5495 results for "*oma"

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• EGAD00000000119

  Genotypes from cell lines derived from breast carcinoma tissue

  Dataset EGAD00000000119

• EGAD00000000114

  Whole transcriptome sequence data from 18 ovarian clear-cell carcinoma samples and one TOV21G ovarian clear-cell carcinoma cell line

  Dataset EGAD00000000114

• EGAD00000000052

  Sequencing data from natching Pancreatic Carcinoma samples

  Dataset EGAD00000000052

• EGAD00000000051

  Sequencing data from matching Renal Carcinoma samples

  Dataset EGAD00000000051

• Exome data from a high-density melanoma family

  This dataset contains whole-exome sequence data from four individuals in a high-density melanoma family. Sequences were aligned against human reference genome HG19 using BWA.

  Dataset EGAD50000002153

• Large deletion predisposes to familial melanoma

  Mutations in CDKN2A and CDK4 account for ~40% of multi-case melanoma families, with another ~10% attributable to BAP1 and genes associated with telomere maintenance. Thus, a substantial proportion of the genetic risk underlying familial melanoma remains unexplained.

  Study EGAS50000001496

• Whole-genome data from a high-density melanoma family

  This dataset contains whole-genome sequence data from individuals in a high-density melanoma family. Sequences were aligned againt the human reference genome HG19 using BWA.

  Dataset EGAD50000002154

• Predictive value of genomic, transcriptomic and epigenetic biomarkers in patients with recurrent and/or metastatic HNSC treated with PD-1/PD-L1 inhibitors

  Immune checkpoint inhibitors have improved survival in several solid tumors, including head and neck squamous cell carcinoma (HNSCC). However, current use of PD-1/PD-L1 inhibitors relies on PD-L1 expression, which does not reliably predict patient response. Therefore, better predictive biomarkers are needed to identify which patients benefit from immunotherapy. Previous studies suggest that genomic and transcriptomic features may help predict treatment response. This study aims to integrate genomic, transcriptomic, and methylomic data from 31 patients with recurrent/metastatic HNSCC to identify new biomarkers of resistance to anti-PD-1/PD-L1 therapy.

  Study EGAS50000001746

• A tumor-associated photoreceptor signature unifies distinct central nervous system malignancies

  Pineoblastoma is a clinically aggressive childhood brain tumor composed of distinct molecular subgroups with divergent driver genes, demographics, and clinical outcomes. To identify developmental origins and mechanisms governing disease pathogenesis, we derive single-cell transcriptomes from pineal parenchymal tumors, aligning malignant cells with our atlas of pineal gland development to retrace cellular origins. Integrative computational analyses maps pineoblastoma origins to transient cycling pinealocyte progenitors during development. Lineage-specific perturbation of suspected drivers in the early pineal gland yields preclinical models representative of consensus molecular subgroups. Multi-omic characterization of patient tumors and these models uncovers a tumor-associated photoreceptor signature common to pineoblastoma, retinoblastoma, and Group 3 medulloblastoma. Transcriptional activity of this signature within respective cellular origins establishes a developmental basis for molecular similarities between entities. Photoreceptor signature constituents are selective dependencies across these anatomically distinct central nervous system malignancies, motivating future studies evaluating developmentally encoded programs of malignancy as potential therapeutic liabilities.

  Study EGAS50000001457

• ecDNA copy number heterogeneity

  Neuroblastoma exhibits significant inter- and intra-tumour genetic heterogeneity and varying clinical outcomes. Here, we used DNA and RNA sequencing from the same single cells in cell lines and neuroblastoma patients to investigate these effects. We reveal extensive intercellular ecDNA copy number heterogeneity. We also provide direct evidence of how this heterogeneity influences the expression of cargo genes, including MYCN and its downstream targets, and the overall transcriptional state of neuroblastoma cells.

  Study EGAS50000000509