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U1 small nuclear RNA (U1 snRNA), as one of the most abundant ncRNAs in human cells, plays an important role in splicing of pre-mRNAs. Compared to previous studies which have focused on the primary function of U1 snRNA and the neurodegenerative diseases caused by abnormalities of U1 snRNA, this study is to investigate how U1 snRNA over-expression affects the expression of mammal genes on a genome-wide scale. By comparing the gene expression profiles of U1 snRNA over-expressed cells with those of their controls using microarray experiments, 916 genes or loci were identified significantly Differentially Expressed (DE). These 595 up-regulated DE genes and 321 down-regulated DE genes were analyzed using annotations from GO categories and pathways from the KEGG database. As a result, three of 12 enriched pathways were well-known cancer pathways, while the other nine pathways were associated to cancers in previous studies. The further analysis of 73 genes involved in 12 pathways suggested that U1 snRNA could regulate cancer gene expression. The microarray data under the GEO Series accession number GSE84304 is available in the NCBI GEO database.
Next-generation sequencing provides an opportunity for an in-depth biocomputational analysis to identify gene expression patterns between soleus and tibialis anterior, two well-characterized skeletal muscles, and analyze their gene expression profiling. RNA read counts were analyzed for differential gene expression using the R package edgeR. Differentially expressed genes were filtered using a false discovery rate of less than 0.05 c, a fold-change value of more than twenty, and an association with overrepresented pathways based on the Reactome pathway over-representation analysis tool. Most of the differentially expressed genes associated with soleus are coded for components of lipid metabolism and unique contractile elements. Differentially expressed genes associated with tibialis anterior encoded mostly for glucose and glycogen metabolic pathway regulatory enzymes and calcium-sensitive contractile components. These gene expression distinctions partly explain the genetic basis for skeletal muscle specialization, and they may help to explain skeletal muscle susceptibility to disease and drugs and further refine tissue engineering approaches.
Gastric cancer is the second leading cause of cancer death worldwide, both in men and women. A genomewide gene expression analysis was carried out to identify differentially expressed genes in gastric adenocarcinoma tissues as compared to adjacent normal tissues. We used Agilent's whole human genome oligonucleotide microarray platform representing ~41,000 genes to carry out gene expression analysis. Two-color microarray analysis was employed to directly compare the expression of genes between tumor and normal tissues. Through this approach, we identified several previously known candidate genes along with a number of novel candidate genes in gastric cancer. Testican-1 (SPOCK1) was one of the novel molecules that was 10-fold upregulated in tumors. Using tissue microarrays, we validated the expression of testican-1 by immunohistochemical staining. It was overexpressed in 56% (160/282) of the cases tested. Pathway analysis led to the identification of several networks in which SPOCK1 was among the topmost networks of interacting genes. By gene enrichment analysis, we identified several genes involved in cell adhesion and cell proliferation to be significantly upregulated while those corresponding to metabolic pathways were significantly downregulated. The differentially expressed genes identified in this study are candidate biomarkers for gastric adenoacarcinoma.
Aim of Review. Huge effort is being made among the transplant community investigating novel biomarkers that enable transplant clinicians to identify patients at risk for allograft rejection or those who will develop tolerance so that immunosuppression could be safely minimized or even ideally withdrawn. Despite the important advances achieved in the identification of several potential biomarkers of tolerance, rejection, or both, validation and demonstration of their clinical utility still needs to be tested, which will need international cooperative networks. It is important to note that the reproducibility of differently expressed genes might be affected by many factors such as gene ranking and selection methods, inherent differences between types, and the choice of thresholds. However, because microarray analyses are expensive and time consuming and their statistical evaluation is often very difficult, gene expression analysis using the RTPCR method is nowadays recommended. Conclusions. In the field of organ transplantation, gene-expression-based decision might help in improving patient and graft outcome and there are a multitude of studies showing that gene-expression profiling is feasible.
