4894 results for "*oma"

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• Germline and somatic SMARCA4 mutations characterize small-cell carcinoma of the ovary, hypercalcemic type.

  Small-cell carcinoma of the ovary, hypercalcemic type (SCCOHT) is the most common undifferentiated ovarian malignancy in women under 40 years1. We sequenced the exomes of six individuals from three SCCOHT families. After discovering segregating deleterious germline mutations in SMARCA4 in all three families, we tested DNA from a fourth family, which also possessed a segregating SMARCA4 germline mutation. All familial tumors sequenced harboured either a somatic mutation or loss of the wild-type allele. Immunohistochemical (IHC) analysis of these and additional familial and non-familial cases showed loss of the SMARCA4 protein (BRG1) in 38/40 tumors overall. Sequencing of cases with available DNA revealed at least one germline or somatic deleterious SMARCA4 mutation in 30/32 cases. Additionally, the SCCOHT cell line BIN-67 contained bi-allelic deleterious mutations in SMARCA4. Our findings identify alterations in SMARCA4 as the major cause of SCCOHT, which could lead to genetic counseling and new treatment approaches.

  Study EGAS00001000721

• Spatial transcriptomics analysis of HPV-dependent and HPV-independent vulval squamous cell carcinoma

  In this study we have used sequencing-based spatial transcriptomics (ST) optimised for FFPE tissue to investigate gene expression in a cohort of HPVi and HPVd VSCC, including assessment of pre-invasive LS, HSIL and DVIN and associated inflammation. Our data indicate significant differences in gene expression between VSCC of different aetiologies, with marked differences in immune-related gene expression both within the invasive disease and in peri-tumoural inflammatory areas.

  Study EGAS00001007981

• ICGC Oesophageal adenocarcinoma - normal samples

  The oesophageal project will focus on adenocarcinoma which is increasing in incidence in the UK and other developed countries and has a very poor outcome. The primary aims of this project are to deeply sequence tumour and normal genomic DNA (including the precursor condition Barrett’s oesophagus when material is available) to provide a comprehensive catalogue of somatic mutations. This will be achieved through a UK-wide network of hospitals involved in a research collaboration called the OCCAMS consortium. The goal of this project is to use high quality clinical material with accurately annotated clinic-pathological, treatment and outcome data. - This study contains the Normal tissue samples.

  Study EGAS00001000723

• Integrated genetic and epigenetic analysis defines novel molecular clusters in rhabdomyosarcoma

  Rhabdomyosarcoma (RMS) is the most common soft tissue sarcoma in childhood. To unravel the genetic/epigenetic basis of RMS, we studied 60 RMS cases using whole exome/transcriptome sequencing, copy number (CN) profiling, and DNA methylome analysis. Based on DNA methylation patterns, RMS was clustered into 4 distinct subtypes, which exhibited remarkable correlation with mutation/CN profiles, histological phenotypes, and clinical behaviors. A1 and A2 subtypes, especially A1, largely corresponded to alveolar histology with frequent PAX3/7 fusions and alterations in cell cycle regulators. In contrast, mostly showing embryonal histology, both E1 and E2 subtypes were characterized by high frequency of CN alterations and/or allelic imbalances, FGFR4/RAS/AKT pathway mutations and PTEN mutations/methylation and in E2, also by p53 inactivation. Despite generally poor prognosis in RMS, patients in E1 cluster exceptionally showed excellent prognosis. Our results highlight the close relationship between DNA methylation status and gene mutations and biological behavior in RMS.

  Study EGAS00001000884

• Single cell RNA sequencing of CD19 CAR T-cell infusion products

  We performed single cell RNA sequencing of remnants from CD19 CAR T-cell infusion products used for standard of care treatment for relapsed/refractory large B-cell lymphoma. Libraries were prepared using 10X 5’ GEX chemistry and sequenced on an Illumina HiSeq 4000 to obtain >50,000 reads per cell.

  Study EGAS00001004576

• Intratumoural Heterogeneity Underlies Distinct Therapy Responses and Treatment Resistance in Glioblastoma

  Glioblastomas are the most common and lethal neoplasms of the central nervous system. Neighbouring glioma cells maintain extreme degrees of genetic and phenotypic variation that forms intratumoural heterogeneity. This genetic diversity allows the most adaptive tumour clones to show treatment resistance and conserve the tumour bulk. We aimed to model this phenomenon and test the effectiveness of several targeted therapeutic interventions to overcome therapy resistance. Heterogenic tumour masses were first deconstructed into single tumour cells, which were expanded independently as single-cell clones. SNP arrays, whole-genome and RNA sequencing, and CpG methylation analysis validated the unique molecular profile of each tumour clone, which displayed distinct pathologic features, including cell morphology, growth rate, and resistance to temozolomide and ionizing radiation. We also identified variable sensitivities to AURK, CDK, and EGFR inhibitors, consistent with the heterogenic molecular alterations that each clone harboured. These targeted therapies effectively eliminated the temozolomide- and/or irradiation-resistant clones and also parental polyclonal cells. Our findings indicate that polyclonal tumours create a dynamic environment that consists of diverse tumour elements and treatment responses. Designing targeted therapies based on a range of molecular profiles can be a more effective strategy to eradicate treatment resistance, recurrence, and metastasis.

