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PubMed2006

Expression profiles of 10,422 genes at early stage of low nitrogen stress in rice assayed using a cDNA microarray.

Development of crop varieties with high nitrogen use efficiency (NUE) is imperative for sustainable agriculture. Understanding how plant genes respond to low N stress is essential for formulating approaches to manipulating genes for improving NUE. In this study we analyzed the expression profiles of an indica rice cultivar Minghui 63 at seedling stage at 20 min, 1 and 2 h after low N stress with the normal N as the control, using a microarray of 11,494 rice ESTs representing 10,422 unique genes. While no significant difference was detected in the leaf tissue, a total of 471 ESTs were detected as responsive to low N stress in the root tissue with 115 ESTs showing up-regulation and 358 ESTs showing down-regulation. The analysis of expression profiles after low N stress identified following patterns: (1) the genes involved in photosynthesis and energy metabolism were down-regulated rapidly; (2) many of the genes involved in early responses to biotic and abiotic stresses were up-regulated while many other stress responsive genes were down-regulated; (3) regulatory genes including transcription factors and ones involved in signal transduction were both up- and down-regulated; and (4) the genes known to be involved in N uptake and assimilation showed little response to the low N stress. The challenges for future studies are to characterize the functional roles of the low N stress responsive genes in N metabolisms, including the large number of genes presently with unknown functions.

Gene Expression Profiling↗

PubMed2004

Gene expression profiling of renal cell carcinoma.

Renal cell carcinoma (RCC) is a histologically diverse disease, with variable and often unpredictable clinical behavior. The prognosis worsens dramatically with the onset of clinical metastasis, and current regimens of systemic therapy yield only modest benefits for metastatic RCC. Gene expression profiling is a promising technique for refining the diagnosis and staging of RCC, as well as for highlighting potential therapeutic targets. We review the recent advances in expression profiling of RCC and discuss the clinical and biological insights obtained from these studies.

Carcinoma, Renal Cell↗

PubMed2003

A prognostic test for adenocarcinoma of the lung from gene expression profiling data.

Until recently, it has been impossible to determine which patients with resected stage I lung cancer are among the 30% who will die of metastatic cancer within 5 years of surgery. Bioinformatics tools applied to lung cancer expression profiling data have identified prognostic genes that have been used to develop predictor models, but thus far, these models have not been incorporated into routine clinical use because of their inherent complexity and requirement for relatively large numbers of genes. We have used ratios of gene expression to overcome these limitations. Here, we evaluate the ability of this technique to identify patients with stage I lung adenocarcinoma at risk for recurrence. We derived candidate ratio-based tests from analysis of 36 stage I lung adenocarcinoma samples using previously published expression profiling data. Eleven of these tests were identified for additional study and assessed for classification accuracy in an independent set of 60 stage I lung adenocarcinoma samples. We then evaluated the optimal ratio-based test in the independent samples using Kaplan-Meier survival analysis. Finally, we examined the ability of this test to predict outcome in a set of 97 stage I breast adenocarcinoma. We found that subsets of the independent lung cancer samples predicted to be associated with either good or poor outcome using the optimal ratio-based test differed significantly (P=0.0056) in terms of survival with a classification accuracy of 74% (P=0.0043, Fisher's exact test). When this test was applied to stage II and III lung cancers, most specimens were classified as poor outcome cancers. Interestingly, we found that the same test significantly (P=0.0417) predicted recurrence of stage I breast tumors, suggesting that at least some of the marker genes we identified may have generalized prognostic significance for adenocarcinoma. Our results provide additional evidence that expression ratios are highly accurate in predicting cancer recurrence and may be used in a simple test to predict response to surgical therapy in early-stage lung adenocarcinoma.

Adenocarcinoma↗

PubMed2000

Identification of tumor-suppressor genes using human melanoma cell lines UACC903, UACC903(+6), and SRS3 by comparison of expression profiles.

