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PubMed2004

Customizing chemotherapy for colon cancer: the potential of gene expression profiling.

The value of gene expression profiling, or microarray analysis, for the classification and prognosis of multiple forms of cancer is now clearly established. For colon cancer, expression profiling can readily discriminate between normal and tumor tissue, and to some extent between tumors of different histopathological stage and prognosis. While a definitive in vivo study demonstrating the potential of this methodology for predicting response to chemotherapy is presently lacking, the ability of microarrays to distinguish other subtleties of colon cancer phenotype, as well as recent in vitro proof-of-principle experiments utilizing colon cancer cell lines, illustrate the potential of this methodology for predicting the probability of response to specific chemotherapeutic agents. This review discusses some of the recent advances in the use of microarray analysis for understanding and distinguishing colon cancer subtypes, and attempts to identify challenges that need to be overcome in order to achieve the goal of using gene expression profiling for customizing chemotherapy in colon cancer.

Colonic Neoplasms↗

PubMed2000

Reproducibility of alternative probe synthesis approaches for gene expression profiling with arrays.

Before gene expression profiling with microarray technology can be transferred to the diagnostic setting, we must have alternative approaches for synthesizing probe from limited RNA samples, and we must understand the limits of reproducibility in interpreting gene expression results. The current gold standard of probes for use with both microarrays and high-density filter arrays are synthesized from 1 microg of purified poly(A)+ RNA. We evaluated two approaches for synthesizing cDNA probes from total RNA with subsequent hybridization to high-density filter arrays: 1) reverse transcription (RT) of 5 microg total RNA and 2) RT-polymerase chain reaction (RT-PCR) of 1 microg total RNA, using the SMART system. The reproducibility of these two approaches was compared to the current gold standard. All three methods were highly reproducible. Triplicate experiments resulted in the following concordance correlation coefficients to evaluate reproducibility: 0.88 for the gold standard, 0.86 for cDNA probe synthesized by RT from total RNA, and 0.96 for the SMART cDNA probe synthesized from total RNA. We also compared the expression profile of 588 genes for the total RNA methods to that obtained with the gold standard. Of 150 positive genes detected by the gold standard, 97 (65%) were detected by cDNA probe synthesized by RT of total RNA, and 122 (81%) were detected by the SMART cDNA probe. We conclude that SMART cDNA probe produces highly reproducible results and yields gene expression profiles that represent the majority of transcripts detected with the gold standard.

DNA Probes↗

PubMed2004

Gene cataloging and expression profiling in human gastric cancer cells by expressed sequence tags.

To understand the molecular mechanism associated with gastric carcinogenesis, we identified genes expressed in gastric cancer cell lines and tissues. Of 97,609 high-quality ESTs sequenced from 36 cDNA libraries, 92,545 were coalesced into 10,418 human Unigene clusters (Build 151). The gene expression profile was produced by counting the cluster frequencies in each library. Although the profiles of highly expressed genes varied greatly from library to library, those genes related to cell structure formation, heat shock proteins, the glycolysis pathway, and the signaling pathway were highly represented in human gastric cancer cell lines and in primary tumors. Conversely, the genes encoding immunoglobulins, ribosomal proteins, and digestive proteins were down-regulated in gastric cancer cell lines and tissues compared to normal tissues. The transcription levels of some of these genes were confirmed by RT-PCR. We found that genes related to cell adhesion, apoptosis, and cytoskeleton formation were particularly up-regulated in the gastric cancer cell lines established from malignant ascites compared to those from primary tumors. This comprehensive molecular profiling of human gastric cancer should be useful for elucidating the genetic events associated with human gastric cancer.

Base Sequence↗

PubMed2004

Expression profiling using random genomic DNA microarrays identifies differentially expressed genes associated with three major developmental stages of the protozoan parasite Leishmania major.

