953 resultados para Expression Profiling
Resumo:
Estradiol and progesterone are crucial for the acquisition of receptivity and the change in transcriptional activity of target genes in the implantation window. The aim of this study was to differentiate the regulation of genes in the endometrium of patients with recurrent implantation failure (IF) versus those who became pregnant after in vitro fertilization (IVF) treatment. Moreover, the effect of embryo-derived factors on endometrial transcriptional activity was studied. Nine women with known IVF outcome (IF, M, miscarriage, OP, ongoing pregnancy) and undergoing hysteroscopy with endometrial biopsy were enrolled. Biopsies were taken during the midluteal phase. After culture in the presence of embryo-conditioned IVF media, total RNA was extracted and submitted to reverse transcription, target cDNA synthesis, biotin labelling, fragmentation and hybridization using the Affymetrix Human Genome U133A 2.0 Chip. Differential expression of selected genes was re-analysed by quantitative PCR, in which the results were calculated as threshold cycle differences between the groups and normalized to Glyceraldehyde phosphate dehydrogenase and beta-actin. Differences were seen for several genes from endometrial tissue between the IF and the pregnancy groups, and when comparing OP with M, 1875 up- and 1807 down-regulated genes were returned. Real-time PCR analysis confirmed up-regulation for somatostatin, PLAP-2, mucin 4 and CD163, and down-regulation of glycodelin, IL-24, CD69, leukaemia inhibitory factor and prolactin receptor between Op and M. When the different embryo-conditioned media were compared, no significant differential regulation could be demonstrated. Although microarray profiling may currently not be sensitive enough for studying the effects of embryo-derived factors on the endometrium, the observed differences in gene expression between M and OP suggest that it will become an interesting tool for the identification of fertility-relevant markers produced by the endometrium.
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Arabidopsis expressing the castor bean (Ricinus communis) oleate 12-hydroxylase or the Crepis palaestina linoleate 12-epoxygenase in developing seeds typically accumulate low levels of ricinoleic acid and vernolic acid, respectively. We have examined the presence of a futile cycle of fatty acid degradation in developing seeds using the synthesis of polyhydroxyalkanoate (PHA) from the intermediates of the peroxisomal beta-oxidation cycle. Both the quantity and monomer composition of the PHA synthesized in transgenic plants expressing the 12-epoxygenase and 12-hydroxylase in developing seeds revealed the presence of a futile cycle of degradation of the corresponding unusual fatty acids, indicating a limitation in their stable integration into lipids. The expression profile of nearly 200 genes involved in fatty acid biosynthesis and degradation has been analyzed through microarray. No significant changes in gene expression have been detected as a consequence of the activity of the 12-epoxygenase or the 12-hydroxylase in developing siliques. Similar results have also been obtained for transgenic plants expressing the Cuphea lanceolata caproyl-acyl carrier protein thioesterase and accumulating high amounts of caproic acid. Only in developing siliques of the tag1 mutant, deficient in the accumulation of triacylglycerols and shown to have a substantial futile cycling of fatty acids toward beta-oxidation, have some changes in gene expression been detected, notably the induction of the isocitrate lyase gene. These results indicate that analysis of peroxisomal PHA is a better indicator of the flux of fatty acid through beta-oxidation than the expression profile of genes involved in lipid metabolism.
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Down syndrome (DS) is characterized by extensive phenotypic variability, with most traits occurring in only a fraction of affected individuals. Substantial gene-expression variation is present among unaffected individuals, and this variation has a strong genetic component. Since DS is caused by genomic-dosage imbalance, we hypothesize that gene-expression variation of human chromosome 21 (HSA21) genes in individuals with DS has an impact on the phenotypic variability among affected individuals. We studied gene-expression variation in 14 lymphoblastoid and 17 fibroblast cell lines from individuals with DS and an equal number of controls. Gene expression was assayed using quantitative real-time polymerase chain reaction on 100 and 106 HSA21 genes and 23 and 26 non-HSA21 genes in lymphoblastoid and fibroblast cell lines, respectively. Surprisingly, only 39% and 62% of HSA21 genes in lymphoblastoid and fibroblast cells, respectively, showed a statistically significant difference between DS and normal samples, although the average up-regulation of HSA21 genes was close to the expected 1.5-fold in both cell types. Gene-expression variation in DS and normal samples was evaluated using the Kolmogorov-Smirnov test. According to the degree of overlap in expression levels, we classified all genes into 3 groups: (A) nonoverlapping, (B) partially overlapping, and (C) extensively overlapping expression distributions between normal and DS samples. We hypothesize that, in each cell type, group A genes are the most dosage sensitive and are most likely involved in the constant DS traits, group B genes might be involved in variable DS traits, and group C genes are not dosage sensitive and are least likely to participate in DS pathological phenotypes. This study provides the first extensive data set on HSA21 gene-expression variation in DS and underscores its role in modulating the outcome of gene-dosage imbalance.
