9958 results for "cancer rna-seq"

in 43.64 milliseconds.

• A capture-based next-generation sequencing panel for the molecular characterization of chronic lymphocytic leukemia

  Study EGAS00001006975

• The INFORM Precision Medicine Study for High-Risk Pediatric Malignancies

  Study EGAS00001005112

• Methylation_cfDNA_cancer

  Genome-wide CpG methylation information of cell-free DNA samples from cancer patients

  Dataset EGAD00010002587

• Transcriptome Sequencing Data of High Grade Serous Ovarian Cancer

  Study EGAS00001004714

• NanoString Cancer

  RCC files of 17 Cartridges from metastatic melanoma

  Dataset EGAD00010002432

• Driver mutations in histone H3.3 and chromatin remodelling genes in paediatric glioblastoma

  Study EGAS00001000226

• University of Michigan Clinical Sequencing Exploratory Research (CSER)

  Overview. The personalization of therapy for cancer will require molecular characterization of unique and shared genetic aberrations. In particular, patients who have a sarcoma or other rare cancers and are candidates for clinical trials could potentially benefit by identifying eligibility for "targeted" drugs based on the "actionable" genes in their specific tumor. Growing technological advances in genomic sequencing has now made it possible to consider the use of sequence data in a clinical setting. For instance, comprehensive testing that includes whole exome and transcriptome sequencing may identify biomarkers for predictive or prognostic purposes and thereby inform treatment choices and prevention strategies. Thus, the translation of high throughput next generation sequencing would support a "personalized" strategy for cancer. However, the translation of clinical sequencing bears unique challenges including identifying patients who could benefit, developing informed consent and human subjects protections, outlining measurable outcomes, interpreting what results should be reported and validated, and how results should be reported. In addition, we know very little about how patients and clinicians will respond to the potentially confusing and overwhelming amount of information generated by genomic sequencing, and we lack model processes for clinically evaluating and presenting these data. For the promise of our innovative biotechnologies to be realized, "translational genomics" research that evaluates genomic applications within real-world clinical settings will be required. This proposal brings together expertise at the University of Michigan including clinical oncology, cancer genetics, genomic science/bioinformatics, clinical pathology, social and behavioral sciences, and bioethics in order to implement this clinical cancer sequencing project. Three integrated Projects have the following themes: Project 1) "Clinical Genomic Study" will identify patients with a rare cancer (i.e., 15 out of 100,000 individuals per year) who are eligible for clinical trials, consent them to the study, obtain biospecimens (tumor tissue, germline tissue), store clinical data, and assemble a multi-disciplinary Sequencing Tumor Board to deliberate on return of actionable or incidental genomic results; Project 2) "Sequencing & Analysis" will process biospecimens and perform comprehensive sequencing and analysis of tumors to identify point mutations, copy number changes, rearrangements/gene fusions, and aberrant gene expression; Project 3) "Ethics & Psychosocial Analysis" will observe the expert review process for evaluating sequence results and will examine the clinician and patient response to the informed consent process, delivery of genomic sequence results, and use of genomic results.

  Study phs000673

• Identifying_Novel_Fusion_Genes_in_Myeloma

  To identify novel fusion genes in Myeloma samples

  Study EGAS00001000220

• Xenograft_Sequencing

  Sequencing of mouse/human carcinoma xenograft samples.

  Study EGAS00001000140

• Bisulphite_MPN_colonies

  Swift kit whole genome bisulphite of MPN colonies

  Study EGAS00001003094

• Mechanism of action and resistance to Trastuzumab Deruxtecan in patients with metastatic breast cancer: the DAISY trial

  Study EGAS00001006905

• DAC - Comparison of sequencing assays for sensitive detection of circulating tumour DNA in stage IA-IV breast cancer

  Dac EGAC00001002549

• DNA methylation and Panel sequencing for pancreatic neuroendocrine carcinomas (PanNECs) and pancreatic neuroendocrine tumors (PanNETs)

  Study EGAS00001005731

• Molecular profiling reclassifies adult astroblastoma into known and clinically distinct tumor entities with frequent MAPK pathway alterations

  Study EGAS00001003798

• Single cell sequencing of breast cancer T cells reveals a tissue-resident memory subset associated with improved prognosis

  Study EGAS00001002845

• Polyomavirus-positive Merkel cell carcinoma derived from a trichoblastoma suggests an epithelial origin of Merkel cell carcinoma

  Study EGAS00001003784

• Genetic characterization of a Unique Neuroendocrine Transdifferentiation Prostate Circulating Tumor Cell - Derived eXplant (CDX) Model

  Study EGAS00001004272

• Data Access Committee for data from EGAS00001002864: Genome analysis of oesophageal cancer and Barretts oesophagus

  Dac EGAC00001000863

• Detection of ctDNA in Plasma of Patients with Clinically Localised Prostate Cancer is Associated with Rapid Disease Progression

  Dac EGAC00001001718

• Division of Molecular Oncology, National Cancer Center Research Institute Data Access Committee

  Dac EGAC00001002007

• Whole-exome sequencing of 47 microsatellites stable Early-onset sporadic rectal cancer (EOSRC) tumors and corresponding normal samples.

  Dac EGAC00001002502

• DAC for Clonal somatic copy number altered driver events inform drug sensitivity in high-grade serous ovarian cancer

  Dac EGAC00001002644

• Metastatic Prostate Follow Up 2

  Validation/deeper sequencing for metastatic prostate cancer samples

  Dataset EGAD00001000989

• CPC-GENE Prostate Cancer Heterogeneity Study

  Aligned Sequence (bam format), Duplicates removed

  Dataset EGAD00001001329

• Global Anaplastic Thyroid Cancer Initiative

  Raw exome sequence data(fastq) for the GATCI project

  Dataset EGAD00001003235