12000 results for "cancer rna-seq"

in 23.84 milliseconds.

• Sequencing data for oesophageal and related samples - OACs release 3 (RNA)

  Dataset EGAD00001003900

• RNAseq data of brain metastasis samples

  Paired-end RNA sequencing data from 95 brain metastasis samples with different primary origins. Sequencing was performed on the Illumina HiSeq 3000.

  Dataset EGAD50000000799

• Sequencing data for filanesib-treated hepatoblastoma samples

  This dataset contains RNA sequencing data of two hepatoblastoma PDX cell models. Cells were either treated with KSP inhibitor filanesib or with DMSO (controls).

  Dataset EGAD50000001314

• Single-cell mRNA-sequencing of neuroblastoma

  Profiling of childhood neuroblastoma by single-cell RNA sequencing

  Dataset EGAD00001009766

• MYC and MINCR-regulated lncRNAs in hT-RPE-MycER cells

  RNA-sequencing data from teh hT-RPE-MycER cell line after MYC activation and after MINCR knock-down in conditions of MYC ON or OFF

  Dataset EGAD00001001598

• Dataset of RNA-sequencing of childhood acute myeloid leukemia

  This dataset includes 139 bam files of mRNA sequencing. All subjects are tumor samples of pediatric acute myeloid leukemia.

  Dataset EGAD00001005078

• Single-cell RNA-sequencing of H3-K27M diffuse midline glioma.

  Fastq files are deposited for single-cell transcriptomes of patient H3-K27M diffuse midline gliomas, generated using the SMART-seq2 method.

  Dataset EGAD00001011339

• Engineered cartilage: deriving design principles from human developmental: RNA (2025-07-30)

  Engineered cartilage: deriving design principles from human developmental pathways . This dataset contains all the data available for this study on 2025-07-30.

  Dataset EGAD00001015664

• Clinical panel sequencing of cancer of unknown primary using Comprehensive cancer panel (CCP)

  This database includes comprehensive cancer panel (CCP) on paired tumour and germline DNA from cancer of unknown primary samples, all of which are matched to WGS data under this study. This data was used to compare biomarker yield against what was achieved with WGS. This dataset contains n=34 tumour-germline paired samples. All samples are in BAM format aligned with GRCh38 reference genome.

  Dataset EGAD50000000655

• Colorectal cancer functional annotation - MPRA

  We performed a Massively Parallel Reporter Assay (MPRA) in colorectal cancer (CRC) cell lines HT29 and SW403 and normal colon cell line HCEC-1CT. We specifically targeted the regions around the CRC GWAS loci to identify which variants alter transcription.

  Study EGAS50000000406

• Liquid biopsy to identify taxane resistance in castration-resistant prostate cancer patients

  Taxanes are life-prolonging treatments for patients with advanced prostate cancer. However, treatment resistance and lethal disease invariably develops. We here used liquid biopsies to identify and characterize resistance to cabazitaxel using a targeted sequencing panel (PCF-SELECT).

  Study EGAS50000001292

• Comprehensive analyses of genetic aberrations in gastroenterological tumors

  Intestinal metaplasia (IM) is a risk factor of gastric cancer in gastric mucosa with Helicobacter pylori infection. To explore the susceptibility to the cancer development in pure gastric IM, we investigated landscape of genetic alterations in gastric single-glands with IM.

  Study JGAS000269

• Multiomic cell-free DNA profiling to inform molecular classification and immunotherapy outcomes in endometrial cancer

  This study involved a cell-free DNA (cfDNA) framework integrating genomic, transcriptomic and epigenomic profiling to investigate patient response to immune checkpoint inhibitors in advanced endometrial cancer (EC) with mismatch repair deficiency (dMMR).

  Study EGAS50000001582

• Digital tEchnology For Lung Cancer Treatment

  DEFLeCT metadata: 1) A table containing the mutational profile for all human genes across the cohort of the 81 PROMOLE lung cancer samples. 2) A table containing the expression levels for all human genes across the cohort of the 81 PROMOLE lung cancer samples. 3) A table containing the clinical, histology data and follow-ups of the cohort of 81 PROMOLE lung cancer patients.

  Dataset EGAD00001010838

• Genetic alterations in benign breast biopsies of subsequent breast cancer patient

  This dataset consists of amplicon sequencing of fibrocystic breast tissues, subsequent cancer tissue and germline control of 17 patients. The target genes include all exons of 27 protein-coding genes and 2 non-coding genes, as well as mutation hotspots in three cancer genes, frequently mutated in breast cancer. Ion AmpliSeq libraries were generated and sequenced on the Ion S5 XL system.

