Application of MeTA-array to nine pancreatic cancer cell lines
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PROVIDER: PRJNA592954 | ENA |
REPOSITORIES: ENA
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Project description:Aberrant DNA hypermethylation, the most well defined epigenetic changes in cancer, is associated with inappropriate gene silencing and this feature is utilized to search for tumor-specific DNA methylation biomarkers. Methyl-CpG binding domain (MBD) proteins (MBPs) can elicit the repressive potential of methylated DNA and play a major role in gene silencing mechanisms. Therefore, if the genes governed by MBPs are specifically reactivated, it should be possible to uncover them. We developed a method termed “methyl-CpG targeted transcriptional activation (MeTA)” that employs a fusion gene comprised of the MBD from MBD2 and the NFkB transcriptional activation domain. Microarray coupled with MeTA (MeTA-array) provides not only the information about methylated genes but also the one about transcriptional repression in a single experiment. We applied MeTA-array to 12 pancreatic cancer cell lines along with HPDE (normal pancreatic ductal epithelial cell line) and identified 31 candidate tumor-specific hypermethylated genes; 26 of them have never been reported previously using the conventional DNA demethylating agents. Seven genes, IRX4, LHX6, NEFH, NEFL, NEFM, NPTX2 and TMEM204 were further examined their methylation statuses by MSP, and we found that 100% (21/21) of IRX4, 62% (13/21) of LHX6, 100% (21/21) of NEFH, 100% (21/21) of NEFL, 100% (21/21) of NEFM, 100% (21/21) of NPTX2 and 95% (20/21) of TMEM204 were methylated in our series of pancreatic cancer cell lines. Furthermore, 68% (15/22) of IRX4, 55% (12/22) of LHX6, 55% (12/22) of NEFH, 59% (23/22) of NEFL, 82% (18/22) of NEFM and 82% (18/22) of NPTX2 were also hypermethylated in primary pancreatic cancer specimens in a tumor-specific manner. Our results suggest that MeTA-array is a highly efficient method to identify methylation-mediated transcriptionally silenced genes in human cancer.
2020-10-11 | GSE141247 | GEO
Project description:RNAseq-based comparison of basal expression profiles of nine different pancreatic cancer cell lines
2020-10-30 | GSE160434 | GEO
Project description:Basal expression of nine pancreatic cancer cell lines
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Project description:Identification and characterization of epigenetically silenced genes is very important for cancer research. Particularly, information of hypermethylated genes provides clues to understand roles of epigenetics in tumorigeneses, and genes frequently methylated in a tumor-specific manner can be used as tumor markers. DNA methylation inhibitors such as 5-aza-cytidine or 5-aza-2’-deoxycytidine were widely used to search epigenetically silenced genes. However, these inhibitors frequently upregulate genes whose promoters remain unmethylated. We tried to improve the specificity and sensitivity in detecting such methylation-mediated silenced genes in cancer and successfully developed a new method termed “methyl-CpG targeted transcriptional activation (MeTA)” by using a transcriptional activating fragment with a methyl-CpG binding domain (MBD) that specifically recognizes and binds to methylated DNAs. Because MBD proteins in fact mediate transcriptional repression of tumor suppressor genes associated with promoter hypermethylation in cancer, MeTA is thought to be one of the ideal methods to search such genes. In the present study, we applied this method to three representative pancreatic cancer cell lines, AsPC-1, MIA PaCa-2, and PANC-1, with a normal pancreatic ductal epithelial cell line HPDE (as the control). All of these cell lines have already been analyzed their expression profiles by 5-aza-2’-deoxycytidine. We first analyzed the expression of five genes by RT-PCR with Southern hybridization, NEFH, NPTX2, SFRP1, TIMP3, and UCHL1; these genes are known to be methylated in at least any one of these cancer cell lines. Upregulation by “MeTA” was confirmed in all of these genes. Then we searched for upregulated-genes, by two-folds or more, in all the three cancer cell lines after MeTA; nineteen such upregulated genes were identified. Among these, sixteen genes except NEFH, HOXA9, and CLDN5 have not been reported previously using the conventional DNA methylation inhibitors. Methylation status of two genes, SLC32A1 and CSMD2, were further analyzed by methylation-specific PCR and found that SLC32A1 and CSMD2 were methylated in 100% (21/21) and 83% (15/18) pancreatic cancer cell lines analyzed, respectively. Our results suggest that “MeTA” is a highly efficient method to isolate methylation-mediated transcriptionally silenced genes in human pancreatic cancer and that this method can be applied to other types of human cancer.
2012-12-11 | GSE26215 | GEO
Project description:We present a meta-dataset comprising of a total of 178 samples including both primary tumors and tumor-free pancreatic tissues from four independent GEO datasets. To minimise inter-platform variation, only datasets generated from the GPL570 platform (Affymetrix Human Genome U133 Plus 2.0 Array) were processed to develop the meta-dataset. Using multiple open source R packages implemented in our previously developed bioinformatics pipeline, each dataset has been preprocessed with RMA normalisation, merged, and batch effect-corrected via Combat method. With increased sample size, the present meta-dataset serves an excellent 'discovery cohort' for discovering differentially expressed in diseased phenotype.
