3796 results for "*oma"

in 40.91 milliseconds.

• A living biobank of patient-derived ductal carcinoma in situ Mouse-INtraDuctal xenografts identifies factors associated with risk of invasive progression

  Create a living biobank of patient-derived ductal carcinoma in situ (DCIS) Mouse-INtraDuctal (MIND) xenografts to find factors explaining invasive growth. Samples exist of both primary and pdx samples. Invasive growth was scored in the pdx.

  Dataset EGAD00001009336

• NLG-LBC-05 ctDNA project sequencing data

  Low-pass whole-genome sequencing of pretherapy lymphoma cfDNA and targeted sequencing of cfDNA, tumor tissue and whole-blood samples of NLG-LBC-05 patient samples and cfDNA of nine subjects with no known cancer. Hybrid capture target enrichment; panel target and sequencing information provided in PMID:34932792. FASTQ files provided for targeted sequencing, separate sequencing runs per sample noted with prefix "run" if applicable. Sequences from DTX1 and KLHL6 targets are advised to be excluded from analyses due to PCR/plasmid contaminants of in-house origin.

  Dataset EGAD00001009337

• High-resolution lung adenocarcinoma expression subtypes

  High-resolution lung adenocarcinoma expression subtypes identify tumors with dependencies on MET, CDK4, CDK6, and PD-L1

  Dataset EGAD00001009339

• 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 scRNAseq from LUD2015-005 study (NCT02735239, EudraCT 2015-005298-19)

  This dataset contains single-cell RNA-seq generated from the LUD2015-005 study (NCT02735239, EudraCT 2015-005298-19) and additional donors with Barrett's oesophagus using the 5' Single Cell Gene Expression assay from 10x Genomics. Samples were generated from oesophageal tumours, Barrett's oesophagus, and normal oesophagus and gastric tissues, with the aim of generating a reference atlas for cell types found in normal and disease-associated tissue states in the upper GI tract. This reference atlas was used as the basis for a deconvolution workflow to estimate the cell composition of bulk transcriptomes from these tissues, and to assess cell type-specific expression patterns of potential predictive biomarkers for immunochemotherapy regimens in this setting.

  Dataset EGAD00001009401

• 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

• Exploration of neuroblastoma xenograft models for tumor extracellular RNA profiling in murine blood plasma

  Total RNA sequencing (SMARTer Stranded Total RNA-Seq Kit v2) data of extracellular RNA (exRNA) from liquid biopsies of neuroblastoma xenograft models.

  Dataset EGAD00001010905

• Medulloblastoma Illumina WGS

  Illumina whole genome sequencing of Medulloblastoma Blood, Primary tumor, and Relapse tumor

  Dataset EGAD00001009424

• Medulloblastoma Illumina RNA-Seq

  Illumina RNA-sequencing of Medulloblastoma primary and relapse tumor.

  Dataset EGAD00001009425

• Long-read sequencing for cell-free DNA analysis (human pacbio)

  8 pregnant women at the 3rd trimesters, 4 hepatitis B carriers, and 4 patients with hepatocellular carcinoma

  Dataset EGAD00001009427

• Single Cell Genome Sequence for DLP+ library A108765A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1181A passage 1 on DLP library A108765A

  Dataset EGAD00001009428

• Single Cell Genome Sequence for DLP+ library A108847B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1182E passage 1 on DLP+ library A108847B

  Dataset EGAD00001009429

• Single Cell Genome Sequence for DLP+ library A118782A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1050B passage 1, patient-derived xenograft SA1050E passage 1 on DLP+ library A118782A

  Dataset EGAD00001009435

• Single Cell Genome Sequence for DLP+ library A118784A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1050B passage 1, patient-derived xenograft SA1050E passage 1 on DLP+ library A118784A

  Dataset EGAD00001009436

• Single Cell Genome Sequence for DLP+ library A118797B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1184D passage 1 on DLP+ library A118797B

  Dataset EGAD00001009438

• Single Cell Genome Sequence for DLP+ library A118804A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1162B passage 1, patient-derived xenograft SA1096B passage 1 on DLP+ library A118804A

  Dataset EGAD00001009439

• Single Cell Genome Sequence for DLP+ library A118808A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1096B passage 1 on DLP+ library A118808A

  Dataset EGAD00001009440

• Single Cell Genome Sequence for DLP+ library A118808B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1096C passage 1 on DLP+ library A118808B

  Dataset EGAD00001009441

• Single Cell Genome Sequence for DLP+ library A118812B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1180C passage 1 on DLP+ library A118812B

  Dataset EGAD00001009442

• Single Cell Genome Sequence for DLP+ library A118814B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1162B passage 1 on DLP+ library A118814B

  Dataset EGAD00001009443

• Single Cell Genome Sequence for DLP+ library A118816A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1180C passage 1 on DLP+ library A118816A

  Dataset EGAD00001009444

• Single Cell Genome Sequence for DLP+ library A118857B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1184D passage 1 on DLP+ library A118857B

  Dataset EGAD00001009445

• Single Cell Genome Sequence for DLP+ library A95663A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1053F passage 1 on DLP+ library A95663A

  Dataset EGAD00001009446

• Single Cell Genome Sequence for DLP+ library A95668A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient SA1162SA on DLP+ library A95668A

  Dataset EGAD00001009447

• Single Cell Genome Sequence for DLP+ library A95717A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1096A passage 1 on DLP+ library A95717A

  Dataset EGAD00001009450

• Single Cell Genome Sequence for DLP+ library A96113A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1049A passage on DLP+ library A96113A

  Dataset EGAD00001009453

• Single Cell Genome Sequence for DLP+ library A96142B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient SA1162SA on DLP+ library A96142B

  Dataset EGAD00001009455

• Single Cell Genome Sequence for DLP+ library A96189A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1049C passage 1 on DLP+ library A96189A

  Dataset EGAD00001009465

• Single Cell Genome Sequence for DLP+ library A96190B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1051A passage 1 on DLP+ library A96190B

  Dataset EGAD00001009466

• Single Cell Genome Sequence for DLP+ library A96192A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1093C passage 1, patient SA1147 on DLP+ library A96192A

  Dataset EGAD00001009467

• Single Cell Genome Sequence for DLP+ library A96194A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1053B passage 1 on DLP+ library A96194A

  Dataset EGAD00001009468

• Single Cell Genome Sequence for DLP+ library A96194B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1053E passage 1 on DLP+ library A96194B

  Dataset EGAD00001009469

• Single Cell Genome Sequence for DLP+ library A96200B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1052D passage 1 on DLP+ library A96200B

  Dataset EGAD00001009470

• Single Cell Genome Sequence for DLP+ library A96205B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1049A passage 1 on DLP+ library A96205B

  Dataset EGAD00001009471

• Single Cell Genome Sequence for DLP+ library A96206B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1050F passage 1 on DLP+ library A96206B

  Dataset EGAD00001009472

• Single Cell Genome Sequence for DLP+ library A96207A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1051A passage 1 on DLP+ library A96207A

  Dataset EGAD00001009473

• Single Cell Genome Sequence for DLP+ library A96207B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1052B passage 1 on DLP+ library A96207B

  Dataset EGAD00001009474

• Single Cell Genome Sequence for DLP+ library A96210B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient SA1047B on DLP+ library A96210B

  Dataset EGAD00001009475

• 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

• Medulloblastoma Cirlce-Seq

  Circle-Seq experiment.

  Dataset EGAD00001009483

• Medulloblastoma PDX Primary tumor

  Dataset EGAD00001009484

• 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