5707 results for "canc*"

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• Integrative pan-cancer genomic and transcriptomic analyses of refractory metastatic cancer

  Study EGAS00001006648

• Genomic and immune signatures predict clinical outcome in newly diagnosed multiple myeloma treated with immunotherapy regimens

  Study EGAS00001007404

• Wilms_Tumour_organoid_sequencing_WGS

  This study investigates the genomic and transcriptomic characteristics of Wilm's tumour organoids

  Study EGAS00001002692

• Bone marrow single cell genomics from blood cancer samples

  The overall goal of this study was to characterize bone marrow cells based on their transcriptome, surface protein expression and BCR- and TCR VDJ-profile for accurate identification of clinically relevant cell states. This project has received funding from the European Union Horizon 2020 research and innovation programme under grant agreement No 824110 (EASI-Genomics)

  Study EGAS00001007332

• Elucidating the molecular landscape of KRAS/BRAF mutant colorectal cancers

  Study EGAS00001007459

• Understanding_the_multicellular_dynamics_of_clear_cell_renal_cell_carcinoma___single_cell_RNA_sequencing

  This study will reconstruct the single cellular phylogeny of tumour and immune cells in relation to both genomic, functional, and spatial location. 20 tumours in total will be studied, including non-progressing small renal masses, progressing small renal masses, relatively indolent larger tumours, and high risk tumour with metastatic sampling. We aim to: Generate a focused, comprehensive phylogenetic characterisation of tumour cells Understand the dependencies of the cancer genome, transcriptome, tissue architecture and the single cellular micro-environment Quantify the single cellular composition and functional intra- and inter- tumoural heterogeneity Determine the phylogeny of tumour associated lymphocytes and their relationship to neo-epitopes and the immune microenvironment Investigate the mechanisms by which the tumour-normal interface constrains tumoural growth

  Study EGAS00001003519

• Mutational_burden_in_skin_following_UV_treatment_Nanoseq

  We wish to assess the changes in mutational burden in patients under going UV treatment for psoriasis. Using duplex sequencing we will assess mutational burden in traditionally sun exposed (arm) and non-sun exposed (buttock) skin epidermis both pre and post UV treatment.

  Study EGAS00001007681

• HSC_population_dynamics_KSP_samples

  My research project aims to use the clonal dynamics of spontaneously occurring somatic mutations to answer fundamental questions about human haematopoietic stem cell (HSC) biology. The four major questions I will address are: 1. How do age and aging affect normal human HSC dynamics in vivo? 2. How do in vivo perturbations, particularly chemotherapy and increased levels of reactive oxygen species, affect HSC population dynamics? 3. Is response to in vitro perturbation heritable and/or correlated with other features such as age of individual and contribution of the lineage to peripheral blood? 4. How are HSC dynamics altered in people with early driver mutations (clonal haematopoiesis)?

  Study EGAS00001002762

• MutWP6__CRUK_Grand_Challenge_Mutographs_of_Cancer__Botseq

  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. Within Mutographs, work lead by the Sanger Institute will investigate whether detection of somatic mutations and mutational signatures in circulating white blood cells can be developed into a practical, generic system for surveying and monitoring multiple different endogenous and exogenous exposures, providing an ‘observatory’ on somatic mutational processes in humans. Whole genome sequences are generated at the Wellcome Sanger Institute (Illumina HiSeqX). Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods. 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 EGAS00001004330

• Gastric_Mutational_Signatures__GMS_

  This study aims to characterise the mutation burdens and signatures of adult stem cells derived from different regions of the stomach in order to gain insight into the causes and preclinical evolution of the diverse cancer subtypes. Clonal populations of cells from different anatomical locations of the stomach will be derived through organoid culture and/or laser microdissection and interrogated by whole genome sequencing and/or targeted pulldown. A total of circa 300 samples from 20 – 30 donors (cancer and non-cancer patients undergoing total/partial gastrectomy) will be analysed for mutational burden and signatures and genomic findings correlated with topology, age, risk factors and different stages of pre-neoplastic or neoplastic progression.

  Study EGAS00001002939

• Gastric_Mutational_Signatures__GMS_

  This study aims to characterise the mutation burdens and signatures of adult stem cells derived from different regions of the stomach in order to gain insight into the causes and preclinical evolution of the diverse cancer subtypes. Clonal populations of cells from different anatomical locations of the stomach will be derived through organoid culture and/or laser microdissection and interrogated by whole genome sequencing and/or targeted pulldown. A total of circa 300 samples from 20 – 30 donors (cancer and non-cancer patients undergoing total/partial gastrectomy) will be analysed for mutational burden and signatures and genomic findings correlated with topology, age, risk factors and different stages of pre-neoplastic or neoplastic progression.

