Gene expression profile analysis in human hepatocellular carcinoma by cDNA microarray

We performed gene expression profiling of normal and hepatocellular carcinoma (HCC) liver tissues using a high-density microarray that contained 3,063 human cDNA. The results of a microarray hybridization experiment from eight different HCC tissues were analyzed and classified by the Cluster program. Among these differentially-expressed genes, the galectin-3, serine/threonine kinase SGK, translation factor eIF-4A, -4B, -3, fibroblast growth factor receptor, and ribosomal protein L35A were up-regulated; the mRNAs of Nip3, decorin, and the insulin-like growth factor binding protein-3 were down-regulated in HCC. The differential expression of these genes was further confirmed by an RT-PCR analysis. In addition, our data suggest that the gene expression profile of HCC varies according to the histological types.     

DNA microarrays and papillary thyroid carcinoma gene expression profile

The paper presents gene expression profile analysis with DNA microarrays and compares two core technological platforms used for this purpose - high density oligonucleotide microarrays and cDNA microarrays. With this background recent results of papillary thyroid carcinoma analysis with DNA microarrays are presented.     

Gene expression in the normal adult human kidney assessed by complementary DNA microarray

The kidney is a highly specialized organ with a complex, stereotyped architecture and a great diversity of functions and cell types. Because the microscopic organization of the nephron, the functional unit of the kidney, has a consistent relationship to the macroscopic anatomy of the kidney, knowledge of the characteristic patterns of gene expression in different compartments of the kidney could provide insight into the functions and functional organization of the normal nephron. We studied gene expression in dissected renal lobes of five adult human kidneys using cDNA microarrays representing approximately 30,000 different human genes. Total RNA was isolated from sections of the inner and outer cortex, inner and outer medulla, papillary tips, and renal pelvis and from glomeruli isolated by sieving. The results revealed unique and highly distinctive patterns of gene expression for glomeruli, cortex, medulla, papillary tips, and pelvic samples. Immunohistochemical staining using selected antisera confirmed differential expression of several cognate proteins and provided histological localization of expression within the nephron. The distinctive patterns of gene expression in discrete portions of the kidney may serve as a resource for further understanding of renal physiology and the molecular and cellular organization of the nephron.     

Detection of DNA copy number abnormality by microarray expression analysis

Gene copy-number abnormalities (CNAs) are characteristic of solid tumors and are found in association with developmental abnormalities and/or mental retardation. The ultimate impact of CNAs is exerted by the altered expression of encoded genes. We have utilized high-density oligonucleotide arrays from Affymetrix to identify DNA CNAs via their impact on mRNA expression levels. In these studies, we have used three different trisomic cell lines (trisomy 9, trisomy 18, trisomy 21) as models of CNAs and have compared mRNA expression in those trisomic cells with that observed in diploid cell lines of matched tissue origin. Our data clearly show that genes from CNA chromosome regions are substantially over-represented (P<0.000001 by chi-square analysis) in the differentially expressed subset from comparisons of all three trisomic cell lines with normal matching cells. In addition, we have been able to detect the origin of the duplication by a statistical scan for over-expressed genes. These data show that microarray detection of differential mRNA expression can be used to identify significant DNA CNAs.     

Gene expression profiles of endothelial progenitor cells by oligonucleotide microarray analysis

Among the many tissue stem or progenitor cells recently being unveiled, endothelial progenitor cells (EPCs) have attracted particular attention, not only because of their cardinal role in vascular biology and embryology but also because of their potential use in the therapeutic development of a variety of postnatal diseases, including cardiovascular and peripheral vascular disorders and cancer. The aim of this study is to provide some basic and comprehensive information on gene expression of EPCs to characterize the cells in molecular terms. Here, we focus on EPCs derived from CD34-positive mononuclear cells of human umbilical cord blood. The EPCs were purified and expanded in culture and analyzed by a high-density oligonucleotide microarray and real-time RT-PCR analysis. We identified 169 up-regulated and 107 down-regulated genes in the EPCs compared with three differentiated endothelial cells of human umbilical vein endothelial cells (HUVEC), human lung microvascular endothelial cells (LMEC) and human aortic endothelial cells (AoEC). It is expected that the obtained list include key genes which are critical for EPC function and survival and thus potential targets of EPC recognition in vivo and therapeutic modulation of vasculogenesis in cancer as well as other diseases, in which de novo vasculogenesis plays a crucial role. For instance, the list includes Syk and galectin-3, which encode protein tyrosine kinase and β-galactoside-binding protein, respectively, and are expressed higher in EPCs than the three control endothelial cells. In situ hybridization showed that the genes were expressed in isolated cells in the fetal liver at E11.5 and E14.5 of mouse development.     

