4116 results for "*oma"

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• Target sequencing of 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.

  Dataset EGAD50000000743

• 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

• 10X single-nuclei RNA sequencing

  Single-nuclei sequencing data from four neuroblastoma patients. Each patient was run on two lanes, resulting in two runs per patient. Data is provided in paired-end fastq files.

  Dataset EGAD50000000727

• Genomic and Transcriptomic sequencing of neuroblastoma patient

  Genomic and Transcriptomic single-cell sequencing of neuroblastoma patient. Data represents one 96-well plate that was processed with G&T sequencing, resulting in genomic and transcriptomic data from the same single cells. Dataset contains 95 bam files containing the DNA sequencing data and 95 bam files containing the RNA sequencing data.

  Dataset EGAD50000000728

• Genomic and Transcriptomic sequencing of neuroblastoma cell lines

  Genomic and Transcriptomic sequencing of neuroblastoma HSR and ecDNA cell lines. Data represents five 96-well plates that were processed with G&T sequencing, resulting in genomic and transcriptomic data from the same single cells. Dataset contains 95 bam files containing the DNA sequencing data and 95 bam files containing the RNA sequencing data of CHP212 cells, 380 bam files (190 DNA and 190 RNA) for TR14 cells, 188 bam files (94 DNA and 94 RNA) for Kelly cells and 192 bam files (96 DNA and 96 RNA) for IMR5/75 cells.

  Dataset EGAD50000000729

• NanoString Cancer

  RCC files of 17 Cartridges from metastatic melanoma

  Dataset EGAD00010002432

• Single-cell transcriptomics of hepatoblastoma

  10X Genomics single-cell transcriptomics of hepatoblastoma tissues using Chromium Next GEM Single-Cell 3’ Reagent Kits v3.1. Single-cell transcriptomics data (bam files) of PT9, post-chemotherapy tumor sample, and PT13, treatment naive tumor sample. Single-cell solutions were obtained from viably frozen tissue samples using enzymatic digestion.

  Dataset EGAD50000000794

• Single-cell multiome ATAC and gene expression profiling of hepatoblastoma tumor organoids

  10X Genomics single-cell multiome profiling of hepatoblastoma tumor organoids using Chromium Next GEM Single-Cell Multiome ATAC + Gene Expression Kit. Single-cell transcriptomics data (bam file) of multiplexed sample of hepatoblastoma tumor organoids: 3E, 8F1, 10F2, 13F2, 13E, 17E and 96F1. Single-cell solutions were obtained from fresh organoid samples using enzymatic digestion.

  Dataset EGAD50000000795

• Single-cell transcriptomic profiling of hepatoblastoma tumor organoids

  10X Genomics single-cell transcriptomic profiling of hepatoblastoma tumor organoids using Chromium Next GEM Single-Cell 3’ Reagent Kits v3.1 or 3’ CellPlex Multiplexing Kit. Single-cell transcriptomics data (bam files) of hepatoblastoma tumor organoids: 3E, 8F1, 10F2, 13F2, 13F2 late, 13E, 17E, 17F1, 22E, 27F1, 28F1, 31E, 96F1, 121E and 135. Single-cell solutions were obtained from fresh organoid samples using enzymatic digestion.

  Dataset EGAD50000000796

• Spatial transcriptomics of hepatoblastoma

  10X Genomics Visium Spatial transcriptomics analysis of hepatoblastoma and adjacent normal liver. Spatial data of normal liver and PT2 (fastq files), and and PT13, PT14 and PT16 (bam files) using the Visium Spatial Gene Expression Solution. All samples, except PT13, were collected post-chemotherapy.

