a deregulation or hyperactivity in the ongoing network of intracellular and extracellular signaling events. Reverse phase protein microarray technology may offer a new opportunity to measure and profile these signaling pathways, providing data on post-translational phosphorylation events not obtainable by gene microarray analysis. Treatment of ovarian epithelial carcinoma almost always takes place in a metastatic setting since unfortunately the disease is often not detected until later stages. Thus, in addition to elucidation of the molecular network within a tumor specimen, critical questions are to what extent do signaling changes occur upon metastasis and are there common pathway elements that arise in the metastatic microenvironment. For individualized combinatorial therapy, ideal therapeutic selection based on proteomic mapping of phosphorylation end points may require evaluation of the patient's metastatic tissue. Extending these findings to the bedside will require the development of optimized protocols and reference standards. We have developed a reference standard based on a mixture of phosphorylated peptides to begin to address this challenge.

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DNA methylation at promoter CpG islands (CGI) is an epigenetic modification associated with inappropriate gene silencing in multiple tumor types. In the absence of a human pituitary tumor cell line, small interfering RNA-mediated knockdown of the maintenance methyltransferase DNA methyltransferase (cytosine 5)-1 (Dnmt1) was used in the murine pituitary adenoma cell line AtT-20. Sustained knockdown induced reexpression of the fully methylated and normally imprinted gene neuronatin (Nnat) in a time-dependent manner. Combined bisulfite restriction analysis (COBRA) revealed that reexpression of Nnat was associated with partial CGI demethylation, which was also observed at the H19 differentially methylated region. Subsequent genome-wide microarray analysis identified 91 genes that were significantly differentially expressed in Dnmt1 knockdown cells (10% false discovery rate). The analysis showed that genes associated with the induction of apoptosis, signal transduction, and developmental processes were significantly overrepresented in this list (P < 0.05). Following validation by reverse transcription-PCR and detection of inappropriate CGI methylation by COBRA, four genes (ICAM1, NNAT, RUNX1, and S100A10) were analyzed in primary human pituitary tumors, each displaying significantly reduced mRNA levels relative to normal pituitary (P < 0.05). For two of these genes, NNAT and S100A10, decreased expression was associated with increased promoter CGI methylation. Induced expression of Nnat in stable transfected AtT-20 cells inhibited cell proliferation. To our knowledge, this is the first report of array-based "epigenetic unmasking" in combination with Dnmt1 knockdown and reveals the potential of this strategy toward identifying genes silenced by epigenetic mechanisms across species boundaries.

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Giant Cell Arteritis (GCA) is the most common vasculitis affecting the elderly. Archived formalin-fixed paraffin-embedded (FFPE) temporal artery biopsy (TAB) specimens potentially represent a valuable resource for large-scale genetic analysis of this disease. FFPE TAB samples were obtained from 12 patients with GCA. Extracted TAB DNA was assessed by real time PCR before restoration using the Illumina HD FFPE Restore Kit. Paired FFPE-blood samples were genotyped on the Illumina OmniExpress FFPE microarray. The FFPE samples that passed stringent quality control measures had a mean genotyping success of >97%. When compared with their matching peripheral blood DNA, the mean discordant heterozygote and homozygote single nucleotide polymorphisms calls were 0.0028 and 0.0003, respectively, which is within the accepted tolerance of reproducibility. This work demonstrates that it is possible to successfully obtain high-quality microarray-based genotypes FFPE TAB samples and that this data is similar to that obtained from peripheral blood.

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Copy number variations (CNVs) as described in the healthy population are purported to contribute significantly to genetic heterogeneity. Recent studies have described CNVs using lymphoblastoid cell lines or by application of specifically developed algorithms to interrogate previously described data. However, the full extent of CNVs remains unclear. Using high-density SNP array, we have undertaken a comprehensive investigation of chromosome 18 for CNV discovery and characterisation of distribution and association with chromosome architecture. We identified 399 CNVs, of which loss represents 98%, 58% are less than 2.5 kb in size and 71% are intergenic. Intronic deletions account for the majority of copy number changes with gene involvement. Furthermore, one-third of CNVs do not have putative breakpoints within repetitive sequences. We conclude that replicative processes, mediated either by repetitive elements or microhomology, account for the majority of CNVs in the healthy population. Genomic instability involving the formation of a non-B structure is demonstrated in one region.

