DNA microarray analyses of melanoma gene expression: a decade in the mines

2007 ◽  
Vol 20 (6) ◽  
pp. 466-484 ◽  
Author(s):  
Keith S. Hoek
Keyword(s):  
Gene Expression ◽  
Dna Microarray ◽  
Microarray Analyses

Novel Stratification Scheme for AML Based on a Large-Scale DNA Microarray Analysis of CD133-Positive Blasts.

Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 2043-2043
Author(s):  
Hiroyuki Mano ◽  
Yoshihiro Yamashita
Keyword(s):  
Gene Expression ◽  
Gene Expression Profile ◽  
Microarray Analysis ◽  
Dna Microarray ◽  
Expression Profile ◽  
Treatment Strategy ◽  
Large Scale ◽  
Dna Microarray Analysis ◽  
Wide Range ◽  
Microarray Analyses

Abstract AML is a clonal disorder of immature hematopoietic blasts and has a variable clinical outcome. Current classification of AML is based predominantly on the cytogenetic abnormalities and morphology of the malignant blasts and is not always helpful for optimization of treatment strategy. It is, for instance, very difficult to predict the prognosis of AML patients with a normal karyotype, who constitute ~50% of the AML population. DNA microarray analysis has the potential to provide a novel stratification scheme for AML patients, which is based on gene expression profile, and might help to predict the prognosis of, and optimize the treatment strategy for, each affected individual. However, leukemic blasts derived from bone marrow (BM) of AML-related disorders, are not homogeneous. The blasts may constitute from 20% to almost 100% of mononuclear cells (MNCs) in the marrow. Furthermore, given that many leukemic blasts possess the ability to differentiate to a certain extent, the marrow of AML patients contains not only the immature blasts (leukemic stem clone) but also differentiated blasts. A simple comparison of BM MNCs among heterogeneous AML patients is thus likely to reveal a large number of changes in gene expression that only reflect differences either in the percentage of blasts or in the differentiation ability of the blasts. To minimize such population-shift effects in microarray analyses, we established a large-scale cell depository “Blast Bank” for the storage of CD133 (AC133)-positive hematopoietic stem cell-like fractions from individuals with a wide range of hematopoietic disorders. In the present study, we have used Affymetrix HGU133 A&B microarrays to measure the expression profiles of ~33,000 genes in the Blast Bank specimens of 99 adults with AML-related disorders: 83 individuals with AML and 16 patients in the RAEB stage of MDS. In contrast to the previous microarray analyses of BM MNCs of AML, unsupervised hierarchical clustering of the subjects based on the expression profile did not separate the patients into FAB subtype-matched subgroups. Comparison of gene expression profile between the long-time and short-time survivors has identified a small number of outcome-related genes. Supervised class prediction, based on these genes, with k-nearest neighbor method or Cox proportional hazard model both succeeded to clearly separate individuals into subgroups with statistically distinct prognoses. Our analysis may pave a way toward the expression profile-based novel stratification scheme for AML.

Characterization of Oncogene Dysregulation in Multiple Myeloma by Combined FISH and DNA Microarray Analyses.

Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 4844-4844
Author(s):  
Antonino Neri ◽  
Sonia Fabris ◽  
Luca Agnelli ◽  
Michela Mattioli ◽  
Luca Baldini ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Dna Microarray ◽  
Plasma Cell ◽  
Target Genes ◽  
Expression Profiles ◽  
Molecular Cytogenetic ◽  
Igh Locus ◽  
Microarray Analyses

Abstract Chromosomal translocations involving the immunoglobulin heavy chain (IGH@) locus and variuos partner loci are frequently associated with multiple myeloma (MM). We investigated the expression profiles of FGFR3/MMSET, CCND1, CCND3, MAF and MAFB genes, respectively involved in t(4;14)(p16.3;q32), t(11;14)(q13;q32), t(6;14)(p21;q32), t(14;16)(q32;q23) and t(14;20)(q32;q12), in purified plasma cell populations from 39 MMs and six plasma cell leukemias (PCL) using DNA microarray analysis, and compared the results with the presence of translocations as assessed by dual-color FISH or RT-PCR. The t(4;14) was found in six MMs, t(11;14) in 9 MMs and 1 PCL, t(6;14) in one MM, t(14;16) in 2 MMs and 1 PCL, and t(14;20) in one PCL. The translocations were associated with the spiked expression of target genes in all cases. Furthermore, gene expression profiling allowed the identification of putative translocations dysregulating CCND1 (1 MM and 1 PCL) and MAFB (1 MM and 1 PCL) without any apparent involvement of immunoglobulin loci. Notably, all of the translocations were mutually exclusive. Markedly increased levels of MMSET expression were found in one MM showing associated FGFR3 and MMSET signals on an unidentified chromosome. Our data suggest the importance of using combined molecular cytogenetic and gene expression approaches to detect genetic aberrations in MM.

scholarly journals The Potential of 2-aza-8-Oxohypoxanthine as a Cosmetic Ingredient

Cosmetics ◽  
2021 ◽  
Vol 8 (3) ◽  
pp. 60
Author(s):  
Hisae Aoshima ◽  
Masayuki Ito ◽  
Rinta Ibuki ◽  
Hirokazu Kawagishi
Keyword(s):  
Gene Expression ◽  
Cell Proliferation ◽  
Microarray Analysis ◽  
Dna Microarray ◽  
Cell Activation ◽  
Skin Barrier ◽  
Efficacy Evaluation ◽  
Activation Effect ◽  
Expression Levels ◽  
Dna Microarray Analysis