To complete its life cycle, protozoan parasites of the genus Leishmania undergo at least three major developmental transitions. However, previous efforts to identify genes showing stage regulated changes in transcript abundance have yielded relatively few. Here we used expression profiling to assess changes in transcript abundance in three stages: replicating promastigotes and infective non-replicating metacyclics, which occur in the sand fly vector, and in the amastigote stage residing with macrophage phagolysosomes in mammals. Microarrays were developed containing 11,484 PCR products that included a number of known genes and 10,464 random 1 kb genomic DNA fragments. Arrays were hybridized in triplicate and genes showing two-fold or greater changes in 2/3 experiments were scored as differentially expressed. Remarkably, only about one percent of the DNAs expression varied by this criteria, in either stage comparison. Northern blot analysis confirmed the predicted change in mRNA abundance for most of these (68%). This set of genes included most of those previously identified in the literature as differentially regulated as well as a number of novel genes. Notably, Leishmania maxicircle transcripts showed strong up-regulation in metacyclic and amastigote parasites, probably associated with changes in parasite energy metabolism. However, current data suggest that expression profiling using shotgun DNA libraries significantly underestimates the extent of regulated transcripts.

Animals↗

PubMed2000

miniSAGE: gene expression profiling using serial analysis of gene expression from 1 microg total RNA.

The use of serial analysis of gene expression (SAGE) to determine gene expression profiles is increasing because the technique can provide absolute transcript numbers in a digital format and identify new genes. We developed a miniSAGE technique, which uses only 1 microg total RNA and reduces the amount of the starting material by 250- to 500-fold. Unlike the other modified SAGE methods, the miniSAGE technique does not require the additional PCR amplifications. The additional PCR amplifications potentially introduce bias and compromise the quantitative aspects of the SAGE method. Three key modifications in the miniSAGE technique are: (i) using the phase lock gel (PLG, Eppendorf) to increase the recovery and the purity of DNA material after each phenol extraction step; (ii) reducing the amount of linkers in the ligation, thereby minimizing their interference with SAGE ditag amplification and increasing the SAGE ditag yield; and (iii) employing the mRNA capture kit (Boehringer Mannheim) to allow the first five steps: mRNA isolation, cDNA synthesis, enzyme cleavage of cDNA, binding of the cleaved biotin-cDNA to the streptavidin-magnetic beads, ligating linkers to the bound cDNA, and the release of cDNA tags to occur within one tube to significantly reduce the loss of material between successive steps. Two fibroblast SAGE libraries have been successfully prepared. The preliminary analysis of 3838 tags from one library demonstrated a typical fibroblast gene expression pattern. This miniSAGE technique will permit a broader application of SAGE.

Biopsy↗

PubMed2002

Large-scale analysis of gene expression profiles.

The accumulation of DNA microarray data has now made it possible to use gene expression profiles to analyse expression data. A gene expression profile contains the expression data for a given gene over various samples, and can be contrasted with an expression signature, which contains the expression data for a single sample. Gene expression profiles are most revealing when samples are grouped appropriately, either by standard clinical or pathological categories or by categories discovered through cluster analysis techniques. Expression profiles can exist at various levels of abstraction, yielding information across various tissues or across diseases within a particular tissue. Hypothesis tests may be applied to expression profiles on a large scale to identify candidate genes of interest.

Cluster Analysis↗

PubMed2006

The UVB-induced gene expression profile of human epidermis in vivo is different from that of cultured keratinocytes.

