Project description:Cancer cell lines can provide robust and facile biological models for the generation and testing of hypothesis in the early stages of drug development and caner biology. Although clinical trials remain the ultimate scientific testing ground for anticancer therapies, the use of appropriate model systems to explore the molecular basis of drug activity and to identify predictive biomarkers during their development can have a profound effect on the design, cost and ultimate success of new cancer drug development. In order to capture the high degree of genomic diversity in cancer and to identify rare molecular subtypes, we have assembled a collection of >1000 cancer cell lines. These lines have been characterised using whole exome sequencing, genome wide analysis of copy number, mRNA gene expression profiling and DNA methylation analysis (http://cancer.sanger.ac.uk/cell_lines). To further characterise this panel of cell lines we have now compiled data for RNA sequencing. The current study represent data for ~450 of the cell lines in the panel, data for the remaining lines can be accessed via the CGHUB data browser hosted at UCSC. <br>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 Raw data files have been archived at the European Genome-Phenome Archive (EGA, www.ebi.ac.uk/ega) by the consortium, with restricted access to protect sample donors' identity.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 the EGA data set is EGAD00001001357 under EGA study accession EGAS00001000828.
Project description:Embryonic genome activation (EGA), a pivotal transcriptional event during preimplantation development, is accompanied by post-transcriptional regulation of maternal mRNAs. Disentangling the transcriptional output of the newly activated embryonic genome from concomitant post-transcriptional processing is important for decoding EGA dynamics.Here, using optimized low-input SLAM-seq (thiol(SH)-linked alkylation for the metabolic sequencing) in mouse embryos, we delineates the temporal hierarchy of EGA nascent transcription during mouse preimplantation embryogenesis and uncovers a mechanistic link between EGA and the first lineage specification, providing new insights into the regulatory architecture of early mammalian development.
2026-01-01 | GSE297541 | GEO
Project description:Exome Sequencing of Osteosarcoma
Project description:This dataset contains processed RNA sequencing expression matrices derived from osteosarcoma patient samples. A total of 40 clinical specimens were analyzed, including 30 primary osteosarcoma tumor tissues and 10 non-sarcoma tissues. Raw sequencing data were preprocessed to generate normalized gene expression matrices suitable for downstream bioinformatic analyses, such as differential expression and pathway enrichment studies.
Project description:CTCF ChIP-seq of 39 primary samples derived from human acute leukemias, namely AML, T-ALL and mixed myeloid/lymphoid leukemias with CpG Island Methylator Phenotype (CIMP). Due to patient confidentiality considerations, the raw data files for this dataset have been deposited to the EGA controlled-access archive under the accession numbers EGAS00001007094 (study); EGAD00001011059 (dataset).
Project description:This study involves characterization of four head and neck cancer cell lines -- NT8e, OT9, AW13516 and AW8507, established from Indian head and neck cancer patients, using SNP arrays, whole exome and whole transcriptome sequencing.