4982 results for "*oma"

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• Single Cell Genome Sequence for DLP+ library A96222A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient SA1105, patient SA1103, patient SA1106, patient SA1104 on DLP+ library A96222A

  Dataset EGAD00001009478

• Single Cell Genome Sequence for DLP+ library A98243B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient SA1096A, patient-derived xenograft SA1052D passage 1 on DLP+ library A98243B

  Dataset EGAD00001009481

• Tracking the evolution of esophageal squamous cell carcinoma under dynamic immune selection by multi-omics sequencing

  Intratumoral heterogeneity (ITH) has been linked to decreased efficacy of clinical treatments. However, although genomic ITH has been characterized in genetic, transcriptomic and epigenetic alterations are hallmarks of esophageal squamous cell carcinoma (ESCC), the extent to which these are heterogeneous in ESCC has not been explored in a unified framework. Further, the extent to which tumor-infiltrated T lymphocytes (TILs) are directed against cancer cells, but how the immune infiltration acts as a selective force to shape the clonal evolution of ESCC is unclear. In this study, we perform multi-omic sequencing on 186 samples from 36 primary ESCC patients. Through multi-omics analyses, it is discovered that genomic, epigenomic, and transcriptomic ITH are underpinned by ongoing chromosomal instability. Based on the RNA-seq data, we observe diverse levels of immune infiltrate across different tumor sites from the same tumor. We reveal genetic mechanisms of neoantigen evasion under distinct selection pressure from the diverse immune microenvironment. Overall, our work offers an avenue of dissecting the complex contribution of the multi-omics level to the ITH in ESCC and thereby enhances the development of clinical therapy.

  Dataset EGAD00001009482

• Single Cell Genome Sequence for DLP+ library A98279A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1050A passage 1, patient SA1234 on DLP+ library A98279A

  Dataset EGAD00001009486

• Single Cell Genome Sequence for DLP+ library A95717B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1050D passage 1 on DLP+ library A95717B

  Dataset EGAD00001009489

• Oxford Nanopore Technologies (ONT) long-read sequencing in a paired diagnostic and post- therapy medulloblastoma

  Oxford Nanopore Technologies (ONT) long-read sequencing in a paired diagnostic and post- therapy medulloblastoma (2 samples). One sequencing was done on GridION, the other one on a P2 Solo. In both cases the SQK LSK-109 Kit was used for preparation.

  Dataset EGAD00001009490

• Paired-end RNA-seq analysis of the 3D evolution of glioma cell populations. Part 2.

  Dataset contains paired-end RNA-seq sequencing data from 221 glioma samples.

  Dataset EGAD00001009497

• Paired-end Whole Exome-seq analysis of the 3D evolution of glioma cell populations. Part 2.

  Dataset contains paired-end Whole Exome sequencing data from 257 glioma samples from 28 patients. 26 normal blood samples are also included.

  Dataset EGAD00001009496

• 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 mRNA-sequencing to generate a transcriptomic atlas of RMS

  Single-cell mRNA-sequencing to generate a transcriptomic atlas of soft tissue sarcoma tumors

  Dataset EGAD00001009385

• Somatic mutations predict an aggressive phenotype in meningioma but do not drive grade progression

  A subset of meningiomas progress in histopathological grade and drivers of progression are poorly understood. We aimed to identify somatic mutations and copy number alterations (CNAs) associated with grade progression in a unique matched tumour dataset. This dataset consists of DNA sequencing from 10 individuals with meningiomas, where the meningiomas have underdone grade progression. 50 meningiomas were sequenced from the 10 individuals using the hybrid capture-based TruSight Oncology 500 (TSO500) Library Preparation Kit, and 13 of those meningiomas were also sequenced using Agilent SureSelect Clinical Research Exome V2. BAM files for the sequencing data are included in the dataset.

  Dataset EGAD00001009391

• Additional RNASeq files for Roussel MBPRP

  Additional RNASeq files for Roussel paper titled "Combination of CDK4/6 with BET-bromodomain and PI3K/mTOR inhibitors in medulloblastoma in vitro and in vivo"

  Dataset EGAD00001009394

• Targeted DNA sequencing dataset for the study "Molecular profiling of EBV associated diffuse large B-cell lymphoma"

  We performed deep targeted DNA sequencing with a panel of 74 selected cancer-related genes previously identified to be recurrently mutated in EBV associated DLBCL. Sequencing was performed on a HiSeq platform (Illumina) with 250 bp paired-end reads. There are 68 FFPE samples in this targetedDNAseq-dataset with 46 unpaired tumors and 22 normals used as a panel of normals.

  Dataset EGAD00001009396

• Oesophageal adenocarcinoma RNAseq from LUD2015-005 study (NCT02735239, EudraCT 2015-005298-19)

  This dataset contains bulk transcriptomes from the inoperable cohorts of the LUD2015-005 study (NCT02735239, EudraCT 2015-005298-19). Transcriptomes were prepared from pre-treatment oesophageal tumour biopsies using a ribodepletion approach in order to assess both previously reported (e.g. PD-L1 expression) and novel predictive expression-based biomarkers for immunochemotherapy treatment in this setting. On-treatment and post-treatment biopsies were generated as well to characterize response to therapy, and samples were also prepared from paired normal GI tissues for a subset of patients. scRNA-seq based deconvolution was also applied to bulk transcriptomes in this study to estimate the cell composition of tumour biopsies and assess the link between the presence of specific cell types with immunochemotherapy outcomes.

