Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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Convergence of Mutation and Epigenetic Alterations Identifies Common Target Genes in Breast and Colon Cancer

ABSTRACT: 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.

ORGANISM(S): Homo sapiens

SUBMITTER: Leander Van Neste

PROVIDER: E-GEOD-10613 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Convergence of mutation and epigenetic alterations identifies common genes in cancer that predict for poor prognosis.

Chan Timothy A TA Glockner Sabine S Yi Joo Mi JM Chen Wei W Van Neste Leander L Cope Leslie L Herman James G JG Velculescu Victor V Schuebel Kornel E KE Ahuja Nita N Baylin Stephen B SB

PLoS medicine 20080501 5

<h4>Background</h4>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 w ...[more]

PMID: 18507500

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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:Reversal of gene promoter DNA hypermethylation and associated abnormal gene silencing is an attractive approach to cancer therapy. The DNA methylation inhibitor, decitabine (5-aza-2'-deoxycitidine), is proving efficacious for hematological neoplasms especially at lower, less toxic, doses. Experimentally, high doses induce rapid DNA damage and cytotoxicity, but these may not explain the prolonged time to response seen in patients. Transient exposure of leukemic and solid tumor cells to clinically-relevant nanomolar doses, without causing immediate cytotoxicity or apoptosis, produces sustained reduced tumorigenicity, and for leukemia cells, diminished long-term self-renewal. These effects appear triggered by cellular reprogramming and include sustained decreases in promoter DNA methylation with associated gene re-expression, and anti-tumor changes in multiple key cellular regulatory pathways, most of which are high priority targets for pharmacologic anti-cancer strategies. Thus, low dose decitabine regimens appear to have broad applicability for cancer management. [Gene expression profiling] Leukemia cell lines Kasumi-1 and KG1A are treated with 10nM DAC during 72 hours and gene expression was assayed at day 3, 7 and 14 after the start of the treatment. Appropriate mock treated samples were used as control in each case. In addition, Kasumi-1 cells were also treated with a higher dose of DAC (500nM), 100nM ARA-C and 300 nM TSA, again controlled against mock treated Kasumi-1 cells, to separate dose and agent dependent effects. MCF7 was studied as an example of a solid tumor cell line. Therefore MCF7 cells were treated with 100nM DAC and results were assayed at day 1, day 3 and day 10. [Methylation profiling] The effects of the demethylating agent DAC were studied in the leukemia cell line Kasumi-1 over a 28 day time course. Intermediate time points were studied at days 3, 7, 14 and 21. These results were verfied in KG1A and KG1 leukemia cell lines, at one selected time point. The effects on one primary sample were also studied. Four normal leukemia samples (PL1, 2, 4 and 5) were used as general controls. The effect of DAC was compared to ARA-C, TSA. Both mock treated and day 3 DAC treated Kasumi-1 cells were repeated. These results were verified at one selected time point for the DAC treated MCF7 breast cancer cell line.

Project description:Once thought to be transcriptional noise, large non-coding RNAs (lncRNAs) have recently been demonstrated to be functional molecules. Cell type-specific expression patterns of lncRNAs suggest that their transcription may be regulated epigenetically. Using a custom-designed microarray, here we examine the expression profile of lncRNAs in embryonic stem (ES) cells, lineage-restricted neuronal progenitor cells (NPC), and terminally differentiated fibroblasts. In addition, we also analyze the relationship between their expression and their promoter H3K4 and H3K27 methylation patterns. We find that numerous lncRNAs in these cell types undergo changes in the levels of expression and promoter H3K4me3 and H3K27me3. Interestingly, lncRNAs that are expressed at lower levels in ES cells exhibit higher levels of H3K27me3 at their promoters. Consistent with this result, knockdown of the H3K27me3 methyltransferase Ezh2 results in derepression of these lncRNAs in ES cells. Thus, our results establish a role for Ezh2-mediated H3K27 methylation in lncRNA silencing in ES cells and reveal that lncRNAs are subject to epigenetic regulation in a similar manner to that of protein-coding genes. lncRNA expression analysis was performed in 5 different cell types: (1) ES cells, (2) neuroprogenitors, (3) tail tip fibroblasts, (4) Ezh2 knockdown #1 ES cells, and (5) Ezh2 knockdown #2 ES cells. Total RNA was extracted and RNA quality was assessed via Agilent Bioanlayzer. mRNA was amplified using the Low RNA Linear Amplification Kit (Agilent Technologies) by standard manufacturer's protocol. Hybridization of experimental RNA labeled with Cy5 and Cy3-labeled Universal Reference RNA (Ambion) was carried out by standard protocol on a custom-designed array manufactured by Agilent Technologies. Briefly, three unique 60nt probes were designed for each entry in the Fantom3 database and were synthesized along with lineage marker control probes on a 2x105K format array. Upon array scanning, data was quality filtered, normalized by the Lowess method, and all probes corresponding to a given lncRNA were averaged using the UNC Microarray Database (UNCMD). Intraclass correlation analysis was carried out in the UNCMD.

Dataset Information

Convergence of Mutation and Epigenetic Alterations Identifies Common Target Genes in Breast and Colon Cancer

Publications

Convergence of mutation and epigenetic alterations identifies common genes in cancer that predict for poor prognosis.

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