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Pectobacterium atrosepticum on Gram-negatiivinen bakteeri, joka aiheuttaa perunan tyvi- ja märkämätää. P. atrosepticum bakteerin optimilämpötila on melko alhainen ja se on yleinen lauhkeilla alueilla. Tyvimätä leviää pääasiassa siemenperunan välityksellä ja siksi se on ongelma erityisesti siemenperunan tuotannossa. P. atrosepticum kannan SCRI1043 genomi on julkaistu ja sitä tutkitaan malliorganismina märkä- ja tyvimädän taudinaiheuttamisen ymmärtämiseksi. Tämä opportunistinen taudinaiheuttaja voi elää isäntäkasvissa kuukausia piilevänä, aiheuttamatta näkyviä oireita. Suotuisissa olosuhteissa bakteerit alkavat jakautua ja tuottaa kasvin kudoksia hajottavia entsyymejä. Mädäntyvä kasvimassa tarjoaa ravinteita bakteerien kasvuun ja mahdollistaa isäntäkasvin asuttamisen. Soluseiniä hajottavien entsyymien merkitys taudinaiheuttamisessa on hyvin tunnettu, mutta oireettomasta jaksosta ja taudin alkuvaiheista tiedätään vain vähän. Bakteerin genomi sisältää monia toksiineja, adhesiineja, hemolysiineja ja muita proteiineja, joilla saattaa olla merkitys taudinaiheuttamisessa. Tässä työssä käytettiin proteomiikkaa ja mikrosiruanalysiä P. atrosepticum bakteerin erittyvien proteiinien ja geeniekspression tutkimiseen. Proteiinit, jotka eritetään ulos bakteerista, toimivat todennäköisesti taudinaiheuttamisessa, koska ne ovat suorassa kontaktissa isäntäkasvin kanssa. Analyysit suoritettiin olosuhteissa, jotka muistuttavat kasvin soluvälitilaa: matala pH, vähän ravinteita ja matala lämpötila. Isäntäkasvin läsnäolon vaikutusta proteiinien tuottoon ja geeniekspressioon tutkittiin lisäämällä perunauutetta kasvatusalustaan. Tutkimuksessa tunnistettiin P. atrosepticum bakteerin monia jo tunnettuja ja mahdollisesti taudinaiheuttamiseen liittyviä proteiineja. Perunauute lisäsi hiljattain tunnistetun, proteiinien eritysreittiä (tyyppi VI sekreetio, T6SS) koodaavien geenien ilmentymistä. Lisäksi bakteerin havaittiin erittävän useita T6SS:n liittyviä proteiineja kasvualustaan, johon oli lisätty perunauutetta. T6SS:n merkitys bakteereille on vielä epäselvä ja sen vaikutuksesta taudinaiheuttamiseen on julkaistu ristiriitaisia tuloksia. Märkä- ja tyvimädän ymmärtäminen molekulaarisella tasolla luo pohjan tautien kontrollointiin tähtäävään soveltavaan tutkimukseen. Tämä tutkimus lisää tietoa kasvi-patogeeni- interaktiosta ja sitä voidaan tulevaisuudessa käyttää hyväksi esimerkiksi diagnostiikassa, resistenttien perunalajikkeiden jalostuksessa tai viljely- ja varastointiolosuhteiden parantamisessa.

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During the past ten years, large-scale transcript analysis using microarrays has become a powerful tool to identify and predict functions for new genes. It allows simultaneous monitoring of the expression of thousands of genes and has become a routinely used tool in laboratories worldwide. Microarray analysis will, together with other functional genomics tools, take us closer to understanding the functions of all genes in genomes of living organisms. Flower development is a genetically regulated process which has mostly been studied in the traditional model species Arabidopsis thaliana, Antirrhinum majus and Petunia hybrida. The molecular mechanisms behind flower development in them are partly applicable in other plant systems. However, not all biological phenomena can be approached with just a few model systems. In order to understand and apply the knowledge to ecologically and economically important plants, other species also need to be studied. Sequencing of 17 000 ESTs from nine different cDNA libraries of the ornamental plant Gerbera hybrida made it possible to construct a cDNA microarray with 9000 probes. The probes of the microarray represent all different ESTs in the database. From the gerbera ESTs 20% were unique to gerbera while 373 were specific to the Asteraceae family of flowering plants. Gerbera has composite inflorescences with three different types of flowers that vary from each other morphologically. The marginal ray flowers are large, often pigmented and female, while the central disc flowers are smaller and more radially symmetrical perfect flowers. Intermediate trans flowers are similar to ray flowers but smaller in size. This feature together with the molecular tools applied to gerbera, make gerbera a unique system in comparison to the common model plants with only a single kind of flowers in their inflorescence. In the first part of this thesis, conditions for gerbera microarray analysis were optimised including experimental design, sample preparation and hybridization, as well as data analysis and verification. Moreover, in the first study, the flower and flower organ-specific genes were identified. After the reliability and reproducibility of the method were confirmed, the microarrays were utilized to investigate transcriptional differences between ray and disc flowers. This study revealed novel information about the morphological development as well as the transcriptional regulation of early stages of development in various flower types of gerbera. The most interesting finding was differential expression of MADS-box genes, suggesting the existence of flower type-specific regulatory complexes in the specification of different types of flowers. The gerbera microarray was further used to profile changes in expression during petal development. Gerbera ray flower petals are large, which makes them an ideal model to study organogenesis. Six different stages were compared and specifically analysed. Expression profiles of genes related to cell structure and growth implied that during stage two, cells divide, a process which is marked by expression of histones, cyclins and tubulins. Stage 4 was found to be a transition stage between cell division and expansion and by stage 6 cells had stopped division and instead underwent expansion. Interestingly, at the last analysed stage, stage 9, when cells did not grow any more, the highest number of upregulated genes was detected. The gerbera microarray is a fully-functioning tool for large-scale studies of flower development and correlation with real-time RT-PCR results show that it is also highly sensitive and reliable. Gene expression data presented here will be a source for gene expression mining or marker gene discovery in the future studies that will be performed in the Gerbera Laboratory. The publicly available data will also serve the plant research community world-wide.