In order to obtain a comprehensive picture of the molecular events regulating cutaneous photodamage of intact human epidermis, suction blister roofs obtained after a single dose of in vivo ultraviolet (UV)B exposure were used for microarray profiling. We found a changed expression of 619 genes. Half of the UVB-regulated genes had returned to pre-exposure baseline levels at 72 h, underscoring the transient character of the molecular cutaneous UVB response. Of special interest was our finding that several of the central p53 target genes remained unaffected following UVB exposure in spite of p53 protein accumulation. We next compared the in vivo expression profiles of epidermal sheets to that of cultured human epidermal keratinocytes exposed to UVB in vitro. We found 1931 genes that differed in their expression profiles between the two groups. The expression profile in intact epidemis was geared mainly towards DNA repair, whereas cultured keratinocytes responded predominantly by activating genes associated with cell-cycle arrest and apoptosis. These differences in expression profiles might reflect differences between mature differentiating keratinocytes in the suprabasal epidermal layers versus exponentially proliferating keratinocytes in cell culture. Our findings show that extreme care should be taken when extrapolating from findings based on keratinocyte cultures to changes in intact epidermis.

Adult↗

PubMed2001

Monitoring signal transduction in cancer: tyrosine kinase gene expression profiling.

Abnormal expression of tyrosine kinase (TK) genes is common in tumors, in which it is believed to alter cell growth and response to external stimuli such as growth factors and hormones. Although the etiology and pathogenesis of carcinomas of the thyroid or breast remain unclear, there is evidence that the expression of TK genes, such as receptor tyrosine kinases, or mitogen-activated protein kinases, is dysregulated in these tumors, and that overexpression of particular TK genes due to gene amplification, changes in gene regulation, or structural alterations leads to oncogenic transformation of epithelial cells. We developed a rapid scheme to measure semiquantitatively the expression levels of 50-100 TK genes. Our assay is based on RT-PCR with mixed based primers that anneal to conserved regions in the catalytic domain of TK genes to generate gene-specific fragments. PCR products are then labeled by random priming and hybridized to DNA microarrays carrying known TK gene targets. Inclusion of differently labeled fragments from reference or normal cells allows identification of TK genes that show altered expression levels during malignant transformation or tumor progression. Examples demonstrate how this innovative assay might help to define new markers for tumor progression and potential targets for disease intervention. (J Histochem Cytochem 49:673-674, 2001)

Breast Neoplasms↗

PubMed2000

Gene expression profiles of human endometrial cancer samples using a cDNA-expression array technique: assessment of an analysis method.

The recently developed cDNA expression array technique can be used to generate gene-expression fingerprints of tumour specimens. To gain insight into molecular mechanisms involved in the development and progression of cancer, this cDNA expression array technique could be a useful tool, however, no established methods for interpreting the results are yet available. We used the Atlas cancer cDNA expression array (Clontech, USA) for analysing total RNA isolated from four human endometrial carcinoma samples (two cell-lines and two tissue samples), one benign endometrial tissue sample and a human breast cancer cell-line, in order to develop a method for analysing the array data. The obtained gene-expression profiles were highly reproducible. XY-scatterplots and regression analysis of the logarithmic transformed data provided a practical method to analyse the data without the need of preceding normalization. Three genes (Decorin, TIMP3 and Cyclin D1) were identified to be differentially expressed between the benign endometrial tissue sample and the endometrial carcinoma samples (tissue and cell-lines). These three genes may potentially be involved in cancer progression. A higher degree of similarity in gene-expression profile was found between the endometrial samples (tissue and cell-lines) than between the endometrial samples and the breast cancer cell-line, which is indicative for an endometrial tissue-specific gene-expression profile.

DNA, Complementary↗

PubMed2002

Gene expression profiling in developing human hippocampus.

