4119 results for "*oma"

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• The Precision Medicine in Liver Cancer across an Asia-pacific NETwork (PLANET)

  Hepatocellular carcinoma (HCC) is the 2nd most important cause of cancer deaths in the world. The outcomes of treatment in HCC are poor compared to other common cancers because there are no good systemic therapy drugs. We designed a prospective study that will involve 5 different sites within the established Asia-Pacific Hepatocellular Carcinoma Trials Group to study both the genetics as well as immune profiles of HCC in different ethnicities. In this study, patients will be followed-up and at recurrence the tissues to understand the evolution of disease progression. Here, we presented both the genomic (DNA) and phenotypic (RNA) evolution for the first batch of 56 patients. The detailed findings will be listed in the corresponding publication soon.

  Study EGAS00001003813

• Tracing early predictors of glioma evolution under therapy

  Clonal evolution drives cancer progression and therapeutic resistance. Recent studies revealed divergent longitudinal trajectories in gliomas, but early molecular traits steering post-treatment cancer evolution remain unclear. We analyzed sequencing data of 544 initial-recurrent adult diffuse glioma pairs to identify genomic and transcriptomic early predictors of tumor evolution in each molecular subtype.

  Study EGAS00001006894

• Sequencing of longitudinal glioma pairs

  Clonal evolution drives cancer progression and therapeutic resistance. Recent studies revealed divergent longitudinal trajectories in gliomas, but early molecular traits steering post-treatment cancer evolution remain unclear. We analyzed sequencing data of 544 initial-recurrent adult diffuse glioma pairs to identify genomic and transcriptomic early predictors of tumor evolution in each molecular subtype.

  Dataset EGAD00001009845

• The Leeds Melanoma Cohort gene expression data access committee

  Dac EGAC00001000893

• Sequencing data for oesophageal and related samples - Abbas et al (WGS)

  Data supporting: "Mutational signature dynamics shaping the evolution of oesophageal adenocarcinoma" Abbas et al (WGS for 1397 samples)

  Dataset EGAD00001011196

• Sequencing data for oesophageal and related samples - Abbas et al (RNA)

  Data supporting: "Mutational signature dynamics shaping the evolution of oesophageal adenocarcinoma" Abbas et al (RNA for 197 samples)

  Dataset EGAD00001011269

• Single-cell RNA-seq and spatial transcriptomics data for the sarcoidosis baseline project

  Granulomas are lumps of immune cells that can form in various organs. Most granulomas appear unstructured, yet they have some resemblance to lymphoid organ formation. To better understand granuloma formation, we performed single-cell sequencing and spatial transcriptomics on granulomas from patients with sarcoidosis and bioinformatically reconstructed the underlying gene-regulatory networks. We discovered an immune stimulatory environment in granulomas that repurposed transcriptional programs associated with lymphoid organ development. Granuloma formation followed characteristic spatial patterns and involved genes linked to immunometabolism, cytokine and chemokine signaling, and extracellular matrix remodeling. Three cell types emerged as key players in granuloma formation: metabolically reprogrammed macrophages, cytokine-producing Th17.1 cells, and fibroblasts with inflammatory and tissue remodeling phenotypes. Pharmacological inhibition of one of the identified processes attenuated granuloma formation in a sarcoidosis mouse model. We show that human granulomas adopt characteristic aspects of normal lymphoid organ development in aberrant combinations, indicating that granulomas constitute aberrant lymphoid organs.

  Study EGAS00001006970

• Methylome profiling of Solitary fibrous tumor/Hemangiopericytoma (SFT/HPC) and a patient derived cell-line model

  Solitary fibrous tumor/Hemangiopericytoma (SFT/HPC) is a rare subtype of soft tissue sarcoma associated with NAB2-STAT6 gene fusions. This study established and characterized a novel SFT/HPC patient-derived cell line called SFT-S1 using the twist human methylome panel.

