Search Results - EGA European Genome-Phenome Archive

Invasive lobular carcinoma (ILC) is the second most common histological subtype of breast cancer accounting for 10-15% of cases. ILC differs from invasive ductal carcinoma (IDC)with respect to epidemiology, histology, and clinical presentation. Moreover, ILC is lesssensitive to chemotherapy, more frequently bilateral, and more prone to form gastrointestinal, peritoneal, and ovarian metastases than IDCs. In contrast to IDC, the prognostic value ofhistological grade (HG) in ILC is controversial. One of the three major components of histological grading (tubule formation) is missing in ILC which hinders the process of gradingin this histological subtype and results in the classification of approximately two thirds of ILC as HG 2.Over the last decade, a number of gene expression signatures have shed light onto breast cancer classification, allowing breast cancer care to become more personalized. Withrespect to the management of estrogen receptor (ER)-positive breast cancer, several gene expression signatures provide prognostic and/or predictive information beyond what is possible with current classical clinico-pathological parameters alone. Nevertheless, most studies using gene expression signature have not considered different histologic subtypesseparately. Recently, a comprehensive research program has elucidated some of the biological underpinnings of invasive lobular carcinoma. Genetic material extracted from 200 ILC tumor samples were studied using gene expression profiling and identified ILCmolecular subtypes. These proliferation-driven gene signatures of ILC appear to have prognostic significance. In particular, the Genomic Grade (GG) gene signature improved upon HG in ILC and added prognostic value to classic clinico-pathologic factors. In addition this study demonstrated that most ILC are molecularly characterized as luminal-A (~75%)followed by luminal-B (~20%) and HER2-positve tumors (~5%). Moreover, we investigated the prognostic value of known gene signatures/ gene modules in the same cohort of ILC. As a second step within the scope of this project, we aim to investigate the interactionsbetween somatic ILC tumor mutations to observed transcriptome findings. To this end, we aim to perform somatic mutation analysis for the ILC tumors for which Affymetrix gene expression profiling is available. To this end, we will use a gene screen assay, which specifically interrogates the mutational status of a few hundreds of cancer genes. We believe that this pioneering effort will be fundamental for a tailored treatment of ILC withimprovement in patients' outcome.

Dataset EGAD00001000288

Whole genome analyses of the childhood cancer neuroblastoma

Neuroblastomas are tumors of peripheral sympathetic neurons and are the most common solid tumor in children. To determine the genetic basis for neuroblastoma we performed whole-genome sequencing (6 cases), exome sequencing (16 cases), genome-wide rearrangement analyses (32 cases), and targeted analyses of specific genomic loci (40 cases) using massively parallel sequencing. On average each tumor had 19 somatic alterations in coding genes (range, 3-70). Among genes not previously known to be involved in neuroblastoma, chromosomal deletions and sequence alterations of chromatin remodeling genes, ARID1A and ARID1B, were identified in 8 of 71 tumors (11%) and were associated with early treatment failure and decreased survival. Using tumor-specific structural alterations, we developed an approach to identify rearranged DNA fragments in sera, providing personalized biomarkers for minimal residual disease detection and monitoring. These results highlight dysregulation of chromatin remodeling in pediatric tumorigenesis and provide new approaches for the management of neuroblastoma patients.

Dataset EGAD00001000282

SCAT_Osteosarcoma_Validation

This experiment is to validate putative somatic substitutions and indels identified in an exome screen of ~50 osteosarcoma tumour/normal pairs. It is the first stage in our ICGC commitment to study osteosarcoma. The validation process is an important component of our analysis to clarify the data prior to looking for evidence of new cancer genes, or subverted pathways important in the development of cancer. 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/

Dataset EGAD00001000280

Data set for Whole-genome-Sequencing of adult medulloblastoma

Dataset EGAD00001000275

UK10K_RARE_COLOBOMA REL-2012-07-05

Dataset EGAD00001000206

Neuroblastoma samples (Analyses_vcf files)

Dataset EGAD00001000202

Neuroblastoma samples

Dataset EGAD00001000196

UK10K_RARE_COLOBOMA REL-2012-01-13

Dataset EGAD00001000179

Identification of SPEN as a novel cancer gene and FGFR2 as a potential therapeutic target in adenoid cystic carcinoma

Dataset EGAD00001000175

UK10K_RARE_COLOBOMA REL-2012-02-22

Dataset EGAD00001000185

SCAT osteosarcoma sequencing

Dataset EGAD00001000107

Meningioma Exome

Dataset EGAD00001000099

Pancreatic adenocarcinoma QCMG 20120201

Dataset EGAD00001000096

Glioma cell lines rearrangement screen

Dataset EGAD00001000090

Splenic Marginal Zone Lymphoma with villous lymphocytes exome sequencing

Dataset EGAD00001000081

Integrative Oncogenomics of Multiple Myeloma

Dataset EGAD00001000074

Kaposi sarcoma exome

Dataset EGAD00001000071

Acral melanoma study whole genomes

Dataset EGAD00001000060

Acral melanoma study whole exomes

Dataset EGAD00001000061

EGAD00000000119

Genotypes from cell lines derived from breast carcinoma tissue

Dataset EGAD00000000119

EGAD00000000114

Whole transcriptome sequence data from 18 ovarian clear-cell carcinoma samples and one TOV21G ovarian clear-cell carcinoma cell line

Dataset EGAD00000000114

EGAD00000000052

Sequencing data from natching Pancreatic Carcinoma samples

Dataset EGAD00000000052

EGAD00000000051

Sequencing data from matching Renal Carcinoma samples

Dataset EGAD00000000051

Exome data from a high-density melanoma family

This dataset contains whole-exome sequence data from four individuals in a high-density melanoma family. Sequences were aligned against human reference genome HG19 using BWA.