  Dataset EGAD00001004874

• A case of colorectal cancer with ERBB2 c.2264T>C (p.Leu755Ser) mutation

  This data set contains next generation sequencing (NGS) data of two serial tumor samples (primary and a metastasis) from a patient with colorectal cancer showing an ERBB2 c.2264T>C (p.Leu755Ser). NGS was performed using the Illumina TruSeq Amplicon Cancer Panel (TSACP, Illumina) covering 212 amplicons in 48 cancer associated genes on the Illumina MiSeq sequencing platform. The dataset contains two BAM files.

  Dataset EGAD00001002252

• Multi-site tumor sampling highlights molecular intra-tumor heterogeneity in malignant pleural mesothelioma

  Background:Malignant pleural mesothelioma (MPM) is a heterogeneous cancer. Better knowledge of molecular and cellular intra-tumor heterogeneity throughout the thoracic cavity is required to develop efficient therapies. This study focuses on molecular intra-tumor heterogeneity using the largest series to date in MPM and is the first to report on the multi-omics profiling of a substantial series of multi-site tumor samples. Methods:Intra-tumor heterogeneity was investigated in 16 patients from whom biopsies were taken at distinct anatomical sites. The paired biopsies collected from apex, side wall, costo-diaphragmatic or highest metabolic sites as well as 5 derived cell lines were screened using targeted sequencing. Whole exome sequencing, RNA sequencing, and DNA methylation were performed on a subset of the cohort for deep characterization. Molecular classification, recently defined histo-molecular gradients, and cell populations of the tumor microenvironment were assessed. Results:Sequencing analysis identified heterogeneous variants notably in NF2, a key tumor suppressor gene of mesothelial carcinogenesis. Subclonal tumor populations were shared among paired biopsies, suggesting a polyclonal dissemination of the tumor. Transcriptome analysis highlighted dysregulation of cell adhesion and extracellular matrix pathways, linked to changes in histo-molecular gradient proportions between anatomic sites. Methylome analysis revealed contribution of epigenetic mechanisms in two patients. Finally, significant changes in the expression of immune mediators and genes related to immunological synapse, as well as differential infiltration of immune populations in the tumor environment were observed and led to a switch from a hot to a cold immune profile in three patients. Conclusions:This comprehensive analysis reveals patient-dependent spatial intra-tumor heterogeneity at the genetic, transcriptomic and epigenetic levels and in the immune landscape of the tumor microenvironment. Results support

  Study EGAS00001005328

• WTCCC case-control study for Breast cancer

  WTCCC genome-wide case-control association study for Breast cancer (BC) using the 1958 British Birth Cohort collection as controls.

  Study EGAS00000000024

• Framome cancer samples

  Cancer samples for neo-open reading frame peptides that comprise the tumor framome are a rich source of neoantigens for cancer immunotherapy.

  Dataset EGAD50000000420

• Transcriptomic characterization of the histopathological growth patterns in breast cancer liver metastases

  Characterizing transcriptommic profiles of the two main histopathological growth patterns in liver metastases in patients with breast cancer.

  Study EGAS50000000225

• Whole exome sequence in EGFR-TKI resistant non-small cell lung cancer

  Whole exome analysis to clear molecular basis and mutation spectrum in EGFR-TKI resistant non-small cell lung cancer

  Study JGAS000102

• Cancer_Cell_Line_Exome_Sequencing_

  Genomic characterisation of a large series of cancer cell lines.

  Study EGAS00001000978

• Somatic_mutations_in_twin_breast_cancers

  The aim of this study is to investigate the somatic mutations in twins with BRCA1/2 negative breast cancer with no strong family history.

  Study EGAS00001002379

• OCCAMS_Oesophageal Cancer Organoids_1

  ***THIS DATA CAN ONLY BE USED FOR NON-COMMERCIAL CANCER RESEARCH*** Sequencing of organoid cell lines derived from oesophageal tumour sections taken from patients diagnosed with primary oesophageal cancer who underwent tumour resection surgery.