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A preliminary understanding into the phenotypic effect of DNA segment copy number variation (CNV) is emerging. These rearrangements were demonstrated to influence, in a somewhat dose-dependent manner, the expression of genes that map within them. They were also shown to modify the expression of genes located on their flanks and sometimes those at a great distance from their boundary. Here we demonstrate, by monitoring these effects at multiple life stages, that these controls over expression are effective throughout mouse development. Similarly, we observe that the more specific spatial expression patterns of CNV genes are maintained through life. However, we find that some brain-expressed genes mapping within CNVs appear to be under compensatory loops only at specific time points, indicating that the effect of CNVs on these genes is modulated during development. Notably, we also observe that CNV genes are significantly enriched within transcripts that show variable time courses of expression between strains. Thus, modifying the copy number of a gene may potentially alter not only its expression level, but also the timing of its expression.
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The Potocki-Lupski syndrome (PTLS) is associated with a microduplication of 17p11.2. Clinical features include multiple congenital and neurobehavioral abnormalities and autistic features. We have generated a PTLS mouse model, Dp(11)17/+, that recapitulates some of the physical and neurobehavioral phenotypes present in patients. Here, we investigated the social behavior and gene expression pattern of this mouse model in a pure C57BL/6-Tyr(c-Brd) genetic background. Dp(11)17/+ male mice displayed normal home-cage behavior but increased anxiety and increased dominant behavior in specific tests. A subtle impairment in the preference for a social target versus an inanimate target and abnormal preference for social novelty (the preference to explore an unfamiliar mouse versus a familiar one) was also observed. Our results indicate that these animals could provide a valuable model to identify the specific gene(s) that confer abnormal social behaviors and that map within this delimited genomic deletion interval. In a first attempt to identify candidate genes and for elucidating the mechanisms of regulation of these important phenotypes, we directly assessed the relative transcription of genes within and around this genomic interval. In this mouse model, we found that candidates genes include not only most of the duplicated genes, but also normal-copy genes that flank the engineered interval; both categories of genes showed altered expression levels in the hippocampus of Dp(11)17/+ mice.