2019-04-11 | E-MTAB-6690 | biostudies-arrayexpress
Project description:Identification and characterization of epigenetically silenced genes is very important for cancer research. Particularly, information of hypermethylated genes provides clues to understand roles of epigenetics in tumorigeneses, and genes frequently methylated in a tumor-specific manner can be used as tumor markers. DNA methylation inhibitors such as 5-aza-cytidine or 5-aza-2M-bM-^@M-^Y-deoxycytidine were widely used to search epigenetically silenced genes. However, these inhibitors frequently upregulate genes whose promoters remain unmethylated. We tried to improve the specificity and sensitivity in detecting such methylation-mediated silenced genes in cancer and successfully developed a new method termed M-bM-^@M-^\methyl-CpG targeted transcriptional activation (MeTA)M-bM-^@M-^] by using a transcriptional activating fragment with a methyl-CpG binding domain (MBD) that specifically recognizes and binds to methylated DNAs. Because MBD proteins in fact mediate transcriptional repression of tumor suppressor genes associated with promoter hypermethylation in cancer, MeTA is thought to be one of the ideal methods to search such genes. In the present study, we applied this method to three representative pancreatic cancer cell lines, AsPC-1, MIA PaCa-2, and PANC-1, with a normal pancreatic ductal epithelial cell line HPDE (as the control). All of these cell lines have already been analyzed their expression profiles by 5-aza-2M-bM-^@M-^Y-deoxycytidine. We first analyzed the expression of five genes by RT-PCR with Southern hybridization, NEFH, NPTX2, SFRP1, TIMP3, and UCHL1; these genes are known to be methylated in at least any one of these cancer cell lines. Upregulation by M-bM-^@M-^\MeTAM-bM-^@M-^] was confirmed in all of these genes. Then we searched for upregulated-genes, by two-folds or more, in all the three cancer cell lines after MeTA; nineteen such upregulated genes were identified. Among these, sixteen genes except NEFH, HOXA9, and CLDN5 have not been reported previously using the conventional DNA methylation inhibitors. Methylation status of two genes, SLC32A1 and CSMD2, were further analyzed by methylation-specific PCR and found that SLC32A1 and CSMD2 were methylated in 100% (21/21) and 83% (15/18) pancreatic cancer cell lines analyzed, respectively. Our results suggest that M-bM-^@M-^\MeTAM-bM-^@M-^] is a highly efficient method to isolate methylation-mediated transcriptionally silenced genes in human pancreatic cancer and that this method can be applied to other types of human cancer. Three representative pancreatic cancer cell lines, AsPC-1, MIA PaCa-2, and PANC-1, with a normal pancreatic ductal epithelial cell line HPDE (as the control) were transfected with pcDNA6/myc-His vector or pcDNA6-3xFLAG-NFkB (AD)-MBD and were harvested 48 h after transfection.
2012-12-11 | E-GEOD-26215 | biostudies-arrayexpress
Project description:We used microarrays to detail the hypoxic gene expression profile in human pancreatic cancer cells
2016-12-01 | GSE67549 | GEO
Project description:A series of studies have been published that evaluate the chromosomal copy number changes of different tumor classes using array Comparative Genomic Hybridization (array CGH), however the chromosomal aberrations that distinguish the different tumor classes have not been fully characterized. Therefore, we performed a meta-analysis of different array CGH data sets in an attempt to classify samples tested across different platforms. As opposed to RNA expression a common reference is used in dual channel CGH arrays: normal human DNA, theoretically facilitating cross-platform analysis. To this aim, cell line and primary cancer data sets from three different dual channel array CGH platforms obtained by four different institutes were integrated. The cell line data were used to develop preprocessing methods which performed noise reduction and transformed samples into a common format. The transformed array CGH profiles allowed perfect clustering by cell line, but importantly not by platform or institute. The same preprocessing procedures used for the cell line data were applied to data from 373 primary tumors profiled by array CGH, including controls. Results indicated that there is no apparent feature related to the institute or platform and that array CGH allows for unambiguous cross-platform meta-analysis. Major clusters with common tissue origin were identified. Interestingly, tumors of hematopoietic and mesenchymal origins cluster separately from tumors of epithelial origin. Therefore it can be concluded that chromosomal aberrations of tumors from hematopoietic and mesenchymal origin versus tumors of epithelial origin are distinct, and these differences can be picked up by metaanalysis of array CGH data. This suggests the possibility of prospectively using combined analysis of diverse copy number datasets for cancer subtype classification. Keywords: comparative genomic hybridization, meta-analysis, cancer
2006-08-29 | GSE5051 | GEO