4842 results for "*oma"

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• Somatic whole exome sequencing of a hypermutated gliosarcoma case

  The dataset includes the whole-exome sequencing (WES) of an extramedullary tumor anterior to the spinal cord at T4, which was resected and diagnosed as gliosarcoma. The patient initially diagnosed with a low-grade brain glioma via biopsy, followed by adjuvant radiation and temozolomide treatment. WES was performed using Illumina NovaSeq6000 with 2x100 bp reads. Mean coverage of 152.4x and 230.6x was achieved for normal and tumor, respectively.

  Dataset EGAD00001006816

• WGS of Glioblastoma stem cells (Sachamitr et al)

  WGS of 17 GSC populations derived from patient tumours

  Dataset EGAD00001006848

• Mutational signatures in esophageal squamous cell carcinoma from eight countries of varying incidence – sequence data (Mutographs)

  Mutational signatures in esophageal squamous cell carcinoma from eight countries of varying incidence – sequence data (Mutographs)

  Dataset EGAD00001006868

• Dedifferentiated Melanoma (2021-02-02)

  De- and transdifferentiation of melanoma is a rare histopathological phenomenon that has not be characterised genetically. In this project we plan to sequence the genomes of de and transdifferentiated cases so as to define their genetic make-up. . This dataset contains all the data available for this study on 2021-02-02.

  Dataset EGAD00001006931

• Cryopreservation of human cancers conserves tumour heterogeneity for single-cell multi-omics analysis

  Single-cell RNA-Sequencing of three primary breast cancers, two primary prostate cancers, and a metastatic melanoma sample from Wu et al. (2021) Genome Medicine study. Each tumour was sequenced across different cryopreservation conditions including Fresh Tissue (FT), cryopreserved single-cell suspensions (CCS), cryopreserved solid tissue fragments (CT) and a cryopreserved after overnight cold storage (CO). Data was generated using the Chromium controller (10X Genomics) and sequenced on the NextSeq platform.

  Dataset EGAD00001007030

• Dataset of whole-exome sequencing of clonally related neuroblastoma and teratoma

  This dataset includes bam files of WES of clonally related neuroblastoma and teratoma as well as peripheral blood samples as a control. Neuroblastoma and teratoma samples were formalin-fixed paraffin embedded.

  Dataset EGAD00001007039

• Multiple Myeloma ChipSeq data on six histone modifications

  The data contained in this dataset is ChipSeq BAM files aligned to reference genome hg38. The ChipSeq was based on a combination of six histone modifications as follows: H3K4me1, H3K4me3, H3K9me3, H3K27me3, H3K27Ac and H3K36me3. The samples are patient-derived xenografts generated by passaging primary patient CD138+ selected cells through the SCID-rab myeloma mouse model.

  Dataset EGAD00001008353

• Exploring the driver events of eccrine poromas and porocarcinomas: A retrospective, cross-institutional study of 90 cases

  Eccrine poroma (EP) and porocarcinoma (EPC) are rare benign and malignant adnexal neoplasms of the terminal sweat gland duct, respectively. Both can arise de novo, however, EPCs can also arise from a pre-existing EP. To-date, genetic investigation of these tumors has involved studies with small sample sizes and/or limited analyses. To comprehensively compare the driver events and mutational landscape of these tumors, we performed a retrospective multi-institutional whole-exome sequencing and RNA sequencing study on the largest cohort of EPs and EPCs to-date (n=90). We uncovered novel events and delineated different pathways of tumorigenesis underlying these tumors, with EPs driven largely by fusion genes, and EPCs driven largely by somatic mutations, with rare YAP1 and frequent PAK gene novel fusions.

  Dataset EGAD00001015376

• Genome and transcriptome sequence data from a metastatic carcinoma of the lung patient

  Genome and transcriptome sequence data from a metastatic carcinoma of the lung patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002983

• Djerroudi et al., E-cadherin inactivation shapes tumor microenvironment specificities in invasive lobular carcinoma

  Invasive lobular breast carcinoma (ILC) shows specific stromal features, T lymphocyte infiltration (TIL) being associated with poor prognosis. Here, we reveal the involved mechanism by performing single cell RNA sequencing, combined immunohistochemistry, deconvolution of bulk RNA sequencing from large retrospective ILC series, and functional assays using primary cells. We show that ILC accumulate FAP+ inflammatory cancer-associated fibroblasts (iCAF) through a previously undescribed mechanism mediated by E-cadherin/CDH1 on CAF plasticity. Indeed, CDH1 inactivation in ILC cancer cells prevents differentiation of iCAF into myofibroblastic CAF (myCAF), leading to iCAF accumulation. In turn, iCAF increase TIL infiltration and shape their spatial organization in ILC. Subsequently, CDH1-inactivated ILC cancer cells promote immune escape by lack of retention and activation of ITGAE-expressing resident memory CD8+ T lymphocytes (TRM). Hence, our study uncovers reciprocal interactions between CDH1-inactivated cancer cells, iCAF and CD8+ TRM, revealing why and how TILs have a poor prognosis in ILC patients, a mechanism extrapolated to other CDH1-mutated cancer types.