Differential analysis of DNA microarray gene expression data

Here, we review briefly the sources of experimental and biological variance that affect the interpretation of high-dimensional DNA microarray experiments. We discuss methods using a regularized t-test based on a Bayesian statistical framework that allow the identification of differentially regulated genes with a higher level of confidence than a simple t-test when only a few experimental replicates are available. We also describe a computational method for calculating the global false-positive and false-negative levels inherent in a DNA microarray data set. This method provides a probability of differential expression for each gene based on experiment-wide false-positive and -negative levels driven by experimental error and biological variance.     

Gene expression microarray analysis of early oxygen-induced retinopathy in the rat

Different inbred strains of rat differ in their susceptibility to oxygen-induced retinopathy (OIR), an animal model of human retinopathy of prematurity. We examined gene expression in Sprague–Dawley (susceptible) and Fischer 344 (resistant) neonatal rats after 3 days exposure to cyclic hyperoxia or room air, using Affymetrix rat Genearrays. False discovery rate analysis was used to identify differentially regulated genes. Such genes were then ranked by fold change and submitted to the online database, DAVID. The Sprague–Dawley list returned the term “response to hypoxia,” absent from the Fischer 344 output. Manual analysis indicated that many genes known to be upregulated by hypoxia-inducible factor-1α were downregulated by cyclic hyperoxia. Quantitative real-time RT-PCR analysis of Egln3, Bnip3, Slc16a3, and Hk2 confirmed the microarray results. We conclude that combined methodologies are required for adequate dissection of the pathophysiology of strain susceptibility to OIR in the rat.     

Gene expression profile of mouse bone marrow stromal cells determined by cDNA microarray analysis

Bone marrow stromal cells (BMSC) have gained increased attention because of their multipotency and adult stem cell character. They have been shown to differentiate into other cell types of the mesenchymal lineage and also into non-mesenchymal cells. The exact identity of the original cells, which are isolated from bone marrow by their selective adherence to plastic, remains unknown to date. We have established and characterized mouse BMSC cultures and analyzed three independent samples by cDNA microarrays. The expression profile was compared with two previous expression studies of human BMSC and revealed a high degree of concordance between different techniques and species. To gain clues about the positional context and biology of the isolated cells within the bone marrow stroma, we searched our data for genes that encode proteins of the extracellular matrix, cell adhesion proteins, cytoskeletal proteins and cytokines/cytokine receptors. This analysis revealed a close association of BMSC with vascular cells and indicated that BMSC resemble pericytes.     

DNA microarray analysis of region-specific gene expression in the mouse epididymis

Microarray analysis was carried out to identify genes with enriched expression in the initial segment region of the mouse epididymis. A set of approximately 15 000 clones developed at the National Institutes for Aging and consisting of expressed sequence tags (ESTs) derived from pre- and peri-implantation embryos, Embryonic Day 12.5 female gonad/mesonephros, and newborn ovary were hybridized with probes generated against the initial segment (epididymal region 1) and the remainder of the epididymis (epididymal regions 2-5). The median values for the normalized ratios of region 1 to regions 2-5 from three independent experiments were averaged for each gene/EST using Genespring 5.0 software. The majority of clones showed a ratio of 1.0, suggesting they were expressed at similar levels in all epididymal regions. In addition, 123 clones exhibited 2-fold or higher expression in the initial segment, including Cres3, prostein, lipocalin 2, ALEX3, synaptotagmin-like 4, erm, and milk fat globule factor, whereas 216 clones, including elafin-like 1, lactotransferrin, Sin3B, zinc-finger protein 91, and membrane-type frizzled-related protein, showed 2-fold or higher expression in epididymal regions 2-5. Northern blot analyses of 12 clones predicted by microarray analysis to be either enriched in the initial segment (n = 8), enriched in epididymal regions 2-5 (n = 2), or similar in all regions (n = 2) were carried out. All clones exhibited the expected region-specific expression, thus confirming the microarray results. The studies presented here show a global survey of region-specific gene expression in the epididymis, identifying 15287 sequences, the majority of which have not previously been shown to be expressed in this organ.     