  Study EGAS50000000026

• Evaluating potential drug candidates for the treament of Henamgiopericytoma on patient derived cell line models

  Solitary fibrous tumor/Hemangiopericytoma (SFT/HPC) is a rare subtype of soft tissue sarcoma associated with NAB2-STAT6 gene fusions. This study established and characterized a novel SFT/HPC patient-derived cell line called SFT-S1. Potential drug candidates that could be repurposed for the treatment of SFT/HPC were screened.

  Study EGAS50000000027

• Whole genome sequencing of Sinonasal hemangiopericytoma and patient derived cell line model

  Solitary fibrous tumor/Hemangiopericytoma (SFT/HPC) is a rare subtype of soft tissue sarcoma associated with NAB2-STAT6 gene fusions. This study established and characterized a novel SFT/HPC patient-derived cell line called SFT-S1 using whole genome sequencing.

  Study EGAS50000000025

• Methylome profiling of Solitary fibrous tumor/Hemangiopericytoma (SFT/HPC) and a patient derived cell-line model

  Solitary fibrous tumor/Hemangiopericytoma (SFT/HPC) is a rare subtype of soft tissue sarcoma associated with NAB2-STAT6 gene fusions. This study established and characterized a novel SFT/HPC patient-derived cell line called SFT-S1 using the twist human methylome panel.

  Dataset EGAD50000000040

• Evaluating potential drug candidates for the treament of Henamgiopericytoma on patient derived cell line models

  Solitary fibrous tumor/Hemangiopericytoma (SFT/HPC) is a rare subtype of soft tissue sarcoma associated with NAB2-STAT6 gene fusions. This study established and characterized a novel SFT/HPC patient-derived cell line called SFT-S1. Potential drug candidates that could be repurposed for the treatment of SFT/HPC were screened. Screening was performed through RNA-Seq

  Dataset EGAD50000000039

• Whole genome sequencing of Sinonasal hemangiopericytoma and patient derived cell line model

  Solitary fibrous tumor/Hemangiopericytoma (SFT/HPC) is a rare subtype of soft tissue sarcoma associated with NAB2-STAT6 gene fusions. In this study, a novel SFT/HPC was characterized using whole genome sequencing.

  Dataset EGAD50000000038

• Single-cell multi-omic analysis of control and glioblastoma samples from the brain and border regions.

  Single-cell RNA-sequencing. Some samples were analyzed using CITE-Seq and samples were multiplexed and run on the same 10X reaction

  Dataset EGAD50000000045

• Origination of Ovarian Cancer is Dependent on Specific Aneuploidy Landscape

  Ovarian high-grade serous carcinoma (HGSC), a highly chromosomally instable malignancy, develops through sequential stages of precursors in fallopian tubes including histologically unremarkable but TP53 mutated clones (p53 signature) and serous tubal intraepithelial carcinoma (STIC). Here, we applied RealSeqS to assess aneuploidy in 127 microdissected tubal regions. We found nearly all p53 signatures lost the entire Chr17 chromosome, offering a “two-hit” mechanism of both TP53 and BRCA1 in BRCA1 germline mutation carriers. Proliferatively active STICs harbor gains of 19q12 (CCNE1), 19q13.2, 8q24 (MYCyc), or 8q arm, while proliferatively dormant STICs show 22q loss. Based on aneuploidy patterns in a training set (n= 67), we developed an algorithm, REAL-FAST, to classify NFTE and STICs into 5 clusters. In an independent validation set (n= 72), REAL-FAST was able to detect STIC/HGSC with high sensitivity and specificity. Taken together, REAL-FAST promises a molecular test for diagnosing HGSC precursor lesions based on specific aneuploidy patterns.