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A simple non-targeted differential HPLC-APCI/MS approach has been developed in order to survey metabolome modifications that occur in the leaves of Arabidopsis thaliana following wound-induced stress. The wound-induced accumulation of metabolites, particularly oxylipins, was evaluated by HPLC-MS analysis of crude leaf extracts. A generic, rapid and reproducible pressure liquid extraction procedure was developed for the analysis of restricted leaf samples without the need for specific sample preparation. The presence of various oxylipins was determined by head-to-head comparison of the HPLC-MS data, filtered with a component detection algorithm, and automatically compared with the aid of software searching for small differences in similar HPLC-MS profiles. Repeatability was verified in several specimens belonging to different series. Wound-inducible jasmonates were efficiently highlighted by this non-targeted approach without the need for complex sample preparation as is the case for the 'oxylipin signature' procedure based on GC-MS. Furthermore this HPLC-MS screening technique allowed the isolation of induced compounds for further characterisation by capillary-scale NMR (CapNMR) after HPLC scale-up. In this paper, the screening method is described and applied to illustrate its potential for monitoring polar and non-polar stress-induced constituents as well as its use in combination with CapNMR for the structural assignment of wound-induced compounds of interest
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Background: Estrogen receptor positive (ER+) breast cancers (BC) are heterogeneous with regard to their clinical behavior and response to therapies. The ER is currently the best predictor of response to the anti-estrogen agent tamoxifen, yet up to 30-40% of ER+ BC will relapse despite tamoxifen treatment. New prognostic biomarkers and further biological understanding of tamoxifen resistance are required. We used gene expression profiling to develop an outcome-based predictor using a training set of 255 ER+ BC samples from women treated with adjuvant tamoxifen monotherapy. We used clusters of highly correlated genes to develop our predictor to facilitate both signature stability and biological interpretation. Independent validation was performed using 362 tamoxifen-treated ER+ BC samples obtained from multiple institutions and treated with tamoxifen only in the adjuvant and metastatic settings.Results: We developed a gene classifier consisting of 181 genes belonging to 13 biological clusters. In the independent set of adjuvantly-treated samples, it was able to define two distinct prognostic groups (HR 2.01 95% CI: 1.29-3.13; p = 0.002). Six of the 13 gene clusters represented pathways involved in cell cycle and proliferation. In 112 metastatic breast cancer patients treated with tamoxifen, one of the classifier components suggesting a cellular inflammatory mechanism was significantly predictive of response.Conclusion: We have developed a gene classifier that can predict clinical outcome in tamoxifen-treated ER+ BC patients. Whilst our study emphasizes the important role of proliferation genes in prognosis, our approach proposes other genes and pathways that may elucidate further mechanisms that influence clinical outcome and prediction of response to tamoxifen.
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The use of immunosuppressive drugs in transplanted patients is associated with the development of diabetes, possibly due to β-cell toxicity. To better understand the mechanisms leading to post-transplant diabetes, we investigated the actions of prolonged exposure of isolated human islets to therapeutical levels of tacrolimus (Tac) or cyclosporin A (CsA). Islets were isolated from the pancreas of multiorgan donors by enzymatic digestion and density gradient centrifugation. Functional, survival and molecular studies were then performed after 4 days of incubation with therapeutical concentrations of Tac or CsA. Glucose-induced insulin secretion was significantly decreased in Tac, but not in CsA exposed islets, which was associated with a reduction of the amount of insulin granules as shown by electron microscopy. The percentage of apoptotic β-cells was higher in Tac than CsA exposed islets. Microarray experiments followed by Gene Set Enrichment Analysis revealed that gene expression was more markedly affected upon Tac treatment. In conclusion, Tac and CsA affect features of beta-cell differently, with several changes occurring at the molecular level.
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BACKGROUND: The diagnosis of malignant hematologic diseases has become increasingly complex during the last decade. It is based on the interpretation of results from different laboratory analyses, which range from microscopy to gene expression profiling. Recently, a method for the analysis of RNA phenotypes has been developed, the nCounter technology (Nanostring® Technologies), which allows for simultaneous quantification of hundreds of RNA molecules in biological samples. We evaluated this technique in a Swiss multi-center study on eighty-six samples from acute leukemia patients. METHODS: mRNA and protein profiles were established for normal peripheral blood and bone marrow samples. Signal intensities of the various tested antigens with surface expression were similar to those found in previously performed Affymetrix microarray analyses. Acute leukemia samples were analyzed for a set of twenty-two validated antigens and the Pearson Correlation Coefficient for nCounter and flow cytometry results was calculated. RESULTS: Highly significant values between 0.40 and 0.97 were found for the twenty-two antigens tested. A second correlation analysis performed on a per sample basis resulted in concordant results between flow cytometry and nCounter in 44-100% of the antigens tested (mean = 76%), depending on the number of blasts present in a sample, the homogeneity of the blast population, and the type of leukemia (AML or ALL). CONCLUSIONS: The nCounter technology allows for fast and easy depiction of a mRNA profile from hematologic samples. This technology has the potential to become a valuable tool for the diagnosis of acute leukemias, in addition to multi-color flow cytometry.