The gene expression profile of developing human hippocampus is of particular interest and importance to neurobiologists devoted to development of the human brain and related diseases. To gain further molecular insight into the developmental and functional characteristics, we analyzed the expression profile of active genes in developing human hippocampus. Expressed sequence tags (ESTs) were selected by sequencing randomly selected clones from an original 3'-directed cDNA library of 150-day human fetal hippocampus, and a digital expression profile of 946 known genes that could be divided into 16 categories was generated. We also used for comparison 14 other expression profiles of related human neural cells/tissues, including human adult hippocampus. To yield more confidence regarding differential expression, a method was applied to attach normalized expression data to genes with a low false-positive rate (<0.05). Finally, hierarchical cluster analysis was used to exhibit related gene expression patterns. Our results are in accordance with anatomical and physiological observations made during the developmental process of the human hippocampus. Furthermore, some novel findings appeared to be unique to our results. The abundant expression of genes for cell surface components and disease-related genes drew our attention. Twenty-four genes are significantly different from adult, and 13 genes might be developing hippocampus-specific candidate genes, including wnt2b and some Alzheimer's disease-related genes. Our results could provide useful information on the ontogeny, development, and function of cells in the human hippocampus at the molecular level and underscore the utility of large-scale, parallel gene expression analyses in the study of complex biological phenomena.

Adult↗

PubMed2002

Gene expression profiling of lymphoid malignancies.

Comprehensive gene expression profiling using DNA microarrays is providing a molecular classification of cancer into disease categories that are homogeneous with respect to pathogenesis and clinical behavior. Gene expression profiling revealed that diffuse large B cell lymphoma (DLBCL) consists of at least two molecularly distinct diseases that are derived from distinct stages of B cell differentiation and have strikingly different clinical outcomes. By contrast, chronic lymphocytic leukemia (CLL) was found to be a single disease defined by a characteristic gene expression signature. Nonetheless, gene expression profiling distinguished two clinically divergent CLL subtypes and provided evidence that signaling through the B cell antigen receptor may play a role in the clinically aggressive subtype. Gene expression analysis also illuminated the mechanism of lymphomagenesis caused by BCL-6 translocations and provided evidence that the NF-kappa B signaling pathway is a new molecular therapeutic target in DLBCL.

DNA-Binding Proteins↗

PubMed2004

Comparative expressed sequence hybridization studies of hairy cell leukemia show uniform expression profile and imprint of spleen signature.

Comparative expressed sequence hybridization (CESH) to chromosomes is a recently introduced technique that identifies chromosomal regions corresponding to a differential gene expression. This technique is analogous to comparative genomic hybridization (CGH) that detects genomic imbalances. We applied CESH for the study of hairy cell leukemia (HCL), a disorder with a largely unknown expression profile. Twelve HCL cases with spleen involvement were investigated by CESH and CGH. While the latter analysis identified only a few nonrecurrent genomic imbalances, CESH showed a consistent expression profile in all HCL cases. In addition, pairing normal spleen with normal lymph node, a "spleen signature" was established by CESH. This signature most likely reflects the expression profile of spleen-specific components, such as the sinusoidal lining cells from the red pulp and the marginal zone B cells from the white pulp. Imprint of the spleen signature was found in the HCL expression profile, suggesting that HCL may originate from a particular B-cell subset present in these splenic components. Besides pairing HCL with normal lymph node and spleen, we identified an "HCL signature" comprising several chromosome regions with altered expression. The most significantly underexpressed regions include 3p24, 3p21, 3q13.3-q22, 4p16, 11q23, 14q22-q24, 15q21-q22, 15q24-q25, and 17q22-q24; and 13q31 and Xq13.3-q21 were the most significantly overexpressed. These regions possibly harbor genes related to the biology and the pathogenesis of HCL. Their identification warrants further molecular investigations.

Cell Line, Tumor↗

PubMed2005

ASIAN: a web server for inferring a regulatory network framework from gene expression profiles.

The standard workflow in gene expression profile analysis to identify gene function is the clustering by various metrics and techniques, and the following analyses, such as sequence analyses of upstream regions. A further challenging analysis is the inference of a gene regulatory network, and some computational methods have been intensively developed to deduce the gene regulatory network. Here, we describe our web server for inferring a framework of regulatory networks from a large number of gene expression profiles, based on graphical Gaussian modeling (GGM) in combination with hierarchical clustering (http://eureka.ims.u-tokyo.ac.jp/asian). GGM is based on a simple mathematical structure, which is the calculation of the inverse of the correlation coefficient matrix between variables, and therefore, our server can analyze a wide variety of data within a reasonable computational time. The server allows users to input the expression profiles, and it outputs the dendrogram of genes by several hierarchical clustering techniques, the cluster number estimated by a stopping rule for hierarchical clustering and the network between the clusters by GGM, with the respective graphical presentations. Thus, the ASIAN (Automatic System for Inferring A Network) web server provides an initial basis for inferring regulatory relationships, in that the clustering serves as the first step toward identifying the gene function.

