15016 results for "cancer studies using rna-seq"

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• DAC for Liquid CNA in High Grade Serous Ovarian Cancer

  Low pass sequencing of sequential cell free and tumour DNA with matched whole genome sequencing from five patients with high grade serous ovarian cancer presented in Hockings et al Cancer Research paper, 2025.

  Dac EGAC50000000648

• Pan Prostate Cancer Group DK BAM files

  This dataset contains the BAM files from 32 Danish patients with prostate cancer, both germline and tumor tissues. These samples are part of the Pan Prostate Cancer Genome project.

  Dataset EGAD50000002318

• Metastatic_Breast_Cancer_Validation

  Validation of point mutations and small insertions and deletions in primary and associated metastatic breast cancer samples with matched normal tissues.

  Study EGAS00001001968

• Metastatic_breast_cancer_targeted_gene_screen

  The samples will be sequenced for a targeted panel of cancer relevant genes (n ~ 370) and analysed for somatic mutations.

  Study EGAS00001000704

• Epi_Tax_targeted_sequencing

  Sequencing of 350 cancer genes in BC samples from patients treated with either Epirubicin or Paclitaxel monotherapy in the neoadjuvant setting.

  Study EGAS00001000587

• EGAD00010000389

  Cambridge control samples using a 24k expression array from Illumina

  Dataset EGAD00010000389

• EGAD00010000482

  ccRCC case samples using methylation array

  Dataset EGAD00010000482

• EGAD00010000484

  ccRCC control samples using 250K Nsp

  Dataset EGAD00010000484

• MethylationEPIC_JMML_tech_Schoenung

  DNA methylation analysis of JMML patients from Europe, Japan and USA using EPIC arrays

  Dataset EGAD00010001998

• MethylationEPIC_JMML_valid_Schoenung

  DNA methylation analysis of JMML patients from Europe, Japan and USA using EPIC arrays

  Dataset EGAD00010002000

• Methylation450k_JMML_meta_Schoenung

  DNA methylation analysis of JMML patients from Europe, Japan and USA using 450k arrays

  Dataset EGAD00010001999

• Genetic investigation of 12q-amplified osteosarcomas

  Genetic investigation of 12q-amplified osteosarcomas using both whole genome short- and longread and transcriptome sequencing.

  Dac EGAC50000000340

• MiRNA_Validation

  Rounded Log2 CPM well-expressed miRNA levels in plasma; determined using the HTG EdgeSeq miRNA Whole Transcriptome Assay

  Dataset EGAD00010002752

• MiRNA_TrainTest

  Rounded Log2 CPM well-expressed miRNA levels in plasma; determined using the HTG EdgeSeq miRNA Whole Transcriptome Assay

  Dataset EGAD00010002754

• Childhood Cancer Data Initiative (CCDI): Integrating Longitudinal Clinical, Sociodemographic and Genomic Data into the NCCR

  The goal of this study is to contribute clinical and genomic data from a large institutional cohort of pediatric cancer patients who had tumor genomic profiling between 2013 and 2019 at Dana-Farber/Boston Children's Hospital Cancer and Blood Disorders Center. Clinical data include demographics, diagnosis (classified according to the International Classification of Diseases for Oncology (ICD-O-3.2), stage, and biospecimen associated data. Tumors were sequenced with OncoPanel, a targeted next-generation DNA sequencing panel of up to 447 cancer genes for detection of single-nucleotide variants (SNV), insertions, and deletions, and copy number alterations (CNA), as well as selected intronic regions for up to 60 genes for the detection of structural variants (SV). This dataset includes a patient and sample identifier (GENIE ID) that can be used to link the genomic data included in this dataset to additional longitudinal clinical cancer data on a subset of patients that was submitted to the National Childhood Cancer Registry (NCCR).

  Study phs002677

• WGS analysis of Japanese liver cancer

  Liver cancer is prevalent worldwide, mainly associated with virus infection, and its underlying etiology and genomic structure are heterogeneous. Here we provide a whole-genome landscape of somatic alterations in 300 Japanese liver cancers. Our comprehensive analysis elucidated point mutations in non-coding regions, structural variants (SVs), and virus integrations, in addition to coding mutations, and demonstrated new mutational signatures related with liver carcinogenesis, novel recurrently mutated coding and non-coding regions such as lincRNA NEAT1/MALAT1, promoters, CTCF binding sites, and regulatory regions. SV analysis found a significant association with replication timing, and revealed that known cancer genes (CDKN2A, CCND1, APC, and TERT) and new cancer genes (ASH1L, NCOR1, MACROD2) were recurrently affected by SVs, leading to altered expression of nearby genes. These results emphasize the value of whole genome sequencing analysis to discover cancer driver mutations and to understand comprehensive molecular profiles of liver cancer, especially for SVs and non-coding mutations.

  Study JGAS000151