  Dataset EGAD00001009399

• Oesophageal adenocarcinoma WGS from LUD2015-005 study (NCT02735239, EudraCT 2015-005298-19)

  This dataset contains whole genome sequencing (WGS) generated from the inoperable cohorts of the LUD2015-005 study (NCT02735239, EudraCT 2015-005298-19). WGS data were generated with the aim to assess previously reported (e.g. tumour mutational burden) and novel predictive genomic markers for immunochemotherapy treatment in this setting. Using these data, mutation and copy number profiles were generated for the LUD2015-005 study, which were assessed for correlation with patient outcomes from this trial.

  Dataset EGAD00001009400

• An aggregated vcf file

  Germline variants calls were defined using the sequenced reads derived from 230 patients with hepatocellular carcinoma. This dataset is comprised of one aggregated vcf file.

  Dataset EGAD00001009410

• Medulloblastoma Nanopore whole genome sequencing 3 samples

  ONT (PromethION) sequencing of chromothriptic medulloblastoma. Three samples: blood, primary tumor, and relapse tumor. Includes a fourth low-coverage run that multiplexes blood and primary tumor.

  Dataset EGAD00001009411

• Colonbiome shot-gun metagenomics

  156 samples of shot-gun gut metagenomics, corresponding to 51 patients with CRCm 54 patients with adenoma, and 51 healthy controls

  Dataset EGAD00001010068

• Myeloid-specific KDM6B inhibition sensitizes Glioblastoma to PD1 blockade

  This data set include FASTQ files for five experiments: Human scRNA-Seq data (6 samples), Human Visium spatial transcriptomic data (3 samples), Mouse scRNA-seq data (4 samples), Mouse scATAC-seq data (2 samples), Mouse ChIP-seq data (8 samples). For the mouse scATAC-seq data (2 samples), there are originally three FASTQ files, R1, R2 and R3 files. The R1 and R2 FASTQ files were merged into one larger file ("R1R2") per sample for submission as paired-end sequencing setting to follow the EGA guidelines. They can be split into individual R1 and R2 files in order to be processed by Cell Ranger software. The files with IC1 suffix are CHIP-seq Input control for anti-KDM6B antibody pull down experiments and the files with IC2 suffix are CHIP-seq Input control for anti-H3K27ME3 antibody pull down experiments in murine model.

  Dataset EGAD00001010073

• An IL-1β driven neutrophil-stromal cell axis fosters a BAFF-rich microenvironment in multiple myeloma

  This depository contains data from two bulk RNA sequencing experiments: 1) Bulk RNA sequencing data of peripheral blood neutrophils from healthy donors cultured with a) human adipose-derived stromal cells (ADSC) as a model for mesenchymal stromal cells (MSC), and b) IL-1β stimulated ADSC as a model for inflammatory MSC as found in multiple myeloma (MM). 2) Bulk RNA sequencing data from ADSCs cultured a) without stimuli, b) with recombinant human IL-1β, c) with supernatant from iMSC-like cells, d) with neutrophils previously cultured with MSC, e) with neutrophils previously cultured with iMSC, f) with neutrophils previously cultured with iMSC in the presence of anti-human IL-1β or g) with neutrophils previously cultured with iMSC in the presence of an isotype control.

  Dataset EGAD00001010080

• Single-cell RNA and DNA sequencing data obtained after genome-and-transcriptome separation.

  This dataset contains single-cell RNA and DNA sequencing data (fastq, n=928) obtained after genome-and-transcriptome separation. The RNA-seq data was obtained by Smart-seq2 amplification and Nextera XT library preparation. The DNA-seq data was obtained either by Gtag library preparation and amplification or by PicoPlex whole-genome amplification followed by Nextera XT library preparation. The single cells originate from a human PDX melanoma model and from HCC38 and HCC38 BL cell lines. The sequencing libraries were sequenced with Illumina instruments.

  Dataset EGAD00001010096

• VRK3 depletion in Pontine Diffuse Midline Glioma DMG-K27 altered cells

  In order to investigate possible mechanisms underlying the phenotype of cell fitness decline observed following decrease of VRK3 in pontine DMG-K27 altered cells 7, we examined differences in global gene expression. RNA-seq was performed 44h and 60h post-transduction with two distinct shRNAs targeting VRK3 to be able to evaluate the early impact of VRK3 knock-down (KD) in four independent in vitro models of DMG

  Dataset EGAD00001010097

• 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

• Genomics of acral lentiginous melanoma

  Melanoma is the most aggressive type of skin cancer, causing about 75% of dermatological cancer deaths. Acral lentiginous melanoma (ALM) is the most common subtype of melanoma in admixed Latin American populations, but very few tumour genomes and exomes, all from European-descent individuals, have been analysed across several studies. Because of this, the genomic landscape of ALM is mostly unknown. Our aim in this project is to define this landscape and identify driver somatic alterations by whole-exome sequencing a collection of ALM germline/tumour paired FFPE samples from the National Cancer Institute of Mexico. . This dataset contains all the data available for this study on 2023-03-09.

  Dataset EGAD00001010126

• Tapestri snDNA-seq data along with matched bulk data for validation

  Files from Tapestri snDNA-seq of archival tissue samples from 16 pancreatic ductal adenocarcinoma (PDAC) patients. Matched bulk sequencing (whole-exome, whole-genome, MSK-IMPACT) data are attached for a subset of the patients.

  Dataset EGAD00001009735