  Dataset EGAD00001001889

• Combinatorial Indexed 10x Genomics Single-Cell ATAC-seq on Human Cerebral Cortex

  Single-cell chromatin accessibility profiling (scATAC) using droplet fluidics (10x Genomics) is inherently limited in throughput due to the number of available indexed droplets. This study leverages single-cell combinatorial indexing workflows with modified adapter designs to enable indexed tagmentation and superloading of pre-indexed nuclei into the 10x Genomics scATAC workflow, enabling a substantial increase in the number of cell profiles that can be obtained per channel. This workflow, 10x single-cell combinatorial indexed ATAC-seq (txsciATAC), is demonstrated on human brain tissue (middle frontal gyrus), along with mouse brain tissue to enable doublet and crosstalk assessment. This study includes all human data and includes a single preparation taken through nuclei isolation and indexed tagmentation using 96 indexes then split to produce two datasets, one targeting 20k cells and one targeting 70k, each using a single channel of the 10x Chromium controller.

  Study phs003497

• 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

• Genome-wide DNA methylation profiles by MeDIP-seq of cord blood cells and cord blood mononuclear cells obtained from twins conceived through in vitro fertilization and naturally conceived controls

  The study included 47 newborn twins conceived though in vitro fertilisation (IVF) and 60 non-IVF-conceived twins from the Peri/postnatal Epigenetic Twins Study (PETS). Cord blood was collected at birth and used to process mononuclear cells. Whole blood cells (WBCs) from cord blood of 98 twins (40 IVF and 58 non-IVF) and cord blood mononuclear cells (CBMCs) of 82 twins (35 IVF and 47 non-IVF) were subjected to DNA methylation profiling. Methylated DNA immunoprecipitation followed by deep sequencing (MeDIP-seq) was applied to generate genome-wide DNA methylation profiles in a total of 180 samples. Single-end reads were mapped onto hg19 using BWA. Methylation levels were quantified using MEDIPS and used to identify IVF-associated differentially methylated regions.

  Study EGAS00001002248

• ATAC-Seq of healthy and IBD blood samples

  PBMCs from blood samples of 9 age- and gender-matched healthy subjects and 25 IBD patients were isolated through a Ficoll density gradient and used to isolate live CD4 T cells through a magnetic cell isolation kit (Miltenyi Biotec). Twelve thousand live CD4 T cells were then used to prepare ATAC-Seq libraries. Briefly, crude nuclei of live CD4+ T cells were treated with Tagment DNA buffer and Tagment DNA Enzyme (Nextera DNA Library Prep Kit, Illumina), and then the DNA was purified by MinElute PCR Purification Kit (Qiagen). Transposed DNA fragments were amplified using specific adapters followed by purification with MinElute PCR Purification Kit (Qiagen). Fragments from 240-360pb were selected in the PippinHT system (Sage Science). The quality of the library and its DNA concentration were assessed by Bioanalyzer instruments (Agilent Technologies) and ultimately submitted for sequencing using Illumina HiSeq 2500 sequencer, V4 chemistry.

  Study EGAS00001007343

• 59 CLPD-NK cases WGS & WTS data

  For the cohort of 59 samples, we performed TruSeq DNA PCR-Free whole-genome sequencing library preparation according to manufacturer’s instructions (llumina, ILMN, San Diego, CA) on the automated NGS Star liquid handling platform (Hamilton, Bonaduz, Switzerland) followed by 2x150 bp paired-end sequencing on the HiSeqX or NovaSeq6000 (ILMN). An average coverage of >100x was achieved. For whole transcriptome analysis, the TruSeq Total Stranded RNA kit was used, starting with 250 ng of total RNA, to generate RNA libraries following the manufacturer’s recommendations (ILMN). 2x100bp paired-end reads were sequenced on the NovaSeq 6000 with a median of 50 mio. reads per sample (ILMN).

  Dataset EGAD00001008558

• Human Colorectal Cancer Exome Sequencing

  Human Colorectal Cancer Exome Sequencing

  Dataset EGAD00001000031

• Extreme intratumor heterogeneity and driver evolution in mismatch repair deficient gastro-esophageal cancer

  Study EGAS00001003434

• Parallel sequencing of extrachromosomal circular DNAs and transcriptomes in single cancer cells

  Study EGAS00001007026

• Pan Prostate Cancer Group Data Access Control Committee

  DACC for the PanProstate Cancer Group projects

  Dac EGAC50000000602

• The patterns and dynamics of genomic instability in metastatic pancreatic cancer