  Study EGAS50000000761

• Single-cell RNAseq data from 6 Invasive Lobular Carcinoma (ILC)

  Fastq files of single-cell RNAseq data from from Cancer Associated Fibroblasts (CAFs), cancer cells and immune cells isolated from 6 primary Invasive Lobular Carcinomas (ILCs)

  Dataset EGAD50000001121

• Balanced_Brain_Tumour_Whole_Genome_Sequencing

  We propose to definitively characterise the somatic genetics of a number of pediatric malignant tumours including ependymoma, high grade glioma and central nervous system primitive neurectodermal tumours through generation of comprehensive catalogues of somatic mutations by high coverage genome sequencing.

  Study EGAS00001000360

• WNT7B-reporter organoids sorted

  Transcriptomic data from pancreatic ductal adenocarcinoma (PDAC) organoids to investigate the role of WNT7B. This dataset includes: - Bulk mRNA sequencing of WNT7B-reporter pancreatic ductal adenocarcinoma (PDAC) organoids sorted for cells displaying low, medium and high expression of the reporter

  Study EGAS50000001543

• PDAC organoids treated with LGK974

  Transcriptomic data from pancreatic ductal adenocarcinoma (PDAC) organoids to investigate the role of WNT7B. This dataset includes: - Bulk mRNA sequencing of LGK974 treated pancreatic ductal adenocarcinoma (PDAC) organoids from three different patients for 24h

  Study EGAS50000001542

• Personalized analysis of ctDNA for detection of molecular residual disease and recurrence in a cohort of surgically treated patients with head and neck squamous cell carcinoma

  Despite advances in multimodal treatment, survival for patients with advanced head and neck squamous cell carcinoma (HNSCC) has improved only modestly. The recent advent of tumor-informed assays capable of detecting circulating cell-free tumor DNA (ctDNA) has enabled early detection of molecular residual disease (MRD) and recurrence following curative therapy. We assessed ctDNA in plasma from 76 and saliva from 54 HNSCC patients, respectively, who received primary curative-intent surgery.

  Study EGAS50000001018

• A New CA19-9 Cut-Off Value Identifies Lewis Antigen Status and Refines Prognostic Stratification in PDAC

  This study investigates the clinical utility of serum CA19-9 levels in pancreatic ductal adenocarcinoma (PDAC), with a focus on identifying patients with Lewis antigen–negative status due to germline FUT3 variants. Using data from multicenter prospective cohorts in Taiwan, we analyzed CA19-9 classification, FUT2/FUT3 genotypes, and clinicopathological annotations. The goal of this study is to refine prognostic stratification and reduce false-negative interpretation of CA19-9 in PDAC patients. All participants provided informed consent, and the study was approved by the relevant institutional review boards.

  Study EGAS50000001575

• PDAC clinical phenotype data with CA19-9 and Lewis antigen status

  This dataset contains individual-level clinical phenotype data from patients with pancreatic ductal adenocarcinoma, including CA19-9 measurements, Lewis antigen status, and relevant clinicopathological variables. Data were generated as part of an ethically approved study and are available under controlled access.

  Dataset EGAD50000002254

• PDAC Phenotype and Germline Genotype Data Access Committee

  This Data Access Committee (DAC) is responsible for reviewing and approving requests for access to controlled phenotype metadata and derived germline FUT2/FUT3 genotype data from patients with pancreatic ductal adenocarcinoma (PDAC). Access is granted to bona fide researchers for non-commercial research purposes only, subject to approval by the DAC and in accordance with the original informed consent and applicable ethical regulations.

