Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

RNAi knock down of NIPP1 and EZH2 in human prostate cell line PC-3 to investigate whether they regulate a common set of genes

ABSTRACT: NIPP1 and EZH2 contribute to the silencing of a common set of genes. Since both NIPP1 and EZH2 turned out to be essential for the initiation and maintenance of global H3K27 trimethylation, a key step in the PcG-mediated transcriptional regulation of genes, we have subsequently examined by DNA-microarray analyses whether the loss of NIPP1 or EZH2 results in the expected regulation of a common set of genes.

PC-3 cells were transfected in four independent experiments with a control siRNA or siRNA duplexes for the knockdown of EZH2 or NIPP1. To minimize indirect effects, RNA was already isolated 48h after transfection. At this time, the knockdown of NIPP1 or EZH2 was verified by quantitative qRT-PCR and amounted to 73 ± 7% and 82 ± 3% (n = 4), respectively. The isolated RNA pools were labeled with a fluorescent dye and were hybridized onto whole human genome Agilent gene chips. These chips contained 44,000 60-mer oligonucleotides, corresponding to ca 27,000 unambiguously annotated genes. Using SAM (significance analysis of microarray) analysis (P < 0.05), performed by comparing the NIPP1 or EZH2 knockdown against RNAi control, we selected 1581 and 2024 genes as significant in the NIPP1 or EZH2 knockdown, respectively. Using p<0.01, the loss of NIPP1 or EZH2 resulted in a significant upregulation of 281 genes and 319 genes, respectively, and downregulation of 409 and 175 genes respectively ). The knockdown of NIPP1 or EZH2 was confirmed in the microarray and the results of the expression array data were confirmed by qRT-PCR on a selection of affected genes, representing the entire range of fold-changes and using samples independent of those used for the microarray analysis.

Strikingly, the list of the 50 genes that were most upregulated (SAM test, p<0.01) by the knockdown of NIPP1 were, in most cases, also upregulated following the knockdown of EZH2. In contrast, there was no obvious correlation between the 50 genes that were most downregulated after the knockdown of NIPP1 or EZH2. More detailed analysis revealed that 43% (121 genes) of the genes that were upregulated after the knockdown of NIPP1 were also upregulated by the loss of EZH2. In contrast, only 6% (25 genes) of the genes that were downregulated by the knockdown of NIPP1 were also downregulated by the loss of EZH2. Using another approach and using the list of significant genes based upon SAM test and p<0.05, we noted a significant linear correlation (R= 0.59 ± 0.01) between the extent to which genes were significantly upregulated by the loss of NIPP1 and the changes in the expression of these same genes following the knockdown of EZH2. No such correlation (R= 0.01 ± 0.01) was obtained for genes that were significantly downregulated. In the residual plot of these regressions, an obvious bend became apparent between the up and downregulated genes of the NIPP1 knockdown, confirming that we are in fact dealing with two differently regulated subpopulations. To validate this subdivision, the microarray data for a knockdown of EZH2, EED or SUZ12 which represent the core of the PRC2 complex, recently published by Bracken et al. ( 2006 ), were identically analyzed. In the residual plots, a bend between the up and downregulated genes was consistently present. We can conclude from our microarray data that NIPP1 silence a same set of genes as EZH2 and that NIPP1 also act as a transcriptional activator independent of EZH2.

ORGANISM(S): Homo sapiens

SUBMITTER: Aleyde Van Eynde

PROVIDER: E-TABM-128 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Similar Datasets