The development and progression of cancer are believed to be due to multiple genetic alterations resulting in complex changes in expression of many genes. The parental malignant melanoma cell line UACC903 displays anchorage-independent growth, and the chromosome 6-suppressed subline UACC903(+6) displays anchorage-dependent growth. The anchorage-independent revertant cell line SRS3 derived from UACC903(+6) by retroviral transduction resembles the phenotype of UACC903. In this study, we first compared the expression profiles of 3317 genes between these three cell lines in pairs by cDNA microarrays, resulting in identification of genes with known suppressor activities. We then demonstrated connexin 43 (Cx43)-suppressing anchorage-independent growth of UACC903 on overexpression. Of 3317 genes with informative expression detected by cDNA microarray, 321 (9.68%) showed expression changes between at least one pair of the three cell lines. Notably, 12 genes displayed higher levels of expression in UACC903(+6) than in both UACC903 and SRS3, providing candidates for further identification of melanoma-suppressor genes. Genes encoding Cx43 (suppressor activity), monocyte chemotactic protein 1 (suppressor activity), and cysteine proteinase P32alpha (apoptotic activity) were all upregulated in UACC903(+6), in contrast to both UACC903 and SRS3. Transfection of Cx43, encoded on human chromosome 6q21-q23, a region frequently altered in malignant melanoma, resulted in its overexpression and the suppression of anchorage-independent growth of UACC903. Thus, our result proves the principle that the combination of the ability to alter cellular phenotype by successive genetic alterations and the ability to examine the global expression profiles facilitates the identification of tumor suppressor genes. Mol. Carcinog. 28:119-127, 2000.

Base Sequence↗

PubMed2004

Gene expression profiles of livers from thermally injured rats.

The liver plays an important role in a severe thermal injury by modulating immune function, inflammatory processes and the acute phase response, which are an orchestrated attempt to restore homeostasis. Using high-density oligonucleotide arrays, we examined the gene expression profile in the livers of rats between 2 and 240 h after a 40% total body surface area (TBSA) burn. Alterations in gene expression unique to a thermal injury were identified. Approximately 39 genes out of 8700 genes on each array across all the time points showed a significant change in expression patterns. Real time reverse transcription-polymerase chain reaction (RT-PCR) and Western blot analyses verified significant changes in early growth response-1 (Egr-1) messenger RNA (mRNA) and protein levels corresponding to the array data. Significant increases in serum levels of alpha-2-macroglobulin that correspond to changes in its mRNA levels were observed at 6 and 24 h after burn, p<0.05. The genomic pattern for liver in the hypermetabolic phase after the burn injury involves transcription factors, stress and inflammatory responses, cytoskeletal and extracellular matrix modifications, and regulation of cell proliferation and differentiation. During the initial phase of thermal injury gene expression profiles in the liver may provide some insight into how cellular protection mechanisms and systemic hypermetabolism are initiated and controlled. The genome wide changes observed may provide a rational therapeutic strategy to improve burn care.

Animals↗

PubMed2004

Gene expression profiling in non-small cell lung cancer: from molecular mechanisms to clinical application.

Non-small cell lung cancer (NSCLC) is the most common cause of premature death from malignant disease in western countries. A better understanding of the molecular mechanisms underlying NSCLC etiology, pathogenesis, and therapeutics will lead to improved clinical outcomes. Recent technological advances in gene expression profiling (in particular, with cDNA and oligonucleotide microarrays) allow the simultaneous analysis of the expression of thousands of genes. In this review, the technology of global gene expression profiling is discussed, and the progress made thus far with it in NSCLC is reviewed. A new molecular classification of NSCLC has been developed, which has provided important insights into etiology and pathogenesis. Other studies have found potential biomarkers for NSCLC that may be of use in diagnosis, screening, and assessing the effectiveness of therapy. Finally, advances have been made in the understanding of the molecular mechanisms of NSCLC progression and the molecular mechanisms of action of currently used cytotoxic drugs. This may facilitate the improvement of current therapeutics and the identification of novel targets. Taken together, these advances hold the promise of an improved understanding of the molecular biology of NSCLC and its treatment, which in turn will lead to improved outcomes for this deadly disease.

Biomarkers, Tumor↗

PubMed2005

Distinction in gene expression profiles demonstrated in parathyroid adenomas by high-density oligoarray technology.

