Project description:Illumina human Omni5Exome arrays were used to investigate CNVs in Sѐzary syndrome tumours as part of a larger study involving whole exome sequencing of the same samples and targeted resequencing of a further cohort.
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 Raw data files have been archived at the European Genome-Phenome Archive (EGA, www.ebi.ac.uk/ega) by the consortium, with restricted access to protect sample donors' identity.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:Illumina human Omni5Exome arrays were used to investigate CNVs in SÑzary syndrome tumours as part of a larger study involving whole exome sequencing of the same samples and targeted resequencing of a further cohort. 16 Samples underwent SNP array including 10 tumour/gDNA matched samples that also underwent whole exome sequencing, public databases were used as further control data for calling CNVs.
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.
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:Canine mammary gland tumors (CMTs) have been suggested as promising cancer models to human breast cancer due to their many biological and clinical similarities. Here, we collected 222 samples consist of 158 tumor samples and 64 matched normal samples of CMTs. Fresh tissue samples were transferred in to RNAlater, and refrigerated overnight at 4°C and then stored at -80°C. Total RNA was extracted from tissues using RNeasy mini kit. We aligned RNA-Seq raw data from 222 samples to canine reference genome CanFam3.1 using Tophat. We assembled transcript and calculated FPKM values using Cufflinks. All tumor samples were evaluated by histopathological characteristics including histopathological subtype, grade, and lymphatic invasion, and annotated with corresponding sequencing data. The histopathological classification and the histological grading system of CMTs were adopted from those of human breast cancer. In addition, immunohistochemical evaluation was performed in samples for estrogen receptor (ER) and human epidermal growth factor receptor 2 (HER2) status. DISCLAIMER: Using this dataset became freely available on Jul 22, 2019. On the other hand, we are now preparing a key paper about comparative analysis of canine and human breast cancer based on this dataset. If you plan to submit a similar paper using this dataset before the main paper is published, please feel free to contact the submitter (swkim@yuhs.ac) to coordinate submission.