As a gynecological oncology, ovarian cancer has high incidence and mortality. To study the mechanisms of ovarian cancer, the present study analyzed the GSE37582 microarray. GSE37582 was downloaded from Gene Expression Omnibus and included data from 74 ovarian cancer cases and 47 healthy controls. The differentially-expressed genes (DEGs) were screened using linear models for microarray data package in R and were further screened for functional annotation. Next, Gene Ontology and pathway enrichment analysis of the DEGs was conducted. The interaction associations of the proteins encoded by the DEGs were searched using the Search Tool for the Retrieval of Interacting Genes, and the protein-protein interaction (PPI) network was visualized by Cytoscape. Moreover, module analysis of the PPI network was performed using the BioNet analysis tool in R. A total of 284 DEGs were screened, consisting of 145 upregulated genes and 139 downregulated genes. In particular, downregulated FBJ murine osteosarcoma viral oncogene homolog (FOS) was an oncogene, while downregulated cyclin-dependent kinase inhibitor 1A (CDKN1A) was a tumor suppressor gene and upregulated cluster of differentiation 44 (CD44) was classed as an 'other' gene. The enriched functions included collagen catabolic process, stress-activated mitogen-activated protein kinases cascade and insulin receptor signaling pathway. Meanwhile, FOS (degree, 15), CD44 (degree, 9), B-cell CLL/lymphoma 2 (BCL2; degree, 7), CDKN1A (degree, 7) and matrix metallopeptidase 3 (MMP3; degree, 6) had higher connectivity degrees in the PPI network for the DEGs. These genes may be involved in ovarian cancer by interacting with other genes in the module of the PPI network (e.g., BCL2-FOS, BCL2-CDKN1A, FOS-CDKN1A, FOS-CD44, MMP3-MMP7 and MMP7-CD44). Overall, BCL2, FOS, CDKN1A, CD44, MMP3 and MMP7 may be correlated with ovarian cancer.
Solitary fibrous tumors (SFTs) are rare spindle-cell tumors. Their cell-of-origin and molecular basis are poorly known. They raise several clinical problems. Differential diagnosis may be difficult, prognosis is poorly apprehended by histoclinical features, and no effective therapy exists for advanced stages.
The characteristics of tumor cells of primary vitreoretinal lymphoma (PVRL) have not been defined, although researches have shown that most cases are of diffuse large B-cell lymphoma (DLBCL). To determine the subtype and biological characteristics of tumor cells of PVRL, we performed a gene expression profiling analysis. RNA was extracted from the vitreous fluid of 7 PVRL patients and from nodal samples of 10 DLBCL patients: 6 of germinal center B-cell (GCB) type and 4 of activated B-cell (ABC) type determined by Hans' criteria. Six PVRL samples showed gene expression profiles that were similar to each other. The patterns were different from those of the ABC-type nodular DLBCL but relatively close to those of the GCB-type nodular DLBCL. Interestingly, all of the 6 examined PVRL samples had either MYD88L265P or mutation in the immunoreceptor tyrosine-based activation motif (ITAM) region of CD79B. Five PVRL patients with similar gene expression profiles were treated with a standardized regimen: intravitreal administration of methotrexate (MTX) followed by six courses of systemic high doses of MTX. As a result, 2 patients had CD79B mutations and showed early central nervous system (CNS) progression. Patients without CNS progression did not have this mutation. In conclusion, PVRL had unique genetic features: an expression pattern different from ABC-type and relatively close to GCB-type DLBCL. CD79B mutations showed potential to serve as prognostic markers for CNS progression.
