12068 results for "cancer rna-seq"

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• Cancer Genomics of the Kidney

  The aim of CAGEKID is to carry out comprehensive detection of DNA markers for conventional (clear cell) renal carcinoma. The project includes complete analysis of somatic and constitutional DNA variation, methylation patterns and expression in a large number of constitutional/tumor pairs. CAGEKID is a part of the International Cancer Genome Consortium, ICGC.

  Dataset EGAD00001004018

• Whole exome profiling of spatial biopsies of high grade serous epithelial ovarian cancer patients

  This data set is comprised of data from seven distinct high grade serous epithelial ovarian cancer (HGS-EOC) partients, from whom multiple biopsies were taken at the time of surgery, from the ovary and from different locations in the peritoneal cavity. This data set contains 28 samples, sequenced with a whole exome sequencing approach.

  Dataset EGAD00001004154

• Somatic copy number alterations profiling in non-small cell lung cancer and their correlation with clinical efficacy in first-line treatment

  Genomic data from FFPE tumor samples of 258 patients with non-small cell lung cancer (NSCLC), profiled by shallow whole-genome sequencing (sWGS) at 1x. The study aimed to characterize somatic copy number alterations (SCNAs) and SCNA burden to assess their clinical relevance for patient stratification across different first-line treatments.

  Dac EGAC50000000929

• Prospective Lynch Syndrome Database entries

  These data have been used to produce cancer incidence results for https://pubmed.ncbi.nlm.nih.gov/37181409/ , https://pubmed.ncbi.nlm.nih.gov/40231433/ and https://plsd.eu as available in March 2026. The tables contain demographic information at individual level, individual cancer events with given age, as well as prophylactic and therapeutic surgeries to remove organs. The data have been de-identified to ensure anonymity.

  Dataset EGAD50000002468

• bulk RNA-seq: A Cultured Leukemia Stem Cell Model Enables Validation of CDK6 as a Stemness Target Against Acute Myeloid Leukemia

  Acute myeloid leukemia (AML) represents a group of aggressive hematological malignancies, the clinical management of which is made challenging due to the persistence of rare and therapy resistant leukemia stem cells (LSCs) which serve as a source of disease relapse and poor outcomes. There are currently a paucity of methods to reliably enrich and study LSCs, hindering the development of therapies that specifically target LSCs. In this study, we deeply characterize the OCI-AML8227 culture model, which maintains a functional stemness hierarchy originating from its highly primitive CD34⁺CD38⁻ cells, to elucidate LSC biology and uncover LSC-specific therapeutic vulnerabilities. We analyzed both bulk and single-cell proteomics, transcriptomics, and epigenomics to generate a LSC protein-protein interaction network, which was then integrated with an LSC-focused small molecule screen using this model. From these findings, CDK6 was discovered as a therapeutic vulnerability specific to LSCs, which was validated in findings from the BEAT-AML cohort and a patient-derived xenograft (PDX) panel of AML samples through palbociclib treatment. Taken together, our studies validate CDK6 as a druggable vulnerability in LSCs, and authenticate OCI-AML8227 cells as a LSC target discovery engine.

  Study EGAS50000000789

• Atypical teratoid/rhabdoid tumoroids reveal subgroup-specific drug vulnerabilities RNA-Seq

  Atypical teratoid/rhabdoid tumors (ATRTs) represent a rare, but aggressive pediatric brain tumor entity. They are genetically uniquely defined by alterations in the SWI/SNF chromatin remodeling complex members SMARCB1 or SMARCA4. ATRTs can be further classified in different molecular subgroups based on their epigenetic profiles. Although recent studies suggest that the different subgroups have distinct clinical features, subgroup-specific treatment regimens have not been developed thus far. This is hampered by the lack of pre-clinical in vitro models representative of the different molecular subgroups. Here, we describe the establishment of ATRT tumoroid models from the ATRT-MYC and ATRT-SHH subgroups. We demonstrate that ATRT tumoroids retain subgroup-specific epigenetic and gene expression profiles. High throughput drug screens on our ATRT tumoroids revealed distinct drug sensitivities between and within ATRT-MYC and ATRT-SHH subgroups. Whereas ATRT-MYC universally displayed high sensitivity to multi-targeted tyrosine kinase inhibitors, ATRT-SHH showed a more heterogeneous response with a subset showing high sensitivity to Notch inhibitors, which corresponded to high expression of Notch receptors. Our ATRT tumoroids represent the first pediatric brain tumor organoid model, providing a representative pre-clinical model which enables the development of subgroup-specific therapies.

  Study EGAS00001006866

• Gene expression matrix for Smart-seq2 data of peripheral blood B cells

  The dataset contains scRNA-seq gene expression matrix (csv file) and metadata (csv file) after quality control filtering for data generated with the Smart-seq2 protocol. Transcript expression was quantified with Salmon v0.11.3 using cDNA sequences from GRCh38.94 and k-mer length 25, and was aggregated to gene level and transcript-length-corrected using tximport v1.8.0. The dataset comprises IgA+ transglutaminase 2-specific and other IgA+ B cells from the peripheral blood of 355 cells from two untreated celiac disease patients.