Cluster Analysis↗

PubMed2003

Gene Expression Dynamics Inspector (GEDI): for integrative analysis of expression profiles.

UNLABELLED: Genome-wide expression profiles contain global patterns that evade visual detection in current gene clustering analysis. Here, a Gene Expression Dynamics Inspector (GEDI) is described that uses self-organizing maps to translate high-dimensional expression profiles of time courses or sample classes into animated, coherent and robust mosaics images. GEDI facilitates identification of interesting patterns of molecular activity simultaneously across gene, time and sample space without prior assumption of any structure in the data, and then permits the user to retrieve genes of interest. Important changes in genome-wide activities may be quickly identified based on 'Gestalt' recognition and hence, GEDI may be especially useful for non-specialist end users, such as physicians. AVAILABILITY: GEDI v1.0 is written in Matlab, and binary Matlab.dll files which require Matlab to run can be downloaded for free by academic institutions at http://www.chip.org/~ge/gedihome.html SUPPLEMENTARY INFORMATION: http://www.chip.org/~ge/gedihome.html

Algorithms↗

PubMed2006

Analysis of microarray experiments of gene expression profiling.

The study of gene expression profiling of cells and tissue has become a major tool for discovery in medicine. Microarray experiments allow description of genome-wide expression changes in health and disease. The results of such experiments are expected to change the methods employed in the diagnosis and prognosis of disease in obstetrics and gynecology. Moreover, an unbiased and systematic study of gene expression profiling should allow the establishment of a new taxonomy of disease for obstetric and gynecologic syndromes. Thus, a new era is emerging in which reproductive processes and disorders could be characterized using molecular tools and fingerprinting. The design, analysis, and interpretation of microarray experiments require specialized knowledge that is not part of the standard curriculum of our discipline. This article describes the types of studies that can be conducted with microarray experiments (class comparison, class prediction, class discovery). We discuss key issues pertaining to experimental design, data preprocessing, and gene selection methods. Common types of data representation are illustrated. Potential pitfalls in the interpretation of microarray experiments, as well as the strengths and limitations of this technology, are highlighted. This article is intended to assist clinicians in appraising the quality of the scientific evidence now reported in the obstetric and gynecologic literature.

Algorithms↗

PubMed2002

Clues to pathogenesis of spondyloarthropathy derived from synovial fluid mononuclear cell gene expression profiles.

OBJECTIVE: To use gene expression profiles of spondyloarthropathy (SpA) synovial fluid mononuclear cells (SFMC) to determine if there are transcripts that support the unfolded protein response (UPR) hypothesis, and to identify which cytokines/chemokines are being expressed and which cell fractions are involved. METHODS: Gene expression profiles were generated by microarray screening of SFMC of 5 patients with SpA, 5 patients with rheumatoid arthritis (RA), and peripheral blood mononuclear cells (PBMC) of 6 controls. Results were validated by reverse transcription polymerase chain reaction using samples from a larger panel of subjects. RESULTS: The repertoires of proinflammatory cytokines/chemokines expressed by SpA and RA SFMC were very similar: monocyte chemotractant protein 1 (MCP-1), interleukin 8 (IL-8), IL-1beta, endothelial-monocyte activating polypeptide II, interferon-gamma, and tumor necrosis factor-alpha. MCP-1 was highly expressed in SpA SFMC. There was enhanced expression of immunoglobulin heavy chain binding protein (BiP) in SpA, which is compatible with the UPR hypothesis. BiP was most highly expressed in the adherent fraction of SpA SFMC. CONCLUSION: Previous data postulating UPR in SpA are based on in vitro experiments with transfected cell lines. Our patient derived data suggest that it also occurs in vivo in the macrophages of SpA joints.