Project description:Silencing of tumor suppressor genes plays a vital role in head and neck carcinogenesis. Aberrant hypermethylation in the promoter region of some known or putative tumor suppressor genes (TSGs) occurs frequently during the development of various cancers including head and neck squamous cell carcinoma (HNSCC). In this study we used an expanded mRNA expression profiling approach followed by microarray expression analysis to identify epigenetically inactivated genes in HNSCC. Two HNSCC cell lines were treated with 5-aza-2M-bM-^@M-^Y-deoxycytidine followed by microarray analysis to identify epigenetically silenced genes in HNSCC. 1960, 614, and 427 genes were upregulated in HNSCC cell lines JHU-012, JHU-011 and the combination of both cell lines, respectively. HNSCC tumor and normal mucosal samples were used for gene profiling by a 47K mRNA gene expression array and we found, 7140 genes were downregulated in HNSCC tumors compared to normal mucosa as determined by microarray analysis and were integrated with cell line data. Integrative analysis defined 126 candidate genes, of which only seven genes showed differentially methylation in tumors and no methylation in normal mucosa after bisulfite sequencing. After validation by QMSP, one gene, GNG7, was confirmed as being highly methylated in tumors and unmethylated in normal mucosal and salivary rinse samples demonstrating cancer-specific methylation in HNSCC tissues. TXNIP and TUSC2 were partially methylated in tumors and normal salivary rinses but unmethylated in normal mucosa. We concluded GNG7 as a highly specific promoter methylated gene associated with HNSCC. In addition, TXNIP and TUSC2 are also potential biomarkers for HNSCC. We performed pharmacological unmasking analysis on two HNSCC cancer cell lines JHU-O11 and JHU-O12 by treating cells with or without 5-aza-dC, followed by RNA extraction and microarray analysis using Affymetrix U133 Plus 2.0. The array data were analyzed by initially dChip and then SAM. We performed a four-phase strategy to obtain the unmasked genes in the cells treated with 5-aza and downregulated genes in primary tumors. In the first phase, we compared the cell lines, either JHU-012 or JHU-011, before treatment to the cell lines treated with 5-aza, in order to identify genes that were reexpressed M-bM-^IM-% 2 fold. We found 1960 genes that were upregulated by 5-aza-dC in JHU-O12 cell line. SAM output was obtained at a delta value of 2.05 with a false discovery rate (FDR) of 10% and the d-score cut-off was 1.17. 614 reexpressed genes were found in 5 aza-treated JHU-O11 (SAM output; delta: 2.089, FDR%: 10, d-score cut-off: 2.8). 427 genes were commonly upregulated in both cell lines when the cell lines were normalized and analyzed together (SAM output; delta: 1.44, FDR%: 10, d-score cut-off: 1.88). In the second phase of our analysis, we further extracted RNA and performed the 47K mRNA expression array analysis on 13 primary HNSCC tumors samples and 5 normal mucosa samples from non-cancer control patients. After initial dChip and SAM analysis (SAM output; delta: 1.247, FDR%: 5.24, d-score cut-off:0.24), we found 7140 downregulated genes in primary HNSCC tumors compared with normal mucosa. In the third phase, we investigated these three data sets: a) SAM output of 1960 upregulated genes after 5-aza treatment of JHU-012 vs SAM output of 7140 downregulated genes in primary HNSCC: We found that 210 genes that were upregulated by 5-aza-dC in the JHU-O12 cell line and showed downregulation in tumor samples, b) SAM output of 614 upregulated genes after 5-aza treatment of JHU-011 vs SAM output of 7140 downregulated genes in primary HNSCC: We found 79 genes that were upregulated by 5-aza-dC in the JHU-O11 cell line and showed downregulation in tumor samples, c) SAM output from analyzing both cell lines together in the same SAM computation, of 427 upregulated genes after 5-aza treatment of JHU-011 and JHU-012 vs SAM output of 7140 downregulated genes in primary HNSCC: We found 44 genes that were upregulated by 5-aza-dC in JHU-O11 and JHU-012 cell lines and showed downregulation in tumor samples, suggesting that methylation might be involved in gene downregulation. In the fourth phase of our strategy, we rank-ordered the results of upregulated genes obtained from these 3 data sets and found 126 common genes. We then examined promoter regions of the 126 genes for CpG islands and performed bisulfite sequencing analysis of the promoter region of these genes. We found that 7 genes showed a differential methylation pattern between normal and neoplastic samples. After validation of these genes in a cohort of 33 HNSCC patients and normal salivary and mucosal samples from healthy people by QMSP, we found 3 genes of interest.

Project description:NIPP1, an established interactor of protein phosphatase 1 (PP1), is implicated in PRC2-mediated regulation of gene expression. Here, we explore whether PP1 associated with NIPP1 is involved in NIPP1-mediated regulation of genes. Therefore, we generated Hela Tet-off (HTO) cell lines that stably and inducibly express a Flag-tagged version of wild-type NIPP1 (HTO-NIPP1wt) or mutant NIPP1 (HTO_NIPP1m). The latter mutant lacks the major PP1 binding site by two point mutations in the RVXF-motif, an established PP1 - binding motif. All cell lines were derived from the same parental HeLa Tet-Off (HTO-PT) cell line which expresses only tTA transactivator and is used as a control. The Flag fusions were only expressed in the absence of doxycyline and at levels that were up to twofold higher than that of endogenous NIPP1. We performed a gene expression profiling of the HTO cell lines, using Whole Human Genome Oligo microarrays from Agilent. A Paired SAM analysis identified 1365 genes with an altered expression (P < 0.01) between the Flag-NIPP1 and parental cell lines. Importantly, only 185 genes were differentially expressed (P<0.01) between the Flag-NIPP1m and parental cell lines. Even more strikingly, only 5% of the genes that were affected by the expression of Flag-NIPP1 also showed a significantly different expression in the Flag-NIPP1m cells. A similar small overlap was noted when the analysis was restricted to the 50 genes that were most upregulated or downregulated by the expression of Flag-NIPP1. Finally, scatter plot analysis revealed no significant correlation between the genes that were affected by the expression of Flag-NIPP1 or Flag-NIPP1m. Collectively, these data demonstrate that a moderate increase in the concentration of NIPP1 affects the expression of numerous genes by a mechanism that depends on associated PP1. In total 12 samples were processed. Three different cell lines were analysed: HTO_parental, HTO_NIPP1wt and HTO_NIPP1m. For each cell line 4 replicates were obtained. The HTO_parental cell line is the control cell line. For the HTO_NIPP1wt the 4 replicates were obtained from two replicates of two different transgenic cell lines expressing FlagNIPP1wt (cell line wt n°1 and 2). Each cell line derived from the same parental control cell line.

Dataset Information

RNAi knock down of NIPP1 and EZH2 in human prostate cell line PC-3 to investigate whether they regulate a common set of genes

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets