4815 results for "*oma"

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• Genome and transcriptome sequence data from a rectosigmoid adenocarcinoma (colorectal cancer) patient

  Genome and transcriptome sequence data from a rectosigmoid adenocarcinoma (colorectal cancer) patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002567

• Genome and transcriptome sequence data from a ductal carcinoma of left breast patient

  Genome and transcriptome sequence data from a ductal carcinoma of left breast patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002574

• pancreatic ductal adenocarcinoma exomes in study: Pro-immunogenic Impact of MEK inhibition combined with an anti-CD40 immunostimulatory antibody

  This dataset contains 3 pairs of exomes, germline (from whole blood) and patient-derived xenograft (PDX), from human pancreatic durctal adenocarcinoma patients. The data is referred to in the publication: "Pro-immunogenic impact of MEK inhibition synergizes with agonist anti-CD40 immunostimulatory antibodies in tumor therapy" (Nature Communications, 2020) Abstract: Cancer types with lower mutational load and a non-permissive tumor microenvironment are intrinsically resistant to immune checkpoint blockade. While the combination of cytostatic drugs and immunostimulatory antibodies constitutes an attractive concept for overcoming this refractoriness, suppression of immune cell function by cytostatic drugs may limit therapeutic efficacy. Here we show that targeted inhibition of mitogen-activated protein kinase (MAPK) kinase (MEK) does not impair dendritic cell-mediated T-cell priming and activation. Accordingly, combining MEK inhibitors (MEKi) with agonist antibodies (Abs) targeting the immunostimulatory CD40 receptor resulted in potent synergistic anti-tumor efficacy. Detailed analysis of the mechanism of action of MEKi GDC-0623 by means of flow cytometric analysis of the tumor immune infiltrate and whole tumor transcriptomics showed that, in addition to its cytostatic impact on tumor cells, this drug exerts multiple pro-immunogenic effects, including the suppression of M2-type macrophages, myeloid derived suppressor cells and CD4+ T-regulatory cells. In addition, MEKi was found to induce tumor-cell intrinsic interferon signaling, which contributed to antigen presentation by tumor cells. Finally, the tumoridical impact of MEKi involves the activation of multiple pro-inflammatory pathways involved in immune cell effector function in the tumor microenvironment. Our data therefore indicate that the combination of MEK inhibition with agonist anti-CD40 Ab is a promising therapeutic concept, especially for the treatment of mutant Kras-driven tumors such as pancreatic ductal adenocarcinoma.

  Dataset EGAD00001005938

• The mutational landscape of human somatic and germline cells

  During the course of a lifetime normal human cells accumulate mutations. Here, using multiple samples from the same individuals we compared the mutational landscape in 29 anatomical structures from soma and the germline. Two ubiquitous mutational signatures, SBS1 and SBS5/40, accounted for the majority of acquired mutations in most cell types but their absolute and relative contributions varied substantially. SBS18, potentially reflecting oxidative damage, and several additional signatures attributed to exogenous and endogenous exposures contributed mutations to subsets of cell types. The mutation rate was lowest in spermatogonia, the stem cell from which sperm are generated and from which most genetic variation in the human population is thought to originate. This was due to low rates of ubiquitous mutation processes and may be partially attributable to a low cell division rate of basal spermatogonia. The results provide important insights into how mutational processes affect the soma and germline.

  Dataset EGAD00001006642

• Chordoma Extension (known cancer genes)

  Extension analysis to pursue candidate genes of interest in chordoma

  Dataset EGAD00001001239

• Genome and transcriptome sequence data from a metastatic adenocarcinoma of the GE junction patient

  Genome and transcriptome sequence data from a metastatic adenocarcinoma of the GE junction patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002595

• Chordoma Extension Study

  Extension analysis to pursue candidate genes of interest in chordoma

  Dataset EGAD00001001238

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: Colorectal_LCM (2020-02-20)

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute. Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development. . This dataset contains all the data available for this study on 2020-02-20.

  Dataset EGAD00001005994

• Pediatric Glioblastoma with Persistent STAG2 Mutation

  This case represented the genomic findings of a pediatric glioblastoma patient who underwent multiple surgical resections and treated with standard chemoradiation, as well as a novel recombinant poliovirus vaccine therapy. The results present the preservation of a STAG2 mutated clone, besides elimination and emergence of other clones with oncogenic mutations through disease progression under different treatment modalities. Although STAG2 deficiency comprises only a small subset of gliomas, this case adds clinical evidence to existing preclinical data supporting a role for STAG2 mutations in gliomagenesis and resistance to standard therapies.

  Dataset EGAD00001006202

• Genome and transcriptome sequence data from a porocarcinoma patient

  Genome and transcriptome sequence data from a porocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002596

• Glioblastoma stem cell lines RNA-seq (Guilhamon et al.)

  RNA was extracted from GSCs using the Qiagen RNeasy Plus kit. RNA sample quality was measured by Qubit (Life Technologies) for concentration and by Agilent Bioanalyzer for RNA integrity. All samples had RIN above 9. Libraries were prepared using the TruSeq Stranded mRNA kit (Illumina). Two hundred nanograms from each sample were purified for polyA tail containing mRNA molecules using poly-T oligo attached magnetic beads, then fragmented post-purification. The cleaved RNA fragments were copied into first strand cDNA using reverse transcriptase and random primers. This is followed by second strand cDNA synthesis using RNase H and DNA Polymerase I. A single “A” base was added and adapter ligated followed by purification and enrichment with PCR to create cDNA libraries. Final cDNA libraries were verified by the Agilent Bioanalyzer for size and concentration quantified by qPCR. All libraries were pooled to a final concentration of 1.8nM, clustered and sequenced on the Illumina NextSeq500 as a pair-end 75 cycle sequencing run using v2 reagents to achieve a minimum of ~40 million reads per sample.

  Dataset EGAD00001006813

• Melanoma Germlines subset for BAP1

  These samples comprise both melanoma cases and controls sequenced for a selection of loci linked to disease susceptibility. These bams are a subset of the sequencing restricted specifically to the GRCh37 coding areas of the BAP1 gene.

  Dataset EGAD00001002743

• Co-amplification of MYC and CCNE1 in aggressive childhood osteosarcoma

  Osteosarcoma, the most common primary malignant tumour of bone, affects children and adults alike. No fundamental biological differences between paediatric and adult osteosarcoma are known. Here, we apply multi-region whole genome sequencing to an index case of a four-year old child whose aggressive tumour harboured high level, focal amplifications of MYC and CCNE1 connected by translocations. We re-analysed copy number readouts of 258 cases of high-grade osteosarcoma from three different cohorts and identified an additional three cases with MYC and CCNE1 co-amplification, confined to children and associated with aggressive disease. Examining the age distribution of MYC and CCNE1 amplicons across all cases revealed a significant enrichment of focal MYC amplification in children, whereas CCNE1 amplification is not strictly restricted to children. Our findings indicate that amplification of the MYC oncogene, known to be associated with a poor outcome, delineates a variant of osteosarcoma specific to childhood. When co-amplified with CCNE1, it may herald an aggressive disease course.

  Dataset EGAD00001006859

• Single cell sequencing of a post-PD-1 inhibitor metastatic melanoma mass

  Three technical replicates of FACS-sorted T cells (CD45+CD3+) and one replicate of FACS-sorted tumor cells (MCSP+) were loaded to a targeted 10,000 cells per lane on the 10X Genomics Chromium Controler with the single cell 5’ Immune Repertoire and Gene Expression profiling kit. In total, we loaded ~30,000 individual tumor infiltrating lymphocytes (TILs) and ~10,000 melanoma cells on the 10X platform (10X Genomics, CA, USA). Reverse transcription, TCR enrichment, and library preparations were performed according to the 10X Genomics 5’ V(D)J protocol revision C. Transcriptome libraries were pooled and sequenced on the Illumina NovaSeq 6000 S2 flow cell with 26 R1, 8 i7, and 91 R2 cycles respectively. The TCR libraries were pooled and sequenced on the Illumina MiSeq V2 150 cycles paired-end. Single cell transcriptomic and TCR data was processed with the 10X Genomics Cell Ranger Pipeline version 2.2.0 with the software-provided GRCh38 reference transcriptomes. After quality control, there was RNAseq profile data available from 6267 immune and 4303 melanoma cells. Downstream processing and visualization was encompassed through Seurat and tSNE plots.

  Dataset EGAD00001006013

• Mixing Sample Low Grade Glioma Gender Male, Age , 34,44

  Mixed Sample of scRNA-Seq primary low grade glioma. Genders: Male, Age: 34, 44.

  Dataset EGAD00001006018

• Whole genome sequencing data of lung adenocarcinomas

  This dataset includes the whole-genome sequencing data from a study entitled "Tracing Oncogene Rearrangements in the Mutational History of Lung Adenocarcinoma". Whole-genome sequencing libraries were generated by PCR-free methods, and sequencing run was made in HiSeq X Ten machines. PCR duplicates-marked, indel-realigned, and base-recalibrarted BAM files are provided in our dataset.

  Dataset EGAD00001004793

• Sequencing data for ICGC Oesophageal Adenocarcinoma tissue samples - chemo_cohort

  Sequencing data for ICGC Oesophageal Adenocarcinoma tissue samples - chemo_cohort

  Dataset EGAD00001002241

• Leeds Paired Primary and Recurrent GBM RNAseq

  Whole transcriptome, strand-directional RNAseq data for paired primary dn recurrent samples from patients with glioblastoma

  Dataset EGAD00001005224

• Genome and transcriptome sequence data from an adenocarcinoma of primary unknown cancer patient

  Genome and transcriptome sequence data from an adenocarcinoma of primary unknown cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002577

• Melanoma C32 ENU resistance to Combination Therapy

  This study involves mutagenizing C32, a melanoma cell line, with ENU to identify those mutations which engender resistance to a targeted treatment.

  Dataset EGAD00001002234

• Genome and transcriptome sequence data from a metastatic adenocarcinoma patient

  Genome and transcriptome sequence data from a metastatic adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003077

• Genome and transcriptome sequence data from a metastatic rectal carcinoma patient

  Genome and transcriptome sequence data from a metastatic rectal carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004898

• Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient

  Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005907

• Congenital mesoblastic nephroma and infantile fibrosarcoma

  The genetic basis of many rare childhood cancers remains unknown. These include a spectrum of infant soft tissue tumors without canonical gene fusions, encompassing congenital mesoblastic nephroma (CMN) of the kidney and infantile fibrosarcoma (IFS). Here, we integrated whole genome and transcriptome sequencing and identified diagnostic markers and novel therapeutic strategies.

  Dataset EGAD00001003884

• Exome sequencing data to study therapeutic targeting of ependymoma

  This dataset contains whole exome sequencing data from 24 patients. The Agilent SureSelect Human All Exon 50-Mb target enrichment kit was used to capture all human exons for deep sequencing. For each patient a tumour and control sample has been sequenced on a Illumina HiSeq2000 instrument in paired-end mode. Up to three lanes per sample have been sequenced resulting in 118 Fastq files.

  Dataset EGAD00001003973