4911 results for "*oma"

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• High-resolution structural genomics reveals new therapeutic vulnerabilities in glioblastoma

  We investigated the role of 3D genome architecture in instructing functional properties of glioblastoma stem cells (GSCs) by generating the highest-resolution 3D genome maps to-date for this cancer. Integration of DNA contact maps with chromatin and transcriptional profiles identified specific mechanisms of gene regulation, including individual physical interactions between regulatory regions and their target genes. Residing in structurally conserved regions in GSCs was CD276, a gene known to play a role in immuno-modulation. We show that, unexpectedly, CD276 is part of a stemness network in GSCs and can be targeted with an antibody-drug conjugate to curb self-renewal, a key stemness property. Our results demonstrate that integrated structural genomics datasets can be employed to rationally identify therapeutic vulnerabilities in self-renewing cells.

  Study EGAS00001003493

• Ewings_Sarcoma_Rearrangement_Screen

  Cancer is driven by mutations in the genome. We will uncover the mutations that give rise to Ewing’s sarcoma, a bone tumour that largely affects children. We will use second generation Illumina massively parallel sequencing, and bespoke software, to characterise the genomes and transcriptomes of Ewings’ sarcoma tumours.

  Study EGAS00001000362

• 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

• Onco-exaptation of an Endogenous Retroviral LTR Drives IRF5 Expression in Hodgkin Lymphoma

  The transcription factor interferon regulatory factor 5 (IRF5) is upregulated in Hodgkin lymphoma (HL) and a key regulator of the aberrant transcriptome characteristic of this disease. Here we show that IRF5 upregulation in HL is driven by transcriptional activation of a normally dormant endogenous retroviral LOR1a long terminal repeat (LTR) upstream of IRF5. Specifically, through screening of RNA-seq libraries, we detected LTR-IRF5 chimeric transcripts in multiple HL cell lines but not in normal B-cell controls. In HL, the LTR was in an open and hypomethylated epigenetic state and we further show the LTR is the site of transcriptional initiation. Among HL cell lines, usage of the LTR promoter strongly correlates with overall levels of IRF5 mRNA and protein, indicating that LTR transcriptional awakening is a major contributor to IRF5 upregulation in HL. Taken together, oncogenic IRF5 overexpression in HL is the result of a specific LTR transcriptional activation. We propose that such LTR derepression is a distinct mechanism of oncogene activation (“onco-exaptation”) and that such a mechanism warrants further investigation in molecular and cancer research.

  Study EGAS00001001205

• Evolution of GBM through therapy

  Primary glioblastoma (GBM) tumours recur following treatment. This is likely due to intratumour heterogeneity (ITH), which reduces the effectiveness of cancer therapies by enabling therapy-driven tumour evolution: Darwinian selection of genotypically and/or phenotypically distinct cells (subclones) that resist treatment to seed regrowth of an even less treatable recurrence. To investigate this we sequenced a pilot cohort of nine paired primary and locally recurrent GBM tumours, alongside matched blood samples, in order to begin characterising therapy resistant cells and thereby infer the mechanisms by which they evaded treatment. These data were included in the first data release from the Glioma Longitudinal AnalySiS (GLASS) consortium.

  Study EGAS00001003546

• Automated system for scoring hematoxylin and eosin-stained ovarian cancer sections by identifying single cells uncovered that stromal cell ratio is a significant predictor for overall survival and progression-free survival.

  Concerted efforts in genomic studies have revealed profound insights in prognostic ovarian cancer subtypes. On the other hand, abundant histology slides have been generated to date, yet their uses remain very limited and largely qualitative. Our goal is to develop automated histology analysis as an alternative subtyping technology for ovarian cancer that is cost-efficient and do not rely on DNA quality. We develop an automated system for scoring hematoxylin and eosin-stained (H&E) primary tumour sections of 91 late-stage ovarian cancer to identify single cells including cancer and stromal cells. We demonstrated high accuracy of our system based on expert pathologists’ scores (cancer=97.1%, stromal=89.1%) as well as compared to immunohistochemistry scoring (correlation=0.87). Quantitative stromal cell ratio is significantly associated with poor overall survival after controlling for clinical parameters including debulking status and age (multivariate analysis p=0.0021, HR=2.54, CI=1.40-4.60) and progression-free survival (multivariate analysis p=0.022, HR=1.75, CI=1.09–2.82). We demonstrate how automated image analysis enables objective quantification of microenvironmental composition of ovarian tumours. Our analysis reveals a strong effect of the tumour microenvironment on ovarian cancer progression and highlights the potential of therapeutic interventions that target the stromal compartment or cancer-stroma signalling in the stroma-high, late-stage ovarian cancer subset.

