SEARCH · PubMed Health

Results for “Gene Expression Profiling”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 217 records · Page 12Linked to original sources

PubMed1999

Expression profiling by iAFLP: A PCR-based method for genome-wide gene expression profiling.

The availability of comprehensive sets of genes has prompted the researchers to carry out systematic collection of gene expression data. RT-PCR has the highest specificity and sensitivity for transcript detection among all available methods. Low throughput, especially when quantitative data are desired, has precluded RT-PCR from genome-wide application. Here we report a PCR-based expression profiling method, introduced amplified fragment length polymorphism (iAFLP), that has the same specificity and sensitivity as RT-PCR and a throughput level comparable to that of DNA-microarray hybridization. In this method, restricted ends of total cDNAs from six sources were ligated with adaptors having various length of short insertions to a common sequence (polymorphic adaptors). Amplification of a pool of these differentially adapted cDNAs with a gene-specific primer and an adaptor primer allows us to quantitate the abundance of any transcript in six mRNA sources. Using three different primer colors this technique allows quantitation of expression of 864 genes across six different sources per day with a single autosequencer, which is comparable to the throughput of microarray analysis in terms of number of genes x number of sources.

Animals↗

PubMed2001

Gene expression profile of ARPE-19 during repair of the monolayer.

BACKGROUND: The purpose of this study was to identify the profile of gene expression during retinal pigment epithelial (RPE) wound repair. METHODS: ARPE-19 cells derived from a human RPE cell line were grown for 4 weeks and injured by creating multiple concentric wounds. Unwounded cultures served as controls. During the proliferative phase of wound repair, total RNA was extracted from control and wounded cultures, and a [32P]dATP-labeled cDNA probe was synthesized and hybridized to Atlas Arrays (Clontech, Palo Alto, Calif.) containing 588 cDNAs. The autoradiograms obtained were then analyzed using the Molecular Dynamics software program. Semiquantitative PCR was carried out to confirm up-regulation of four genes associated with wound repair. ELISA was performed to quantitate the secreted MCP-1. RESULTS: In wounded cultures prominent up-regulation (greater than fivefold) was seen for genes encoding DNA synthesis and DNA repair proteins. A greater than threefold increase was seen for genes encoding mitogen-activated protein kinase, CD44, MCP-1 (monocyte chemotactic protein), thymosin beta-10, and HDGF (hepatoma-derived growth factor), among others. Genes encoding tumor suppressors were downregulated three- to five-fold in the wounded compared with the unwounded cultures. Semiquantitative PCR confirmed up-regulation of transcripts for thymosin beta-10, HDGF, CD44, and MCP-1. ELISA showed a 20% increase in secreted MCP-1. CONCLUSIONS: Gene array analysis revealed a differentiation program that included increased expression of genes involved in wound repair (adhesion molecules, cytokines, signal transducers), along with increased MCP-1 secretion. The RPE may be an early participant in the inflammatory response that occurs with proliferative vitreoretinopathy.

Cells, Cultured↗

PubMed2002

Classifying toxicity and pathology by gene-expression profile--taking a lead from studies in neoplasia.

Microarray technology has given rise to the ability to classify and predict toxin-induced pathological change using gene-expression profiles. However, to date gene-expression profiling of pathological subtype has been exploited mainly in the pathological classification of neoplasia. Using an example of resistance to doxorubicin in vitro and gene-expression profiling in neoplasia, this article explores the potential and challenges for gene-expression profiling in the delineation and understanding of toxicity and toxin-induced pathological change.

Animals↗

PubMed2000

Gene expression profile in prion protein-deficient fibroblasts in culture.

To investigate the physiological function of the cellular isoform of prion protein (PrP(C)), the gene expression profile was studied by analyzing a cDNA expression array containing 597 clones of various functional classes in two distinct skin fibroblast cell lines designated SFK and SFH, established from PrP-deficient (PrP(-)(/-)) mice and PrP(+/+) mice, respectively. The cells were incubated in the culture medium with or without inclusion of basic fibroblast growth factor (bFGF). When SFK cells were compared with SFH cells in untreated conditions, the expression of 15 genes, including those essential for cell proliferation and adhesion, was reduced, whereas the expression of 27 genes, including those involved in the insulin-like growth factor-I (IGF-I) signaling pathway, was elevated. Northern blot analysis verified a significant down-regulation of the receptor tyrosine kinase substrate Eps8, cyclin D1, and CD44 mRNAs, and a substantial up-regulation of phosphatidylinositol 3-kinase p85, IGF-I, and serine protease inhibitor-2.2 mRNAs in SFK cells. The patterns of induction or reduction of gene expression after exposure to bFGF showed considerable overlap between both cell types. Furthermore, both Eps8 and CD44 mRNA levels were reduced greatly in the brain tissues of the cerebrum isolated from the PrP(-)(/-) mice. These results indicate that the disruption of the PrP gene resulted in an aberrant regulation of a battery of genes important for cell proliferation, differentiation, and survival, including those located in the Ras and Rac signaling pathways.

