4116 results for "*oma"

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• A single-cell multi-omic atlas of nodal B-cell non-Hodgkin lymphomas

  CITE-Seq (cellular indexing of transcriptomes and epitopes) of 51 lymph node (LN) samples from including mantle cell lymphoma (MCL, n = 8), follicular lymphoma (FL, n = 12), germinal center (GCB, n = 5) or activated B-cell (non-GCB/ABC, n = 7) diffuse large B-cell lymphoma (DLBCL), and marginal zone lymphomas (MZL, n = 11), in addition to non-malignant reactive lymph nodes (rLN, n = 8). Of the malignant LN samples, 20 were collected at the time of initial diagnosis and 23 were from patients who had previously undergone one or more lines of systemic treatment. Relapse samples were collected at least 3 months after cessation of systemic treatment. This dataset also includes 5 prime RNA sequencing and immune receptor sequencing (10X Genomics) for 11 of these samples (2 rLN, 2 MCL, 3 FL, 2 DLBCL (GCB) and 2 MZL).

  Dataset EGAD50000000497

• Dataset for manuscript titled: Spatial Intra-Tumour Heterogeneity and Treatment-Induced Genomic Evolution in Oesophageal Adenocarcinoma: Implications for Prognosis and Therapy

  Dataset for manuscript titled: Spatial Intra-Tumour Heterogeneity and Treatment-Induced Genomic Evolution in Oesophageal Adenocarcinoma: Implications for Prognosis and Therapy

  Dataset EGAD00001015373

• ISA Nutrition 2015

  Comprehensive data on lifestyle-related modifiable factors, sociodemographic, anthropometric, economic, biochemical, and genetic markers related to the occurrence of cardiometabolic diseases as part of the observational cross-sectional survey (2015 Health Survey of Sao Paulo with Focus on Nutrition (2015 ISA-Nutrition), a population-based study. Data of 805218 SNPs for 841 individuals was genotyped using the Axioma 2.0 Precision Medicine Research Array in the Thermo Fisher Scientific laboratory (Affymetrix Inc, Santa Clara, CA).

  Dataset EGAD00010002678

• Whole genome sequencing of patients with or at risk for HCC

  Liver cancer is a major cause of cancer mortality worldwide. Screening individuals at high risk, including those with cirrhosis and viral hepatitis, provides an avenue for improved survival, but current screening methods are inadequate. In this study, we used whole-genome cell-free DNA (cfDNA) fragmentome analyses to evaluate 724 individuals from the United States, the European Union, or Hong Kong with hepatocellular carcinoma (HCC) or who were at average or high-risk for HCC. Using a machine learning model that incorporated multifeature fragmentome data, the sensitivity for detecting cancer was 88% in an average-risk population at 98% specificity and 85% among high-risk individuals at 80% specificity. We validated these results in an independent population. cfDNA fragmentation changes reflected genomic and chromatin changes in liver cancer, including from transcription factor binding sites. These findings provide a biological basis for changes in cfDNA fragmentation in patients with liver cancer and provide an accessible approach for noninvasive cancer detection.

  Study EGAS00001007249

• Failure of Differentiation of the Rhombic Lip Constitutes Medulloblastoma

  We used single-cell transcriptomics to study cells from the developing human cerebellum, and show that different molecular subgroups of medulloblastoma resemble distinct glutamatergic progenitors.

  Study EGAS00001005826

• Stratifying and Targeting Pediatric Medulloblastoma through Genomics

  In this project, genomic analyses of pediatric medulloblastoma samples, obtained through the international medulloblastoma consortium, will be performed. RNA and miRNA expression profiles of 1000 samples, representing all four subgroups (Wnt, Shh, Group C, and D), will be studied to identify novel subtypes within each subgroup. The resulting subtype-specific expression profiles will support the development of reliable and robust biomarkers to more accurately and reliably classify medulloblastomas for treatment in clinical trials. For that purpose, two assays will be developed: an antibody-based immunohistochemical assay and an orthogonal nucleic acid-based hybridization assay. Additional genomic DNA analysis of the 300 high risk subgroup cases will support the discovery of subgroup specific somatic mutations in order to inform current clinical trials of targeted therapies, and to identify genes and pathways already targeted in other diseases. Such therapies could be rapidly transitioned to Phase II trials in medulloblastoma. Furthermore, the discovery of somatic mutations could be used for developing as well as validating specific biomarkers. The project team will also try to identify risk factors that predispose children to this type of cancer.

  Study EGAS00001000273

• Molecular profiling of acinar cell carcinoma of the salivary glands

  Samples of acinar cell carcinoma (AciCC) of the salivary glands and paired normal salivary gland tissue were analyzed by whole transcriptome RNA-seq (n=10), whole genome sequencing (n=6), whole genome bisulfite sequencing (n=3) and ChIP-seq (H3K27ac, H3K4me3, H3K27me3, NR4A3, CTCF).

  Study EGAS00001002795

• A Genomics-Driven Artificial Intelligence-Based Model Classifies Breast Invasive Lobular Carcinoma and Discovers CDH1 Inactivating Mechanisms

  We developed an artificial intelligence (AI)-model applied to histological images using CDH1 biallelic mutations, pathognomonic for breast invasive lobular carcinoma (ILC), as ground truth. We evaluated the performance of the AI-model to predict the presence of CDH1 biallelic mutations and to diagnose ILC. Subsequently, we investigated the molecular underpinning cases of predicted by the model to harbor a CDH1 biallelic mutations but lacking these alterations according to targeted sequencing. Among this analyses, we subjected to whole genome sequencing (WGS) one ILC case lacking CDH1 biallelic mutations by targeted sequencing and lacking CDH1 promoter methylation to determine the molecular basis of its lobular phenotype.

  Study EGAS50000000485

• Breast Invasive Lobular Carcinoma CDH1 WGS dataset

  We subjected to whole genome sequencing (WGS) one ILC case lacking CDH1 biallelic mutations. Both tumor and normal samples were sequenced.

  Dataset EGAD50000000696

• DAC for Breast Invasive Lobular Carcinoma CDH1 study

  We developed an artificial intelligence (AI)-model applied to histological images trained using CDH1 biallelic mutations, pathognomonic for breast invasive lobular carcinoma (ILC), as ground truth. We evaluated the performance of the AI-model to predict the presence of CDH1 biallelic mutations and to diagnose ILC. Subsequently, we investigated the molecular underpinning of cases predicted by the model to harbor a CDH1 biallelic mutations but lacking these alterations according to targeted sequencing. We then subjected one ILC lacking CDH1 biallelic mutations and lacking CDH1 promoter methylation to whole genome sequencing (WGS) to determine the molecular basis of its lobular phenotype.

  Dac EGAC50000000333

• Disease recurrence after pathologic response (Recurrence DNAseq)

  In this study we aim to gain insight into the mechanisms of immune evasion after initial pathologic response to neoadjuvant immune checkpoint inhibition in macroscopic stage III melanoma by pooling data of the neoadjuvant OpACIN, OpACIN-neo and PRADO trials(EGAD00001012116, EGAS00001004832, EGAD00001006730, EGAS50000000268). Therefore we analyzed in-depth paired baseline(n=10) and recurrent tumor samples of the lymph nodes(n=10) and brain metastasis (n=2) through Whole Exome Sequencing (WES) analyses. Additionally we incorporated transcriptome sequencing data from 22 patients (21 paired-end samples and one single end sample)

  Study EGAS50000000488

• Disease recurrence after pathologic response

  In this study we aim to gain insight into the mechanisms of immune evasion after initial pathologic response to neoadjuvant immune checkpoint inhibition in macroscopic stage III melanoma by pooling data of the neoadjuvant OpACIN, OpACIN-neo and PRADO trials. Here we used RNAseq data from 21 patients(paired end)

  Dataset EGAD50000000698

• Disease recurrence after pathologic response

  In this study we aim to gain insight into the mechanisms of immune evasion after initial pathologic response to neoadjuvant immune checkpoint inhibition in macroscopic stage III melanoma by pooling data of the neoadjuvant OpACIN, OpACIN-neo and PRADO trials. Therefore we analyzed in-depth paired baseline and recurrent tumor samples through a.o. DNA sequencing analyses.

  Dataset EGAD50000000699

• Disease recurrence after pathologic response

  In this study we aim to gain insight into the mechanisms of immune evasion after initial pathologic response to neoadjuvant immune checkpoint inhibition in macroscopic stage III melanoma by pooling data of the neoadjuvant OpACIN, OpACIN-neo and PRADO trials. Therefore we analyzed in-depth paired baseline(n=10) and recurrent tumor samples of the lymph nodes(n=10) and brain metastasis (n=2) through Whole Exome Sequencing (WES) analyses.

  Dataset EGAD50000000700

• Single-cell analysis for metastatic gastric adenocarcinoma

  Intra-tumoral heterogeneity (ITH) is the fundamental property of cancer, however, the origins of ITH remain poorly understood. Here we performed single-cell RNA sequencing of peritoneal carcinomatosis (PC) from patients with advanced gastric adenocarcinoma (GAC), constructed a transcriptome map of 45,048 PC cells, profiled the transcriptome states of diverse tumor cell lineages and types, incisively explored ITH of PC tumor cells, and identified significant correlates with patient survival.

  Study EGAS00001004443

• Combined single-cell transcriptomics and T-cell receptor sequencing reveal heterogeneity of mycosis fungoides between and within patients and identify a CD4+ cytotoxic subtype

  Comprehensive analysis of the malignant cells present in the skin lesions of Mycosis fungoides, the most common subtype of cutaneous T-cell lymphoma, is complicated by the fact that malignant from reactive T cells are challenging to distinguish with certainty. To this end, combined single-cell RNA and TCR sequencing allows unambiguous identification of MF cells, thereby revealing a marked heterogeneity between and within patients with unexpected functional phenotypes. It should be further noted, that mRNA expression of established CTCL protein markers in single-cell transcriptomics to identify MF cells should be used with caution; however, our study uncovered an exciting gene expression pattern that serves as a beacon separating malignant from reactive T cells.

  Study EGAS50000000226

• Whole genome sequencing and somatic mutation profiles and whole genome transcription files of pediatric medulloblastoma

  Fastq, Mutect (SNVs), Platypus (indels), and InfoGenomeR (SVs and CNAs) calls from whole genome sequencing data and fastq files of whole genome transcription data of five patients with pediatric medulloblastoma.

  Dataset EGAD00001009507

• Single-cell transcriptomics of neuroblastoma tumors

  Single-cell RNA-sequencing (CITE-seq) and single-nucleus RNA-sequencing data were generated from neuroblastoma patient tumors to uncover transcriptional heterogeneity at a single-cell resolution. In addition, we used the data to validate our findings of the NBAtlas.

  Study EGAS50000000223

• Single-cell transcriptomics of neuroblastoma tumors

  Single-cell, single-nucleus and CITE-sequencing of neuroblastoma tumors with 10X Genomics

  Dataset EGAD50000000328

• H3.3G34R/V-transformed interneuron progenitors co-opt PDGFRA for gliomagenesis

  Histone H3.3 glycine 34 to arginine/valine (H3.3G34R/V) mutations occur in deadly hemispheric high-grade gliomas. These tumors show exquisite regional and temporal specificity, suggesting a developmental context permissive to the effects of G34R/V mutations. Here we present the molecular landscape of G34R/V gliomas (n=85) and show that 50% bear activating mutations in PDGFRA, with strong selection pressure for PDGFRAMUT clones at recurrence. We show that G34R/V tumors arise in interneuron progenitors of the foetal ventral forebrain expressing GSX2 and the DLX family of homeobox transcription factors, where terminal neuronal differentiation is impaired through aberrant G34R/V-mediated H3K27me3. Frequent co-occurrence of G34R/V & PDGFRAMUT is facilitated in this interneuron lineage-of-origin as PDGFRA forms an aberrant chromatin loop with the adjacent GSX2, hijacking its active chromatin conformation. At the single-cell level, G34R/V tumours entirely lack oligodendroglial transcriptional programs prominent in other glioma entities, and instead harbour dual neuronal and astroglial compartments. CRISPR-removal of H3.3G34R/V does not impact tumorigenicity suggesting this mutation becomes dispensable, while PDGFRAMUT are potently oncogenic regardless of G34 mutation. Collectively, our results suggest that G34R/V gliomas arise in foetal interneuron progenitors unable to undergo terminal differentiation, enabling co-option of PDGFRA through inappropriate expression and activating mutations to promote gliogenesis and oncogenicity. Reliance on PDGFRA for oncogenesis may be of therapeutic opportunity in G34R/V glioma.

  Study EGAS00001004301

• Whole Genome - Uveal Melanoma

  Whole genome sequencing on 1 uveal melanoma and corresponding germline sample. Libraries were prepared using the Kapa HyperPrep kit (Roche, 07962363001). Paired-end libraries (2 x 150 bp) were sequenced on a NovaSeq 6000 instrument (Illumina).

  Dataset EGAD50000000764

• Exome - Uveal Melanomas

  Whole exome sequencing on 11 uveal melanoma samples and corresponding germline samples. Libraries were prepared using the SureSelectXT2 Clinical Research Exome V2 kit (Agilent, 5190-9500 and G9621B). Paired-end libraries (2 x 100 bp) were sequenced on HiSeq 2000/2500 or NovaSeq 6000 instruments (Illumina).

  Dataset EGAD50000000767

• FASTQ Data from In Situ Hi-C on Medulloblastoma Tissue Samples

  29 Hi-C datasets [8 G3 (MB3667, MB3687, MB3690, MB3692, MB3693, MB4010, MB4037, MB4141), 13 G4 (MB0558, MB3510, MB3670, MB3689, MB3716, MB3760, MB3761, MB3807, MB4079, MB4132, MB4174, MBSF7, SNC_2_5), 7 SHH (MB3612, MB3661, MB3662, MB3695, MB3697, MB3724, MB4143), and 1 WNT (MB4036)]. Fresh tissue samples were obtained from The Hospital for Sick Children (Toronto, ON). In situ Hi-C libraries were generated using approximately 2.5 million dissociated cells as input. All Hi-C libraries were sequenced at 150 bp PE with a Hi-Seq X instrument (Illumina) at McGill Genome Centre (Montreal, QC).

  Dataset EGAD50000000771

• Medulloblastoma Hi-C Data Access Committee

  Contact Information Marco Gallo marco.gallo@bcm.edu

  Dac EGAC50000000357

• Target sequencing for 53 synovial sarcoma patients

  This dataset contains 138 .bam files sequenced with Illumina NovaSeq 6000. The files with the variant calling performed to the sequencing data, as well as the clinical data (phenotype) extracted during the sample extraction.

  Study EGAS50000000522