3794 results for "*oma"

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• Single cell targeted RNA sequencing

  Single cell hybrid-capture targeted sequencing of CD19 CAR T-cell infusion products used for standard of care treatment for relapsed/refractory large B-cell lymphoma.

  Dataset EGAD00001006327

• RNA-Seq samples from the BELOB clinical trial study to find transcriptome associations with response to Bevacizumab and CCNU in glioblastoma patients

  RNA-Seq samples from the BELOB clinical trial study to find transcriptome associations with response to Bevacizumab and CCNU in glioblastoma patients

  Dataset EGAD00001006329

• Analysis of the Patient derived cells that model the intratumoral heterogeneity of hypermutated IDH1 mutant glioma

  Dataset contains paired-end Whole Exome sequencing data from 2 glioma patients (1 oligodendroglioma and 1 astrocytoma) , derived cultured cells, and derived murine xenografts.

  Dataset EGAD00001006340

• Additional Neuroblastoma whole genome sequencing data (Part 2)

  Additional Neuroblastoma whole genome sequencing data

  Dataset EGAD00001006344

• Whole Exome Sequences IberianRoma

  Dataset with 81 whole exome sequences from Iberian Roma samples.

  Dataset EGAD00001006357

• Genome-wide data Iberian Roma

  VCF file with genome-wide data for 62 Iberian Roma samples.

  Dataset EGAD00001006358

• Genomic characterisation of MGUS

  The hematological malignancy multiple myeloma (MM), also called Kahler's disease or plasma cell (PC) myeloma, is characterized by a clonal expansion of PCs originating in the bone marrow (BM). The expansion of these cells leads to an overproduction of antibodies and results in typical symptoms such as anemia, renal failure and bone lesions. All cases of MM are preceded by the asymptomatic, non-malignant pre-stage monoclonal gammopathy of undetermined significance (MGUS). Of all MGUS patients, only 1% per year will progress to MM. Despite efforts to elucidate the molecular mechanisms underlying the MGUS-to-MM progression, its pathogenesis still remains largely unknown. Additionally, the genetic profiles of MGUS patients have only been limitedly investigated due to the only incidental finding of MGUS, the difficulties in BM sampling and isolating a sufficient number of aberrant PCs from the BM aspirates of MGUS patients. Consequently, reliable biomarkers to individually predict which MGUS patients will progress to MM and which will not, are lacking. Therefore, it is highly required to study the molecular pathogenesis of MGUS and the role of genetic events in relation to the malignant transformation to MM.

  Dataset EGAD00001006363

• RRBS profiling for a cohort including 88 precancer specimens from 62 resected lung nodules from 39 patients including atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (ADC) and 39 matched normal lung tissues.

  To study the evolution of DNA methylation at genome level and methylation intra-tumor heterogeneity (ITH) during early lung carcinogenesis, we performed multiregional reduced representation bisulfite sequencing (RRBS) of 127 resected lung samples from 39 patients using single end library Hiseq3000.

  Dataset EGAD00001006367

• Follicular T cell lymphoma

  Paired-end RNA-seq of follicular T cell lymphoma for the discovery of fusion transcripts

  Dataset EGAD00001006379

• Medulloblastoma whole and focused exome sequencing (n=13 patients, n=37 samples)

  Whole exome sequencing: 24 samples matched tumor-normal and one matched CSF. Focused exome sequencing: 17 samples matched tumor-normal-2 time point CSF.

  Dataset EGAD00001006387

• WES raw data for study "Molecular and functional profiling of plasmablastic lymphoma"

  1 cell line and 123 patient samples including 38 normal (22 paired normal and 16 unpaired), 85 tumor-initial, FASTQ file types, Agilent SureSelect Human All Exon V6 Kit

  Dataset EGAD00001006400

• Whole exome sequencing of endometriod ovarian cancer tumours

  Whole Exome sequencing data of tumour samples for 112 patients with endometrioid ovarian carcinoma in FASTQ format. Data was derived as summarized below: Library Preparation: Libraries were prepared from each DNA sample using the Illumina TruSeq Exome Library Prep kit (#FC-150-1002) according to the provided protocol using modifications for working with FFPE sourced material. Libraries were quantified using the Qubit 2.0 Fluorometer and the Qubit DNA HS assay (#Q32854) and the size distribution of fragments was assessed using the Agilent Bioanalyser with the DNA HS Kit (#5067-4626). Library QC: Exome-captured sequencing library pools were quantified using the Qubit 2.0 Fluorometer and the Qubit DNA HS assay (#Q32854) and the size distribution of fragments was assessed using the Agilent Bioanalyser with the DNA HS Kit (#5067-4626). Fragment size and quantity measurements were used to calculate molarity for each library pool. Sequencing: Sequencing was performed using the NextSeq 500/550 High-Output v2 (150 cycle) Kit (# FC-404-2002) on the NextSeq 550 platform (Illumina Inc, #SY-415-1002).

  Dataset EGAD00001006389

• EPC (eccrine porocarcinoma) WES samples

  Whole-exome sequencing (WES) in a well-characterized sample of 14 matched EP tumour/healthy surrounding tissue samples. The sequencing was done with paired EXOME sequencing on Illumina HiSeq 4000 using Agilent SureSelect XT HS + Human All Exon V7.

  Dataset EGAD00001006395

• Oncoscan SNP arrays for study "Molecular and functional profiling of plasmablastic lymphoma"

  1 cell line and 82 Oncoscan SNP tumor initial samples, zipped Affymetrix CEL file types, Oncoscan CNV FFPE Assay Kit, Thermo Fisher Scientific GeneChipTM Scanner 3000 7G

  Dataset EGAD00010001978

• ChIP-Seq files for RMS.