Animals↗

PubMed2002

A paradigm for class prediction using gene expression profiles.

We propose a general framework for prediction of predefined tumor classes using gene expression profiles from microarray experiments. The framework consists of 1) evaluating the appropriateness of class prediction for the given data set, 2) selecting the prediction method, 3) performing cross-validated class prediction, and 4) assessing the significance of prediction results by permutation testing. We describe an application of the prediction paradigm to gene expression profiles from human breast cancers, with specimens classified as positive or negative for BRCA1 mutations and also for BRCA2 mutations. In both cases, the accuracy of class prediction was statistically significant when compared to the accuracy of prediction expected by chance. The framework proposed here for the application of class prediction is designed to reduce the occurrence of spurious findings, a legitimate concern for high-dimensional microarray data. The prediction paradigm will serve as a good framework for comparing different prediction methods and may accelerate the development of molecular classifiers that are clinically useful.

Algorithms↗

PubMed2002

Gene expression profiles of bladder cancers: evidence for a striking effect of in vitro cell models on gene patterns.

In order to assess the effect of in vitro models on the expression of key genes known to be implicated in the development or progression of cancer, we quantified by real-time quantitative PCR the expression of 28 key genes in three bladder cancer tissue specimens and in their derived cell lines, studied either as one-dimensional single cell suspensions, two-dimensional monolayers or three-dimensional spheroids. Global analysis of gene expression profiles showed that in vitro models had a dramatic impact upon gene expression. Remarkably, quantitative differences in gene expression of 2-63-fold were observed in 24 out of 28 genes among the cell models. In addition, we observed that the in vitro model which most closely mimicked in vivo mRNA phenotype varied with both the gene and the patient. These results provide evidence that mRNA expression databases based on cancer cell lines, which are studied to provide a rationale for selection of therapy on the basis of molecular characteristics of a patient's tumour, must be carefully interpreted.

Clone Cells↗

PubMed2003

Intragraft gene expression profiles by cDNA microarray in small-for-size liver grafts.

The aim of this study is to identify the molecular mechanism of small-for-size graft injury through large-scale expression measurement of intragraft gene profile by carrier DNA (cDNA) microarray screening in liver transplantation. The studies compared 1,081 intragraft genes expression profiles using cDNA microarray of small-for-size grafts (<30% of recipient liver weight) with those of whole grafts (control group) 1, 3, and 24 hours after reperfusion in a rat liver transplantation model. Intragraft gene expression was detected by quantitative reverse-transcriptase polymerase chain reaction (RT-PCR). Hepatic ultrastructural features were shown by electron microscopy. In the small-for-size grafts, by cDNA microarray study, the vasoconstriction genes were found up-regulated together with adhesion molecules at 1 hour after reperfusion. Three and 24 hours after reperfusion, the vasopressin genes were found up-regulated together with adhesion molecules, inflammatory mediators and cell death signals, accompanied with down-regulation of the genes related to energy metabolism. By quantitative RT-PCR, intragraft messenger RNA (mRNA) expression of endothelin-1 (ET-1) and endothelin-1 receptor A (ETA) was up-regulated during the first 24 hours after reperfusion accompanied with down-regulation of heme oxygenase-1 (HO-1). The intragraft mRNA and plasma levels of inflammatory cytokines (interleukin [IL]-6, IL-15, tumor necrosis factor [TNF]-alpha) also were overexpressed during the first 24 hours after reperfusion. Sinusoidal congestion and disruption were found accompanied with mitochondrial swelling during the first 24 hours after reperfusion. The up-regulation of intragraft vasoconstriction genes accompanied by early overexpression of adhesion molecules and apoptotic signals, as well as down-regulation of HO-1 in small-for-size grafts may be related to sinusoidal injury leading to graft damage in liver transplantation.

Animals↗

PubMed1999

Gene Expression Profiles of Human Fetal Nasopharyngeal Tissue.