OBJECTIVES: Somatic deletion of chromosome 11q13 is the most frequent genetic aberration in parathyroid adenoma. To gain further insight into the genetic etiology of parathyroid tumor development, we examined a comprehensive gene expression profile of parathyroid adenomas and normal parathyroid tissues. The results were then evaluated with respect to differences between adenomas and normal parathyroid tissue, and to the presence of loss of heterozygosity (LOH) in chromosomal region 11q13. DESIGN AND METHODS: Sporadic parathyroid adenomas and normal parathyroids were hybridized against HG-U95Av2 oligonucleotide arrays (Affymetrix) containing a total of 12,625 probe sets. Quantitative real-time PCR (QRT-PCR) was performed in a larger series of parathyroid adenomas, in order to con-firm the microarray results. RESULTS: Cyclin D1 and c-Jun showed increased expression in adenomas vs normal parathyroids by microarray analysis and QRT-PCR, suggesting an oncogenic role of these genes in parathyroid tumor development. At unsupervised hierarchical clustering, the adenomas fell into two groups: Group I adenomas were characterized by 11q13 LOH, while Group II adenomas lacked this abnormality. In addition, a t-test analysis identified largely non-overlapping genes with differential expression in the tumors subgroups; e.g. in Group I tumors the putative oncogene ENC 1 was found highly over-expressed vs Group II adenomas. CONCLUSIONS: The microarray analyses revealed partly distinctive and partly common expression profiles in parathyroid adenomas with and without 11q13 LOH. In addition, approximately half of the under-expressed genes were mapped to chromosome 11, in agreement with a dose effect following loss of this chromosome.

Adenoma↗

PubMed2003

Functional differentiation of peroxisomes revealed by expression profiles of peroxisomal genes in Arabidopsis thaliana.

It is well known that peroxisomal matrix proteins contain one of two targeting signals, PTS1 and PTS2. We comprehensively surveyed genes related to peroxisomal function and biogenesis in the entire Arabidopsis genome sequence. Here, we identified 256 gene candidates of PTS1- and PTS2-containing proteins and another 30 genes of non-PTS-containing proteins. Of these, only 29 proteins have been reported to be functionally characterized as peroxisomal proteins in higher plants. We extensively investigated expression profiles of genes described above in various organs of Arabidopsis: Statistical analyses of these expression profiles revealed that peroxisomal genes could be divided into five groups. One group showed ubiquitous expression in all organs examined, while the other four were classified as showing organ-specific expression in seedlings, cotyledons, roots and in both cotyledons and leaves. These data proposed more detailed description of differentiation of plant peroxisomes.

Arabidopsis↗

PubMed2003

The distinct gene expression profiles of chronic lymphocytic leukemia and multiple myeloma suggest different anti-apoptotic mechanisms but predict only some differences in phenotype.

We compared gene expression in purified tumor cells from untreated patients with chronic lymphocytic (CLL) (n=24) and newly diagnosed multiple myeloma (MM) (n=29) using the Affymetrix HuGeneFL microarray with probes for approximately 6800 genes. Hierarchical clustering analysis showed that CLL and MM have distinct expression profiles (class prediction). Gene and protein expression (measured by flow cytometry) correlated well for CD19, CD20, CD23, and CD138 in CLL and MM, but not for immunoglobulin light chain, CD38 and CD79b in CLL, or CD45 and CD52 in MM. CLL and MM differentially expressed 18% of 130 apoptosis related genes, suggesting differences in mechanisms of cell survival.

Antigens, CD↗

PubMed2005

Mediator expression profiling epistasis reveals a signal transduction pathway with antagonistic submodules and highly specific downstream targets.

Mediator is an evolutionarily conserved coregulator of RNA polymerase II transcription. Microarray structure-function analysis of S. cerevisiae Mediator reveals functional antagonism between the cyclin-dependent kinase (Cdk) submodule and components from the Tail (Med15, Med2, Med3), Head (Med20, Med18), and Middle (Med31). Certain genes exhibit increased or decreased expression, depending on which subunit is deleted. Epistasis analysis with expression-profile phenotypes shows that MED2 and MED18 are downstream of CDK8. Strikingly, Cdk8-mediated modification of a single amino acid within Mediator represses the regulon of a single transcription factor, Rcs1/Aft1. Highly specific gene regulation is thought to be determined by activators and combinatorial use of cofactors. Here, subtle modification of the general transcription machinery through one of its own components is shown to determine highly specific expression patterns. Expression profiling can therefore precisely map regulatory cascades, and our findings support a role for Mediator as a direct processor of signaling pathways for determining specificity.

