Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Transcription profiling of human CT116 cells and isogenic genetic knockouts rveals identity of the human cancer cell DNA hypermethylome

ABSTRACT: 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.

ORGANISM(S): Homo sapiens

SUBMITTER: Wayne Yu

PROVIDER: E-GEOD-4763 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Comparing the DNA hypermethylome with gene mutations in human colorectal cancer.

Schuebel Kornel E KE Chen Wei W Cope Leslie L Glöckner Sabine C SC Suzuki Hiromu H Yi Joo-Mi JM Chan Timothy A TA Van Neste Leander L Van Criekinge Wim W van den Bosch Sandra S van Engeland Manon M Ting Angela H AH Jair Kamwing K Yu Wayne W Toyota Minoru M Imai Kohzoh K Ahuja Nita N Herman James G JG Baylin Stephen B SB

PLoS genetics 20070731 9

We have developed a transcriptome-wide approach to identify genes affected by promoter CpG island DNA hypermethylation and transcriptional silencing in colorectal cancer. By screening cell lines and validating tumor-specific hypermethylation in a panel of primary human colorectal cancer samples, we estimate that nearly 5% or more of all known genes may be promoter methylated in an individual tumor. When directly compared to gene mutations, we find larger numbers of genes hypermethylated in indiv ...[more]

PMID: 17892325

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Project description: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.

Project description:The identification and characterization of tumor suppressor genes has enhanced our understanding of the biology of cancer and enabled the development of new diagnostic and therapeutic modalities. Whereas in past decades, a handful of tumor suppressors have been slowly identified using techniques such as linkage analysis, large-scale sequencing of the cancer genome has enabled the rapid identification of a large number of genes that are mutated in cancer. However, determining which of these many genes play key roles in cancer development has proven challenging. Specifically, recent sequencing of human breast and colon cancers has revealed a large number of somatic gene mutations, but virtually all are heterozygous, occur at low frequency, and are tumor-type specific. Keywords: Microarray, Hypermethylome, DNA-hypermethylation, DAC, TSA, Epigenetic, Mutation, Colorectal Cancer, Breast Cancer The candidate hypermethylome genes were identified as described below. These genes were compared to the CAN genes identified by Sjöblom T et al (Science, 2006). Cell culture and treatment. For drug treatments, log phase MCF7, T-47D, MDA-MB231 and MDA-MB-468 cells were cultured in McCoys 5A media (Invitrogen) containing 10% BCS and 1x penicillin/streptomycin with 5M 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. 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. 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 platform and packages from Bioconductor bioinformatics software project. The log ratio of red signal to green signal was calculated and Loess normalization as implemented in the limma package from Bioconductor.

Project description:Transcriptional profiling of MSC, Osteoblasts and U2OS cells. The aim was to quantitate relative gene expression in MSC, osteoblasts and U2OS. MSC and osteoblasts were used as normal cells in this study because osteosarcoma most likely originates from MSC or osteoblasts. Cell culture and treatment: U2OS cells were cultured in McCoys 5A media (Invitrogen) containing 10% FBS. MSC and osteoblasts were cultured as described by Jaiswal et al. (J Cell Biochem 64, 295-312; 1997). Cells were treated with 5 uM 5-Azadeoxycytidine (5-Aza-CdR) or 300 nM Trischostatin-A (TSA) for 96 hours or 18 hours, respectively. Microarray analysis: Total RNA was extracted using the Qiagen kit according to the manufacturer's instructions, including a DNase step. RNA was quantified using the NanoDrop ND-100, followed by quality assessment with the 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 manufacturer's instructions. The labeled cRNA was purified using the RNeasy mini kit (Qiagen) and quantified. RNA spike-in controls (Agilent Technologies) were added to the 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 Scanner G2505B under the default settings recommended by Agilent Technologies. Data analysis: All arrays were subject to the 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 platform and packages from the Bioconductor bioinformatics software project. To determine the expression levels of genes in MSC, Osteoblasts and U2OS, the data were LOWESS-normalized, the probe intensities of the mock channel (no drug treatment) were extracted and set to the same scale by quantile normalization. Mean of replicate samples were calculated for each probe.

Dataset Information

Transcription profiling of human CT116 cells and isogenic genetic knockouts rveals identity of the human cancer cell DNA hypermethylome

Publications

Comparing the DNA hypermethylome with gene mutations in human colorectal cancer.

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