To study differentially expressed genes in nasopharynx tissues of embryo during development, and to observe the gene changes, total RNAs were respectively extracted from the nasopharynx tissue which came from fetuses of 5, 6, 7, and 8 month, Probes were yielded by reverse transcription and were used to hybridize with the Atlas(TM) human cDNA expression arrays. The results showed that the genes expression profile were distinctly different and different expression levels were found in the same gene during development. Results indicated that gene expression pattern had a character of time-dependence, such as early growth response protein 1 and the cDNA expression array provided a powerful method for studying gene expression profile in a large range of genes.

Journal Article↗

PubMed2003

Accurate and reproducible gene expression profiles from laser capture microdissection, transcript amplification, and high density oligonucleotide microarray analysis.

Gene expression profiling using high density oligonucleotide arrays is a powerful method to generate an unbiased survey of a cell's transcriptional landscape. Increasingly complex biological questions require that this approach be applicable to the small numbers of cells that are obtained from sources such as laser capture microdissection (LCM) of solid tissues. In this report, we demonstrate that two rounds of transcript amplification can generate accurate and reproducible gene expression profiles using high density oligonucleotide microarrays, starting with as little as 10 ng of total RNA. Biased amplification of the 3' end of transcripts does not have a major impact on the overall transcript profile due to the 3' bias of probe sets incorporated in the array design. Furthermore, greater than 95% of all genes detected demonstrate less than a twofold difference in expression when independent tissue dissections of identical cell populations are compared. The accuracy and technical reproducibility of the method suggests that expression profiling using transcript amplification and high density oligonucleotide microarrays can be used on a routine basis.

Breast Neoplasms↗

PubMed2003

Breast cancer classification and prognosis based on gene expression profiles from a population-based study.

Comprehensive gene expression patterns generated from cDNA microarrays were correlated with detailed clinico-pathological characteristics and clinical outcome in an unselected group of 99 node-negative and node-positive breast cancer patients. Gene expression patterns were found to be strongly associated with estrogen receptor (ER) status and moderately associated with grade, but not associated with menopausal status, nodal status, or tumor size. Hierarchical cluster analysis segregated the tumors into two main groups based on their ER status, which correlated well with basal and luminal characteristics. Cox proportional hazards regression analysis identified 16 genes that were significantly associated with relapse-free survival at a stringent significance level of 0.001 to account for multiple comparisons. Of 231 genes previously reported by others [van't Veer, L. J., et al. (2002) Nature 415, 530-536] as being associated with survival, 93 probe elements overlapped with the set of 7,650 probe elements represented on the arrays used in this study. Hierarchical cluster analysis based on the set of 93 probe elements segregated our population into two distinct subgroups with different relapse-free survival (P < 0.03). The number of these 93 probe elements showing significant univariate association with relapse-free survival (P < 0.05) in the present study was 14, representing 11 unique genes. Genes involved in cell cycle, DNA replication, and chromosomal stability were consistently elevated in the various poor prognostic groups. In addition, glutathione S-transferase M3 emerged as an important survival marker in both studies. When taken together with other array studies, our results highlight the consistent biological and clinical associations with gene expression profiles.

Breast Neoplasms↗

PubMed2002

Tumor specific gene expression profiles in human leiomyosarcoma: an evaluation of intratumor heterogeneity.

Leiomyosarcomas are malignant smooth muscle tumors characterized by a spectrum of histopathologic features and clinical behavior. Gene expression profiling of leiomyosarcomas may identify differential gene signatures that may allow for the clinical stratification of the tumors. Typically, surgical specimens from these tumors are large and manifest a variegated macroscopic appearance. Because of their large size at the time of diagnosis, sufficient tissue is available for regional and clonal heterogeneity assessment. However, if the gene expression profiles of samples taken from different locations in the tumors are drastically different, biologic classification on the basis of random sample analysis may not be adequate. Therefore, to assess intertumor and intratumor heterogeneity, the authors performed a gene expression study using leiomyosarcoma specimens from three excised sarcomas from an equal number of different patients. Comparisons between tumor and normal samples from the three patients as well as between carefully mapped peripheral and core specimens from the same tumor (excised from one of the patients), were performed. Analysis of the expression profiles demonstrated minimal intratumor variations compared with intertissue variations, indicating homogeneous tumor specific gene expression profiles. The authors also identified genes that are expressed differentially in tumor and normal tissue.

Biomarkers, Tumor↗

PubMed2000

Novel strategies for therapeutic design in molecular oncology using gene expression profiles.