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PURPOSE: Pediatric rhabdomyosarcoma (RMS) has two common histologic subtypes: embryonal (ERMS) and alveolar (ARMS). PAX-FOXO1 fusion gene status is a more reliable prognostic marker than alveolar histology, whereas fusion gene-negative (FN) ARMS patients are clinically similar to ERMS patients. A five-gene expression signature (MG5) previously identified two diverse risk groups within the fusion gene-negative RMS (FN-RMS) patients, but this has not been independently validated. The goal of this study was to test whether expression of the MG5 metagene, measured using a technical platform that can be applied to routine pathology material, would correlate with outcome in a new cohort of patients with FN-RMS. EXPERIMENTAL DESIGN: Cases were taken from the Children's Oncology Group (COG) D9803 study of children with intermediate-risk RMS, and gene expression profiling for the MG5 genes was performed using the nCounter assay. The MG5 score was correlated with clinical and pathologic characteristics as well as overall and event-free survival. RESULTS: MG5 standardized score showed no significant association with any of the available clinicopathologic variables. The MG5 signature score showed a significant correlation with overall (N = 57; HR, 7.3; 95% CI, 1.9-27.0; P = 0.003) and failure-free survival (N = 57; HR, 6.1; 95% CI, 1.9-19.7; P = 0.002). CONCLUSIONS: This represents the first, validated molecular prognostic signature for children with FN-RMS who otherwise have intermediate-risk disease. The capacity to measure the expression of a small number of genes in routine pathology material and apply a simple mathematical formula to calculate the MG5 metagene score provides a clear path toward better risk stratification in future prospective clinical trials. Clin Cancer Res; 21(20); 4733-9. ©2015 AACR.
Resumo:
Endometriosis is a common hormone-dependent gynecological disease leading to severe menstrual and/or chronic pelvic pain with or without subfertility. The disease is defined by the presence of endometrium-like tissue outside the uterine cavity, primarily on the pelvic peritoneum, ovaries and infiltrating organs of the peritoneal cavity. The current tools for diagnosis and treatment of endometriosis need to be improved to ensure reliable diagnosis and effective treatment. In addition, endometriosis is associated with increased risk of ovarian cancer and, therefore, the differential diagnosis between the benign and malignant ovarian cysts is of importance. The long-term objective of the present study was to support the discovery of novel tools for diagnosis and treatment of endometriosis. This was approached by exploiting genome-wide expression analysis of endometriosis specimens. A novel expression profiling -based classification of endometriosis indicated specific subgroups of lesions partially consistent with the clinical appearance, but partially according to unknown factors. The peritoneum of women with endometriosis appeared to be altered in comparison to that of healthy control subjects, suggesting a novel aspect on the pathogenesis of the disease. The evaluation of action and metabolism of sex hormones in endometrium and endometriosis tissue indicated a novel role of androgens in regulation of the tissues. In addition, an enzyme involved in androgen and neurosteroid metabolism, hydroxysteroid (17beta) dehydrogenase 6, was found to be highly up-regulated in endometriosis tissue as compared to healthy endometrium. The enzyme may have a role in the pathogenesis of endometriosis or in the endometriosis associated pain generation. Finally, a new diagnostic biomarker, HE4, was discovered distinguishing patients with ovarian endometriotic cysts from those with malignant ovarian cancer. The information acquired in this study enables deeper understanding of endometriosis and facilitates the development of improved diagnostic tools and more specific treatments of the disease
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Our understanding of the pathogenesis of organ‐specific autoinflammation has been restricted by limited access to the target organs. Peripheral blood, however, as a preferred transportation route for immune cells, provides a window to assess the entire immune system throughout the body. Transcriptional profiling with RNA stabilizing blood collection tubes reflects in vivo expression profiles at the time the blood is drawn, allowing detection of the disease activity in different samples or within the same sample over time. The main objective of this Ph.D. study was to apply gene‐expression microarrays in the characterization of peripheral blood transcriptional profiles in patients with autoimmune diseases. To achieve this goal a custom cDNA microarray targeted for gene‐expression profiling of human immune system was designed and produced. Sample collection and preparation was then optimized to allow gene‐expression profiling from whole‐blood samples. To overcome challenges resulting from minute amounts of sample material, RNA amplification was successfully applied to study pregnancy related immunosuppression in patients with multiple sclerosis (MS). Furthermore, similar sample preparation was applied to characterize longitudinal genome‐wide expression profiles in children with type 1 diabetes (T1D) associated autoantibodies and eventually clinical T1D. Blood transcriptome analyses, using both the ImmunoChip cDNA microarray with targeted probe selection and genome‐wide Affymetrix U133 Plus 2.0 oligonucleotide array, enabled monitoring of autoimmune activity. Novel disease related genes and general autoimmune signatures were identified. Notably, down‐regulation of the HLA class Ib molecules in peripheral blood was associated with disease activity in both MS and T1D. Taken together, these studies demonstrate the potential of peripheral blood transcriptional profiling in biomedical research and diagnostics. Imbalances in peripheral blood transcriptional activity may reveal dynamic changes that are relevant for the disease but might be completely missed in conventional cross‐sectional studies.
