Project description:This experiment contains a subset of data from the BLUEPRINT Epigenome project ( http://www.blueprint-epigenome.eu ), which aims at producing a reference haemopoetic epigenomes for the research community. 29 samples of primary cells or cultured primary cells of different haemopoeitc lineages from cord blood are included in this experiment. This ArrayExpress record contains only meta-data. Raw data files have been archived at the European Genome-Phenome Archive (EGA, www.ebi.ac.uk/ega) by the consortium, with restricted access to protect sample donors' identity. The relevant accessions of EGA data sets is EGAD00001001165. Details on how to apply for data access via the BLUEPRINT data access committee are on the EGA data set pages. The mapping of samples to these EGA accessions can be found in the 'Sample Data Relationship Format' file of this ArrayExpress record. Information on individual samples and sequencing libraries can also be found on the BLUEPRINT data coordination centre (DCC) website: http://dcc.blueprint-epigenome.eu
Project description:This experiment contains a subset of data from the BLUEPRINT Epigenome project ( http://www.blueprint-epigenome.eu ), which aims at producing a reference haemopoetic epigenomes for the research community. 4 samples of primary cells from tonsil with cell surface markes CD20med/CD38high in young individuals (3 to 10 years old) are included in this experiment. This ArrayExpress record contains only meta-data. Raw data files have been archived at the European Genome-Phenome Archive (EGA, www.ebi.ac.uk/ega) by the consortium, with restricted access to protect sample donors' identity. The relevant accessions of EGA data sets is EGAD00001001523. Details on how to apply for data access via the BLUEPRINT data access committee are on the EGA data set pages. The mapping of samples to these EGA accessions can be found in the 'Sample Data Relationship Format' file of this ArrayExpress record. Information on individual samples and sequencing libraries can also be found on the BLUEPRINT data coordination centre (DCC) website: http://dcc.blueprint-epigenome.eu
Project description:This experiment contains a subset of data from the BLUEPRINT Epigenome project ( http://www.blueprint-epigenome.eu ), which aims at producing a reference haemopoetic epigenomes for the research community. 74 samples of primary cells or cultured primary cells of different haemopoeitc lineages from cord blood, venous blood, bone marrow and thymus are included in this experiment. This ArrayExpress record contains only meta-data. Raw data files have been archived at the European Genome-Phenome Archive (EGA, www.ebi.ac.uk/ega) by the consortium, with restricted access to protect sample donors' identity. There are 32 EGA data set accessions, which can be found under the Comment[EGA_DATA_SET] column in the 'Sample Data Relationship Format' (SDRF) file of this ArrayExpress record (http://www.ebi.ac.uk/arrayexpress/files/E-MTAB-3827/E-MTAB-3827.sdrf.txt). Details on how to apply for data access via the BLUEPRINT data access committee are on the EGA data set pages. Likewise, mapping of samples to these EGA accessions can be found in the SDRF file. Please note that the raw data files for 11 sequencing runs have yet been deposited at EGA, so they are marked with \\ot available\\ under the Comment[SUBMITTED_FILE_NAME] field in the SDRF file, and were included for the sake of completeness. Further iInformation on individual samples and sequencing libraries can also be found on the BLUEPRINT data coordination centre (DCC) website: http://dcc.blueprint-epigenome.eu\
Project description:In this study, we investigated somatic mutations in T cells in patients with various hematological disorders. To analyze immune cell phenotypes with somatic mutations, we performed scRNA+TCRab sequencing from 9 patients with chronic GVHD and clonal expansions of CD4+ or CD8+ T cells based on T cell receptor sequencing. CD45+ PBMCs (lymphocytes and monocytes) were sorted with BD Influx cell sorter and subjected to sequencing with Chromium VDJ and Gene Expression platform (v1.1, 10X Genomics). Sequencing was performed with Novaseq 6000 (Illumina). The immune cell phenotypes were compared to healthy controls processed in the same laboratory (accession number E-MTAB-11170). Due to data privacy concerns, the raw sequencing data is in the European Genome-Phenome Archive (EGA) under accession code [xxxx] and can be requested through the EGA Data Access Committee.
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:Aberrant expression of microRNA (miRNA) has been reported in various cancers. To clarify the role of miRNA in gastric carcinogenesis, we performed miRNA microarray analysis and investigated expressional changes of miRNAs in a 5-aza-2'-deoxycytidine (DAC)-treated gastric cancer cell line, KATO-ІІІ.
Project description:DAC represents a therapeutic option for elderly AML patients. However, there is still a lack of data for valid biomarkers in respect to response. We executed a gene expression analysis prior to treatment to evaluate gene expression patterns associated with response that might be used to predict DAC therapy outcome. In our cohort an objective ORR of 27% was seen. In a class comparison analysis 333 genes were identified that correlated significantly with response. In this gene signature genes that were prior associated with adverse outcome to regular chemotherapy were enriched in the response group. Interistingly for the non response cohort TSG showed an increased expression, suggesting that epigenetic silencing due to promoter hypermethylation might play a lesser role in theses leukemia pathogenesis.
Project description:We observed gene expression difference between different groups after MDA-MB-231 treated with DMSO, 10 μM DAC, 1 μM DEX, or DAC+DEX. Data obtained from high-throughput sequencing (Illumina NovaSeq 6000 platform) were transformed into raw sequenced reads by CASAVA base calling and stored in FASTQ format. Gene expression of each groups are listed in raw data files. Some different expression genes between two groups are further validated with qRT-PCR.