  ChIP-Seq files accompanying the paper titled "Identification of Therapeutic Targets in Rhabdomyosarcoma Through Integrated Genomic, Epigenomic, and Proteomic Analyses".

  Dataset EGAD00001006398

• Cam_121 RNA-Seq data

  This dataset contains RNA-Seq data from 204 primary melanomas and 177 regional lymph nodes. More details can be found in the manuscript: "Tumour gene expression signature in primary melanoma predicts long-term outcomes: A prospective multicentre study"

  Dataset EGAD00001006401

• Sequencing files for 7 melanoma patients

  Files from whole exome sequencing of matched normals and multiple tumors from 7 melanoma patients. The tumors include primary tumors and distant metastases.

  Dataset EGAD00001006410

• Regulatory T cell transcriptomic reprogramming characterizes adverse events by checkpoint inhibitors in solid tumors

  Tregs were sorted as CD4+CD25+CD127- cells from peripheral blood of patients with advanced metastatic melanoma, stage III(B-D)-IV, who were receiving treatment with anti-PD1 (n =26); and patients with kidney, non-small cell lung, liver and bladder cancer who were receiving treatment with anti-PD1. RNA was extracted and polyA libraries were prepared using the Illumina Truseq sample preparation kit v.2. Single-end sequencing was performed on NextSeq500.

  Dataset EGAD00001006415

• Whole genome sequencing of EBV Associated Nasopharyngeal Carcinoma

  Whole genome sequencing of EBV Associated Nasopharyngeal Carcinoma

  Dataset EGAD00001006429

• Whole genome sequencing of retinoblastoma reveals the diversity of rearrangements disrupting RB1 and uncovers a treatment related mutational signature

  Background: The development of retinoblastoma is thought to require pathological genetic changes in both alleles of the RB1 gene. However, cases exist where RB1 mutations are undetectable suggesting alternative pathways to malignancy. Methods: We applied comprehensive whole genome sequencing (WGS) and transcriptomics to sporadic retinoblastomas derived from twenty patients attending our clinic, contrasting these results to that obtained through customary clinical testing. We sought RB1 and other driver mutations, investigated mutation burden, mutational signatures and phylogenetic relatedness in one case of bilateral retinoblastoma. Results: At least one RB1 mutation was identified in all retinoblastomas. We confirmed RB1 mutations previously identified by clinical screening, identified three new RB1 mutations and provided clarity to the mechanism behind a further six mutations. Eight tumours carried structural rearrangements involving RB1 ranging from relatively simple to extremely complex rearrangement patterns, including a chromothripsis-like pattern in one tumour. Potential driver mutations included mutations in BCOR (5/20) and amplification of MYCN (2/20) and MDM4 (1/20). We show that RB1 mutations are not mutually exclusive of MYCN amplifications, and further reveal that all tumours demonstrate increased MYCN expression suggesting a universal role in retinoblastoma tumorigenesis.  Bilateral tumours obtained from one patient harboured conserved germline but divergent somatic RB1 mutations, indicating independent evolution. In-keeping with previous WGS of paediatric cancers, the mutation burden in retinoblastomas was extremely low. Mutational signature analysis showed a predominance of signatures associated with cell division and an absence of ultraviolet-related DNA damage. In a tumour exposed to chemotherapy prior to enucleation, a profound platinum-related mutational signature was observed. Conclusions: WGS provides a complete picture of the genomic landscape of retinoblastomas, allowing the discovery of mutations otherwise undetected by conventional clinical screening approaches. The presence of at least one RB1 mutation in all retinoblastomas and the relative paucity of driver mutations in other genes suggests mutations beyond RB1, MYCN and BCOR are rare. Whilst most RB1 mutations are identifiable by clinical screening, the increased resolution and ability to detect otherwise elusive rearrangements of RB1 by WGS, confirming whether they are somatic or germline, has important repercussions on clinical management and advice on recurrence risks.

  Dataset EGAD00001006431

• Breast implant-associated anaplastic large cell lymphoma shallow whole genome sequencing for copy number analysis and Whole exome sequencing data.

  Shallow whole genome sequencing of 29 BIA-ALCL patients for copy number analysis and 24 Alk-negative ALCL samples as control cohort. 7 Whole exome sequencing BIA-ALCL samples.

  Dataset EGAD00001006433

• RNA data for Glioblastoma (EGAS00001003953, H016)

  RNA data for human glioblastoma patients, EGAS00001003953. 64 human samples, 2 cell lines (LN229, ZH487).

  Dataset EGAD00001006547

• 20201006_EGA_MELA_CRKL_RNA

  Illumina RNASeq sequencing of tumour samples from 53 cases of cutaneous melanoma and 61 cases of acral melanoma

  Dataset EGAD00001006439

• Whole exome sequencing datasets for Low-grade Serous Ovarian Carcinoma

  This dataset includes whole exome sequencing reads from 10 normal and 14 cell lines based on Agilent SureSelect XT Human All Exon v6. They are all 2*100bp reads sequenced using Illumina HiSeq4000.

  Dataset EGAD00001006440

• Whole transcriptome sequencing datasets for Low-grade Serous Ovarian Carcinoma

  This dataset includes whole transcriptome sequencing reads from 8 cell lines based on TruSeq stranded mRNA kit (Illumina). They are all 2*75bp reads sequenced using Illumina NextSeq500.

  Dataset EGAD00001006441