  Dac EGAC50000000893

• How to use the EGA search box

  Tips on how to search Tip 1: Use simple and clear keywords No matter what you are searching: a study, a dataset or a committee; the search will look recursively in all the fields of all the entities in the database. Thus, there is no need to specify which type of data you are looking for. Try to use single and specific words and avoid long and complex expressions. Try it out: cancer rna-seq instead of cancer studies using RNA-seq. Tip 2: Narrow your results using search operators Search operators give you more control over the results. They manage the way keywords are used to restrict the search. By default, the search engine applies an OR operator when a space is inserted between two words. Include AND (capitalised) between the keywords in your search in order to show only pages containing both terms. Try it out: Search all the studies based on transcriptomic data, including those ones that use RNA sequencing to obtain this data. Tip 3: Do not worry about details The search engine automatically checks for the most common spelling mistakes of given words and suggests the use of the correct version. It also ignores capital letters and most punctuation so none of these mistakes will hamper the accuracy of your search. Besides, when using a combination of words, the search engine will suggest similar combinations with a higher number of results. Tip 4: Use words that are likely to appear within the text Unfortunately, our search engine is not able to interpret words yet. Therefore, words which do not appear in the body text will not return any result despite them denoting a group of present terms. For instance, if we are looking for studies focused on neurological diseases, using neurological as a keyword would not be the best option. Instead, you should use the name of each neurological disease such as bipolar disorder, schizophrenia or depression. In the same fashion, incomplete words do not return any result. Please include an asterisk (*) before and/or after the incomplete word in order to allow for partial matching. Try it out: canc* instead of canc(without wildcard). Also you can try out *oma, or even *geneti* Tip 5: Narrow down your search by filtering the results You can filter the results by the following options: general, study, and dataset. Under these categories, you will find more sub-filters to refine your search. Make sure that you click on Apply in order to filter the results. You can clear the filtering anytime. Advanced Searches Additional example queries: Search for DUO:0000005 and word lung example query Or write: DUO:0000005 AND lung Search for an exome sequencing study in dbGaP example query Or write: study_type: "exome sequencing" AND repository:dbGaP Search for an exome sequencing study in EGA example query Or write: study_type: "exome sequencing" AND repository:ega Search for a dataset that is at the EGA beacon and with type "Whole genome sequencing" and with number of samples between 100 and 2000 and with technology "Illumina HiSeq 2000" example query Or write: is_in_beacon:true AND dataset_types:"Whole genome sequencing" AND samples:[100 TO 2000] AND dataset_technologies:"Illumina HiSeq 2000" Search for PMIDS example query Or write: pmids:32025007

  Documentation discovery/metadata/search-box

• Identification of gene mutations and fusion genes in patients with Sézary Syndrome

  Sezary syndrome (SS) is a leukemic form of cutaneous T-cell lymphoma (CTCL) with an aggressive clinical course. The goal of our study is to understand the genetic basis of the disease by looking for driver gene mutations and fusion genes in 15 erythrodermic patients with circulating Sezary cels, fourteen of them fulfilling the diagnostic criteria of SS. Peripheral blood samples were collected for each patient and CD4+ T-lymphocytes and Granulocytes were isolated. DNA and RNA was extracted for matched normal and tumor materials. Whole exome sequencing was performed on matched normal and tumor tissues of 12 patients and RNA sequencing was performed on 10 patients. For 7 of these patients, we have both exome as well as RNA sequencing data. In this study, we present a complex genomic landscape of Sezary syndrome with several point mutations, copy number variations and fusion events which could contribute to the pathogenesis of SS.

  Study EGAS00001001706

• Prognostic relevance of microenvironmental factors CD163 and CD8 combined with EZH2 and chromosome 18 gain in a validation cohort of follicular lymphoma patients of the Lunenburg Lymphoma Biomarker Consortium

  Background: In follicular lymphoma (FL), studies addressing the prognostic value of microenvironment-related immunohistochemical (IHC) markers and tumor cell-related genetic markers have yielded conflicting results, precluding implementation in practice. Therefore, the Lunenburg Lymphoma Biomarker Consortium (LLBC) performed a validation study for published markers. Methods: To maximize sensitivity, an end-of-spectrum design was applied for 122 uniformly immunochemotherapy-treated FL patients retrieved from international trials and registries; early failure (EF): progression or lymphoma-related death <2 years versus long remission: response duration of >5 years. IHC staining for T-cells and macrophages was performed on tissue microarrays from initial biopsy and scored with a validated computer-assisted protocol. Shallow whole-genome and deep targeted sequencing was performed on the same samples. Results: 96/122 cases with complete molecular and immunohistochemical data were included in the analysis. EZH2 wild-type (p=0.006), gain of chromosome 18 (p=0.002), low percentages of CD8+ cells (p=0.011) and CD163+ areas (p=0.038) were associated with EF. No significant differences in other markers were observed, thereby refuting previous claims on their prognostic significance. Conclusion: Using an optimized study design, this LLBC study validates wild-type EZH2 status, gain of chromosome 18, low percentages of CD8+ cells and CD163+ area as predictors of EF to immunochemotherapy in FL.