The present study screened potential genes related to lung adenocarcinoma, with the aim of further understanding disease pathogenesis. The GSE2514 dataset including 20 lung adenocarcinoma and 19 adjacent normal tissue samples from 10 patients with lung adenocarcinoma aged 45-73 years was downloaded from Gene Expression Omnibus. Differentially expressed genes (DEGs) between the two groups were screened using the t-test. Potential gene functions were predicted using functional and pathway enrichment analysis, and protein-protein interaction (PPI) networks obtained from the STRING database were constructed with Cytoscape. Module analysis of PPI networks was performed through MCODE in Cytoscape. In total, 535 upregulated and 465 downregulated DEGs were identified. These included ATP5D, UQCRC2, UQCR11 and genes encoding nicotinamide adenine dinucleotide (NADH), which are mainly associated with mitochondrial ATP synthesis coupled electron transport, and which were enriched in the oxidative phosphorylation pathway. Other DEGs were associated with DNA replication (PRIM1, MCM3, and RNASEH2A), cell surface receptor-linked signal transduction and the enzyme-linked receptor protein signaling pathway (MAPK1, STAT3, RAF1, and JAK1), and regulation of the cytoskeleton and phosphatidylinositol signaling system (PIP5K1B, PIP5K1C, and PIP4K2B). Our findings suggest that DEGs encoding subunits of NADH, PRIM1, MCM3, MAPK1, STAT3, RAF1, and JAK1 might be associated with the development of lung adenocarcinoma.
Although the sequence of events leading to wound repair has been described at the cellular and, to a limited extent, at the protein level this process has yet to be fully elucidated. Genome wide transcriptional analysis tools promise to further define the global picture of this complex progression of events.
The aim of this study was to describe the expression of genes, including ameloblastin (Ambn), amelogenin X chromosome (Amelx), and enamelin (Enam) during early (pre-secretory) tooth development. The expression of these genes has predominantly been studied at post-secretory stages. Deoxyoligonucleotide microarrays were used to study gene expression during development of the murine first molar tooth germ at 24 h intervals, starting at the 11th embryonic day (E11.5), and up to the 7th day after birth (P7). The profile search function of Spotfire software was used to select genes with similar expression profile as the enamel genes (Ambn, Amelx, and Enam). Microarray results where validated using real-time reverse transcription-polymerase chain reaction (real-time RT-PCR), and translated proteins identified by Western-blotting. In situ localization of the Ambn, Amelx, and Enam mRNAs were monitored from E12.5 to E17.5 using deoxyoligonucleotide probes. Bioinformatics analysis was used to associate biological functions with differentially expressed (DE; p ≤ 0.05) genes. Microarray results showed a total of 4362 genes including Ambn, Amelx, and Enam to be significant DE throughout the time-course. The expression of the three enamel genes was low at pre-natal stages (E11.5-P0) increasing after birth (P1-P7). Profile search lead to isolation of 87 genes with significantly similar expression to the three enamel proteins. These mRNAs were expressed in dental epithelium and epithelium derived cells. Although expression of Ambn, Amelx, and Enam were lower during early tooth development compared to secretory stages enamel proteins were detectable by Western-blotting. Bioinformatic analysis associated the 87 genes with multiple biological functions. Around 35 genes were associated with 15 transcription factors.
Sjögren's syndrome (SS) is a common chronic autoimmune disease characterized by lymphocytic infiltration of exocrine glands. The affected cases commonly present with oral and ocular dryness, which is thought to be the result of inflammatory cell-mediated gland dysfunction. To identify important molecular pathways involved in SS, we used high-density microarrays to define global gene expression profiles in the peripheral blood. We first analyzed 21 SS cases and 23 controls, and identified a prominent pattern of overexpressed genes that are inducible by interferons (IFNs). These results were confirmed by evaluation of a second independent data set of 17 SS cases and 22 controls. Additional inflammatory and immune-related pathways with altered expression patterns in SS cases included B- and T-cell receptor, insulin-like growth factor-1, granulocyte macrophage-colony stimulating factor, peroxisome proliferator-activated receptor-alpha/retinoid X receptor-alpha and PI3/AKT signaling. Exploration of these data for relationships to clinical features of disease showed that expression levels for most interferon-inducible genes were positively correlated with titers of anti-Ro/SSA (P<0.001) and anti-La/SSB (P<0.001) autoantibodies. Diagnostic and therapeutic approaches targeting interferon-signaling pathway may prove most effective in the subset of SS cases that produce anti-Ro/SSA and anti-La/SSB autoantibodies. Our results strongly support innate and adaptive immune processes in the pathogenesis of SS, and provide numerous candidate disease markers for further study.