  Study EGAS00001001694

• Revealing active mutational processes in tumours using DigiPico/MutLX at unprecedented accuracy

  Active mutational processes in a tumor result in genetic micro-heterogeneity that can determine the tumor’s evolutionary trajectory. Identification of these processes by studying micro-heterogeneity can unveil novel aspects of tumor evolution with potential therapeutic implications. Such studies, however, are inherently problematic because of the discovery of excessive false positive mutations. Here we report the optimization and validation of a robust whole genome sequencing and analysis pipeline (DigiPico/MutLX) that virtually eliminates false positive results. Using our method, we identified, for the first time, a sub-clonal local hyper-mutation (kataegis) event in a recurrent ovarian carcinoma, which was unidentifiable from the bulk WGS data of the same tumor. Overall, we propose DigiPico/MutLX method as a powerful framework for the reliable study of genetic micro-heterogeneity in tumor and normal tissues.

  Study EGAS00001003555

• Single cell transcriptomic and genomic profiling of carcinogenesis in patients with familial adenomatous polyposis

  Familial Adenomatous Polyposis (FAP) is characterized by hundreds to thousands of adenocarcinomas at different evolutional stages in the colon and rectum. Much effort has been made to illuminate the key genomic alterations that facilitate the transition from adenoma to carcinoma. However, the strong heterogeneity of the tumors may hamper these efforts. Here, by sequencing matched adjacent normal tissues, adenomas at different stages and carcinomas from the same patient, we precisely traced the process of colorectal carcinogenesis. Our study offers an accurate genomic landscape during the initiation and progression of carcinogenesis, especially for the transition between adenomas and carcinomas.

  Study EGAS00001003598

• Analysis of copy number variation landscape of glioma by shallow coverage whole genome sequencing

  We reported shallow coverage whole genome sequencing (WGS) is an economic method for identification of whole genome somatic copy number variation (SCNV). Combining with a Taqman low density array (TLDA) designed for molecular subtyping of glioma, it enabled classification of glioma into biological entities with different cellular origin and genomic alterations. Further, we also showed shallow-coverage WGS enabled systematic identification of clonal and subclonal SCNV in glioma genomes and the burden and pattern of SCNV can serve as an objective marker of tumor progression and predict risk and relapse.

  Study EGAS00001003690

• Integrated genomic, transcriptional and epigenomic analyses in germinal center-cell lymphomas link the mutation landscape with differential DNA methylation in Burkitt lymphoma

  Biologically and clinically diverse B-cell neoplasms, including Burkitt, follicular and diffuse large B-cell lymphoma, show features of germinal center (GC) B-cells. Here we present a comprehensive analysis of the epigenetic landscape of GC-B-cell lymphomas using whole genome bisulfite sequencing paired with genome and transcriptome sequencing from 29 primary tumor samples and four normal GC-B-cell samples. All lymphomas studied showed extensive genome-wide methylation losses as well as intragenic regions where DNA methylation levels were strongly correlated with expression of associated genes. Pathway analysis revealed that these intragenic regions were enriched in signaling networks differentially activated in Burkitt and follicular lymphomas and affected regulatory mechanisms deregulated by recurrent mutations in a large fraction of Burkitt lymphomas (including the ID3/TCF3 complex, the SWI/SNF remodeling complex and the inhibitory GI signaling pathway). Taken together, these results provide a global picture of Burkitt lymphoma pathomechanism and demonstrate a tight connection between epigenetic regulation and other levels of regulatory control in these tumors.

  Study EGAS00001001067