  Dataset EGAD50000000338

• Somatic L1 retrotransposition mapping in high-grade serous ovarian carcinoma using LDI-PCR/Nanopore-sequencing (part 2)

  Somatic L1 retrotransposition was mapped in high-grade serous carcinoma (HGSC) tumors using LDI-PCR/Nanopore-seq method. This method identifies somatic L1 insertions originating from two active L1 loci at chr22q12.1 and chrXp22.2. Multiple tumors from the same patient were utilised to understand L1-mediated intrapatient heterogeneity. Long-read data generated by LDI-Nanopore sequencing was aligned to the reference genome (GRCh38). This dataset contains the remaining file of this study.

  Dataset EGAD50000001757

• Epigenome mapping in purified cells of the digestive and urogenital organs: Participation in International Human Epigenome Consortium (IHEC) (ChIP-seq)

  The aim of this study is to participate in International Human Epigenome Consortium (IHEC, http://ihec-epigenomes.org/), through disclosure of quality epigenome profiles of various normal cell lineages and diseased cells purified from surgically resected materials of multiple Japanese people.

  Study JGAS000027

• Transcriptome analysis of human iPSC-derived microglia in a novel human 3D cortical tissue model

  scRNA-seq analysis of human iPSC-derived microglia in a novel, human in vitro 3D cortical tissue model. Samples include three distinct conditions (each as biological duplicates): wild-type microglia extracted from cultures after 1 month (WT_1mo) and 3 months (WT_3mo) of culturing, as well as knock-in microglia extracted from cultures carrying three familial AD mutations in the APP gene (Swedish, Iberian, Arctic; introduced by CRISPR/Cas9-mediated knock-in) after 3 months of culturing (KI_3mo).

  Dataset EGAD50000000677

• McGill Sperm Methylome Sequencing Data

  The study includes NGS-based WGBS on one sperm DNA sample pooled from 30 participants, and methylC-capture sequencing (MCC-Seq) on the same pooled sperm sample as well as 45 sperm DNA samples derived from both fertile and infertile individuals in two cohorts (Toronto, a fertile cohort; Montreal, an idiopathic infertility cohort). All the data were generated with 100bp paired-end reads using the Illumina HiSeq2000 or 4000 systems.

  Dataset EGAD00001004978

• Longitudinal Single-Cell Profiling in Refractory Mantle Cell Lymphoma

  we performed sequential scRNA-seq of 21 specimens (discovery cohort) collected at baseline, during treatment, and/or at disease remission/progression from 3 ibrutinib-responsive (R) patients (Pt-V, C and D) and 2 non-responsive (NR) patients (Pt-B and E). In addition, the PBMC samples from two healthy donors (N1 and N2) were included as the normal controls.

  Dataset EGAD00001006994

• Pervasive H3K27 acetylation and ERV expression in H3.3K27M gliomas present a therapeutic vulnerability

  We sequenced a total of 2 H3.3K27WT (pcGBM2, G477; 3 replicates total) and 2 H3.3K27M (DIPGVI, DIPGXIII; 6 replicates total) patient-derived cell lines as well as Crispr/Cas9 H3.3K27M-KO clones for one of the cell lines (3 replicates total; DIPGXIII-KO) using ATAC-Seq. P-XX designates passages of replicates. These samples can be found at GEO under accession number GSE128744. This repository contains 1 replicate of G477 to be released under controlled access.

  Dataset EGAD00001004961

• Validation of SNVs found by Exome-seq in S2-SF1, -SF5 and -SF9 hiPSCs

  PCR products were obtained from each target loci using genomic DNA from human iPS cells. Subsequently, PCR products are pooled and subjected to Illumina library preparation. The library will be sequenced either by HiSeq or MiSeq. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001000631

• Human primary and metastatic colorectal cancer (CRC) samples

  Dac EGAC00001002954

• Genetic alterations in metastatic uveal melanoma

  Study EGAS00001003303

• OSCC WES + WGS Boot et al. 2020

  Study EGAS00001004376

• Ovarian Cancer Laboratory, University of Oxford

  Dac EGAC00001000518

• Lung Cancer Single-cell Data Access Committee

  Dac EGAC00001001220

• Breast Cancer Cell Line Data Access Committee

  Dac EGAC00001000134

• DAC for the Prostate Cancer Lymph Node dataset

  Dac EGAC00001000586

• The Ovarian Cancer Association Consortium Data Access Committee

  Dac EGAC00001000616

• Spatial Maps of Prostate Cancer Transcriptomes Data Access

  Dac EGAC00001000913

• Data Access Commitee for gastric cancer ascites

  Dac EGAC00001001026

• DAC for MCO colorectal cancer genomics at UNSW

  Dac EGAC00001001122