The Drosophila trachea is a premier genetic system to investigate the fundamental mechanisms of tubular organ formation. Tracheal fusion cells lead the branch fusion process to form an interconnected tubular network. Therefore, fusion cells in the Drosophila trachea will be an excellent model to study branch fusion in mammalian tubular organs, such as kidneys and blood vessels. The fusion process is a dynamic cellular process involving cell migration, adhesion, vesicle trafficking, cytoskeleton rearrangement, and membrane fusion. To understand how these cellular events are coordinated, we initiated the critical step to assemble a gene expression profile of fusion cells. For this study, we analyzed the expression of 234 potential tracheal-expressed genes in fusion cells during fusion cell development. 143 Tracheal genes were found to encode transcription factors, signal proteins, cytoskeleton and matrix proteins, transporters, and proteins with unknown function. These genes were divided into four subgroups based on their levels of expression in fusion cells compared to neighboring non-fusion cells revealed by in situ hybridization: (1) genes that have relative high abundance in fusion cells, (2) genes that are dynamically expressed in fusion cells, (3) genes that have relative low abundance in fusion cells, and (4) genes that are expressed at similar levels in fusion cells and non-fusion tracheal cells. This study identifies the expression profile of fusion cells and hypothetically suggests genes which are necessary for the fusion process and which play roles in distinct stages of fusion, as indicated by the location and timing of expression. These data will provide the basis for a comprehensive understanding of the molecular and cellular mechanisms of branch fusion.
Recent developments in molecular genetics, including progress in the human genome project, have allowed identification of genes at an unprecedented rate. To date gene expression profiling studies have focused on identifying transcripts that are specifically or preferentially enriched within the inner ear on the assumption that they are more likely to be important for auditory and vestibular function. It is now apparent that some genes preferentially expressed in the cochleo-vestibular system are not crucial for hearing or balance or their functions are compensated for by other genes. In addition, transcripts expressed at low abundance in the inner ear are generally under-represented in gene profiling studies. In this review, we highlight the limitations of current gene expression profiling strategies as a discovery tool for genes involved in cochleo-vestibular development and function. We argue that expression profiling based on hierarchical clustering of transcripts by gene ontology, combined with tissue enrichment data, is more effective for inner ear gene discovery. This approach also provides a framework to assist and direct the functional characterization of gene products.
Dermatitis herpetiformis (DH) is an autoimmune blistering skin disease associated with gluten-sensitive enteropathy (CD). In order to investigate the pathogenesis of skin lesions at molecular level, we analysed the gene expression profiles in skin biopsies from 6 CD patients with DH and 6 healthy controls using Affymetrix HG-U133A 2.0 arrays. 486 genes were differentially expressed in DH skin compared to normal skin: 225 were upregulated and 261 were downregulated. Consistently with the autoimmune origin of DH, functional classification of the differentially expressed genes (DEGs) indicates a B- and T-cell immune response (LAG3, TRAF5, DPP4, and NT5E). In addition, gene modulation provides evidence for a local inflammatory response (IL8, PTGFR, FSTL1, IFI16, BDKRD2, and NAMPT) with concomitant leukocyte recruitment (CCL5, ENPP2), endothelial cell activation, and neutrophil extravasation (SELL, SELE). DEGs also indicate overproduction of matrix proteases (MMP9, ADAM9, and ADAM19) and proteolytic enzymes (CTSG, ELA2, CPA3, TPSB2, and CMA1) that may contribute to epidermal splitting and blister formation. Finally, we observed modulation of genes involved in cell growth inhibition (CGREF1, PA2G4, and PPP2R1B), increased apoptosis (FAS, TNFSF10, and BASP1), and reduced adhesion at the dermal epidermal junction (PLEC1, ITGB4, and LAMA5). In conclusion, our results identify genes that are involved in the pathogenesis of DH skin lesions.