Chromosomal Proteins, Non-Histone↗

PubMed2006

Identification of novel oligodendroglioma-associated candidate tumor suppressor genes in 1p36 and 19q13 using microarray-based expression profiling.

Loss of heterozygosity (LOH) on chromosomal arms 1p and 19q is the most common genetic alteration in oligodendroglial tumors and associated with response to radio- and chemotherapy as well as favorable prognosis. Using microsatellite analysis, we previously identified the chromosomal regions 1p36.22-p36.31 and 19q13.3, as candidate tumor suppressor gene regions being commonly deleted in these tumors. To identify genes within these regions that are downregulated in oligodendroglial tumors with LOH 1p/19q, we performed cDNA microarray-based RNA expression profiling of 35 gliomas with known allelic status on 1p and 19q, including 7 oligodendrogliomas and 8 diffuse astrocytomas of World Health Organization (WHO) grade II, as well as 14 anaplastic oligodendrogliomas and 6 anaplastic oligoastrocytomas of WHO grade III. The microarrays used for expression profiling carried approximately 7,000 gene-specific cDNAs, with complete coverage of the genes located in 1p36.13-p36.31 and 19q13.2-q13.33. Microarray analysis identified 8 genes from these regions (MGC4399, SRM, ICMT, RPL18, FTL, ZIN, FLJ10781 and DBP), which all showed significantly lower expression in 1p/19q-deleted gliomas when compared to gliomas without 1p/19q losses. Quantitative real-time reverse transcription-PCR analyses were performed for the MGC4399, ICMT and RPL18 genes and confirmed the microarray findings. In addition, we found that the cytosolic phospholipase A2 (PLA2G4C) gene at 19q13.3 demonstrated significantly lower expression in anaplastic oligodendrogliomas (WHO grade III) when compared to well-differentiated oligodendrogliomas (WHO grade II). Taken together, our study provides a set of interesting novel candidate genes that may play important roles in the pathogenesis of oligodendroglial tumors.

Adolescent↗

PubMed2004

cDNA microarray analysis of early gene expression profiles associated with hepatitis B virus X protein-mediated hepatocarcinogenesis.

Chronic hepatitis B virus (HBV) infection is one of the major causes of hepatocellular carcinoma. HBV encodes an oncogenic hepatitis B virus X protein (HBx), which can transactivate host cell transcriptional machinery and mediate cellular transformation. To disclose the early genetic response in HBx-mediated transformation process, we constructed a conditional HBx-expressing hepatocyte cell line, which allows us to compare the gene expression profiles under controllable HBx induction. A cDNA microarray containing more than 8700 mouse genes and ESTs was utilized to examine the gene expression profiles. We identified 260 candidate genes and 259 ESTs which have shown aberrant expression under HBx induction. Most of them are involved in signal transduction pathway, cell cycle control, metastasis, transcriptional regulation, immune response, and metabolism. These results provide additional insight into early cellular targets of HBx, which could give us a better understanding of the function of HBx and their progressive changes during HBx-mediated hepatocarcinogenesis.

Base Sequence↗

PubMed2002

Gene expression profiles of genistein-treated PC3 prostate cancer cells.