  Pancreatic cancer is an aggressive malignancy with a five-year mortality of 97–98%, usually due to widespread metastatic disease. Previous studies indicate that this disease has a complex genomic landscape, with frequent copy number changes and point mutations, but genomic rearrangements have not been characterized in detail. Despite the clinical importance of metastasis, there remain fundamental questions about the clonal structures of metastatic tumours, including phylogenetic relationships among metastases, the scale of ongoing parallel evolution in metastatic and primary sites, and how the tumour disseminates. Here we harness advances in DNA sequencing to annotate genomic rearrangements in 13 patients with pancreatic cancer and explore clonal relationships among metastases. We find that pancreatic cancer acquires rearrangements indicative of telomere dysfunction and abnormal cell-cycle control, namely dysregulated G1-to-S-phase transition with intact G2–M checkpoint. These initiate amplification of cancer genes and occur predominantly in early cancer development rather than the later stages of the disease. Genomic instability frequently persists after cancer dissemination, resulting in ongoing, parallel and even convergent evolution among different metastases. We find evidence that there is genetic heterogeneity among metastasis-initiating cells, that seeding metastasis may require driver mutations beyond those required for primary tumours, and that phylogenetic trees across metastases show organ-specific branches. These data attest to the richness of genetic variation in cancer, brought about by the tandem forces of genomic instability and evolutionary selection.

  Study EGAS00000000064

• Machine learning to detect the SINEs of cancer

  We previously described an approach called RealSeqS to evaluate aneuploidy in plasma cell-free DNA (cfDNA) through the amplification of ~350,000 repeated elements with a single primer. We hypothesized that an unbiased evaluation of the large amount of sequencing data obtained with RealSeqS might reveal other differences between plasma samples from patients with and without cancer. This hypothesis was tested through the development of a novel machine-learning approach called Alu Profile Learning Using Sequencing (A-PLUS) and its application to samples from 5108 individuals, 2037 with cancer and the remainder without cancer. Samples from cancer patients and controls were pre-specified into four cohorts used for: 1) model training, 2) analyte integration and threshold determination, 3) validation, and 4) reproducibility. A-PLUS alone provided a sensitivity of 40.5% across 11 different cancer types in the Validation Cohort, at a specificity of 98.5%. Combining A-PLUS with aneuploidy and 8 common protein biomarkers detected 51% of 1167 cancers at 98.9% specificity. We found that part of the power of A-PLUS could be ascribed to a single feature – the global reduction of AluS sub-family elements in the circulating DNA of cancer patients. We confirmed this reduction through the analysis of another independent dataset obtained with a very different approach (whole genome sequencing). The evaluation of Alu elements therefore has the potential to enhance the performance of several methods designed for the earlier detection of cancer.

  Study EGAS00001007169

• Whole-exome sequencing of breast cancer metastasis and corresponding blood samples

  This study included samples from metastatic breast cancer patients who underwent a biopsy in the context of SAFIR01 (NCT01414933), SAFIR02 (NCT02299999), SHIVA (NCT01771458) and MOSCATO (NCT01566019) prospective trials. These French multicentre trials used high throughput genome analysis on fresh frozen tumor biopsies as a therapeutic decision tool for metastatic cancer patients, with solid cancers (SHIVA, MOSCATO) or specifically with breast cancer (SAFIR01, SAFIR02). All patients gave their informed consent for translational research and genetic analyses of their somatic DNA. Overall, whole-exome sequencing for a total of 216 pairs of metastatic tumor and unmutated DNA derived from corresponding blood samples was performed using Illumina technology. The results of the analysis of the mutational profile of metastatic breast cancer was reported in Lefebvre et al. (PMID:28027327).

  Study EGAS00001001695

• Molecular sub-classification of hormone receptor-positive breast cancer

  Patients with estrogen and/or progesterone receptor-positive breast cancer benefit from hormonal treatment, yet high global death burdens due to high prevalence and long-term recurrence risk call for biomarkers to guide additional treatment approaches. From a prospective, observational study of postmenopausal early breast cancer patients treated with tamoxifen or aromatase inhibitors gene expression analyses of 612 tumors was performed using the NanoString® Breast Cancer 360 panel. We identified novel gene expression signatures, i.e. BRCAness and Tumor Inflammation Signature (associated with high tumor lymphocyte infiltration), that may aid to select high-risk patients in order to improve adjuvant treatment by targeting DNA repair deficiency or immune-checkpoints in addition to standard chemo-endocrine treatment. The overall goal is to foster novel concepts for a stratified early breast cancer management.

