3995 results for "*geneti*"

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• A biobank of patient-derived pediatric brain tumor models

  Brain tumors are the leading cause of cancer-related death in children. Genomic studies have provided insights into molecular subgroups and oncogenic drivers of pediatric brain tumors that may lead to novel therapeutic strategies. To evaluate new treatments, better preclinical models adequately reflecting the biological heterogeneity are needed. Through the Children’s Oncology Group ACNS02B3 study, we have generated and comprehensively characterized 30 patient-derived orthotopic xenograft models and 7 cell lines representing 14 molecular subgroups of pediatric brain tumors. Patient-derived orthotopic xenograft models were found to be representative of the human tumors they were derived from in terms of histology, immunohistochemistry, gene expression, DNA methylation, copy number, and mutational profiles. In vivo drug sensitivity of targeted therapeutics was associated with distinct molecular tumor subgroups and specific genetic alterations. These models and their molecular characterization provide an unprecedented resource for the cancer community to study key oncogenic drivers and to evaluate novel treatment strategies.

  Study EGAS00001002536

• 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

• HipSci_RNASEQ_Battens

  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 perform RNAseq on iPS lines from Battens patients.

  Study EGAS00001001987

• HipSci_RNASEQ_Ataxia

  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 perform RNAseq on iPS lines from hereditary cerebral ataxia patients.

  Study EGAS00001001992

• T2D-GENES: Exome sequencing

  The Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples (T2D-GENES) is a large collaboration effort between the University of Michigan, Broad Institute, the Wellcome Trust Centre for Human Genetics, University of Chicago, NIDDK, Texas Biomedical Research Institute, University of Texas Health Science Center, University of North Carolina, Blood Systems Research Institute, and University of Mississippi Medical Center. The goal of this study is to identify genetic variants for type 2 diabetes through multiethnic sequencing studies. In this study, we use next generation sequencing to assess the role of common, low frequency, and rare variants on type 2 diabetes risk. We preformed exome sequencing in 6,546 T2D cases and 6,457 control individuals of multiethnic origin, including individuals of African American, East Asian, South Asian, Hispanic, and European descent.

  Study EGAS00001001460

• HipSci_RNASEQ_BPD

  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 perform RNAseq on iPS lines from Blood platelet disorders patients.

  Study EGAS00001001993

• HipSci_RNASEQ_Hypertrophic_Cardiomyopathy

  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 perform RNAseq on iPS lines from Hypertrophic Cardiomyopathy patients.

  Study EGAS00001001994

• TRACERx 100: metastatic samples

  Whole exome sequencing of 10 metastatic biopsies from four TRACERx100 patients (see EGA dataset EGAS00001002247), collected either after relapse or death. The data from these samples are initially published with Abbosh, C. et al. Phylogenetic ctDNA analysis depicts early stage lung cancer evolution. Nature http://dx.doi.org/10.1038/nature22364 (2017). Abstract: Earlier detection of relapse following primary surgery for non-small cell lung cancer and the characterization of emerging subclones seeding metastatic sites might offer new therapeutic approaches to limit tumor recurrence. The potential to non-invasively track tumor evolutionary dynamics in ctDNA of early-stage lung cancer is not established. Here we conduct a patient-specific approach to ctDNA profiling in the first 100 lung TRACERx (TRAcking Cancer Evolution through therapy (Rx)) study participants, including one patient co-recruited to the PEACE (Posthumous Evaluation of Advanced Cancer Environment) post-mortem study. We identify independent predictors of ctDNA release in early-stage non-small cell lung cancer and perform tumor volume limit of detection analyses. Through blinded profiling of post-operative plasma, we observe evidence of adjuvant chemotherapy resistance and identify patients destined to experience recurrence of their lung cancer. Finally, we show that phylogenetic ctDNA profiling tracks the subclonal nature of lung cancer relapse and metastases, providing a new approach for ctDNA driven therapeutic studies.

  Study EGAS00001002415

• HipSci___Whole_Exome_sequencing___Cardiomyopathy

  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 perform whole exome sequencing using Agilent whole exome pulldown method on iPS cells generated from skin biopsies or blood samples from rare disease patients diagnosed with hypertrophic cardiomyopathy

  Study EGAS00001001980

• Multisample genomic analysis of solid childhood cancers using high resolution SNP-arrays, Whole Exome Sequencing and Targeted Deep Sequencing.

  We mapped the prevalence of genetically distinct clones over 248 regions in 54 childhood cancers. This revealed that primary tumors can simultaneously follow up to four evolutionary patterns in different anatomic areas. The most common pattern consists of a fluctuating presence over anatomic space of subclones with very few mutations. The second most common is a surprisingly stable coexistence, over vast areas, of clones with different changes in chromosome numbers. This is contrasted by a third, less frequent, pattern where a novel clone harboring driver mutations or structural chromosome rearrangements completely replaces its progenitor. The fourth and rarest pattern is the local emergence of a myriad of clones with TP53 inactivation. Strikingly, death from disease was limited to tumors exhibiting the two latter, most dynamic patterns.

  Study EGAS00001002662