Our previous studies have shown that genistein inhibits the growth of PC3 prostate cancer cells and induces apoptosis by inhibiting nuclear factor kappaB (NF-kappaB) and Akt signaling pathways. To better understand the precise molecular mechanism(s) by which genistein exerts its effects on PC3 cells, we utilized cDNA microarray to interrogate 12,558 known genes to determine the gene expression profiles altered by genistein treatment. We found a total of 832 genes that showed a greater than twofold change after genistein treatment from two independent experiments with a high degree of concordance. Among these genes, 774 genes were down-regulated and 58 genes were up-regulated with genistein treatment. Cluster analysis showed nine different types of expression alternations. These genes were also subjected to cluster analysis according to their biological functions. We found that genistein regulated the expression of genes that are critically involved in the regulation of cell growth, cell cycle, apoptosis, cell signaling transduction, angiogenesis, tumor cell invasion and metastasis. Reverse transcription-polymerase chain reaction (RT-PCR) analysis was used to confirm the results of cDNA microarray, and the results of RT-PCR were consistent with the microarray data. We conclude that genistein affected the expression of a large number of genes that are related to the control of cell survival and physiologic behaviors. The gene expression profiles provide comprehensive molecular mechanism(s) by which genistein exerts its pleiotropic effects on cancer cells. Genistein-induced regulation of these genes may be further exploited for devising chemopreventive and/or therapeutic strategies for prostate cancer.

Base Sequence↗

PubMed1996

A pancreatic cancer-specific expression profile.

We present an approach making use of technology established in the context of the genome project to describe a pancreatic cancer-specific expression profile and to identify new potential disease genes or disease-associated-genes. By use of gridded arrays of pancreatic cancer cDNA libraries and differential hybridizations we show that 4% the gridded cDNA library clones contain sequences preferentially expressed in pancreatic cancer. EST-sequencing of 369 distinct (408 total), differentially expressed sequences identified novel genes (32.5%) or homologs to EST-sequences with unknown function (26.3%). Homologies to known genes allow to determine a pancreatic cancer-specific expression profile, which provides for the first time evidence for complex primary and secondary alterations of gene expression responsible for the development of the phenotype of pancreatic cancer cells. In addition this has led to the identification of novel differentially expressed genes, which represent potential oncogenes or disease-associated markers and may be helpful for the development of therapeutic or diagnostic modalities.

Animals↗

PubMed2004

Gene expression profiling reveals multiple toxicity endpoints induced by hepatotoxicants.

Microarray technology continues to gain increased acceptance in the drug development process, particularly at the stage of toxicology and safety assessment. In the current study, microarrays were used to investigate gene expression changes associated with hepatotoxicity, the most commonly reported clinical liability with pharmaceutical agents. Acetaminophen, methotrexate, methapyrilene, furan and phenytoin were used as benchmark compounds capable of inducing specific but different types of hepatotoxicity. The goal of the work was to define gene expression profiles capable of distinguishing the different subtypes of hepatotoxicity. Sprague-Dawley rats were orally dosed with acetaminophen (single dose, 4500 mg/kg for 6, 24 and 72 h), methotrexate (1mg/kg per day for 1, 7 and 14 days), methapyrilene (100mg/kg per day for 3 and 7 days), furan (40 mg/kg per day for 1, 3, 7 and 14 days) or phenytoin (300 mg/kg per day for 14 days). Hepatic gene expression was assessed using toxicology-specific gene arrays containing 684 target genes or expressed sequence tags (ESTs). Principal component analysis (PCA) of gene expression data was able to provide a clear distinction of each compound, suggesting that gene expression data can be used to discern different hepatotoxic agents and toxicity endpoints. Gene expression data were applied to the multiplicity-adjusted permutation test and significantly changed genes were categorized and correlated to hepatotoxic endpoints. Repression of enzymes involved in lipid oxidation (acyl-CoA dehydrogenase, medium chain, enoyl CoA hydratase, very long-chain acyl-CoA synthetase) were associated with microvesicular lipidosis. Likewise, subsets of genes associated with hepatotocellular necrosis, inflammation, hepatitis, bile duct hyperplasia and fibrosis have been identified. The current study illustrates that expression profiling can be used to: (1) distinguish different hepatotoxic endpoints; (2) predict the development of toxic endpoints; and (3) develop hypotheses regarding mechanisms of toxicity.

Animals↗

PubMed2004

Identifying interventional and pathogenic mechanisms by generative inverse modeling of gene expression profiles.

