Unknown,Transcriptomics,Genomics,Proteomics

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Transcription profiling of human embryonal carcinomas

ABSTRACT: Many cancers may originate in stem or early progenitor cells 1-4 which depend on epigenetic modulation of gene expression for normal function (ref). We have studied whether epigenetic states in cancers, and particularly abnormal gene silencing associated with promoter DNA hypermethylation in CpG rich regions (refs), may represent links between cancer and stem cell epigenetic patterns. We studied embryonal carcinomas (EC) which are malignancies of embryonic stem (ES) cells, but retain high potential for multi-lineage differentiation 5-8. Surprisingly, genes DNA hypermethylated and silenced in adult cancers are unmethylated in ES and EC cells. Remarkably, the promoter chromatin of the genes in EC cells is virtually identical to the same genes in adult cancers when the latter are induced to de-methylate. This chromatin, as recently reported for CpG island promoters of low expression, developmentally related, genes in ES cells (refs), is âbivalentâ and contains both active and repressive histone modifications. The latter includes trimethyl lysine 27 of histone H3 (H3K27me3), which may recruit DNA methylation (refs), and the promoter regions are enriched for polycomb group (PcG) proteins which place this H3K27me3 mark. Thus, many genes which undergo abnormal DNA methylation and permanent silencing in adult cancers may be programmed to do so by a pre-existent stem cell-like chromatin pattern inherent to the cells in which they arise. Experiment Overall Design: Data analysis. All arrays were subject to quality checks recommended by the manufacturer. Images were visually inspected for artifacts and distributions of signal and background intensity of both red and green channels are examined to identify anomalous arrays. No irregularities were observed, and all arrays were retained and used. Experiment Overall Design: All calculations were performed using the R statistical computing platform, (cite R) and packages from Bioconductor bioinformatics software project (cite Bioconductor). The log ratio of red median signal to green median signal was calculated after background-subtraction and loess normalzation as implemented in the limma package from Bioconductor. ( cite Smyth) Individual arrays were scaled to have the same inter-quartile range (75th percentile -25th percentile) Log fold changes were averaged over dye-swap replicate microarrays to produce a single set of expression values for each condition.

ORGANISM(S): Homo sapiens

SUBMITTER: Wayne Yu

PROVIDER: E-GEOD-4809 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:Altered gene expression is a hallmark of human cancers and arises in part through abnormal epigenetic regulation of gene transcription. The best characterized epigenetic alteration involves tumor suppressor gene inactivation via transcriptional repression associated with aberrant DNA hypermethylation of promoter region CpG islands1. Despite characterization of a growing number of such genes, the majority have yet to be identified. We now describe a genome wide microarray gene expression approach for human colorectal cancer cells, which can efficiently identify hundreds of hypermethylated genes for any cancer type. We compared isogenic cells altered pharmacologically versus genetically to induce genomic demethylation, to pinpoint genes activated by DNA demethylation, but not by inhibition of class I and II histone deacetylases (HDACs). We achieve an 82% success rate in predicting genes with densely hypermethylated CpG islands and complete gene silencing. The genes are similarly hypermethylated in primary tumors and have previously undetected tumor suppressor functions. Our approach provides the first highly efficient, comprehensive, platform for defining the cancer âDNA hypermethylome" Experiment Overall Design: Cell culture and treatment. HCT116 cells and isogenic genetic knockout derivatives were maintained as previously described14. For drug treatments, log phase HCT116 cells were cultured in McCoys 5A media (Invitrogen) containing 10% BCS and 1x penicillin/streptomycin with ïµïM 5aza-deoxycytidine (DAC) (Sigma; stock solution: 1mM in PBS) for 96 hours, replacing media and DAC every 24 hours. Cell treatment with 300nM Trichostatin A (Sigma; stock solution: 1.5mM dissolved in ethanol) was performed for 18 hours. Control cells underwent mock treatment in parallel with addition of equal volume of PBS or ethanol without drugs. Experiment Overall Design: Microarray analysis. Total RNA was harvested from log phase cells using the Qiagen kit according to the manufacturers instructions, including a DNAase step. RNA was quantified using the NanoDrop ND-100 followed by quality assessment with 2100 Bioanalyzer (Agilent Technologies). RNA concentrations for individual samples were greater than 200ng/ul, with 28s/18s ratios greater than 2.2 and RNA integrity numbers of 10 (highest). Sample amplification and labeling procedures were carried out using the Low RNA Input Fluorescent Linear Amplification Kit (Agilent Technologies) according to the manufacturers instructions. The labeled cRNA was purified using the RNeasy mini kit (Qiagen) and quantified. RNA spike-in controls (Agilent Technologies) were added to RNA samples before amplification. 0.75 microgram of samples labeled with Cy3 or Cy5 were mixed with control targets (Agilent Technologies), assembled on Oligo Microarray, hybridized, and processed according to the Agilent microarray protocol. Scanning was performed with the Agilent G2565BA microarray scanner under default settings recommended by Agilent Technologies. Experiment Overall Design: Data analysis. All arrays were subject to quality checks recommended by the manufacturer. Images were visually inspected for artifacts and distributions of signal and background intensity of both red and green channels were examined to identify anomalous arrays. No irregularities were observed, and all arrays were retained and used. All calculations were performed using the R statistical computing platform37 and packages from Bioconductor bioinformatics software project38. The log ratio of red signal to green signal was calculated after background-subtraction and LoEss normalization as implemented in the limma package from Bioconductor39,40. Individual arrays were scaled to have the same inter-quartile range (75th percentile -25th percentile) Log fold changes were averaged over dye-swap replicate microarrays to produce a single set of expression values for each condition.