Mycobacterium tuberculosis (M.tb) infects 8 million and kills 2.2 million people each year worldwide. M.tb modulates the immune response of the infected individual. Empirically, suppressor carbohydrates (SC) produced by CD8+ T cells in response to M.tb were found to induce a T helper 2 response rather than a protective T helper 1 response in human mononuclear (MN) cells. This study (1) identifies the genes that modulate the T helper response, (2) describes their function, and (3) postulates a detailed model for the M.tb infection mechanism. MN cells from five healthy donors were pulsed with SC and gene expression profiles of 18,861 genes were assessed in a micro-array experiment. Twenty-eight genes were found to be increased and 60 genes were decreased (FDR=1%, fold change>1.4) in response to SC. MIP3 alpha and platelet factor 4 (v1) are both significantly enriched (p< or =0.001) in the GO category "chemokine activity". Repressed genes were significantly (p< or =0.001) over-represented in the GO terms "response to pathogenic bacteria", "inflammatory response", "coagulation" and "apoptosis". Indeed, SC significantly reduced numbers of Annexin V/CD4+ cells, while inducing hypoproliferation in CD4+ and non-adherent lymphocytes. This may indicate that M.tb renders a portion of the CD4+ T cell population unresponsive. Furthermore, validating QRT-PCR analysis suggests that monocytes provide an immuno-modulatory signal to CD4+ T cells in M.tb infection. These observations will allow development of new therapeutic interventions to restore the desired T helper 1 response.
Osteosarcoma (OS) is the most common type of primary bone malignancy and has a poor prognosis. To investigate the mechanisms of osteosarcoma, the present analyzed the GSE28424 microarray. GSE28424 was downloaded from the Gene Expression Omnibus, and included a collective of 19 OS cell lines and four normal bone cell lines, which were used as controls. Subsequently, the differentially expressed genes (DEGs) were screened using the Limma package in Bioconductor. Gene Ontology (GO) and pathway enrichment analysis of the DEGs was performed using the Database for Annotation, Visualization and Integrated Discovery, interactions between the proteins encoded by the DEGs were identified using STRING, and the protein‑protein interaction (PPI) network was visualized using Cytoscape. In addition, modular analysis of the PPI network was performed using the Clique Percolation Method (CPM) in CFinder. A total of 1,170 DEGs were screened, including 530 upreguated and 640 downregulated genes. The enriched functions included organelle fission, immune response and response to wounding. In addition, RPL8 was observed to be involved with the ribosomal pathway in module A of the PPI network of the DEGs. PLCG1, SYK and PLCG2 were also involved in the B‑cell receptor signaling pathway in module B and the Fc‑epsilon RI signaling pathway in module C. In addition, AURKA (degree=39), MAD2L1 (degree=38), CDCA8 (degree=38), BUB1 (degree=37) and MELK (degree=37) exhibited higher degrees of connectivity in module F. The results of the present study suggested that the RPL8, PLCG1, PLCG2, SYK, MAD2L1, AURKA, CDCA8, BUB1 and MELK genes may be involved in OS.
Gene expression profiling is a highly sensitive technique which is used for profiling tumor samples for medical prognosis. RNA quality and degradation influence the analysis results of gene expression profiles. The impact of this influence on the profiles and its medical impact is not fully understood. As patient samples are very valuable for clinical studies, it is necessary to establish criteria for the RNA quality to be able to use these samples in later analysis.
The Structural Maintenance of Chromosome 3 protein (SMC3) plays an essential role during the sister chromatid separation, is involved in DNA repair and recombination and participates in microtubule-mediated intracellular transport. SMC3 is frequently elevated in human colon carcinoma and overexpression of the protein transforms murine NIH3T3 fibroblasts. In order to gain insight into the mechanism of SMC3-mediated tumorigenesis a gene expression profiling was performed on human 293 cells line stably overexpressing SMC3.
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