  Dataset EGAD50000000797

• Spatially resolved transcriptomics reveals profound subclonal heterogeneity and T cell dysfunction in extramedullary myeloma

  Investigating the spatial architecture and microenvironment of EMD lesions in Multiple Myeloma patients using spatial whole transcriptome sequencing (10X Visium), tomography for spatially resolved transcriptomics (TOMO-seq), and single-cell RNA sequencing (scRNAseq)

  Study EGAS50000000227

• UniKilinikum Wuerzburg MSNZ AGRasche/AG Riedel EMD DAC

  This is a Data access committee for the Data presented in the paper tilted "Spatially resolved transcriptomics reveals profound subclonal heterogeneity and T cell dysfunction in extramedullary myeloma"

  Dac EGAC50000000173

• Contribution of specific cell types to the development of Barrett’s esophagus and carcinoma via germline genetic risk

  This study was designed to elucidate how individual cell types in Barrett’s esophagus (BE) and esophageal adenocarcinoma (EAC) contribute to disease development via germline genetic risk. We performed single cell RNA-sequencing (scRNA-seq) of BE, EAC and paired normal esophagus and gastric fundus tissue samples. After analyzing individual cell types, we integrated the scRNA-seq data and data of a genome-wide association study (GWAS) on BE/EAC to determine cell type-specific genetic risk. Raw data from the RNA-sequencing is provided here.

  Study EGAS50000000530

• Contribution of specific cell types to the development of Barrett’s esophagus and carcinoma via germline genetic risk

  We sought to elucidate how individual cell types in Barrett’s esophagus (BE) and esophageal adenocarcinoma (EAC) contribute to disease development via germline genetic risk.

  Dac EGAC50000000235

• Tumor Evolution Analysis Uncovered Immune-Escape Related Mutations in Relapsed Diffuse Large B-Cell Lymphoma

  More than 60% of patients with primary diffuse large B-cell lymphoma (DLBCL) achieve durable remissions upon the chemoimmunotherapy with R-CHOP. However, the outcome of the relapse patients is extremely poor. To characterize the molecular features that underlie treatment resistance, we performed whole-exome sequencing (n=44) and deep targeted sequencing (n=27) of 44 diagnosis-relapse DLBCL pairs. We found that the overall landscape of genetic alterations was concordant between diagnosis and relapse DLBCL. By a deep comparison of the longitudinal sequencings, we identified relapse-enriched mutations that involved in evasion of immune surveillance (CD58, TNFRSF14, PKD1, FAS), resistance to DNA damaging agents (ATM, TP53), and critical tumor suppressor gene (ZFHX3). Knockdown of ATM and ZFHX3 resulted in increased drug resistance in both germinal center B cell like (GCB) and activated B cell like (ABC) DLBCL cell lines in vitro, while the knockdown of TNFRSF14 and FAS conferred resistance specifically in GCB cell lines. Furthermore, we summarized two evolutionary patterns of DLBCL relapse as the “durable retention” model with stable clone structure, and the “selective sweep” model which exhibited significant clonal switch. Of note, genetic alterations leading to attenuated immune responses usually presented as trunk mutations in the “durable retention” model (7/12) while were newly acquired or expanded upon relapse in the “selective sweep” model (9/16). Overall, our study demonstrated that relapse DLBCL derives from distinct clonal evolutionary patterns, and highlighted immune escape as an important contributor of tumor relapse.

  Study EGAS50000000032

• Cancer cell and tumor microenvironment biomarkers associated with disease-free survival with adjuvant nivolumab in the phase 3 CheckMate 274 trial

  In the CheckMate 274 trial, adjuvant nivolumab versus placebo demonstrated an improvement in the primary endpoint of disease-free survival (DFS) in patients with high-risk muscle-invasive urothelial carcinoma after radical resection. An extensive analysis of tumor biomarkers, including their associations with DFS, was performed. Analysis of genome-wide differential gene expression and known gene signatures found that immune-related genes and pathways, in particular an IFNγ signature, were predictive of DFS in nivolumab-treated patients. Predictive and prognostic associations, respectively, were found for tumor-infiltrating CD4 and CD8 T cells. Analysis of a composite predictive model suggested that CD4 gene expression and tumor cell PD-L1 expression had the greatest contributions to predicting outcomes in nivolumab-treated patients. These results reinforce recent studies establishing the importance of biomarkers of adaptive immunity, and in particular CD4 T cells, in influencing response to PD-1/PD-L1 blockade and establish the potential predictive rather than solely prognostic nature of such findings.