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Aneuploidy is among the most obvious differences between normal and cancer cells. However, mechanisms contributing to development and maintenance of aneuploid cell growth are diverse and incompletely understood. Functional genomics analyses have shown that aneuploidy in cancer cells is correlated with diffuse gene expression signatures and that aneuploidy can arise by a variety of mechanisms, including cytokinesis failures, DNA endoreplication and possibly through polyploid intermediate states. Here, we used a novel cell spot microarray technique to identify genes with a loss-of-function effect inducing polyploidy and/or allowing maintenance of polyploid cell growth of breast cancer cells. Integrative genomics profiling of candidate genes highlighted GINS2 as a potential oncogene frequently overexpressed in clinical breast cancers as well as in several other cancer types. Multivariate analysis indicated GINS2 to be an independent prognostic factor for breast cancer outcome (p = 0.001). Suppression of GINS2 expression effectively inhibited breast cancer cell growth and induced polyploidy. In addition, protein level detection of nuclear GINS2 accurately distinguished actively proliferating cancer cells suggesting potential use as an operational biomarker.

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In several species including the buffalo cow, prostaglandin (PG) F-2 alpha is the key molecule responsible for regression of corpus luteum (CL). Experiments were carried out to characterize gene expression changes in the CL tissue at various time points after administration of luteolytic dose of PGF(2 alpha) in buffalo cows. Circulating progesterone levels decreased within 1 h of PGF(2 alpha) treatment and evidence of apoptosis was demonstrable at 18 h post treatment. Microarray analysis indicated expression changes in several of immediate early genes and transcription factors within 3 h of treatment. Also, changes in expression of genes associated with cell to cell signaling, cytokine signaling, steroidogenesis, PG synthesis and apoptosis were observed. Analysis of various components of LH/CGR signaling in CL tissues indicated decreased LH/CGR protein expression, pCREB levels and PKA activity post PGF(2 alpha) treatment. The novel finding of this study is the down regulation of CYP19A1 gene expression accompanied by decrease in expression of E-2 receptors and circulating and intra luteal E-2 post PGF(2 alpha) treatment. Mining of microarray data revealed several differentially expressed E-2 responsive genes. Since CYP19A1 gene expression is low in the bovine CL, mining of microarray data of PGF(2 alpha)-treated macaques, the species with high luteal CYP19A1 expression, showed good correlation between differentially expressed E-2 responsive genes between both the species. Taken together, the results of this study suggest that PGF(2 alpha) interferes with luteotrophic signaling, impairs intraluteal E-2 levels and regulates various signaling pathways before the effects on structural luteolysis are manifest.

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Background: DNA methylation and its perturbations are an established attribute to a wide spectrum of phenotypic variations and disease conditions. Indian traditional system practices personalized medicine through indigenous concept of distinctly descriptive physiological, psychological and anatomical features known as prakriti. Here we attempted to establish DNA methylation differences in these three prakriti phenotypes. Methods: Following structured and objective measurement of 3416 subjects, whole blood DNA of 147 healthy male individuals belonging to defined prakriti (Vata, Pitta and Kapha) between the age group of 20-30years were subjected to methylated DNA immunoprecipitation (MeDIP) and microarray analysis. After data analysis, prakriti specific signatures were validated through bisulfite DNA sequencing. Results: Differentially methylated regions in CpG islands and shores were significantly enriched in promoters/UTRs and gene body regions. Phenotypes characterized by higher metabolism (Pitta prakriti) in individuals showed distinct promoter (34) and gene body methylation (204), followed by Vata prakriti which correlates to motion showed DNA methylation in 52 promoters and 139 CpG islands and finally individuals with structural attributes (Kapha prakriti) with 23 and 19 promoters and CpG islands respectively. Bisulfite DNA sequencing of prakriti specific multiple CpG sites in promoters and 5'-UTR such as; LHX1 (Vata prakriti), SOX11 (Pitta prakriti) and CDH22 (Kapha prakriti) were validated. Kapha prakriti specific CDH22 5'-UTR CpG methylation was also found to be associated with higher body mass index (BMI). Conclusion: Differential DNA methylation signatures in three distinct prakriti phenotypes demonstrate the epigenetic basis of Indian traditional human classification which may have relevance to personalized medicine.

