8431 results for "canc*"

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• Use of Deep Sequencing to Dectect Clonal Mutations In Sun Exposed Skin Epidermis

  This study aims to define the landscape of somatic mutations in sun exposed human skin by deep sequencing, analyse their frequency and use the data to infer the effect of mutations on proliferating cell behaviour. The frequency of each mutation will reflect the size of the clone of cells in the tissue sample. By analyzing small samples, clones with as few as 100 cells will be detectable. Allele frequency distributions for each mutation will be used to infer cell fate using published methods (Klein et al. 2010). This study will shed unprecedented light on the early clonal events that lead to the emergence of cancer.

  Dataset EGAD00001001090

• Cancer-associated genome-wide hypomethylation and copy number aberrations

  Noninvasive detection of cancer-associated genome-wide hypomethylation and copy number aberrations by plasma DNA bisulfite sequencing

  Dataset EGAD00001001093

• Batches 1-3 prostatectomy analysis

  Whole Genome Sequencing Illumina HiSeq data from 95 men with prostate cancer. Samples were taken from primary tissue obtained at prostatectomy (target sequencing depth 50X) with matched blood control (target sequencing depth 30X). This data is from batches 1 to 3 and is the bulk of the data used in Wedge et al, Nature Genetics 2018 (PMID: 29662167). As of September 2020, some of the studies using these data include: Wedge et al, Nature Genetics 2018 (PMID: 29662167) Pan-Cancer Analysis of Whole Genomes, Nature 2020 (PMID: 32025007)

  Dataset EGAD00001001116

• WGS and WES of 78 pairs Chinese gastric cancer

  Gastric Cancer (GC) is a highly heterogeneous disease. To identify potential clinically actionable therapeutic targets that may inform individualized treatment strategies, we performed whole-exome sequencing on 78 GCs of differing histologies and anatomic locations, as well as whole-genome sequencing on two GC cases, each with 3 primary tumours and 2 matching lymph node metastases. The data showed two distinct GC subtypes with either high-clonality (HiC) or low-clonality (LoC).

  Dataset EGAD00001001118

• FFPE Normal Panel V3 Cancer Panel

  FFPE normal panel generation for use with V3 cancer panel 0618521

  Dataset EGAD00001001122

• Chip-exo and Chip-nexus for five TFs in three colorectal cancer cell lines

  Chip-exo and Chip-nexus for FOXA1, HNF4A, KLF5, MYC, and TCF7L2 in colorectal cancer cell lines LoVo, GP5D, COLO320DM

  Dataset EGAD00001004099

• Spatial Maps of Prostate Cancer Transcriptomes

  A total of 14 samples that has been analyzed with the Spatial Transcriptomics method. H&E stain can be sent if requested.

  Dataset EGAD00001004121

• The spatio-temporal evolution of lymph node spread in early breast cancer

  Set of multi-region sequenced breast cancer primary samples, lymph nodes and ctDNA. We collected samples from 11 breast cancer patients with lymph node involvement but no sign of distant metastasis. We performed a mix of whole-exome sequencing, targeted capture sequencing, and whole-genome sequencing of primary tumour samples and lymph nodes, as well as targeted capture sequencing of circulating tumour DNA.

  Dataset EGAD00001004122

• Structural rearrangements generate cell-specific, gene-independent CRISPR-Cas9 loss of fitness effects.

  CRISPR-Cas9 genome editing is widely used to study gene function, from basic biology to biomedical research. Structural rearrangements are a ubiquitous feature of cancer cells and their impact on the functional consequences of CRISPR-Cas9 gene-editing has not yet been assessed. Utilizing CRISPR-Cas9 knockout screens for 250 cancer cell lines, we demonstrate that targeting structurally rearranged regions, in particular tandem or interspersed amplifications, is highly detrimental to cellular fitness in a gene independent manner. In contrast, amplifications caused by whole chromosomal duplications have little to no impact on fitness. This effect is cell line specific and dependent on the ploidy status. We devise a copy-number ratio metric that substantially improves the detection of gene-independent cell fitness effects in CRISPR-Cas9 screens. Furthermore, we develop a computational tool, called Crispy, to account for these effects on a single sample basis and provide corrected gene fitness effects. Our analysis demonstrates the importance of structural rearrangements in mediating the effect of CRISPR-Cas9-induced DNA damage, with implications for the use of CRISPR-Cas9 gene-editing in cancer cells.

  Dataset EGAD00001004124

• Normal prostatectomy project analysis and leftovers

  Data collected as part of the Normal prostatectomy project analysis. Whole genome sequencing (WGS, targeted at 30X for normal tissue and 50X for tumour tissue) was performed on morphologically normal tissue samples from 30 patients with prostate cancer. In addition, seven prostate tissue samples were sequenced from 7 non-cancer patients: two collected after a cystoprostatectomy and five from samples collected at autopsy. Matched blood controls were included for all patients. An extra five samples were sequenced from the stroma of cell cultured fibroblasts. In addition a few tumour samples obtained at prostatectomy and their blood matched controls are included in this dataset from the main study that are not included elsewhere.

  Dataset EGAD00001004125