  Study EGAS50000000560

• ROBUST (NCT02285062)

  The ROBUST clinical trial is a Phase III, randomized, double-blind, placebo-controlled study designed to compare the efficacy and safety of lenalidomide plus R-CHOP chemotherapy (R2-CHOP) versus placebo plus R-CHOP in newly diagnosed Diffuse Large B-cell Lymphoma (DLBCL). Molecular data was collected for all patients at screening, but the only patients of the Activated B-cell (ABC) cell-of-origin subtype were eligible for study inclusion and clinical follow-up. We have performed unsupervised clustering on this cohort and identified 7 novel transcriptional subtypes of DLBCL, one of which represents a high-risk subset of patients with high MYC expression, ABC-associated biology, and low immune infiltration.

  Study EGAS50000000333

• Chromatin landscape of medulloblastoma reveals context dependent driver

  In this study, we defined subgroup specific chromatin landscape (H3K27ac, H3K27me3, RNA-Seq, 27ac hichip, WGS) of medulloblastoma to identify pathogenic epigenetic alterations that regulate expression of a context dependent driver gene.

  Study EGAS00001006741

• H3K27ac/H3K27me3 landscape of medulloblastoma

  We profiled 111 patient medulloblastoma primary tumor samples by bulk RNA-seq (19 samples), 27ac (98 samples) / 27me3 (61 samples) ChIP-Seq, WGS (4 samples) and 27ac hichip (8 samples). Submitted data consists of data generated from previously unpublished tumors as well as complementary data for data sets already published for identical medulloblastoma tumors (ex: 27me3 ChIP-Seq and RNA-Seq data submitted for a tumor with publicly available WGS data). The raw fastqs and hg19 aligned RNA-Seq bams are provided.

  Dataset EGAD00001009709

• 3D-GSC_expression_profiles

  In this study, we used RNA-sequencing gene expression profiling in order to characterize specific phenotypic traits in DIPG-derived glioma stem cell (GSC) models. Twenty-two primary GSC models derived from biopsies collected at diagnosis were cultured in an ECM-mimicking compound before for RNA extraction and subsequent rRNA-depletion and sequencing .

  Dataset EGAD00001011079

• 3D-GSC_expression_profiles

  In this study, we used RNA-sequencing gene expression profiling in order to characterize specific phenotypic traits in DIPG-derived glioma stem cell (GSC) models. Twenty-two primary GSC models derived from biopsies collected at diagnosis were cultured in an ECM-mimicking compound before for RNA extraction and subsequent rRNA-depletion and sequencing .

  Study EGAS00001007182

• Genomic Profile of Multiple Localised Spiradenoma and Spiradenocarcinoma

  Multiple spiradenomas and spiradenocarcinoma from a single donor were subjected to exome sequencing. Tumor samples were microdissected from formalin-fixed, paraffin-embedded tissue, and genomic DNA was extracted. The DNA samples were subjected to library generation using the xGen ssDNA & Low-Input DNA Library Preparation Kit, followed by exome capture using the xGen Exome Research Panel v2. The libraries were sequenced on DNBSEQ G400RS. Reads were aligned to GRCh37 with BWA.

  Study EGAS50000000554

• Exome Sequencing of Multiple Localised Spiradenoma and Spiradenocarcinoma

  Tumor samples were microdissected from formalin-fixed, paraffin-embedded tissue and genomic DNA was extracted. DNA libraries were generated using xGen ssDNA & Low-Input DNA Library Preparation Kit (IDT). The libraries were enriched for the exome using xGen Exome Hyb Panel (IDT) and sequenced on DNBSEQ G400RS.

  Dataset EGAD50000000788

• BAM files from whole-genome sequencing of 3 agressive B-cell lymphoma tumour and non-tumor samples

  This dataset contains BAM files from whole-genome sequencing (WGS) of 3 agressive B-cell lymphoma tumour samples for cases 1, 6, and 7 as well as the corresponding non-tumor whole-genome sequencing BAM files.

  Dataset EGAD50000000800

• BAM files from capture-based targeted sequencing of 12 agressive B-cell lymphoma tumour samples (IG-MCL-panel)

  This dataset contains BAM files from capture-based targeted sequencing of 12 agressive B-cell lymphoma tumour samples for cases 1 to 6 and 8 to 13. The sequencing panel used is a MCL-oriented panel containing 159 genes.

  Dataset EGAD50000000801