3883 results for "*geneti*"

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• Succession Of Transiently Active Tumour-Initiating Cell Clones inHuman Pancreatic Cancer

  To elucidate whether newly acquired genetic alterations during serial transplantation of patient derived primary pancreatic cancer cultures contribute to the observed clonal dynamics in vivo, all coding genes of two patient derived primary cultures and derived genetically marked serial xenografts (1°/2°/3°) were sequenced.

  Study EGAS00001000882

• An Unusual Genomic Variant of Pancreatic Ductal Adenocarcinoma with an Indolent Clinical Course

  We describe a patient with biopsy-proven locally advanced pancreatic ductal adenocarcinoma (PDA) who underwent a modified course of gemcitabine and stereotactic body radiation therapy. Whole exome sequencing of this patient's tumor revealed a simple genome landscape with no evidence of mutations, copy number changes, or structural alterations in genes most commonly associated with PDA, i.e. KRAS, CDKN2A, TP53 or SMAD4. An analysis of germline DNA revealed no pathogenic variants of significance. Whole exome and whole genome sequencing identified a somatic mutation of RNF213 and an inversion/deletion of CTNNA2 as the genetic basis of this PDA. Although PDA is classically characterized by a predictable set of mutations, these data suggest that alternate genetic paths to PDA may exist, which can be associated with a more indolent clinical course.

  Study EGAS00001002192

• Pediatric Non-Down Syndrome Acute Megakaryoblastic Leukemia is Characterized by Distinct Genomic Subsets with Varying Outcomes

  Acute Megakaryoblastic Leukemia (AMKL) is a subtype of acute myeloid leukemia (AML) in which cells morphologically resemble abnormal megakaryoblasts.  While extremely rare in adults, AMKL accounts for 4-15% of newly diagnosed childhood AML1-3.  A significant proportion of pediatric AMKL cases occur in children with Down syndrome (DS).  These patients have excellent outcomes and are characterized at the genomic level by a founding GATA1 mutation4-6.  In contrast, AMKL in patients without DS (non-DS-AMKL) is frequently associated with poor outcomes.  Previous efforts have identified chimeric oncogenes in a significant number of cases, including RBM15-MKL1, CBFA2T3-GLIS2, KMT2A gene rearrangements and NUP98-KDM5A7-9.  The etiology of 30-40% of cases, however, remains unknown.  To better understand the genomic landscape of non-DS-AMKL, we performed RNA and exome sequencing on specimens from 99 patients (75 pediatric and 24 adult).  We demonstrate that pediatric non-DS-AMKL is a heterogeneous malignancy that can be divided into seven subgroups with varying outcomes.  These subgroups are characterized by chimeric oncogenes with cooperating mutations in epigenetic and kinase signaling genes.  Overall, these data shed light on the etiology of AMKL and provide useful information for treatment tailoring. 

  Study EGAS00001002183

• Whole genome and RNA sequencing of paediatric glioblastoma in the ICGC PedBrain project

  Paediatric glioblastoma (pedGBM) is characterised by substantial intertumoural heterogeneity. In order to identify the genetic lesions underlying tumourigenesis, we analysed whole genomes and transcriptomes of pedGBMs and in vitro model systems by next generation sequencing. Novel fusions of the receptor tyrosine kinase MET lead us to investigate targeted therapy using MET inhibitors. This study is part of the International Cancer Genome Consortium PedBrain Tumor Project (ICGC PedBrain, http://www.pedbraintumor.org/).

