4004 results for "*geneti*"

in 21.12 milliseconds.

• Raw bulk TCRseq data fromTIL and non-TIL expanded TRACERx samples in the manuscript Bulk TCRseq from TRACERx samples from 'Subclonal immune evasion in non-small cell lung cancer'

  Immune checkpoint blockade in non-small cell lung cancer (NSCLC) rarely leads to complete tumour remission, suggesting that tumours harbour subpopulations of cancer cells that can escape immune predation. However, while tumours consist of multiple genetically distinct clones, the extent to which separate tumour subclones differ intrinsically in their functional capacity for immune evasion remains largely unexplored. This has been challenging to address due to an inability to isolate and propagate individual tumour subclones from human cancers. Here, we leverage the multi-region TRACERx lung cancer evolution study to generate a patient-derived platform that allows the functional analysis of immune escape at single clone resolution. We generated libraries of >20 separate NSCLC organoid lines per patient by isolating individual (clonal) organoids established from multiple spatially separated tumour regions. Each organoid subline was co-cultured with autologous tumour infiltrating lymphocytes (TIL) to evaluate their capacity to elicit a T cell response. Organoid lines derived from separate tumour regions, or from single clones within individual regions, differ vastly in their capacity to elicit a T cell response, showing the coexistence of intrinsically immune evading (‘cold) and non-evading (‘hot) clones in the same primary tumour. Organoid lines escaping T cell recognition represent genetically and transcriptionally unique subclones with a distinct evolutionary history, showing that evolutionary sculpting of subclonal diversity can have functional consequences for anti-tumour immunity. Notably, the identification of immune-evasive subclones would not have been possible using computational approaches alone, highlighting the unique value of functional co-culture platforms. This patient-derived functional co-culture platform reveals that tumour evolution can give rise to distinct cancer clones with intrinsic differences in immune evasion capacity and provides an approach to prospectively identify, isolate and characterise immune evading subclones from patients with cancer.

  Study EGAS00001008118

• Inhibiton of the GABPB1L-containing GABP tetramer is sufficient to reverse replicative immortality in TERT promoter mutant glioblastoma cells.

  Over 50 types of cancer acquire TERT promoter mutations. These single point mutations reactivate telomerase, allowing for indefinite maintenance of telomere length and enabling cellular immortalization. The transcription factor binding site created by the point mutations specifically recruit the ETS factor GABP, a multimeric transcription factor composed of the GABPα and GABPβ subunits. GABP can form two functionally independent transcription factor species – a dimer or a tetramer – depending on which of the structurally distinct GABPβ isoforms is incorporated into the complex. In this study, we show that genetic disruption of GABPβ1L, a tetramer forming isoform of GABPβ that is dispensable in normal development, results in TERT silencing in a TERT promoter mutation dependent manner. Failure to activate TERT expression by GABPβ1L culminates in telomere dysfunction, DNA damage, and mitotic cell death exclusively in TERT promoter mutant cells. Furthermore, exogenous expression of TERT is sufficient to prevent telomere degradation and loss of cell viability in GABPβ1L-reduced lines bearing the mutant TERT promoter. Orthotopic injection of tetramer-deficient mutant TERT promoter GBM cells rendered lower tumor burden and prolonged the overall survival of the tumor-bearing mice. These results highlight the potentially widespread role of GABPB1L in enabling replicative immortality of TERT promoter cancers.

  Study EGAS00001002582

• Comprehensive genetic analysis of uveal melanoma heterogeneity during metastatic progression

  Uveal melanoma (UM) is the most common primary intraocular malignancy in adults. Despite improvement of diagnosis and treatment of the primary tumor, there is no effective treatment of metastatic disease and approximately half of patients will die within one year or less following metastases detection. Tumor heterogeneity has been proposed as a key factor of drug resistance. However, it has been scarcely studied in UM. The present project aims searching for specific drivers of the metastatic progression, describing the genomic and transcriptomic landscape of metastatic UM, exploring tumor heterogeneity and investigating its role in drug resistance. Thus whole exome sequencing and transcriptomics have been performed on constitutional, primary tumor and metastatic samples from 28 UM patients.

  Study EGAS00001002761

• Whole genome sequencing of six ethnic groups from Burkina Faso, Cameroon, and Tanzania

  We conducted low-coverage (~10x) sequencing of six ethnic groups from three malaria-endemic countries in sub-Saharan Africa, with the aim of characterising genetic diversity and improving imputation performance for genotyped samples in these populations. This data is part of a pre-publication release and is available under managed access. Please see https://www.malariagen.net/data/terms-use/human-gwas-data for more information on MalariaGEN data access policies. The purpose of the project was to support the discovery and understanding of genetic variants that influence human disease. Specifically defined goals were: a. the discovery of single nucleotide variants at frequencies of 1% or higher in diverse populations, b. even more comprehensive discovery (variants down to frequencies of 0.1 - 0.5%) in functional gene regions, and c. discovery of structural variants, such as copy number variants, other insertions and deletions, and inversions, including sequence-level understanding of breakpoints.

  Study EGAS00001003648

• Integration of human pancreatic islet genomic data refines regulatory mechanisms at Type 2 Diabetes susceptibility loci

  Human genetic studies have emphasised the dominant contribution of pancreatic islet dysfunction to development of Type 2 Diabetes (T2D). However, limited annotation of the islet epigenome has constrained efforts to define the molecular mechanisms mediating the, largely regulatory, signals revealed by Genome-Wide Association Studies (GWAS). We characterised patterns of chromatin accessibility (ATAC-seq, n=17) and DNA methylation (whole-genome bisulphite sequencing, n=10) in human islets, generating high-resolution chromatin state maps through integration with established ChIP-seq marks. We found enrichment of GWAS signals for T2D and fasting glucose was concentrated in subsets of islet enhancers characterised by open chromatin and hypomethylation, with the former annotation predominant. At several loci (including CDC123, ADCY5, KLHDC5) the combination of fine-mapping genetic data and chromatin state enrichment maps, supplemented by allelic imbalance in chromatin accessibility pinpointed likely causal variants. The combination of increasingly-precise genetic and islet epigenomic information accelerates definition of causal mechanisms implicated in T2D pathogenesis.

