5707 results for "canc*"

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• Pancreatic cancer organoids recapitulate disease and allow personalized drug screening

  We report derivation of 30 Patient-Derived Organoid lines (PDOs) from tumors arising in the pancreas and distal bile duct. PDOs recapitulate tumor histology and contain genetic alterations typical for pancreatic cancer. In vitro testing of a panel of 76 therapeutic agents revealed sensitivities currently not exploited in the clinic. The PRMT5 inhibitor EZP015556, shown to target MTAP negative tumors, was validated as such, but also appeared to constitute an effective therapy for a subset of MTAP+ tumors. Taken together, the work presented here provides a platform to identify novel therapeutics to target pancreatic tumor cells using PDOs.

  Study EGAS00001003369

• Probabilistic cell type assignment of single-cell transcriptomic data reveals spatiotemporal microenvironment dynamics in human cancers

  Single-cell RNA sequencing (scRNA-seq) has transformed biomedical research, enabling decomposition of complex tissues into disaggregated, functionally distinct cell types. For many applications, investigators wish to identify cell types with known marker genes. Typically, such cell type assignments are performed through unsupervised clustering followed by manual annotation based on these marker genes, or via "mapping" procedures to existing data. However, the manual interpretation required in the former case scales poorly to large datasets, which are also often prone to batch effects, while existing data for purified cell types must be available for the latter. Furthermore, unsupervised clustering can be error-prone, leading to under- and over- clustering of the cell types of interest. To overcome these issues we present CellAssign, a probabilistic model that leverages prior knowledge of cell type marker genes to annotate scRNA-seq data into pre-defined and de novo cell types. CellAssign automates the process of assigning cells in a highly scalable manner across large datasets while simultaneously controlling for batch and patient effects. We demonstrate the analytical advantages of CellAssign through extensive simulations and exemplify real-world utility to profile the spatial dynamics of high-grade serous ovarian cancer and the temporal dynamics of follicular lymphoma. Our analysis reveals subclonal malignant phenotypes and points towards an evolutionary interplay between immune and cancer cell populations with cancer cells escaping immune recognition.

  Study EGAS00001003452

• MutWP1__CRUK_Grand_Challenge_Mutographs_of_Cancer__Colorectal_LCM

  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.

  Study EGAS00001003455

• MutWP5__CRUK_Mutographs_of_Cancer__Lung__PD43291_Novaseq__Exome_

  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 mutaiton 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 poriton of the study will be compared to other individuals with smoking-related diseases (COPD, pulmonary fibrosis, lung cancer), and normal, non-smoking lungs.

  Study EGAS00001003503

• ICGC Breast Cancer Project

  A comprehensive characterisation and analysis of human breast cancers through genome-wide approaches including genomics, transcriptomics and epigenomics.

  Study EGAS00001001195

• Validation_for_human_early_embryonic_substitutions_

  PCR and MiSeq validation for early embryonic substitution candidates from 400 Breast cancer patients

  Study EGAS00001001218

• Multisite_Primary_Breast_Cancer

  DNA extracted from multiple biopsies taken from different areas of primary breast tumours will be subjected to targeted re-sequencing and analysed in order to assess intra-tumour heterogeneity with respect to mutations in a selection of cancer related genes.

  Study EGAS00001000891

• Chordoma_Extension_Study

  Extension analysis to pursue candidate genes of interest in chordoma

  Study EGAS00001000892

• Chordoma_Extension__known_cancer_genes_

  Extension analysis to pursue candidate genes of interest in chordoma

  Study EGAS00001000895

• NGS_based_viability_screening_using_haploid_cell_line

  Identification of human deubiquitylating enzymes whose knock out result in hypersensitivity to DNA damaging agents, by comparing the sequence reads of ‘barcode region’ from mixed cell culture.

  Study EGAS00001001095

• Myeloma_Follow_up_Pilot

  Targeted capture of exonic and intronic regions of interest for the study of genomic alterations in multiple myeloma.

  Study EGAS00001000743

• Metastatic_breast_cancer_targeted_gene_screen

  The samples will be sequenced for a targeted panel of cancer relevant genes (n ~ 370) and analysed for somatic mutations.