Gene expression profile analysis in astaxanthin-induced Haematococcus pluvialis using a cDNA microarray

The unicellular green alga Haematococcus pluvialis (Volvocales) is known for the ketocarotenoid astaxanthin (3, 3′-dihydroxy-β, β-carotene-4, 4′-dione) accumulation, which is induced under unfavorable culture conditions. In this work, we used cDNA microarray analysis to screen differentially expressed genes in H. pluvialis under astaxanthin-inductive culture conditions, such as combination of cell exposure to high irradiance and nutrient deprivation. Among the 965 genes in the cDNA array, there are 144 genes exhibiting differential expression (twofold changes) under these conditions. A significant decrease in the expression of photosynthesis-related genes was shown in astaxanthin-accumulating cells (red cells). Defense- or stress-related genes and signal transduction genes were also induced in the red cells. A comparison of microarray and real-time PCR analysis showed good correlation between the differentially expressed genes by the two methods. Our results indicate that the cDNA microarray approach, as employed in this work, can be relied upon and used to monitor gene expression profiles in H. pluvialis. In addition, the genes that were differentially expressed during astaxanthin induction are suitable candidates for further study and can be used as tools for dissecting the molecular mechanism of this unique pigment accumulation process in the green alga H. pluvialis. Electronic Supplementary Material Supplementary material is available for this article at and is accessible for authorized users.     

Gene microarray analysis of expression profiles in Suberoyllanilide hyroxamic acid-treated Dendritic cells

Objective

The purpose of this study is to provide a further theoretical basis for the role of Suberoyllanilide hyroxamic acid (SAHA) affect on Dendritic cells (DCs).

Real-time DNA microarray analysis

We present a quantification method for affinity-based DNA microarrays which is based on the real-time measurements of hybridization kinetics. This method, i.e. real-time DNA microarrays, enhances the detection dynamic range of conventional systems by being impervious to probe saturation in the capturing spots, washing artifacts, microarray spot-to-spot variations, and other signal amplitude-affecting non-idealities. We demonstrate in both theory and practice that the time-constant of target capturing in microarrays, similar to all affinity-based biosensors, is inversely proportional to the concentration of the target analyte, which we subsequently use as the fundamental parameter to estimate the concentration of the analytes. Furthermore, to empirically validate the capabilities of this method in practical applications, we present a FRET-based assay which enables the real-time detection in gene expression DNA microarrays.     

DNA microarray data imputation and significance analysis of differential expression

MOTIVATION: Significance analysis of differential expression in DNA microarray data is an important task. Much of the current research is focused on developing improved tests and software tools. The task is difficult not only owing to the high dimensionality of the data (number of genes), but also because of the often non-negligible presence of missing values. There is thus a great need to reliably impute these missing values prior to the statistical analyses. Many imputation methods have been developed for DNA microarray data, but their impact on statistical analyses has not been well studied. In this work we examine how missing values and their imputation affect significance analysis of differential expression. RESULTS: We develop a new imputation method (LinCmb) that is superior to the widely used methods in terms of normalized root mean squared error. Its estimates are the convex combinations of the estimates of existing methods. We find that LinCmb adapts to the structure of the data: If the data are heterogeneous or if there are few missing values, LinCmb puts more weight on local imputation methods; if the data are homogeneous or if there are many missing values, LinCmb puts more weight on global imputation methods. Thus, LinCmb is a useful tool to understand the merits of different imputation methods. We also demonstrate that missing values affect significance analysis. Two datasets, different amounts of missing values, different imputation methods, the standard t-test and the regularized t-test and ANOVA are employed in the simulations. We conclude that good imputation alleviates the impact of missing values and should be an integral part of microarray data analysis. The most competitive methods are LinCmb, GMC and BPCA. Popular imputation schemes such as SVD, row mean, and KNN all exhibit high variance and poor performance. The regularized t-test is less affected by missing values than the standard t-test. AVAILABILITY: Matlab code is available on request from the authors.     

Genetic predisposition to papillary thyroid cancer

Approximately 5% of differentiated thyroid cancers are hereditary. Hereditary non-medullary thyroid cancer may occur as a minor component of familial cancer syndromes (e.g. familial adenomatous polyposis) or as a primary feature (familial non-medullary thyroid cancer [FNMTC]). Among FNMTC, PTC is the most common. Although a hereditary predisposition to non-medullary thyroid cancer is well established, the susceptibility genes are poorly known. Up to now, by linkage analysis using microsatellite markers, several putative loci have been described - 1q21, 6q22, 8p23.1-p22, and 8q24; however, validation studies have been unsuccessful. In the present review we discuss the results of linkage analysis and the most recent results of genome wide association studies (GWAS) with high resolution SNP (single nucleotide polymorphism) arrays.