7184 results for "canc*"

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• Tumour sample for patient SA589

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA589

  Dataset EGAD00001009195

• Tumour sample for patient SA667

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA667

  Dataset EGAD00001009210

• Tumour sample for patient SA666

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA666

  Dataset EGAD00001009209

• Genetic alterations in benign breast biopsies of subsequent breast cancer patient

  This dataset consists of amplicon sequencing of fibrocystic breast tissues, subsequent cancer tissue and germline control of 17 patients. The target genes include all exons of 27 protein-coding genes and 2 non-coding genes, as well as mutation hotspots in three cancer genes, frequently mutated in breast cancer. Ion AmpliSeq libraries were generated and sequenced on the Ion S5 XL system.

  Dataset EGAD00001004874

• Tumour sample for patient SA669

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA669

  Dataset EGAD00001009212

• CYPTAM - PacBio SMRT sequencing

  Dataset contains CYP2D6 sequencing data of 566 individuals who used tamoxifen as adjuvant breast cancer therapy. Phenotype data consists of the ratio between the metabolites endoxifen and desmethyltamoxifen (Metabolic ratio (MR)) as a proxy for CYP2D6 enzyme activity. Each sample is linked to one bam-file containing the CYP2D6 sequence.

  Dataset EGAD00001005972

• Predictor_RIO_TNBC (2019-04-03)

  In this study, samples fom a window study of the PARP inhibitor rucaparib in patients with primary triple negative or BRCA1/2 related breast cancer (RIO trial) will be investigated. Samples will undergo whole genome sequence and analysis, including use of HR Predict. . This dataset contains all the data available for this study on 2019-04-03.

  Dataset EGAD00001004894

• Tumour sample for patient SA671

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA671

  Dataset EGAD00001009213

• MutWP5: CRUK Mutographs of Cancer: Lung: PD37920 (WG) (2020-02-20)

  Sequencing of LCM-derived microbiopsies from explanted lung from COPD patient. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Deep sampling throughout multiple regions of the lung will determine whether there are differences in smoking-related mutation burden in different portions of the lung. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this portion of the study will be compared to other individuals with smoking-related diseases (COPD, pulmonary fibrosis, lung cancer), and normal, non-smoking lungs. . This dataset contains all the data available for this study on 2020-02-20.

  Dataset EGAD00001005990

• Transcriptomic profiling of prostate cancer metastasis xenograft models

  RNA-seq profiling of 2 prostate cancer xenograft mouse models, each at the intact state (n=3), castrated state (n=4) and castrated + AR replacement (n=3).

  Dataset EGAD00001006551

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: Colorectal_LCM (2020-02-20)

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute. Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development. . This dataset contains all the data available for this study on 2020-02-20.

  Dataset EGAD00001005994

• Normal sample for patient SA1035

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1035

  Dataset EGAD00001009216

• Tumour sample for patient SA672

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA672

  Dataset EGAD00001009214

• Normal sample for patient SA218

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA218

  Dataset EGAD00001009220

• Tumour sample for patient SA535

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA535

  Dataset EGAD00001009215

• Normal sample for patient SA219

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA219

  Dataset EGAD00001009221

• Normal sample for patient SA274

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA274

  Dataset EGAD00001009223

• Normal sample for patient SA275

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA275

  Dataset EGAD00001009224

• Genome and transcriptome sequence data from a locally advanced breast cancer patient

  Genome and transcriptome sequence data from a locally advanced breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004897

• Normal sample for patient SA598

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA598

  Dataset EGAD00001009246

• Genome and transcriptome sequence data from a metastatic leiomyosarcoma patient

  Genome and transcriptome sequence data from a metastatic leiomyosarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004901

• Tumour sample for patient SA530

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA530

  Dataset EGAD00001009191

• Normal sample for patient SA395

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA395

  Dataset EGAD00001009230

• Normal sample for patient SA672

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA672

  Dataset EGAD00001009257

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004902