3883 results for "*geneti*"

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• The spatial organization of intratumor heterogeneity andevolutionary trajectories of metastases in hepatocellular carcinoma

  Hepatocellular carcinoma (HCC) has one of the poorest survival amongst cancers. Using multi-regional sampling of nine resected HCC with different etiologies, we find that phylogenetic relationships of these sectors show diverse levels of genetic sharing spanning early to late diversification. Unlike the variegated pattern found in colorectal cancers, a large proportion of HCC display a clear Isolation-By-Distance pattern where spatially closer sectors are genetically more similar. Two resected intra-hepatic metastases showed genetic divergence occurring before and after primary tumor diversification respectively. Interestingly, metastatic tumors had much higher variability than their primary tumors, suggesting that intra-hepatic metastasis is accompanied by rapid diversification at the distant location. The presence of co-existing mutations offers the possibility of drug repositioning for HCC treatment. Taken together, these insights into intra-tumor heterogeneity allow for a comprehensive understanding of the evolutionary trajectories of HCC and suggest novel avenues for personalized therapy.

  Study EGAS00001001603

• Whole exome sequencing of cell-free DNA reveals temporo-spatial heterogeneity and identifies treatment-resistant clones in neuroblastoma

  Background: Neuroblastoma (NB) displays important clinical and genetic heterogeneity, with emergence of new mutations at tumor progression. Patients and Methods: To study clonal evolution during treatment and follow-up, an innovative method based on circulating cell-free DNA (cfDNA) analysis by whole exome sequencing (WES) paired with target sequencing was realized in sequential liquid biopsy samples of 19 NB patients. Results: WES of the primary tumor and cfDNA at diagnosis showed overlap of Single Nucleotide Variants (SNVs) and Copy Number Alterations (CNAs), with 41% and 93% of all detected alterations common to the primary NB and cfDNA. CfDNA WES at a second time point indicated a mean of 22 new SNVs for patients with progressive disease. Relapse-specific alterations included genes of the MAPK pathway and targeted the protein kinase A signaling pathway. Deep coverage target sequencing of intermediate timepoints during treatment and follow-up identified distinct subclones. For 17 seemingly relapse-specific SNVs detected by sequencing detected these alterations in minor subclones, with relapse-emerging SNVs targeting genes of neuritogenesis and cell cycle. Furthermore a persisting, resistant clone with concomitant disappearance of other clones was identified by a mutation in the ubiquitin protein ligase HERC2. Conclusion: Modelisation of mutated allele fractions in cfDNA indicated distinct patterns of clonal evolution, with either a minor, treatment-resistant clone expanding to a major clone at relapse, or minor clones collaborating towards tumor progression. Identification of treatment-resistant clones will enable development of more efficient treatment strategies.cfDNA WES at relapse but not tumor or cfDNA WES at diagnosis, deep coverage target.

  Study EGAS00001002705

• Genetic_Overlap_between_Metabolic_and_Psychiatric_disease

  The Genetic Overlap between Metabolic and Psychiatric Diseases (GOMAP) study comprises samples from four patient groups: 964 schizophrenia samples, 921 type 2 diabetes patients, 582 patients with comorbid schizophrenia and type 2 diabetes and 280 samples with another psychiatric diagnosis.

  Study EGAS00001002723

• Whole-genome sequencing analysis of low-grade astrocytomas within the ICGC PedBrain Tumor Project

  In order to investigate the full range of genetic alterations contributing to the tumourigenesis of low-grade astrocytoma, we have conducted a next-generation sequencing-based analysis on a large series of matched tumor-normal pairs. This study, conducted by the International Cancer Genome Consortium PedBrain Tumor Project (ICGC PedBrain, http://www.pedbraintumor.org/), has revealed multiple new insights into the biological basis of this tumor entity.

  Study EGAS00001000381

• Pediatric Whole Genome Sequencing Diagnostic Utility

  The standard of care for first-tier clinical investigation of the etiology of congenital malformations and neurodevelopmental disorders is chromosome microarray analysis (CMA) for copy number variations (CNVs), often followed by gene(s)-specific sequencing searching for smaller insertion-deletions (indels) and single nucleotide variant (SNV) mutations. We compared diagnostic rate of WGS to CMA and targeted gene testing of 100 patients referred to The Hospital for Sick Children Genetics clinic in 2014. WGS identified genetic variants meeting clinical diagnostic criteria in 34% of cases, representing a 4-fold increase in diagnostic rate over CMA (8%) (p-value = 1.42e-05) alone and >2-fold increase in CMA plus targeted gene sequencing (13%) (p-value = 0.0009). WGS identified all rare clinically significant CNVs that were detected by CMA. In an additional 26 patients, WGS revealed indel and missense mutations presenting in a dominant (63%) or a recessive (37%) manner. We found four subjects with mutations in at least two genes associated with distinct genetic disorders, including two cases harboring a pathogenic CNV and SNV. When considering medically actionable secondary findings in addition to primary WGS findings, 38% of patients would benefit from genetic counselling.

  Study EGAS00001001623

• HipSci whole exome sequencing for embryonic stem cell control lines

  The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we use commercially available embryonic stem cell lines as control samples against which to compare HipSci's iPS cell lines. We performed whole exome sequencing using Agilent whole exome pulldown method.

  Study EGAS00001001726

• Genome_Diversity_in_Africa_Project__Benin

  Globally, human populations show structured genetic diversity as a result of geographical dispersion, selection and drift. Understanding this genetic variation can provide insights into the evolutionary processes that shape both human adaptation and variation in disease. Populations from SSA have the highest levels of genetic diversity. This characteristic, in addition to historical genetic admixture, can lead to complexities in the design of studies assessing the genetic determinants of disease and human variation. However, such studies of African populations are also likely to provide new opportunities to discover novel disease susceptibility loci and variants and refine gene–disease association signals. A systematic assessment of genetic diversity within SSA would facilitate genomic epidemiological studies in the region.The Genome Diversity in Africa Project (GDAP) aims to produce a comprehensive catalogue of human genetic variation in SSA, including single nucleotide polymorphisms (SNPs), structural variants, and haplotypes. This resource will make a substantial contribution to understanding patterns of genetic diversity within and among populations in SSA, as well as providing a global resource to help design, implement and interpret genomic studies in SSA populations and studies comprising globally diverse populations, complementing existing genomic resources. Specifically, we plan to carry out high depth whole genome sequencing of up to 2000 individuals across Africa (25 individuals from each ethnolinguistic group).Our scientific objectives are to: 1) develop a resource that provides a comprehensive catalogue of genetic variation in populations from SSA accessible to the global scientific community; 2) characterise population genetic diversity, structure, gene flow and admixture across SSA; 3) develop a cost-efficient, next-generation genotype array for diverse populations across SSA; and 4) facilitate whole genome-sequencing association studies of complex traits and diseases by developing a reference panel for imputation and resource for enhancing fine-mapping disease susceptibility loci. These scientific objectives will be supported by cross-cutting operational activities, including network and management of the consortium, research ethics, and research capacity building in statistical genetics and bioinformaticsThis data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001001688

• 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

• 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

• Lung_Cancer_Whole_Genomes

  We propose to definitively characterise the somatic genetics of Lung cancer through generation of comprehensive catalogues of somatic mutations by high coverage genome sequencing.

  Study EGAS00001000148