  Study EGAS00001002049

• MutWP1__CRUK_Grand_Challenge_Mutographs_of_Cancer__clear_cell_renal_cell_carcinoma

  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 EGAS00001002608

• Preferential infiltration of distinct Vγ9δ2 T cells into Glioblastoma multiforme

  Glioblastoma multiforme (GBM), the most fatal CNS cancer, is highly infiltrative as a result of phenotypic alteration of cancer cells mainly driven by a mutual interaction among cancer cells, tumor-associated macrophages (TAMs) and other stromal cells. This work aims at characterizing GBM-infiltrating γδ T cells that may regulate the GBM tumor microenvironment and cancer cell gene expression. V(D)J repertoires of tumor-infiltrating and blood circulating γδ T cells from 4 patients were analyzed by NGS-based TCR sequencing. RNA gene expression profiling and immunostaining of cancer tissues were performed as well.

  Study EGAS00001002790

• Pan-neuroblastoma analysis reveals age- and signature-associated driver alterations

  Neuroblastoma is a pediatric malignancy with heterogeneous clinical outcomes depending on age and other factors. To better understand neuroblastoma pathogenesis, here we analyze whole-genome, whole-exome and/or transcriptome sequencing data from 702 neuroblastoma samples, half of which are new data. Over 95% of samples harbor at least one recurrent driver alteration and most aberrations, including MYCN, ATRX, and TERT alterations, differ in frequency by age. MYCN alterations occur at median 2.3 years of age, TERT at 3.8 years, and ATRX at 5.6 years, suggesting age-specific susceptibility to genetic alterations. Mutational signature analysis shows that reactive oxygen-species (ROS)-induced mutations are the most common cause of single nucleotide variant (SNV) drivers in neuroblastoma, including most ALK and Ras pathway SNVs. ROS-induced mutagenesis is both an early event, as it causes truncal variants, and continuous as it also induces relapse-specific mutations. ROS-induced mutations are more abundant in neuroblastomas with MYCN amplification, 17q gains, and increased expression of mitochondrial ribosome genes. We observe recurrent FGFR1 N546K or internal tandem duplication variants in 6 patients and ALK N-terminal structural alterations in 5 samples, identifying additional patients amenable to precision therapy.

  Study EGAS00001003931

• Lindsey E. Jones et al. Patient-derived cells from recurrent tumors that model the evolution of IDH-mutant glioma. Neuro-Oncology Advances, 2020. We established robust, versatile, and well-characterized Patient Derived Cells (PDC) of an IDH1-mutant astrocytoma and an IDH1-mutant oligodendroglioma that represents defined evolutionary stages of chemotherapy-induced hypermutation. The PDCs retain tumor subtype defining features over time as well as classic hallmarks of cancer, including anchorage independent growth and cell immortality. The integrated phylogenies composed of PDCs,single-cell-derived PDCs, patient-derived xenografts, and corresponding spatiotemporal tumor tissue samples also provide new insight into the clonality, evolutionary pattern, and immense mutational load of hypermutated IDH mutant gliomas.

  IDH-mutant lower-grade gliomas can undergo malignant progression via temozolomide-driven hypermutation. Patient-derived cells (PDC) that model the genetically distinct hypermutated (HM) tumor subgroup are generally lacking, and few if any human brain tumor cell models are from defined evolutionary time points. Here, we characterize multiple PDC derived from independent surgical specimens of IDH1-mutant recurrences, including an ATRX and TP53-mutant astrocytoma and a 1p/19q co-deleted and TERT promoter-mutant oligodendroglioma. We determined the evolutionary time points represented by each PDC using exome sequencing and phylogenetic reconstruction, comparing the PDC and single cell clones of the PDC (scPDC) to multiple spatiotemporal tumor tissue samples, PDC-derived xenografts (PDX) and patient-matched blood. The tumor samples exhibited TMZ-induced mutagenesis and a branching pattern of evolution. We found clear evidence of two fully independent founder HM clones in the tumor tissue that are faithfully represented by independent PDC. The PDC, scPDC and PDX also shared the mutagenesis signature and represent the mid and later evolutionary time points of their corresponding tumors. The PDC maintained the tumor subtype-defining features over many passages, including heterozygosity of the IDH1 R132H mutation, production of 2-hydroxyglutarate (2-HG), and subtype-specific telomere maintenance mechanisms. The PDC from both tumors exhibited anchorage-independent growth in soft agar. The oligodendroglioma PDC formed infiltrative intracranial tumors with characteristic oligodendroglioma histology, initially with a long period to tumor formation. We conclude that the PDC, scPDC and PDX faithfully model the heterogeneous clonal origins of the corresponding tumor tissue. The multilevel analysis also provides new insight into the intratumoral heterogeneity and vast mutational load of HM glioma. The PDC from multiple evolutionary time points presented in the context of full clinical timelines may be useful to model evolution and intratumoral heterogeneity, important sources of therapeutic failure.

  Study EGAS00001003992