  Study EGAS00001001139

• Scalable whole-genome single-cell library preparation without pre-amplification

  Single-cell genomics is critical for understanding cellular heterogeneity in cancer, but existing library preparation methods are expensive, require sample preamplification and introduce coverage bias. Here we describe direct library preparation (DLP), a robust, scalable, and high-fidelity method that uses nanoliter-volume transposition reactions for single-cell whole-genome library preparation without preamplification. We examined 782 cells from cell lines and triple-negative breast xenograft tumors. Low-depth sequencing, compared with existing methods, revealed greater coverage uniformity and more reliable detection of copy-number alterations. Using phylogenetic analysis, we found minor xenograft subpopulations that were undetectable by bulk sequencing, as well as dynamic clonal expansion and diversification between passages. Merging single-cell genomes in silico, we generated "bulk-equivalent" genomes with high depth and uniform coverage. Thus, low-depth sequencing of DLP libraries may provide an attractive replacement for conventional bulk sequencing methods, permitting analysis of copy number at the cell level and of other genomic variants at the population level.

  Study EGAS00001002170

• HipSci___Whole_Exome_sequencing___Monogenic_Diabetes

  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 Monogenic Diabetes.

  Study EGAS00001001140

• Genetic Landscape of Esophageal Squamous Cell Carcinoma Defined by Exome Sequencing on Chinese Patient Cohort and Cell Lines

  Esophageal Squamous Cell Carcinoma (ESCC) is one of the deadliest cancers worldwide. To define the genetic landscape of ESCC, whole exome sequencing was performed on 113 pairs of tumor and normal DNA samples collected from Chinese individuals with treatment-naive primary ESCC, along with 8 cell lines, including 7 from KYSE series ESCC cell lines and one immortalized esophageal squamous epithelial cell line Het-1A.

  Study EGAS00001000932

• Paediatric IBD Mosaicism

  This is a DNA sequencing study investigating genetic mechanisms underpinning childhood inflammatory bowel disease.

  Study EGAS00001002489

• Genomic analyses of gynecologic carcinosarcomas reveal frequent mutations in chromatin remodeling genes

  Malignant Mixed Müllerian Tumors, also known as carcinosarcomas, are rare tumors of gynecological origin. Here we perform whole exome analyses of 22 tumors using massively parallel sequencing to determine the mutational landscape of this tumor type. On average, we identify 43 mutations per tumor, excluding four cases with a mutator phenotype that harbored inactivating mutations in mismatch repair genes. In addition to mutations in TP53 and KRAS, we identify genetic alterations in chromatin remodeling genes, ARID1A and ARID1B, in histone methyltransferase MLL3, in histone deacetylase modifier SPOP, and in chromatin assembly factor BAZ1A, in nearly two thirds of cases. Alterations in genes with potential clinical utility are observed in more than three quarters of the cases and included members of the PI 3-kinase and homologous DNA repair pathways. These findings highlight the importance of the dysregulation of chromatin remodeling in carcinosarcoma tumorigenesis and suggest new avenues for personalized therapy.

  Study EGAS00001000941

• Mechanisms_of_patient_response_to_Dabrafenib_in_Melanoma

  Samples will be from the BRF113683 (BREAK-3) study which is a Phase III Randomized, Open-label Study Comparing GSK2118436 to Dacarbazine (DTIC) in Previously Untreated Subjects With BRAF Mutation Positive Advanced (Stage III) or Metastatic (Stage IV) Melanoma (n=250 enrolled)•NGS [Agilent capture (Sanger V2 panel): 360 genes and 20 gene fusions; Illumina HiSEQ Sequencing]•CNV: [via NGS or Affy SNP 6.0 or Illumina Omni (TBD)]Bioinformatics: Analysis will be performed using core Sanger informatics pipelines similar to those previously described (Papaemmanuil E et al. (2013) Blood. 22:3616 -3627). Briefly, copy number analysis will be performed using the ASCAT algorithm, and base substitutions, small insertions and deletions using the CAVEMAN and Pindel algorithms, respectively. Statistical approaches including generalized linear models will be used to predict clinical variables such as maximum clinical response and duration of response using genetic data. Sanger and EBI to conduct analysis; Raw data and correlation with clinical endpoints to be analyzed by both EBI/Sanger and GSK (unique pipeline analyses to increase call confidence)

  Study EGAS00001000946