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Important biological and clinical features of malignancy are reflected in its transcript pattern. Recent advances in gene expression technology and informatics have provided a powerful new means to obtain and interpret these expression patterns. A comprehensive approach to expression profiling is serial analysis of gene expression (SAGE), which provides digital information on transcript levels. SAGE works by counting transcripts and storing these digital values electronically, providing absolute gene expression levels that make historical comparisons possible. SAGE produces a comprehensive profile of gene expression and can be used to search for candidate tumor markers or antigens in a limited number of samples. The Cancer Genome Anatomy Project has created a SAGE database of human gene expression levels for many different tumors and normal reference tissues and provides online tools for viewing, comparing, and downloading expression profiles. Digital expression profiling using SAGE and informatics have been useful for identifying genes that have a role in tumor invasion and other aspects of tumor progression.
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Chronic hepatitis B (HBV) and C (HCV) virus infections are the most important factors associated with hepatocellular carcinoma (HCC), but tumor prognosis remains poor due to the lack of diagnostic biomarkers. In order to identify novel diagnostic markers and therapeutic targets, the gene expression profile associated with viral and non-viral HCC was assessed in 9 tumor samples by oligo-microarrays. The differentially expressed genes were examined using a z-score and KEGG pathway for the search of ontological biological processes. We selected a non-redundant set of 15 genes with the lowest P value for clustering samples into three groups using the non-supervised algorithm k-means. Fisher’s linear discriminant analysis was then applied in an exhaustive search of trios of genes that could be used to build classifiers for class distinction. Different transcriptional levels of genes were identified in HCC of different etiologies and from different HCC samples. When comparing HBV-HCC vs HCV-HCC, HBV-HCC/HCV-HCC vs non-viral (NV)-HCC, HBC-HCC vs NV-HCC, and HCV-HCC vs NV-HCC of the 58 non-redundant differentially expressed genes, only 6 genes (IKBKβ, CREBBP, WNT10B, PRDX6, ITGAV, and IFNAR1) were found to be associated with hepatic carcinogenesis. By combining trios, classifiers could be generated, which correctly classified 100% of the samples. This expression profiling may provide a useful tool for research into the pathophysiology of HCC. A detailed understanding of how these distinct genes are involved in molecular pathways is of fundamental importance to the development of effective HCC chemoprevention and treatment.
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Ropinirole (ROP) is a dopamine agonist that has been used as therapy for Parkinson's disease. In the present study, we aimed to detect whether gene expression was modulated by ROP in SH-SY5Y cells. SH-SY5Y cell lines were treated with 10 µM ROP for 2 h, after which total RNA was extracted for whole genome analysis. Gene expression profiling revealed that 113 genes were differentially expressed after ROP treatment compared with control cells. Further pathway analysis revealed modulation of the phosphatidylinositol 3-kinase (PI3K) signaling pathway, with prominent upregulation of PIK3C2B. Moreover, batches of regulated genes, including PIK3C2B, were found to be located on chromosome 1. These findings were validated by quantitative RT-PCR and Western blot analysis. Our study, therefore, revealed that ROP altered gene expression in SH-SY5Y cells, and future investigation of PIK3C2B and other loci on chromosome 1 may provide long-term implications for identifying novel target genes of Parkinson's disease.