In this study, we verified the effects of 2-aza-8-oxohypoxanthine (AOH) on human epidermal cell proliferation by performing DNA microarray analysis. Cell proliferation was assessed using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay, which measures mitochondrial respiration in normal human epidermal keratinocyte (NHEK) cells. Gene expression levels were determined by DNA microarray analysis of 177 genes involved in skin aging and disease. AOH showed a significant increase in cell viability at concentrations between 7.8 and 31.3 μg/mL and a significant decrease at concentrations above 250 μg/mL. DNA microarray analysis showed that AOH significantly increased the gene expression of CLDN1, DSC1, DSG1, and CDH1 (E-cadherin), which are involved in intercellular adhesion and skin barrier functioning. AOH also up-regulated the expression of KLK5, KLK7, and SPIMK5, which are proteases involved in stratum corneum detachment. Furthermore, AOH significantly stimulated the expression of KRT1, KRT10, TGM1, and IVL, which are considered general differentiation indicators, and that of SPRR1B, a cornified envelope component protein. AOH exerted a cell activation effect on human epidermal cells. Since AOH did not cause cytotoxicity, it was considered that the compound had no adverse effects on the skin. In addition, it was found that AOH stimulated the expression levels of genes involved in skin barrier functioning by DNA microarray analysis. Therefore, AOH has the potential for practical use as a cosmetic ingredient. This is the first report of efficacy evaluation tests performed for AOH.

scholarly journals Time Dependent Gene Expression Changes in the Liver of Mice Treated with Benzene

2008 ◽  
Vol 3 ◽  
pp. BMI.S590 ◽  
Author(s):  
Han-Jin Park ◽  
Jung Hwa Oh ◽  
Seokjoo Yoon ◽  
S.V.S. Rana
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
General Purpose ◽  
Time Dependent ◽  
Expression Data ◽  
Benzene Exposure ◽  
Microarray Analyses ◽  
First Time ◽  
Affymetrix Gene Chip

Benzene is used as a general purpose solvent. Benzene metabolism starts from phenol and ends with p-benzoquinone and o-benzoquinone. Liver injury inducted by benzene still remains a toxicologic problem. Tumor related genes and immune responsive genes have been studied in patients suffering from benzene exposure. However, gene expression profiles and pathways related to its hepatotoxicity are not known. This study reports the results obtained in the liver of BALB/C mice (SLC, Inc., Japan) administered 0.05 ml/100 g body weight of 2% benzene for six days. Serum, ALT, AST and ALP were determined using automated analyzer (Fuji., Japan). Histopathological observations were made to support gene expression data. c-DNA microarray analyses were performed using Affymetrix Gene-chip system. After six days of benzene exposure, twenty five genes were down regulated whereas nineteen genes were up-regulated. These gene expression changes were found to be related to pathways of biotransformation, detoxification, apoptosis, oxidative stress and cell cycle. It has been shown for the first time that genes corresponding to circadian rhythms are affected by benzene. Results suggest that gene expression profile might serve as potential biomarkers of hepatotoxicity during benzene exposure.

scholarly journals DNA microarray analysis of global gene regulation by A-factor in Streptomyces griseus

Microbiology ◽  
2009 ◽  
Vol 155 (7) ◽  
pp. 2197-2210 ◽  
Author(s):  
Hirofumi Hara ◽  
Yasuo Ohnishi ◽  
Sueharu Horinouchi
Keyword(s):  
Gene Expression ◽  
Microarray Analysis ◽  
Dna Microarray ◽  
Streptomyces Griseus ◽  
Exponential Growth Phase ◽  
Mobility Shift ◽  
Dna Microarray Analysis ◽  
Regulatory Cascade ◽  
Transcriptional Units ◽  
Inducible Genes

A-factor (2-isocapryloyl-3R-hydroxymethyl-γ-butyrolactone) is a microbial hormone that triggers morphological differentiation and secondary metabolism in Streptomyces griseus. The effects of A-factor on global gene expression were determined by DNA microarray analysis of transcriptomes obtained with the A-factor-deficient mutant ΔafsA. A-factor was added at a concentration of 25 ng ml−1 to mutant ΔafsA at the middle of the exponential growth phase, and RNA samples were prepared from the cells grown after A-factor addition for a further 5, 15 and 30 min, and 1, 2, 4, 8 and 12 h. The effects of A-factor on transcription of all protein-coding genes of S. griseus were evaluated by comparison of the transcriptomes with those obtained from cells grown in the absence of A-factor. Analysis of variance among the transcriptomes revealed that 477 genes, which were dispersed throughout the chromosome, were differentially expressed during the 12 h after addition of A-factor, when evaluated by specific criteria. Quality threshold clustering analysis with regard to putative polycistronic transcriptional units and levels of upregulation predicted that 152 genes belonging to 74 transcriptional units were probable A-factor-inducible genes. Competitive electrophoretic mobility shift assays using DNA fragments including putative promoter regions of these 74 transcriptional units suggested that AdpA bound 37 regions to activate 72 genes in total. Many of these A-factor-inducible genes encoded proteins of unknown function, suggesting that the A-factor regulatory cascade of S. griseus affects gene expression at a specific time point more profoundly than expected.

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