MOTIVATION: The characterization of genetic mechanisms underlying normal cellular function, cancer development, pathogenesis, and the effect of drug treatment is one of the most challenging topics for cancer research and molecular biology. Existing methods for inferring genetic regulatory networks from genome-wide expression profiles provide important information about gene interactions and regulatory relationships. However, these methods do not provide information about the impact of possible interventions or changes on such regulatory networks to study cause-effect relationships at a systems-biology level. RESULTS: We present a data-driven method called generative inverse modeling, which simulates the effect of local genetic changes on the global cellular state, as reflected by an altered genome-wide expression profile. For each genetic change we define a pathogenic score by calculating to what extent it transforms the simulated expression patterns into patterns measured for pathologically altered tissues. The method can be used to estimate the relevance of genes for disease-specific genetic mechanisms, e.g., as presented here for pathogenesis. Generative inverse modeling is based on a Bayesian probability density estimation from a set of measured gene-expression patterns.

Computational Biology↗

PubMed2004

Expression profiling of sodium butyrate (NaB)-treated cells: identification of regulation of genes related to cytokine signaling and cancer metastasis by NaB.

Histone deacetylase (HDAC) inhibitors induce growth arrest and apoptosis in a variety of human cancer cells. Sodium butyrate (NaB), a short chain fatty acid, is a HDAC inhibitor and is produced in the colonic lumen as a consequence of microbial degradation of dietary fibers. In order to dissect out the mechanism of NaB-induced growth inhibition of cancer cells, we carried out expression profiling of a human lung carcinoma cell line (H460) treated with NaB using a cDNA microarray. Of the total 1728 genes analysed, there were 32 genes with a mean expression value of 2.0-fold and higher and 66 genes with a mean expression value 3.0-fold and lower in NaB-treated cells. For a few selected genes, we demonstrate that their expression pattern by semiquantitative reverse transcription-polymerase chain reaction (RT-PCR) analysis is matching with the results obtained by microarray analysis. Closer view at the expression profile of NaB-treated cells revealed the downregulation of a total of 16 genes associated with cytokine signaling, in particular, interferon gamma (IFNgamma) pathway. In good correlation, NaB-pretreated cells failed to induce interferon regulatory factor 1, an INFgamma target gene, efficiently upon IFNgamma addition. These results suggest that NaB inhibits proinflammatory cytokine signaling pathway, thus providing proof of mechanism for its anti-inflammatory activity. We also found that NaB induced three genes, which are known metastatic suppressors, and downregulated 11 genes, which have been shown to promote metastasis. Upregulation of metastatic suppressor Kangai 1 (KAI1) by NaB in a time-dependent manner was confirmed by RT-PCR analysis. The differential regulation of metastasis-associated genes by NaB provides explanation for the anti-invasive properties of NaB. Therefore, our study presents new evidence for pathways regulated by NaB, thus providing evidence for the mechanism behind anti-inflammatory and antimetastatic activities of NaB.

Apoptosis↗

PubMed2004

Gene expression profiling of human lung tissue from smokers with severe emphysema.

The mechanism by which inhaled smoke causes the anatomic lesions and physiologic impairment of chronic obstructive pulmonary disease remains unknown. We used high-density microarrays to measure gene expression in severely emphysematous lung tissue removed from smokers at lung volume reduction surgery (LVRS) and normal or mildly emphysematous lung tissue from smokers undergoing resection of pulmonary nodules. Class prediction algorithms identified 102 genes that accurately distinguished severe emphysema from non-/mildly emphysematous lung tissue. We also defined a number of genes whose expression levels correlated strongly with lung diffusion capacity for carbon monoxide and/or forced expiratory volume at 1 s. Genes related to oxidative stress, extracellular matrix synthesis, and inflammation were increased in severe emphysema, whereas expression of endothelium-related genes was decreased. To identify candidate genes that might be causally involved in the pathogenesis of emphysema, we linked gene expression profiles to chromosomal regions previously associated with chronic obstructive pulmonary disease in genome-wide linkage analyses. Unsupervised hierarchical clustering of the LVRS samples revealed distinct molecular subclasses of severe emphysema, with body mass index as the only clinical variable that differed between the groups. Class prediction models established a set of genes that predicted functional outcome at 6 mo after LVRS. Our findings suggest that the gene expression profiles from human emphysematous lung tissue may provide insight into pathogenesis, uncover novel molecular subclasses of disease, predict response to LVRS, and identify targets for therapeutic intervention.

Aged↗