  Study EGAS00001003438

• Probabilistic cell type assignment of single-cell transcriptomic data reveals spatiotemporal microenvironment dynamics in human cancers

  Single-cell RNA sequencing (scRNA-seq) has transformed biomedical research, enabling decomposition of complex tissues into disaggregated, functionally distinct cell types. For many applications, investigators wish to identify cell types with known marker genes. Typically, such cell type assignments are performed through unsupervised clustering followed by manual annotation based on these marker genes, or via "mapping" procedures to existing data. However, the manual interpretation required in the former case scales poorly to large datasets, which are also often prone to batch effects, while existing data for purified cell types must be available for the latter. Furthermore, unsupervised clustering can be error-prone, leading to under- and over- clustering of the cell types of interest. To overcome these issues we present CellAssign, a probabilistic model that leverages prior knowledge of cell type marker genes to annotate scRNA-seq data into pre-defined and de novo cell types. CellAssign automates the process of assigning cells in a highly scalable manner across large datasets while simultaneously controlling for batch and patient effects. We demonstrate the analytical advantages of CellAssign through extensive simulations and exemplify real-world utility to profile the spatial dynamics of high-grade serous ovarian cancer and the temporal dynamics of follicular lymphoma. Our analysis reveals subclonal malignant phenotypes and points towards an evolutionary interplay between immune and cancer cell populations with cancer cells escaping immune recognition.

  Study EGAS00001003452

• PSCP_bisulphite_analysis_in_hESCs

  Many studies over the past 10 years, culminating in the recent report of the International Stem Cell Initiative (ISCI, 2011) have shown that hPSC acquire genetic and epigenetic changes during their time in culture. Many of the genetic changes are non-random and recurrent, probably because they provide a selective growth advantage to the undifferentiated cells. Some are shared by embryonal carcinoma cells, the malignant counterparts of ES cells. The origins of these growth advantages are poorly understood, but may come from altered cell cycle dynamics, resistance to apoptosis or altered patterns of differentiation. Less is known about the nature and consequences of epigenetic changes, but it is likely that these similarly affect hPSC behaviour; e.g., enhanced expression of DLK1, an imprinted gene, is associated with altered hPSC growth (Enver et al 2005). Inevitably, these genetic and epigenetic changes will impact on our ability to use hPSC for regenerative medicine, either because malignant transformation of the undifferentiated cells or their differentiated derivatives to be used for transplantation compromises safety, or because they impede the function of those differentiated derivatives, or because they affect the efficiency with which the undifferentiated cells can be expanded and differentiated into desired cell types. Focusing initially upon the existing clinical grade hESC lines, later moving to iPSC, we will Consolidate and extend knowledge of the rate, type and functional impact of the genetic variations that occur during hPSC culture. We will use whole genome and exome sequencing as well as SNP arrays, together with clonal analysis and other cytogenetics techniques. Common changes will be compared with those found in the normal human population, at low frequency in the original cell population or observed during iPSC generation in the HIPSCI project currently based at the WTSI. These studies will provide a better understanding of the range of genetic changes that occur in hPSC beyond the CNVs already identified. In conjunction with cancer genome resources and expertise at WTSI, bioinformatic analyses of these hPSC data will allow us to assess potential impact on hPSC behaviour pertinent to applications in regenerative medicine, notably the likelihood that specific changes arising in undifferentiated PSC cultures may be associated with potential malignant transformation of differentiated progeny. This 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 EGAS00001001625

• Whole-Genome and Epigenomic Landscapes of Etiologically Distinct Subtypes of Cholangiocarcinoma

  Cholangiocarcinoma (CCA) is a hepatobiliary malignancy exhibiting high incidence in countries with endemic liver-fluke infection. We analyzed 489 CCAs from 10 countries, combining whole-genome (71 cases), targeted/exome, copy-number, gene expression, and DNA methylation information. Integrative clustering defined 4 CCA clusters-fluke-positive CCAs (clusters 1/2) are enriched in ERBB2 amplifications and TP53 mutations; conversely, fluke-negative CCAs (clusters 3/4) exhibit high copy-number alterations and PD-1/PD-L2 expression, or epigenetic mutations (IDH1/2, BAP1) and FGFR/PRKA-related gene rearrangements. Whole-genome analysis highlighted FGFR2 3' untranslated region deletion as a mechanism of FGFR2 upregulation. Integration of noncoding promoter mutations with protein-DNA binding profiles demonstrates pervasive modulation of H3K27me3-associated sites in CCA. Clusters 1 and 4 exhibit distinct DNA hypermethylation patterns targeting either CpG islands or shores-mutation signature and subclonality analysis suggests that these reflect different mutational pathways. Our results exemplify how genetics, epigenetics, and environmental carcinogens can interplay across different geographies to generate distinct molecular subtypes of cancer.SIGNIFICANCE: Integrated whole-genome and epigenomic analysis of CCA on an international scale identifies new CCA driver genes, noncoding promoter mutations, and structural variants. CCA molecular landscapes differ radically by etiology, underscoring how distinct cancer subtypes in the same organ may arise through different extrinsic and intrinsic carcinogenic processes.

  Study EGAS00001001653

• MutWP1__CRUK_Grand_Challenge_Mutographs_of_Cancer__Colorectal_LCM

  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. 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 EGAS00001003455