  Study EGAS00001007220

• Biallelic HMBS Inactivation Defines a Homogenous Clinico-Molecular Subtype of Hepatocellular Carcinoma

  Acute intermittent porphyria (AIP), caused by heterozygous germline mutations of the heme synthesis pathway enzyme HMBS (hydroxymethylbilane synthase), confers high risk of hepatocellular carcinoma (HCC) development. Yet, the role of HMBS in liver tumorigenesis remains unclear. Here we explore HMBS alterations in a large series of 758 HCC. We identify recurrent bi-allelic HMBS inactivation, both in AIP patients acquiring a second somatic HMBS mutation and in sporadic HCC with two somatic hits. HMBS alterations are enriched in truncative mutations, in particular in splice regions, leading to abnormal transcript structures. Bi-allelic HMBS inactivation results in a massive accumulation of its toxic substrate porphobilinogen and synergizes with CTNNB1 activating mutations, leading to the development of well differentiated tumors with a transcriptomic signature of Wnt/ß-catenin pathway activation and a DNA methylation signature related to ageing. HMBS-inactivated HCC mostly affect females, in absence of fibrosis and classical HCC risk factors. These data identify HMBS as a tumor suppressor gene whose bi-allelic inactivation defines a homogenous clinical and molecular HCC subtype.

  Study EGAS00001005986

• Single cell multi-omic study of H3-K27M mutant diffuse midline glioma across age and location

  Histone 3 lysine27-to-methionine (H3-K27M) mutations most frequently occur in childhood diffuse midline gliomas (DMGs) of the pons, but are also increasingly recognized in adult DMGs. Their potential heterogeneity at different ages and midline locations are vastly understudied. Here, through dissecting the single-cell transcriptomic, epigenomic and spatial architectures of a comprehensive cohort of patient H3-K27M DMGs, we delineate how age and anatomical location shape glioma cell-intrinsic and -extrinsic features in light of the shared driver mutation. We conducted multi-omic profiling of 50 H3-K27M mutant patient tumors. We performed deep full-length Smart-seq2 fresh single-cell (n=18) or frozen single-nucleus (n=25) RNA-sequencing (sc/snRNA-seq) of 43 tumors). We additionally analyzed the open chromatin profiles of 8 tumors utilizing the single-cell/nucleus assay for transposase-accessible chromatin using sequencing (snATAC-seq)

  Study EGAS00001006994

• Biallelic HMBS Inactivation Defines a Homogenous Clinico-Molecular Subtype of Hepatocellular Carcinoma

  Dataset EGAD00001009745

• Single-cell RNA-sequencing of H3-K27M diffuse midline glioma.

  Fastq files are deposited for single-cell transcriptomes of patient H3-K27M diffuse midline gliomas, generated using the SMART-seq2 method.

  Dataset EGAD00001011339

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: Kidney (1)

  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.

  Dataset EGAD00001006427

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

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

  Dataset EGAD00001006732

• MutWP1 CRUK Grand Challenge Mutographs of Cancer Colorectal

  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.

  Dataset EGAD00001007510

• Whole genome, exome and RNA sequencing of TFCP2-rearranged rhabdomyosarcoma

  Whole genome, exome and RNA sequencing of TFCP2-rearranged rhabdomyosarcoma, 86 samples of paired fastq files, sequenced on: Illumina HiSeq 2500 using Agilent SureSelect WGS, Illumina HiSeq 2500 using Illumina TruSeq RNA, Illumina HiSeq 2500 using Agilent SureSelect v5 WES (+UTRs), Illumina HiSeq 4000 using Agilent SureSelect WGS, Illumina HiSeq 4000 using Illumina TruSeq stranded mRNA Kit, Illumina HiSeq 4000 using Agilent SureSelect v5 WES stranded mRNA Kit, Illumina NovaSeq 6000 using Illumina TruSeq Stranded mRNA, Illumina NovaSeq 6000 using Illumina TruSeq Nano DNA, Illumina HiSeq X Ten using TruSeq Nano DNA.

  Dataset EGAD00001010108

• Methylation profiling of sarcoma and TFCP2-rearranged rhadomyosarcoma samples

  Methylation profiling of 345 sarcoma and TFCP2-rearranged rhadomyosarcoma samples, using the approach described "Genomic, transcriptomic, functional, and mechanistic characterization of rhabdomyosarcoma with FUS-TFCP2 or EWSR1-TFCP2 fusions"

  Dataset EGAD00010002451

• CGMH-OCCC-WES

  CGMH-OCCC-WES data (tumor-normal paired) from 104 patients with ovarian clear cell carcinoma.

  Dataset EGAD50000000048