The sequence of the human genome is estimated to be available by the end of the year 2000 [1]. Pursuant to deciphering the genomic code, and the identification of the estimated 40,000 to 100,000 human genes, anticipated technological advances will make possible examination of global gene expression profiles. Despite the current inaccessibility to the entire genome, many fruitful gene expression profiling studies have been performed using less than 10% of the predicted suite of genes in human or mouse genomes. Even within the confines of this limited set of genes, many insights and discoveries have resulted and their applications to cancer research are particularly profound. This review will focus on recent applications of gene expression profiling that have benefited three major areas of research in molecular oncology: (i) discovery--applications which have found novel genes, families of genes, or pathways involved in cell growth deregulation and tumor development; (ii) diagnosis--applications that have refined, and in some cases, defined, diagnostic methodology; and (iii) therapeutic design--applications which hold potential for chemotherapeutic drug discovery.

Animals↗

PubMed2002

Gene-expression profile of collagen-induced arthritis.

To provide a global analysis of genes involved in the inflammatory process in joints of DBA/1J mice suffering from collagen induced arthritis (CIA) we used oligonucleotide microarrays representing approximately 11,000 genes to determine the gene expression profile of the inflamed paws at peak of disease, and compared them to normal tissue. Peak of disease was determined from clinical evaluation of disease and histopathology of joints. Of the 11,000 genes assayed, 223 showed differential expression of four fold or more (187 upregulated and 36 downregulated). Ninety-five of the genes observed had well-characterized full length sequences in databases, and 128 were unknown (Ests). Inflammation resulted in a profile of increased gene expression of matrix metalloproteinases, immune-related, extra-cellular matrix and cell adhesion molecules, as well as molecules involved in cell division and transcription; differential regulation of molecules involved in signal transduction, protein synthesis and metabolism. Of the 55 genes with known chromosomal locations nine mapped to previously identified QTL, contributing to susceptibility or severity of CIA, i.e. MHC class I, II, Basigin, FAP, Cathepsin K, CD 53, RAF1, glucagon, and retinal taurine transporter. The profile of gene expression supports current theoretical models of disease progression and might open new perspectives for both diagnosis and treatment of arthritis.

Animals↗

PubMed2001

Gene-expression profiles in hereditary breast cancer.

BACKGROUND: Many cases of hereditary breast cancer are due to mutations in either the BRCA1 or the BRCA2 gene. The histopathological changes in these cancers are often characteristic of the mutant gene. We hypothesized that the genes expressed by these two types of tumors are also distinctive, perhaps allowing us to identify cases of hereditary breast cancer on the basis of gene-expression profiles. METHODS: RNA from samples of primary tumor from seven carriers of the BRCA1 mutation, seven carriers of the BRCA2 mutation, and seven patients with sporadic cases of breast cancer was compared with a microarray of 6512 complementary DNA clones of 5361 genes. Statistical analyses were used to identify a set of genes that could distinguish the BRCA1 genotype from the BRCA2 genotype. RESULTS: Permutation analysis of multivariate classification functions established that the gene-expression profiles of tumors with BRCA1 mutations, tumors with BRCA2 mutations, and sporadic tumors differed significantly from each other. An analysis of variance between the levels of gene expression and the genotype of the samples identified 176 genes that were differentially expressed in tumors with BRCA1 mutations and tumors with BRCA2 mutations. Given the known properties of some of the genes in this panel, our findings indicate that there are functional differences between breast tumors with BRCA1 mutations and those with BRCA2 mutations. CONCLUSIONS: Significantly different groups of genes are expressed by breast cancers with BRCA1 mutations and breast cancers with BRCA2 mutations. Our results suggest that a heritable mutation influences the gene-expression profile of the cancer.

Algorithms↗

PubMed2000

Gene expression profiling of primary breast carcinomas using arrays of candidate genes.