Dataset EGAD50000002153

Large deletion predisposes to familial melanoma

Mutations in CDKN2A and CDK4 account for ~40% of multi-case melanoma families, with another ~10% attributable to BAP1 and genes associated with telomere maintenance. Thus, a substantial proportion of the genetic risk underlying familial melanoma remains unexplained.

Study EGAS50000001496

Whole-genome data from a high-density melanoma family

This dataset contains whole-genome sequence data from individuals in a high-density melanoma family. Sequences were aligned againt the human reference genome HG19 using BWA.

Dataset EGAD50000002154

Mitochondrial peroxiredoxin 3 is a tractable cancer therapeutic target modulated by SLC7A11

This study is aimed at elucidating the anti-tumor mechanism and therapeutic potential of the PRX3 inhibitor thiostrepton in mesothelioma by investigating its effects on mitochondrial redox homeostasis, oxidative stress–induced apoptosis, and tumor suppression in preclinical and clinical settings. Mesothelioma explants are treated with thiostrepton and subjected to RNA sequencing under baseline, untreated control, and thiostrepton-treated conditions to characterize treatment-induced transcriptional alterations and identify molecular pathways associated with therapeutic response and resistance.

Study EGAS50000001827

Predictive value of genomic, transcriptomic and epigenetic biomarkers in patients with recurrent and/or metastatic HNSC treated with PD-1/PD-L1 inhibitors

Immune checkpoint inhibitors have improved survival in several solid tumors, including head and neck squamous cell carcinoma (HNSCC). However, current use of PD-1/PD-L1 inhibitors relies on PD-L1 expression, which does not reliably predict patient response. Therefore, better predictive biomarkers are needed to identify which patients benefit from immunotherapy. Previous studies suggest that genomic and transcriptomic features may help predict treatment response. This study aims to integrate genomic, transcriptomic, and methylomic data from 31 patients with recurrent/metastatic HNSCC to identify new biomarkers of resistance to anti-PD-1/PD-L1 therapy.

Study EGAS50000001746

A tumor-associated photoreceptor signature unifies distinct central nervous system malignancies

Pineoblastoma is a clinically aggressive childhood brain tumor composed of distinct molecular subgroups with divergent driver genes, demographics, and clinical outcomes. To identify developmental origins and mechanisms governing disease pathogenesis, we derive single-cell transcriptomes from pineal parenchymal tumors, aligning malignant cells with our atlas of pineal gland development to retrace cellular origins. Integrative computational analyses maps pineoblastoma origins to transient cycling pinealocyte progenitors during development. Lineage-specific perturbation of suspected drivers in the early pineal gland yields preclinical models representative of consensus molecular subgroups. Multi-omic characterization of patient tumors and these models uncovers a tumor-associated photoreceptor signature common to pineoblastoma, retinoblastoma, and Group 3 medulloblastoma. Transcriptional activity of this signature within respective cellular origins establishes a developmental basis for molecular similarities between entities. Photoreceptor signature constituents are selective dependencies across these anatomically distinct central nervous system malignancies, motivating future studies evaluating developmentally encoded programs of malignancy as potential therapeutic liabilities.

Study EGAS50000001457

ecDNA copy number heterogeneity

Neuroblastoma exhibits significant inter- and intra-tumour genetic heterogeneity and varying clinical outcomes. Here, we used DNA and RNA sequencing from the same single cells in cell lines and neuroblastoma patients to investigate these effects. We reveal extensive intercellular ecDNA copy number heterogeneity. We also provide direct evidence of how this heterogeneity influences the expression of cargo genes, including MYCN and its downstream targets, and the overall transcriptional state of neuroblastoma cells.

Study EGAS50000000509

Single cell RNA sequencing of relapsed/refractory multiple myeloma

Study EGAS00001004805

5032 results for "*oma"

in 41.26 milliseconds.

Chordoma Exome Sequencing

DATA_SET_ICGC_PedBrainTumor_Medulloblastoma

Chondrosarcoma Exome

Burden of Disease in Sarcoma

Genetic landscape of hepatocellular carcinoma

Driver mutations in histone H3.3 and chromatin remodelling genes in paediatric glioblastoma

DATA FILES FOR NBL

Tumor sample of a serious ovarian carcinoma

Blood sample of serious ovarian carcinoma patient

Osteosarcoma Whole Genome

Subgroup-specific structural variation across 1,000 medulloblastoma genomes

Whole Genome Sequencing accompanying Genetic landscape of pediatric Rhabdomyosarcoma

Exome sequencing identifies frequent mutation of the SWI/SNF complex gene PBRM1 in renal carcinoma

Osteosarcoma Sequencing

Familial Melanoma Sequencing

ICGC Germany PedBrain Medulloblastoma Pilot_2_LM

Pancreatic adenocarcinoma QCMG 20110901

UK10K_RARE_COLOBOMA REL-2012-11-27

Whole genome sequencing of matched germline-tumour samples in follicular lymphoma

Molecular characterization of invasive lobular carcinoma