  Study EGAS00001002592

• Whole Genomes Define Concordance in Matched Primary, Xenograft, and Organoid Models of Pancreas Cancer

  Pancreatic ductal adenocarcinoma (PDAC) has the worst prognosis of any common solid epithelial tumour. Multiple failed clinical trials necessitate newer approaches to understand the molecular etiology of this disease. Patient-derived xenografts (PDX) and patient-derived organoids (PDO) may serve as pre-clinical disease models; however, characterization remains largely unaddressed at the whole genome level. We conducted a comprehensive assessment of the genetic landscape of tumours and matched PDX and PDO from patients with PDAC. Our data show that PDX and PDO recapitulate PDAC tumourigenesis with respect to simple somatic mutations and copy number changes, and capture major structural variation events.

  Study EGAS00001002597

• 1 Intratumoral genetic heterogeneity and clonal evolution following neoadjuvant chemoradiotherapy (nCRT) in locally advanced rectal tumors.

  Purpose: Neoadjuvant chemoradiotherapy (nCRT) is the standard treatment forpatients with locally advanced rectal cancer. However, little is known about the effect of nCRT in the mutational landscape and intratumoral genetic heterogeneity (ITGH) of rectal tumors. Moreover, response to nCRT vary substantially among patients and the genetic determinants of treatment response are not fully understood. Here, we sought to determine the impact of nCRT in the mutational landscape and ITGH of rectal tumors and to identify putative drivers of therapeutic resistance. Patients and Methods: We analyzed whole-exome sequencing (WES) and clinical data from 79 primary non-treated rectal cancers obtained from The Cancer Genome Atlas (TCGA). We also compared the mutational landscape of a matched set of peripheral blood cells, irradiated tumor-adjacent colonic mucosa and pre and post-treatment tumor samples to determine the iatrogenic effects of nCRT and its impact in tissue genetic heterogeneity. Finally, we performed WES of 7 matched pre and post-treatment tumor samples to examine how nCRT affects the clonal architecture of rectal tumors. Results: We show that rectal tumors exhibit remarkable ITGH, which increases with disease progression. We also show that nCRT, per se, does not introduce novel somatic mutations, nor alters the clonal architecture of the irradiated colonic mucosa. Instead, we show that it acts as a potent selective pressure, favoring the expansion of tumor cell subpopulations more prone to resist therapy and increasing ITGH in the residual tumor. Conclusion: Our results reveal the highly heterogeneous and dynamic clonal architecture of rectal tumors undergoing nCRT. Our results also uncover putative genetic determinants of response to nCRT and a possible role for ITGH in predicting treatment outcome.

  Study EGAS00001003250

• Identification_of_low_frequency_variants_associated_with_ulcerative_colitis_using_whole_genome_sequencing

  2000 ulcerative colitis cases drawn from the UKIBD Genetics Consortium cohort and whole-genome sequenced at 2X depth. A case control association study using control samples whole-genome sequenced by UK10K will be undertaken to identify common, low-frequency and rare variants associated with ulcerative colitis. Data will be combined with similar data across 3000 Crohn's disease cases from the same cohort to identify inflammatory bowel disease (IBD) loci and better understand the genetic differences and similarities of the two common forms of IBD.

  Study EGAS00001000329

• Ultra-Fast Patient-Derived Xenografts Identify Functional and Spatial Tumour Heterogeneities that Drive Therapeutic Resistance

  Treatment of patients with advanced cancers increasingly relies on agents targeting specific molecular or cellular aberrations. These expensive therapies often fail because of pre-existing drug resistance. Intra-tumoural molecular and micro-environmental heterogeneity resistance can create resistance in one or more subclones of a tumour, leading to spatio-functional heterogeneity. We created a rapid approach for quantifying tumour functional phenotypes based on tumour-implantation into the chorioallantoic membrane of chick embryos. We apply this technique to 43 separate biopsies from 6 patients with renal cell carcinoma (RCC) with 36 replicates per biopsy, achieving a 93.6% engraftment rate (1449/1548). Challenging these models with sunitinib, an anti-angiogenic therapy frequently used in RCC allowed us to quantify spatio-functional heterogeneity in individual patients. Prediction of de novo drug resistance in advanced cancer patients would facilitate precision medicine by tailoring systemic therapies and improve clinical trial design outcome measures. We describe a patient-derived xenograft platform where fresh patient tumour samples are implanted into the chorioallantoic membrane (CAM) of chick embryos at high engraftment efficiencies, permitting large scale “tumour avatar” studies to guide the selection of drugs and to predict clinical drug resistance outcomes in renal cell carcinoma (RCC) patients. Applying this “tumour avatar” model in a co-clinical trial on RCC patients, we observe intra-tumoural functional heterogeneity with sunitinib treatment, revealing the presence of drug-resistant clones prior to the initiation of therapy. Multi-regional exome Matched DNA sequencing of the primary tumour and metastases revealed DNA mutational signatures associated with sunitinib resistance at baseline and after treatment. These These studies demonstrate a rapid and affordable method of findings confirm the existence of genetic and surveying functional tumour heterogeneities heterogeneity.

  Study EGAS00001002627

• MutWP1__CRUK_Grand_Challenge__matched_blood_Nanoseq

  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. Non-tumour DNA is also studied for some cancer types. 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 EGAS00001006774