Project description:Both ovarian and pituitary hormones are required for the pubertal development of the mouse mammary gland. Estradiol directs ductal elongation and branching within the adipose stroma of the adolescent mouse mammary gland, while progesterone leads to tertiary branching and alveolar development. The purpose of this investigation was to identify the estrogen-responsive genes that are associated with estrogen-stimulated ductal elongation and branching in the mouse mammary gland in the absence of other ovarian hormones. We also wanted to determine if estrogen-responsive gene regulation at early stages of ductal elongation (ie. when ductal growth was minimal) was similar to those regulated after significant ductal elongation had occurred. To identify estrogen-regulated genes, ovariectomized prepubertal mice were exposed to 17beta-estradiol for four weeks, and mammary gland global gene expression analyzed by microarray analysis at various points during this time course. We determined that while many genes are regulated in all weeks of treatment, there remained a subset of genes that was uniquely regulated at each time-point. This observation was reflected in the biological functions of these genes; some categories were represented in all weeks of treatment while others were specific to only certain time-points. We have also identified estradiol-responsive genes in the mouse mammary gland that co-express with Estrogen Receptor alpha in human breast cancer, which may represent novel effectors of estrogen action and/or biomarkers for the progression of estrogen-dependent cancers and other estrogen-driven diseases. Experiment Overall Design: For each time-course experiment, one frozen #4 mammary gland was individually pulverized from four to five animals per treatment group, then homogenized in 3mL Trizol (Invitrogen, Carlsbad, CA) and RNA was prepared according to the manufacturerâ??s protocol. The RNA from individual animals was then pooled for each treatment group (four to five animals per group) and further purified using the QIAGEN (Valencia, CA) RNeasy Mini kit (Cat. No. 74104) clean-up protocol. Experiment Overall Design: Gene expression analysis was conducted using Agilent Mouse Oligo arrays (pattern number 011978) (Agilent Technologies, Palo Alto, CA). Total RNA was amplified using the Agilent Low RNA Input Fluorescent Linear Amplification Kit protocol. Starting with 500ng of total RNA, Cy3 or Cy5 labeled cRNA was produced according to manufacturerâ??s protocol. For each two color comparison, 750ng of each Cy3 and Cy5 labeled cRNAs were mixed and fragmented using the Agilent In Situ Hybridization Kit protocol. In each case, samples from estradiol-treated animals were co-hybridized with the day 7 placebo sample. Due to the rapid increase in adiposity in the mammary fat pad in the ovariectomized placebo-treated mice in days 14 and 28, the day 7 placebo sample was used as a control for all estradiol treated samples to avoid any variation due to this biological difference. Hybridizations were performed for 17 hours in a rotating hybridization oven using the Agilent 60-mer oligo microarray processing protocol. Slides were washed as indicated in this protocol and then scanned with an Agilent Scanner. Data was obtained using the Agilent Feature Extraction software (v7.5), using defaults for all parameters. Experiment Overall Design: The Agilent Feature Extraction Software performed error modeling, adjusting for additive and multiplicative noise. The resulting data were processed using the Rosetta ResolverÂ® system (version 7.1) (Rosetta Biosoftware, Kirkland, WA).

Project description:One Âµg of total RNA from either an; individual rat or from a pooled sample was amplified and labeled with a; fluorescent dye (either Cy3 or Cy5) using the Low RNA Input Linear Amplification Labeling kit (Agilent Technologies, Palo Alto, CA) following the manufacturerâ??s protocol. The amount and quality of the resulting fluorescently labeled cRNA was assessed using a Nanodrop ND-100 spectrophometer and an Agilent; Bioanalyzer. Equal amounts of Cy3- or Cy5-labeled cRNA were hybridized to the Agilent Rat Oligo Microarray (Agilent Technologies, Inc., Palo Alto, CA) for 17 hrs, prior to washing and scanning. Data was extracted from the resulting; images using Agilentâ??s Feature Extraction Software (Agilent Technologies, Inc., Palo Alto, CA). For day/night comparisons, two types of complementing hybridizations were performed: hepatic RNA from individual day rats was hybridized against a pool made up of RNA from 12 hour offset night rats, and RNA from individual night rats was hybridized against a pool made up of RNA from 12-hour offset day rats. Specifically, hepatic RNA samples from three individual day rats collected ten hours after light on (CT10) were hybridized against a pooled RNA sample composed of equal aliquots of RNA from the livers of six night rats collected ten hrs after lights off (CT22); and RNA samples from three individual night rats collected at CT22 were hybridized against a pooled RNA sample composed of equal aliquots of RNA from the livers of six day rats collected at CT10. This was replicated in a second study for a total of 24 hybridizations of 12 hour offset samples. For time of day comparisons, equal aliquots of RNA from the livers of six; rats collected at each of four different times of the circadian day (CT4, CT10, C16 and CT22) were pooled. The two replicate studies thus resulted in 8 pools (two replicate pools/time point times four time points); each pool was hybridized against a Universal Rat Reference RNA Standard (Stratagene, La Jolla, CA).