  Study EGAS00001002938

• DERMATLAS__SG_basal_cell_adenoma_and_adenocarcinoma_WES

  Virtually no other tumour type is associated with so many different forms as skin cancer. Histologically, tumours of the skin may arise from epithelium, including epidermis, hair follicle, sebaceous or sweat gland, melanocytes, dermal-associated mesenchymal structures or tissue resident immune cells, making for a diversity of clinical presentations. Importantly, many skin tumour types have an extremely poor prognosis. Many skin tumour subtypes have never undergone molecular profiling, or if they have, targeted sequencing has been used and the number of cases analyzed has been so limited that deriving firm conclusions about the profile of driver genes, DNA mutational signatures and germline alleles has not been possible For 70 key skin tumour subtypes defined by the World Health Organization, that have not undergone extensive genetic analysis previoulsy, we propose to perform whole exome and transcriptome sequencing, from a range of body sites, to build a genomic atlas of dermatological tumours, including detailed maps of SNVs, copy number alterations, genome-wide methylation and expression profiles. The cases in this cohort are SG basal cell adenomas and adenocarcinomas.

  Study EGAS00001007745

• DERMATLAS__SG_basal_cell_adenoma_and_adenocarcinoma_RNAseq

  Virtually no other tumour type is associated with so many different forms as skin cancer. Histologically, tumours of the skin may arise from epithelium, including epidermis, hair follicle, sebaceous or sweat gland, melanocytes, dermal-associated mesenchymal structures or tissue resident immune cells, making for a diversity of clinical presentations. Importantly, many skin tumour types have an extremely poor prognosis. Many skin tumour subtypes have never undergone molecular profiling, or if they have, targeted sequencing has been used and the number of cases analyzed has been so limited that deriving firm conclusions about the profile of driver genes, DNA mutational signatures and germline alleles has not been possible For 70 key skin tumour subtypes defined by the World Health Organization, that have not undergone extensive genetic analysis previoulsy, we propose to perform whole exome and transcriptome sequencing, from a range of body sites, to build a genomic atlas of dermatological tumours, including detailed maps of SNVs, copy number alterations, genome-wide methylation and expression profiles. The cases in this cohort are SG basal cell adenomas and adenocarcinomas.

  Study EGAS00001007746

• Implementation of pediatric precision oncology into clinical practice: The individualized Therapies for Children with cancer program “iTHER”

  iTHER is a prospective national precision oncology program aiming to define tumor molecular profiles in children and adolescents with primary very high-risk, relapsed, or refractory pediatric tumors in order to identify relevant aberrations to inform treatment. From April 2017 to April 2021, 302 samples of 253 patients were included. Comprehensive molecular profiling utilizing lcWGS, WES, RNAseq, Affymetrix, and/or 850k methylation profiling was performed for 226 samples. Germline pathogenic variants were identified in 16% of patients. At least one somatic alteration was detected in 204 (90.3%), and 185 (81.9%) were considered druggable, with priority levels very high (6.1%), high (21.3%), moderate (26.0%), intermediate (36.1%), and borderline (10.5%). Diagnosis was revised or refined in 8 patients (3.5%). Spatial and temporal heterogeneity was observed in paired samples of 15 patients, indicating the value of sequential analysis. Of 137 patients with follow-up beyond 12 months, 21 molecularly matched treatments were applied in 19 patients (13.9%) with modest response. Most relevant barriers to not applying targeted therapies included poor performance status, as well as limited access to drugs within clinical trial. iTHER demonstrates feasibility of comprehensive molecular profiling across all ages, tumor types and stages in pediatric cancers, informing of diagnostic, prognostic, and targetable alterations as well as reportable germline variants within a clinically relevant timeframe. Therefore, WES and RNAseq is implemented into standard clinical care at the Princess Máxima Center for all children. Improved access to targeted treatments within biology-driven combination trials is required to eventually improve survival.

  Study EGAS00001007099

• Genomic Rearrangements in Pediatric Cancer

  This study contains a collection of samples used to determine the role and impact of genomic rearrangements in a pan cancer pediatric cohort.

  Study EGAS00001005312

• SYNTHETIC: EOSC4Cancer Study Synthetic Colorectal Cancer Genomic data

  This dataset contains 10 tumor and normal pairs synthetic WGS data of colorectal cancer that were simulated in a standard format of Illumina paired-end reads. NEAT read simulator (version 3.0, https://github.com/zstephens/neat-genreads) is utilized to synthetize these 10 pairs tumor and normal WGS data. In the procedure of data generation, simulated parameters (i.e., sequencing error statistics, read fragment length distribution and GC% coverage bias) are learned from data models provided by NEAT. The average sequencing depth for tumor and normal samples aims to reach around 110X and 60X, respectively. For generation of synthetic normal WGS data per each sample, a germline variant profile from a real patient is down-sampled randomly, which includes 50% germline variants of such a patient. It is then mixed together with an in silico germline variant profile that is modelled randomly using an average mutation rate (0.001), finally constituting a full germline profile for normal synthetic WGS data. For generation of synthetic tumor WGS data per each sample, a pre-defined somatic short variant profile (SNVs+Indels) learn from a real CRC patient is added to the germline variant profile used for creating normal synthetic WGS data of the same patient, which is utilized to produce simulated sequences. Neither copy number profile nor structural variation profile is introduced into the tumor synthetic WGS data. Tumor content and ploidy are assumed to be 100% and 2.

  Study EGAS50000000386