15000 results for "cancer studies using rna-seq"

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• Evolutionary histories of breast cancer and related clones

  Study EGAS00001006282

• Chemosensitive Relapse in Small Cell Lung Cancer Patient-Derived Xenografts

  Genetic and epigenetic analysis of patient-derived xenograft models of acquired chemoresistance in small cell lung cancer.

  Study phs001249

• 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

• BLUEPRINT ChIP-seq data for cells in the haematopoietic lineages, from adult and cord blood samples.

  ChIP-seq data for cells in the haematopoietic lineages, from adult and cord blood samples.

  Study EGAS00001000326

• Tumor Profiler Project - AML scDNA data

  The dataset contains single-cell DNA seq data from 21 patients with Acute Myeloid Leukemia (AML). Samples were collected from bone marrow or blood. Sequencing was performed in paired-end mode and sequencing data is provided in fastq format.

  Dataset EGAD50000000824

• Repression of CADM1 transcription by HPV type 18 is mediated by three-dimensional rearrangement of promoter-enhancer interactions

  'Repression of CADM1 transcription by HPV type 18 is mediated by three-dimensional rearrangement of promoter-enhancer interactions

  Dataset EGAD50000001135

• 17 skin and oral epithelial bulk samples from 2 donors

  Aligned BAM files with removed duplicate reads of targeted sequencing data (exomes of a panel of 153 genes) from 12 skin and 5 oral epithelial bulk samples from 2 donors. Sequences generated by the BGI DNB-SEQ platform.

  Dataset EGAD00001008956

• BLUEPRINT: WGBS-seq of multiple myeloma and plasma cells

  Whole-genome Bisulfite sequencing of two multiple myeloma samples and one pooled sample of plasma cells.

  Dataset EGAD00001000672

• Chromatin accessibility in human monocyte differentiation

  This dataset consists of ATAC-seq data from human monocytes, monocyte-derived dendritic cells or monocyte-derived macrophages as well as monocyte-derived cells that were subjected to siRNA treatment targeting TET2, IRF4 and EGR2. In total, it includes 26 samples.

  Dataset EGAD00001006601

• HEMa_LP

  This dataset contain WGBS sequencing result of HEMa_LP. The cells were cultured in Medium 254 supplemented with PMA-Free Human Melanocyte Growth Supplement-2 (HMGS-2) under 37°C,5% CO2.

  Dataset EGAD00001005486

• 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

• Patient-Derived Lung Cancer Organoid

  Lung cancer shows substantial genetic and phenotypic heterogeneity across individuals, driving a need for personalized medicine. Here we report lung cancer organoids and normal bronchial organoids established from patients tissues comprising five histological subtypes of lung cancer and non-neoplastic bronchial mucosa as in vitro models representing individual patient. The lung cancer organoids recapitulate the tissue architecture of the primary lung tumours and maintain the genomic alterations of the original tumours during long-term expansion in vitro. The normal bronchial organoids maintain cellular components of normal bronchial mucosa. Lung cancer organoids respond to drugs based on their genomic alterations: a BRCA2 mutant organoid to olaparib, an EGFR mutant organoid to erlotinib, and an EGFR mutant/MET amplified organoid to crizotinib. Considering the short length of time from organoid establishment to drug testing, our newly developed model may prove useful for predicting patient-specific drug responses through in vitro patient-specific drug trials.

  Study EGAS00001003786

• A comprehensive human gastric cancer organoid biobank captures tumor subtype heterogeneity and enables therapeutic screening​

  Gastric cancer displays marked molecular heterogeneity with aggressive behavior and treatment resistance. Therefore, good in vitro models that encompass unique subtypes are urgently needed for precision medicine development. Here, we have established a primary gastric cancer organoid (GCO) biobank that comprises normal, dysplastic, cancer and lymph node metastases (n=63) from 34 patients, including detailed whole-exome and transcriptome analysis. The cohort encompasses most known molecular subtypes (including EBV, MSI, intestinal/CIN, and diffuse/GS, with CLDN18-ARHGAP6 or CTNND1-ARHGAP26 fusions or RHOA mutations), capturing regional heterogeneity and subclonal architecture, while their morphology, transcriptome, and genomic profiles remain closely similar to in vivo tumors, even after long-term culture. Large-scale drug screening revealed sensitivity to unexpected drugs that were recently approved or in clinical trials, including Napabucasin, Abemaciclib, and the ATR inhibitor VE-822. Overall, this new GCO biobank, with linked genomic data, provides a useful resource for studying both cancer cell biology and precision cancer therapy.

  Study EGAS00001003145

• Whole-genome plasma sequencing reveals focal amplifications as a driving force in metastatic prostate cancer

  Genomic alterations in metastatic prostate cancer remain incompletely characterized. Here we analyze 493 prostate cancer cases from the TCGA database and perform whole-genome plasma sequencing on 95 plasma samples derived from 43 patients with metastatic prostate cancer. From these samples, we identify established driver aberrations in a cancer-related gene in nearly all cases (97.7%), including driver gene fusions (TMPRSS2:ERG), driver focal deletions (PTEN, RYBP, SHQ1), and driver amplifications (AR, MYC). In serial plasma analyses, we observe changes in focal amplifications in 40% of cases. The mean time interval between new amplifications was 26.4 weeks (range: 5-52 weeks), suggesting that they represent rapid adaptations to selection pressure. An increase in neuron-specific enolase is accompanied by clonal pattern changes in the tumor genome, most consistent with subclonal diversification of the tumor. Our findings suggest a high plasticity of prostate cancer genomes with newly occurring focal amplifications as a driving force in progression

  Study EGAS00001001018