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BACKGROUND: Many analyses of microarray association studies involve permutation, bootstrap resampling and cross-validation, that are ideally formulated as embarrassingly parallel computing problems. Given that these analyses are computationally intensive, scalable approaches that can take advantage of multi-core processor systems need to be developed. RESULTS: We have developed a CUDA based implementation, permGPU, that employs graphics processing units in microarray association studies. We illustrate the performance and applicability of permGPU within the context of permutation resampling for a number of test statistics. An extensive simulation study demonstrates a dramatic increase in performance when using permGPU on an NVIDIA GTX 280 card compared to an optimized C/C++ solution running on a conventional Linux server. CONCLUSIONS: permGPU is available as an open-source stand-alone application and as an extension package for the R statistical environment. It provides a dramatic increase in performance for permutation resampling analysis in the context of microarray association studies. The current version offers six test statistics for carrying out permutation resampling analyses for binary, quantitative and censored time-to-event traits.

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BACKGROUND: Since mature erythrocytes are terminally differentiated cells without nuclei and organelles, it is commonly thought that they do not contain nucleic acids. In this study, we have re-examined this issue by analyzing the transcriptome of a purified population of human mature erythrocytes from individuals with normal hemoglobin (HbAA) and homozygous sickle cell disease (HbSS). METHODS AND FINDINGS: Using a combination of microarray analysis, real-time RT-PCR and Northern blots, we found that mature erythrocytes, while lacking ribosomal and large-sized RNAs, contain abundant and diverse microRNAs. MicroRNA expression of erythrocytes was different from that of reticulocytes and leukocytes, and contributed the majority of the microRNA expression in whole blood. When we used microRNA microarrays to analyze erythrocytes from HbAA and HbSS individuals, we noted a dramatic difference in their microRNA expression pattern. We found that miR-320 played an important role for the down-regulation of its target gene, CD71 during reticulocyte terminal differentiation. Further investigation revealed that poor expression of miR-320 in HbSS cells was associated with their defective downregulation CD71 during terminal differentiation. CONCLUSIONS: In summary, we have discovered significant microRNA expression in human mature erythrocytes, which is dramatically altered in HbSS erythrocytes and their defect in terminal differentiation. Thus, the global analysis of microRNA expression in circulating erythrocytes can provide mechanistic insights into the disease phenotypes of erythrocyte diseases.

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BACKGROUND: The term endothelial progenitor cells (EPCs) is currently used to refer to cell populations which are quite dissimilar in terms of biological properties. This study provides a detailed molecular fingerprint for two EPC subtypes: early EPCs (eEPCs) and outgrowth endothelial cells (OECs). METHODS: Human blood-derived eEPCs and OECs were characterised by using genome-wide transcriptional profiling, 2D protein electrophoresis, and electron microscopy. Comparative analysis at the transcript and protein level included monocytes and mature endothelial cells as reference cell types. RESULTS: Our data show that eEPCs and OECs have strikingly different gene expression signatures. Many highly expressed transcripts in eEPCs are haematopoietic specific (RUNX1, WAS, LYN) with links to immunity and inflammation (TLRs, CD14, HLAs), whereas many transcripts involved in vascular development and angiogenesis-related signalling pathways (Tie2, eNOS, Ephrins) are highly expressed in OECs. Comparative analysis with monocytes and mature endothelial cells clusters eEPCs with monocytes, while OECs segment with endothelial cells. Similarly, proteomic analysis revealed that 90% of spots identified by 2-D gel analysis are common between OECs and endothelial cells while eEPCs share 77% with monocytes. In line with the expression pattern of caveolins and cadherins identified by microarray analysis, ultrastructural evaluation highlighted the presence of caveolae and adherens junctions only in OECs. CONCLUSIONS: This study provides evidence that eEPCs are haematopoietic cells with a molecular phenotype linked to monocytes; whereas OECs exhibit commitment to the endothelial lineage. These findings indicate that OECs might be an attractive cell candidate for inducing therapeutic angiogenesis, while eEPC should be used with caution because of their monocytic nature.