Breast cancer is characterized by an important histoclinical heterogeneity that currently hampers the selection of the most appropriate treatment for each case. This problem could be solved by the identification of new parameters that better predict the natural history of the disease and its sensitivity to treatment. A large-scale molecular characterization of breast cancer could help in this context. Using cDNA arrays, we studied the quantitative mRNA expression levels of 176 candidate genes in 34 primary breast carcinomas along three directions: comparison of tumor samples, correlations of molecular data with conventional histoclinical prognostic features and gene correlations. The study evidenced extensive heterogeneity of breast tumors at the transcriptional level. A hierarchical clustering algorithm identified two molecularly distinct subgroups of tumors characterized by a different clinical outcome after chemotherapy. This outcome could not have been predicted by the commonly used histoclinical parameters. No correlation was found with the age of patients, tumor size, histological type and grade. However, expression of genes was differential in tumors with lymph node metastasis and according to the estrogen receptor status; ERBB2 expression was strongly correlated with the lymph node status (P < 0.0001) and that of GATA3 with the presence of estrogen receptors (P < 0.001). Thus, our results identified new ways to group tumors according to outcome and new potential targets of carcinogenesis. They show that the systematic use of cDNA array testing holds great promise to improve the classification of breast cancer in terms of prognosis and chemosensitivity and to provide new potential therapeutic targets.

Adult↗

PubMed2002

[Gene expression profile of human hepatocellular carcinoma cell lines with different metastatic potentials].

OBJECTIVE: To compare gene expression profile of human hepatocellular carcinoma (HCC) cell lines with different metastatic potentials, so as to screen for metastasis-related genes. METHODS: Gene expression profile of MHCC97-L and HCCLM3, two HCC cell lines with similar genetic background but different in spontaneous metastatic potentials, were studied by cDNA microarray. RESULTS: From 1,626 screened genes, 25 differentially expressed genes were found, 18 showed decreased expression including the decreased expression of cell cycle control genes Rb2, mismatch repair gene hMSH2, and signal transduction gene protein kinase C beta 2 and 7 increased expression including signal transduction gene MAP kinase kinase 6, cell proliferation gene E25, immunity related gene SP40, 40, etc in HCCLM3. CONCLUSION: The genes, being closely associated with cancer metastasis, could be considered as potential markers to predict metastasis and targets for anti-metastasis intervention.

Blotting, Northern↗

PubMed2001

Analysis of gene expression profiles associated with cisplatin resistance in human ovarian cancer cell lines and tissues using cDNA microarray.

Gene expression profiles were analyzed by using cDNA microarray for a cisplatin-sensitive cell line (KF), and three- and thirty-fold cisplatin-resistant ovarian cancer cell lines (KFr and KFrP200) both showing no p53 mutation within exon 5, 6, 7, 8 and no pglycoprotein overexpression. Expression of GST-pi mRNA increased as the level of resistance to cisplatin became high. Microarray analysis revealed that DNA repair associated genes, i.e., XRCC5, XRCC6, ERCC5, hMLH1 were over-expressed in three-fold cisplatin-resistant cell line, KFr as compared to cisplatin-sensitive parental cell line, KF. Apoptosis inhibitors, i.e., IGFR type I and II were over-expressed, and apoptosis inducer, i.e., caspase 3 and BAK were underexpressed in highly cisplatin-resistant cell line, KFrP200 as compared to KFr. As for clinical cases, cDNA microarray was used to compare gene expression profiles directly between two groups, i.e., the chemotherapy (CAP) sensitive group (n = 2) and the resistant group (n = 2). Six genes such as beta tubulin, high-mobility group (nonhistone chromosomal) protein 1, connective tissue growth factor, insulin-like growth factor binding protein 2, alpha tubulin, and RAS-related gene were overexpressed in CAP therapy resistance group, whereas seven genes such as CD9 antigen, alpha-2-macroglobulin, caveolin 2, interleukin 1 receptor antagonist, Rho GTPase activating protein 1, reticulon 3, cyclin-dependent kinase 10, keratin 7 were underexpressed in CAP therapy resistance group. By increasing clinical case number and gene number of microarray to be used in the analysis of expression profile of gene cluster affecting anticancer drug resistance and sensitivity of the ovarian cancer, it would be possible to apply microarray analysis to personalization of chemotherapy such as selection of effective chemotherapy protocol and prediction of therapeutic effect in the near future.

Cisplatin↗

PubMedDate not supplied

DNA-microarrays as tools for the identification of tumor specific gene expression profiles: applications in tumor biology, diagnosis and therapy.

DNA-microarrays allow the analysis of almost the complete gene expression program of tumor samples and normal control samples in a single experiment. This allows the processing of a large number of samples in a reasonable short time. Tumor specific gene expression profiles can be used for molecular tumor classification and as a new diagnostic tool. In addition, the identification of tumor specific genes can help to understand the biology of tumor cells and identified genes can be used for the development of new therapeutic strategies. However, the huge amount of data generated by DNA-microarrays creates new challenges for data analysis. In addition, accuracy and reproducibility of the available techniques require complementary methods for verification of DNA-microarray data.

Child↗