Project description:TP53 mutations are a poor prognostic factor in breast cancers. This study sets out to identify the gene set that determine expression signature of the TP53 status (TP53 signature) and to correlate it with clinical outcome. Using comprehensive expression analysis and DNA sequencing of the TP53 gene in 38 Japanese breast cancer patients, we have isolated a gene set of 33 genes from differentially expressed genes in the learning set (n=26), depending on the TP53 status. Predictive accuracy of TP53 status by gene expression profile was 83.3% in the test set (n=12). As independent external datasets, two published datasets were introduced for validation of TP53 status prediction (251 Swedish samples) and survival analysis (both the Swedish and 295 Dutch samples). TP53 signature has the ability to predict recurrence-free survival (RFS) of 29 stage I and II Japanese breast cancers (log rank, P = 0.032), and RFS, overall survival of two independently published datasets (log rank, both P < 0.0001). Multivariate analysis has shown an independent and significant prognostic factor with a hazard ratio (HR) for recurrence and survival in two external datasets (P < 0.0001). The TP53 signature is also a strong prognostic factor in the subgroups: estrogen-receptor positive, lymph node (LN) positive and negative, intermediate/high risk in St. Gallen criteria, and high risk in National Cancer Institute (NCI) criteria (log rank, P < 0.0001). TP53 signature is a reliable and independent predictor of the outcome of disease in operated breast cancer. Experiment Overall Design: Microarray hybridizations (Agilent: Whole Human Genome Oligo Microarray; 41k unique probe) were carried out with 1Î¼g Cy3 labeled cRNA and 1 Î¼g Cy5 labeled cRNA, both prepared from each sample and reference pool, respectively. Experiment Overall Design: Fluorescent intensities of scanned images were quantified by ArrayVision Ver.8 rev.4 (Imaging research). Experiment Overall Design: The gene expression data was quantified and analyzed by GeneSpring 6.2 (Silicon Genetics). To identify the TP53 status predictor gene set, a Wilcoxon rank sum test along with Benjamini and Hochberg false discovery rate (FDR) was used.

Project description:Expression of CD40 in non-hematopoietic cells has been linked to inflammation. We presented evidence that CD40, a T-cell costimulatory molecule, is expressed in human Î²-cells and the engagement of CD40 in insulinoma cells activated the NFKB and ERK1/2 pathways. CD40 activation in human islets cells induced secretion of IL-8, MCP-1 and MIP-1 Î², which is abrogated by inhibitors of NFkB and ERK1/2 inhibitors. In this study, we have studied gene expression mediated by CD40-CD40L interaction in islet cells. This approach identified 90 genes and transcripts exhibiting at least a 1.7 fold increase in their expression intensity after treatment with soluble CD40L. A significant number of genes were related to inflammation and oxidative stress. We have a strong overexpression of CXCL1 (GroÎ±), CXCL2 (Mif2) and CXCL3; chemokines belonging to CXC family structurally related to Il-8. 11 genes were selected from this group and further quantified by Real Time PCR, including CXCL1. Activation of islet cells with CD40L induced the secretion of CXCL1 in a NFKB dependent manner. Engagement of CD40 in islet cells did not induce apoptosis, neither Î²-cell death and did not enhanced TNF-Î± mediated cell death as observed in insulinoma cells. CD40 activation in insulinoma cells, results in ERK1/2 dependent phsophorylation of synapsin I, a protein associated with the exocytosis machinery in neurons and Î²-cells. However, treatment of islets with soluble CD40L did not affect glucose induced insulin secretion. It has been reported that ductal cells always present in human islet preparations express CD40 constitutively (ref). We found that CD40-CD40L interaction in ductal cells, unlike in Î²-cells, induces secretion of diabetogenic cytokines IFNÎ³ and TNF-Î±. Furthermore, incubation of islets containing ductal cells with CD40L decreased Î²-cells viability as assessed by measurement of their mitochondrial membrane potential Experiment Overall Design: We isolated islet cells from three patients. Part of islet cells from each patient has been treated with CD40L. We compared gene expression in treated cells vs untreated for each patient using dye-swap.

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Transcription profiling of human embryonal carcinomas

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