6052 results for "canc*"

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• Metastatic_Breast_Cancer_Whole_Genome

  We propose to definitively characterise the somatic genetics of Metastatic breast cancer through generation of comprehensive catalogues of somatic mutations in Metastatic breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Study EGAS00001000902

• Somatic_mutation_and_clonal_evolution_in_premalignant_lung_disease___WGS

  Cancer is a genetic disease caused by an accumulations of mutations, however many of these mutations have been identified in pathologically normal tissue. We aim to use laser-capture microscopy (LCM) to sample individual clones from the lung tissue of individuals with a variety of lung diseases (COPD, UIP, IPF, Emphysema, pulmonary hypertension). This will allow us to identify whether cancer-associated mutations appear in this normal tissue, assess the mutational burden present, and identify the mutational processes causing these mutations. Smoking is a large risk factor for developing many of these lung diseases so we are particularly keen to determining whether there is evidence of a smoking signature in these patients.

  Study EGAS00001002747

• Mechanisms_of_patient_response_to_Dabrafenib_in_Melanoma

  Samples will be from the BRF113683 (BREAK-3) study which is a Phase III Randomized, Open-label Study Comparing GSK2118436 to Dacarbazine (DTIC) in Previously Untreated Subjects With BRAF Mutation Positive Advanced (Stage III) or Metastatic (Stage IV) Melanoma (n=250 enrolled)•NGS [Agilent capture (Sanger V2 panel): 360 genes and 20 gene fusions; Illumina HiSEQ Sequencing]•CNV: [via NGS or Affy SNP 6.0 or Illumina Omni (TBD)]Bioinformatics: Analysis will be performed using core Sanger informatics pipelines similar to those previously described (Papaemmanuil E et al. (2013) Blood. 22:3616 -3627). Briefly, copy number analysis will be performed using the ASCAT algorithm, and base substitutions, small insertions and deletions using the CAVEMAN and Pindel algorithms, respectively. Statistical approaches including generalized linear models will be used to predict clinical variables such as maximum clinical response and duration of response using genetic data. Sanger and EBI to conduct analysis; Raw data and correlation with clinical endpoints to be analyzed by both EBI/Sanger and GSK (unique pipeline analyses to increase call confidence)

  Study EGAS00001000946

• MutWP1__CRUK_Grand_Challenge_Mutographs_of_Cancer__pancreas

  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 (Illumina HiSeqX, 40X and 20X depth respectively). 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.

  Study EGAS00001002726

• DKFZ-HIPO Project H021/NCT MASTER

  Clinical genome and transcriptome sequencing in younger adults with advanced-stage cancer across all histologies: DKFZ-HIPO Project H021 (http://www.hipo-heidelberg.org/hipo2/index.php/menu-item-2/32-021-prospective-genetic-characterization-of-tumors-from-individual-patients-of-special-interest) / NCT MASTER (http://www.nct-heidelberg.de/forschung/nct-master.html)

  Study EGAS00001000948

• Dynamics of genomic clones in breast cancer patient xenografts at single cell resolution

  Human cancers, including breast cancers, are comprised of clones differing in mutation content that evolve dynamically in space and time following principles of Darwinian evolution, underpinning important emergent features such as drug resistance and metastasis. Human breast cancer xenoengraftment is used as a means of capturing and studying tumour biology, and breast tumour xenografts are generally assumed to be reasonable models of the originating tumours. However the consequences and reproducibility of engraftment and propagation on the genomic clonal architecture of tumours has not been systematically examined at single cell resolution. Here we show by both deep genome and single cell sequencing methods, the clonal dynamics of initial engraftment and subsequent serial propagation of primary and metastatic human breast cancers in immunodeficient mice. In all cases examined, clonal selection on engraftment was observed in both primary and metastatic breast tumours, varying in degree from extreme selective engraftment of minor (<5% of starting population) clones to moderate, polyclonal engraftment. Furthermore, ongoing clonal dynamics during serial passaging is a feature of tumours experiencing modest initial selection. Through single cell sequencing, we show that major mutation clusters estimated from tumour population sequencing relate predictably to the most abundant clonal genotypes, even in clonally complex and rapidly evolving cases. Finally, we show that similar clonal expansion patterns can emerge in independent grafts of the same starting tumour population, indicating that genomic aberrations can be reproducible determinants of evolutionary trajectories. Our results show that measurement of genomically defined clonal population dynamics will be highly informative for functional studies utilizing patient-derived breast cancer xenoengraftment.

  Study EGAS00001000952

• EBV_AID_project

  Whole genome sequencing of EBV-transformed B cells in order to determine whether EBV induction of activation-induced cytidine deaminase (AID) produces genome-wide mutations and/or chromosomal rearrangements.

  Study EGAS00001000955

• Cancer_Cell_Line_Exome_Sequencing_

  Genomic characterisation of a large series of cancer cell lines.

  Study EGAS00001000978

• Pulldown_DNA_methylation_study_v2

  Pilot study to set up sequencing protocols for targeted pulldown methylation profiling

  Study EGAS00001000979

• SOFT_study___sequencing_premenopausal_breast_cancer

  Our project will examine the role of PIK3CA mutations and their sensitivity to endocrine therapies and its role, with the addition of complete ovarian suppression. We plan to test our hypotheses using tumour samples collected from patients enrolled in the SOFT/IBCSG24-02 clinical study (Suppression of Ovarian Function Trial – (NCT00066690). SOFT is a phase III trial that randomised 3066 premenopausal women to evaluate if adding ovarian suppression to adjuvant endocrine therapy will improve clinical outcomes.

  Study EGAS00001000983