Adolescent↗

PubMed2005

CD34 expression in native human acute myelogenous leukemia blasts: differences in CD34 membrane molecule expression are associated with different gene expression profiles.

BACKGROUND: The stem cell marker CD34 is expressed by leukemia blasts only for a subset of patients with acute myelogenous leukemia (AML). It is still controversial as to whether CD34 expression (defined as at least 10-20% positive cells) has any prognostic effect in patients with AML who receive intensive chemotherapy. The present study investigated whether gene expression profiling could be used to further subclassify CD34(+) AML cell populations. METHODS: AML blasts derived from 25 patients were examined; these patients were randomly selected from a larger consecutive group of patients. CD34 protein expression was determined by flow cytometry and expressed as the percentage of positive cells. Gene expression profiles were determined by complementary DNA microarrays. RESULTS: By unsupervised hierarchical clustering our patients could be grouped into two or three major subsets depending on the methodologic approach before clustering analysis (filtering or flooring of data, respectively). However, both approaches identified a cluster characterized by high gene expression and membrane molecule level of CD34. When using the floored expression profiles, the patient cluster characterized by increased CD34 gene expression was also characterized by a high percentage of CD34(+) cells (median 82%, range 56-100%) compared with the two other major clusters (median 19%, range <1-55%), but three of four outpatients also showed a high percentage of CD34(+) cells. CONCLUSION: A major proportion of patients with AML and high CD34 expression (usually >80% CD34(+) cells; nearly all patients had >50% positive cells) showed similarities in gene expression profile. In contrast, patients with lower CD34 expression often had a profile similar to those of patients regarded as CD34(-) according to conventional criteria. Our results suggest that the possible prognostic effect of CD34 expression should be reevaluated in clinical studies using additional or alternative cutoff values to describe CD34 expression.

Adult↗

PubMed2003

Identification of candidate tumor-suppressor genes in 6q27 by combined deletion mapping and electronic expression profiling in lymphoid neoplasms.

Deletions in the long arm of chromosome 6 (6q) are among the most frequent chromosome aberrations in lymphoid neoplasms. Recently, the region of minimal deletion (RMD1) in 6q27 was narrowed down to 5-9 Mb. In the present study, we aimed to define the distal border of the commonly lost region in 6q27 more precisely and to identify and investigate tumor-suppressor genes (TSGs) from this region. Twenty-nine cases, in which our previous fluorescence in situ hybridization (FISH) screening that used a set of 36 YAC probes revealed loss in 6q25-27, were further investigated by means of FISH. In all cases, deletions of 6q27 extended from yeast artificial chromosome (YAC) 977e10 spanning the proximal border of RMD1 to the most telomeric YAC 933f7 within the recently established YAC-contig of this region. An interstitial homozygous deletion, flanked by the telomeric probe TelVysion6q and YAC 971g12, was detected, which substantially narrows down the RMD1. To identify candidate TSGs down-regulated in malignant lymphomas from this region of homozygous loss, we performed electronic profiling of expressed sequences mapped to this region. This analysis suggested the gene PDCD2 originally thought to be involved in programmed cell death to be probably down-regulated in malignant B-cell lymphomas compared to normal B lymphocytes. Nevertheless, mutation analyses failed to identify mutations in the coding region of PDCD2 in nine lymphomas with FISH-proved 6q27 deletions. Furthermore, epigenetic studies in these nine and an additional 48 lymphomas did not show altered methylation of the PDCD2 locus in these tumors. Possibly haploinsufficiency is effectual in accelerating tumor progression.

Cell Line, Transformed↗