  Study EGAS00001000704

• SPECTA__NGS_Screening_Program_for_Efficient_Clinical_Trial_Access

  SPECTA comprises a network of participating European clinical sites and NGS screening platforms that can screen individual patients for multiple molecular targets and potentially allow the design of trials that will match the specific biology of the diseases affecting specific patients with cancer.

  Study EGAS00001000728

• Transposome_Bisulfite_Sequencing

  DNA belonging to 16 tumour/normal samples were treated with bisulfite, then up to 5 different bisulfite PCRs were performed in each one of the samples. Amplicons form the same sample were pooled and submitted to sequencing on a MiSeq platform.

  Study EGAS00001000751

• Expressed_fusion_transcripts_in_rare_bone_tumours

  mRNA-Seq on total RNA from primary osteoblastomas and phosphaturic mesenchymal tumours, focussing on fusion transcript expression

  Study EGAS00001000763

• MPN_TGS2_Follow_up___PT1_Vori_other

  Targetted capture and resequencing of 94 known myeloid genes across MPN trials (PT1 and Voriconazole study) as well as remaining MPN samples. New bait design Jan 2014.

  Study EGAS00001000765

• Low_Coverage_Sequencing_of_rare_human_histiocytic_tumour

  Sequencing of rare human histiocytic tumour

  Study EGAS00001000768

• CGP_CORE_CELL_LINES___RNA_seq

  Graham to complete

  Study EGAS00001000828

• Moles

  In this project we have sequenced the exome of skin moles (melanocytic naevi) and also normal skin from young and old people. We are interested in looking at the clonality of these lesions and the burden of UV mutations

  Study EGAS00001000789

• Diverse modes of genomic alterations in hepatocellular carcinoma

  Hepatocellular carcinoma is the most prevalent type of liver cancer. We intended to study the genomic landscape of this disease. We conducted whole-genome, exome and transcriptome sequencing for 42 patients. We show diverse modes in which the HCC genome is affected in these patients, including well-known and novel mutations, structural variations, and Hepatitis B-virus integration into the genome.

  Study EGAS00001000824

• RNAseq___Discovery_of_resistance_mechanisms_to_the_BRAF_inhibitor_vemurafenib_in_metastatic_BRAF_mutant_melanoma

  We propose to biopsy 20 consented BRAF mutant melanoma patients at Addenbrooke's Hospital pre-treatment with vemurafenib and also upon the development of resistant disease, with the aim of using exome sequence and SNP6 data to identify novel sequence variants and copy number alterations that can be used to validate observed resistance mechanisms in our cell line models and also to use these models to inform as to likely candidate small molecule inhibitors to overcome resistance and that could be tested in the clinical trial setting.

  Study EGAS00001000813

• Mesothelioma_Whole_Genomes

  Genomic architecture of mesothelioma parent study is project 925. This project is set up in parallel to project 925 in order to Whole genome sequence ten of the 59 tumours in that project.

  Study EGAS00001000830

• FFPE_Normal_Panel_V3_Cancer_Panel

  FFPE normal panel generation for use with V3 cancer panel 0618521

  Study EGAS00001000836

• Primary_angiosarcoma_Whole_Genome_Sequencing

  Whole genome sequencing of primary angiosarcoma

  Study EGAS00001000851

• Integrative_genome_profiling_in_AML

  AML emerges as a consequence of accumulating independent genetic aberrations that direct regulation and/or dysfunction of genes resulting in aberrant activation of signalling pathways, resistance to apoptosis and uncontrolled proliferation. Given the significant heterogeneity of AML genomes, AML patients demonstrate a highly variable response rate and poor median survival in response to current chemotherapy regimens. For the past 4 years we have conducted gene expression profiling on purified bone marrow populations equating to normal haematopoietic stem and progenitor cells from healthy subjects and patients with de novo AML in order to identify AML signatures of aberrantly expressed genes in cancer versus normal. We are now applying a series of bioinformatic methodologies combined with clinical and conventional diagnostic data to establish novel genomics strategies for improved prognostication of AML. Additionally, we use our AML signatures to unravel oncogenic signalling pathway activities in AML patients and test inhibitory drugs for these pathways inn preclinical therapeutic programmes. We consider that superimposing GEP and clinical data for our AML patient cohort with additional data on their mutational status will significantly improve the prognostic power of the study as well as unravel yet unknown mutations associated with aberrant signalling activities of oncogenic pathways.

  Study EGAS00001000858