  Study EGAS00001004594

• MutWP1__CRUK_Grand_Challenge_Mutographs_of_Cancer__Oesophageal_adenocarcinoma

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute (40X and 20X depth respectively). Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Study EGAS00001003702

• Intratumoural heterogeneity and immune modulation in lung adenocarcinoma of female smokers and never smokers

  Lung cancer is still the leading cause of cancer death worldwide despite declining smoking prevalence in industrialised countries. Although lung cancer is highly associated with smoking status, a significant proportion of lung cancer cases develop in patients who never smoked, with an observable bias towards female never smokers. A better understanding of lung cancer heterogeneity and immune system involvement during tumour evolution and progression in never smokers is therefore highly warranted. We employed single nucleus transcriptomics of surgical lung adenocarcinoma (LADC) and normal lung tissue samples from patients with or without smoking history. Immune cells as well as fibroblasts and endothelial cells respond to tobacco smoke exposure by inducing a highly inflammatory state in normal lung tissue. In the presence of LADC, we identified differentially expressed transcriptional programmes in macrophages and cancer-associated fibroblasts, providing insight into how the niche favours tumour progression. Within tumours, we distinguished eight subpopulations of neoplastic cells in female smokers and never smokers. Through pseudotemporal ordering, we inferred a trajectory towards two differentiated tumour cell states implicated in cancer progression and invasiveness. A proliferating cell population sustaining tumour growth exhibits differential immune modulating signatures in both patient groups. Our results resolve cellular heterogeneity and immune interactions in LADC, with a special emphasis on female never smokers and implications for the design of therapeutic approaches.

  Study EGAS00001006331

• Microdissected Pancreatic Cancer Whole Exome Sequencing

  109 micro-dissected pancreatic cancer cases and normal control tissue were subjected to whole-exome sequencing. Microdissection enriches tumor cellularity and enhances mutation calling.

  Study phs000953

• Mutational Landscape Determines Sensitivity to PD-1 Blockade in Non-Small Cell Lung Cancer

  Patients with non-small cell lung cancer were treated with pembrolizumab. Their tumors and matched normal blood were sequenced.

  Study phs000980

• TOTHER3

  Patritumab deruxtecan in HER2-negative breast cancer: part B results of the window-of-opportunity SOLTI TOT-HER3 trial and biological determinants of early response

  Study EGAS50000000385

• Low-coverage whole genome sequencing of plasma from BRCA-mutant breast cancer patients

  Plasma samples from patients with breast cancer (stage IV) who had confirmed BRCA mutations were subjected to low-coverage whole-genome sequencing This dataset contains raw fastq files from 6 breast cancer plasma samples.

  Dataset EGAD50000000810

• WGS data of 100 Breast Cancer patients from SV Based ctDNA Detection study

  Whole Genome Sequencing data of 100 Breast Cancer patients from "Ultrasensitive Detection and Monitoring of Circulating Tumor DNA using Structural Variants in Early-Stage Breast Cancer" study.

  Dataset EGAD50000001175

• Osteosarcoma_RNAseq

  We propose to definitively characterise the somatic genetics of Osteosarcoma cancer through generation of comprehensive catalogues of somatic mutations by high coverage genome and transcriptome sequencing.

  Study EGAS00001000615

• Lung_Cancer_Whole_Genomes

  We propose to definitively characterise the somatic genetics of Lung cancer through generation of comprehensive catalogues of somatic mutations by high coverage genome sequencing.

  Study EGAS00001000148

• HKU Gastric Cancer Genomics study - WGS, DNA genotyping array, expression and methylation profiling

  HKU Gastric Cancer Genomics study - Whole Genome Sequencing, DNA genotyping array, Expression profiling and Methylation profiling

  Study EGAS00001000597

• GEL_WGS_Comparison

  These samples are to be analysed with the CGP Developed cancer panel and the results will be compared with WGS data from 4 different comercial providers.

  Study EGAS00001000649

• HiSeq Colorectal Cancer Dataset

  Set of 19 patients afflicted with colorectal cancer with matching preoperative and postoperative blood plasma, PBMC, and tumor biopsy sequencing data. Originally referenced by Genome-wide cell-free DNA mutational integration enables ultra-sensitive cancer monitoring. Nat Med. 2020, Zviran et. al.

  Dataset EGAD00001011186

• National Cancer Institute (NCI) Head and Neck Cancer Study

  Head and neck cancers have well-documented associations with tobacco and alcohol exposure, but the disease develops in only a small fraction of users, which implies an important role for genetic susceptibility. Therefore, head and neck cancers are an excellent model for studying genetic susceptibility to environmental carcinogens. The primary goal of this study is to perform a comprehensive two-stage, high-density, genome-wide single-nucleotide polymorphism (SNP) analysis of head and neck cancer cases and corresponding frequency matched controls to identify novel genetic risk factors for head and neck cancer. In the study, we genotyped 2242 head and neck cancer cases and 1198 controls using Illumina HumanOmniExpress-12v1 BeadChip.

  Study phs001173