4909 results for "*oma"

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• Translation of non-canonical open reading frames as a cancer cell survival mechanism in childhood medulloblastoma - Ribo-Seq

  This study aims to investigate the dysregulation of RNA translation and identify functional non-canonical open reading frames (ORFs) as potential targets for medulloblastoma treatment. The study involves ribosome profiling and RNAseq of medulloblastoma tissues and cell lines to observe the translation of non-canonical ORFs. Multiple CRISPR-Cas9 screens will be used to identify functional non-canonical ORFs implicated in medulloblastoma cell survival.

  Dataset EGAD00001011193

• Genetic landscape of SMM

  Identifying high risk smoldering myeloma patients and progression mechanism is a prerequisite to implement effective inception strategies and curve myeloma related morbidity and mortality. We hypothesize that genomics may help identify determinants of progression that may help predict outcome and offer effective chemo preventive targets. Eighty-two patients underwent a custom targeted panel sequencing with an additional capture for the translocation loci. These results were compared to 223 newly diagnosed patients (EGAS00001003223 and EGAD00001004117) and 17 MGUS and 10 early myeloma patients. DNA was obtained from either CD138+ cells from the bone marrow of multiple myeloma patients (tumor) or from stem cell harvests or peripheral blood cells from the same patient (control). 100 ng of DNA was fragmented, end-repaired, and adapters ligated using the HyperPlus kit (KAPA Biosystems). After PCR amplification the libraries were hybridized with probes against either a targeted panel consisting of 140 genes and chromosomal regions (Nimblegen) using SeqCap reagents (Nimblegen). Hybridized libraries underwent further amplification before being sequenced on a NextSeq500 (Illumina) using 75 bp paired end reads. Overall, these data highlight the importance of dysregulation of the MAPK pathway in the progression to MM.

  Dataset EGAD00001005285

• CyTOF of 27 DLBCLs

  Diffuse large B-cell lymphoma (DLBCL) is the most common histologic subtype of non-Hodgkin lymphoma and is notorious for its clinical heterogeneity. Patient outcomes can be predicted by cell-of-origin (COO) classification, demonstrating that the underlying transcriptional signature of malignant B-cells informs biological behavior in the context of standard combination chemotherapy regimens. In the current study, we used mass cytometry (CyTOF) to examine tumor phenotypes at the protein level with single cell resolution in a collection of 27 diagnostic DLBCL biopsy specimens from treatment naïve patients. We found that malignant B-cells from each patient occupied unique regions in 37-dimensional phenotypic space with no apparent clustering of samples into discrete subtypes. Interestingly, variable MHC class II expression was found to be the greatest contributor to phenotypic diversity. Within individual tumors, a subset of cases showed multiple phenotypic subpopulations, and in one case we were able to demonstrate direct correspondence between protein-level phenotypic subsets and DNA mutation-defined subclones. In summary, CyTOF analysis can resolve both inter- and intra-tumoral heterogeneity among primary samples, and reveals that each case of DLBCL is unique and may be comprised of multiple, genetically distinct subclones.

  Dataset EGAD00001005419

• Germline BAMs from patients with both uveal and cutaneous melanoma

  Germline BAMs from blood/saliva samples from patients diagnosed with both uveal and cutaneous patients. Reads have been aligned, deduplicated and recalibrated.

  Dataset EGAD00001011676

• RNA sequencing of in vitro generated suppressive myeloid cells using parental and Sialidase expressing A549 cancer cell lines

  Fresh peripheral blood mononuclear cells of four human donors were cultured together with either lung adenocarcinoma A549 cancer cells or A549-expressing H1N1 Sialidase cancer cells. These treatments induced the differentiation of donor cells into immunosuppressive MDSC-like cells, which were further subjected to bulk RNA sequencing. RNA-seq TruSeq libraries were generated from polyA-enriched mRNA isolated from the samples, and sequenced in paired-end mode on 4 lanes of an Illumina NextSeq 500 flow-cell

  Dataset EGAD00001012437

• Genome and transcriptome sequence data from a plexiform neurofibroma tumor patient

  Genome and transcriptome sequence data from a plexiform neurofibroma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015283

• Genome and transcriptome sequence data from a papillary thyroid carcinoma tumor patient

  Genome and transcriptome sequence data from a papillary thyroid carcinoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015303

• Exome Atlas in HCC tumors

  The atlas provides a comprehensive exploration of genetic and transcriptomic landscapes within HCC, offering insights into key genomic alterations and gene expression patterns. The integration of exome sequencing and RNAseq data enhances our understanding of the molecular complexity underlying HCC, potentially paving the way for targeted therapeutic strategies and biomarker discovery in the context of hepatocellular carcinoma.

  Dataset EGAD00001015342

• Dataset for EGAS00001007937

  WGS, RNAseq, Methylation, variant calling analysis for a Novel paediatric case of a spinal high-grade astrocytoma with piloid features in a patient with Noonan Syndrome

  Dataset EGAD00001015412

• RNA-Seq Dataset of Organoid drug profiling identifies methotrexate as a therapy for SCCOHT, a rare pediatric cancer

  We generated and characterized tumoroids from small cell carcinoma of the ovary, hypercalcemic type. Furthermore, we identified a drug that is selective and effective against SCCOHT tumoroids.

  Dataset EGAD00001015441