7253 results for "canc*"

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• 76 cancer and normal whole genomes from eleven SI-NET patients

  This dataset comprises of 76 cancer and normal whole genomes obtained from 11 SI-NET patients, in the form of two fastq files (forward and reverse reads) for each genome containing sequences generated by Illumina NovaSeq 6000 system.

  Dataset EGAD00001006161

• Single Cell RNAseq of PBMC from renal cancer patients

  Single Cell RNAseq of PBMC from renal cancer patients

  Dataset EGAD00001006175

• Data from Representation of genomic intratumor heterogeneity in multi-region non-small cell lung cancer patient-derived xenograft models

  Data from Representation of genomic intratumor heterogeneity in multi-region non-small cell lung cancer patient-derived xenograft models

  Dataset EGAD00001012228

• Whole exome sequencing of long-term, never relapse exceptional responders of trastuzumab-treated HER2+ metastatic breast cancer

  The dataset contains Whole Exome Sequencing data (BAM files) of 22 samples from HER2+ metastatic breast patients. For 9 of the 13 tumours samples there are paired controls available from normal tissue. There are 8 tumours samples that are from treatment-responder patients and 5 tumours samples from non responder patients.

  Dataset EGAD00001006217

• SPECTA Lung cancer RNA FASTQ files

  SPECTA Lung cancer RNA FASTQ files (Illumina TST170 targeted analysis)

  Dataset EGAD00001006222

• Neoplastic pancreatic cysts and associated cancers

  Data from a study of 148 samples from IPMNs, MCNs, and small associated invasive carcinomas from 18 patients using whole exome or targeted sequencing. Sequencing data from 77 samples out of the 148 samples in the complete study are available in this dataset, based on the permissions given by the participating patients and the informed consents.

  Dataset EGAD00001006229

• WES data from 165 tumor/germline samples with muscle invasive bladder cancer.

  In this study, a total of 300 patients with MIBC receiving chemotherapy were included; 62 received NAC before cystectomy and 245 received first-line chemotherapy upon detection of locally-advanced (T4b) or metastatic disease. Treatment response, defined as pathological downstaging (< pTa,CIS,N0) after NAC or complete or partial response after first-line treatment (RECIST criteria). WES was performed using DNA from 165 tumors (76x median coverage) and associated germline DNA (46x median coverage). Data provided here consist of 5,828 fastq files for WES.

  Dataset EGAD00001006239

• RNA-seq data of breast cancer HCI011 model from Ros et al (2020)

  RNA-seq data of the HCI011 and HCI011R models, GDC032 treated and control (total of 21 samples), from the paper: FOXM1 is a biomarker of resistance to PI3Kα inhibition in ER+ breast cancer that is detectable using metabolic imaging (Ros et al, 2020)

  Dataset EGAD00001006245

• SPECTA Lung cancer VCF files

  SPECTA Lung cancer VCF files

  Dataset EGAD00001006260

• WES data of serially passaged TIC-enriched spheres of colorectal cancer

  WES data of serially passaged TIC-enriched spheres of colorectal cancer (CRC)

  Dataset EGAD00001006266

• RNA-Seq of serially passaged TIC-enriched spheres of colorectal cancer

  18 samples of RNA-Seq of serially passaged TIC-enriched spheres of colorectal cancer (CRC), sequenced on HiSeq2000 and HiSeq2500

  Dataset EGAD00001006264

• WGS data of serially passaged TIC-enriched spheres of colorectal cancer

  WGS data of serially passaged TIC-enriched spheres of colorectal cancer

  Dataset EGAD00001006265

• panel data of ALK-positiv non-small cell lung cancer patients

  270 samples with ALK-positiv non-small cell lung cancer, targeted sequencing (198 kb panel size)

  Dataset EGAD00001006297

• WGS data of ALK-positiv non-small cell lung cancer patients

  268 samples with ALK-positiv non-small cell lung cancer, ultra-low coverage whole genome sequencing

  Dataset EGAD00001006298

• Genomic and transcriptomic data of glioma specimens

  Dataset consists of 207 glioma samples of WHO grades II, III and IV. Dataset consists 182 tumor derived genomic data of ~700 cancer-related and epigenetic-related genes with matched blood samples for 48 specimens. Dataset also consists transcriptomic data for 105 specimens. In total 335 bam files were deposited.

  Dataset EGAD00001006299

• AVENIO Expanded ctDNA panel sequence alignments (BAMs) from plasma DNA of BC, CRC and NSCLC patients

  The AVENIO ctDNA Expanded Kit is a next-generation sequencing (NGS) liquid biopsy assay with a 77 gene panel (192 kb) containing genes in U.S. National Comprehensive Cancer Network (NCCN) Guidelines and emerging cancer biomarkers. This pan-cancer assay was applied to 48 plasma samples from patients with breast, colorectal and non-small cell lung cancer. After sequencing 150bp paired-end, reads were aligned to the hg38 genome with the AVENIO Oncology Analysis Software (version 2.0). These files are the deduplicated alignments generated by the analysis software used for subsequent variant, indel and CNV calling.

  Dataset EGAD00001006301

• RNA-SEQ for the Caldas Lab breast cancer PDTX collection

  RNA-SEQ for the Caldas Lab breast cancer PDTX collection. This includes both single and paired end runs

  Dataset EGAD00001006307

• whole exome sequencing (WES) data of the HIPO head and neck cancer (HNC, n=83)

  Paired whole exome sequencing data of the HIPO head and neck cancer (HNC) (n=83), using Agilent SureSelect V4+UTRs and V6+UTRs with the sequencing platforms HiSeq2000 and HiSeq2500. The reads were aligned to hg19. This is part of project H019.

  Dataset EGAD00001006336

• Whole Exome Sequencing of High grade T1 non-muscle invasive bladder cancer

  The dataset consists of a multisample VCF (version 4.1) and the corresponding annotated MAF file, containing the somatic point mutations found from exome sequencing across the high-grade T1 bladder cancer cohort (HGT1, n=61 samples). The VCF file is in accordance with the HTS format specifications (https://samtools.github.io/hts-specs/). The dataset comprises also a CSV file with clinical data.

  Dataset EGAD00001006346

• Sequencing data for oesophageal and related samples - Katz-Summercorn, Jammula et al (WGS)

  Data supporting: “Multi-omic cross-sectional cohort study of pre-malignant Barrett’s esophagus reveals structural variation and retrotransposon activity occur early in cancer evolution.” Katz-Summercorn, Jammula et al. WGS (BAM files)

  Dataset EGAD00001006349

• Targeted sequencing of breast cancer susceptibility genes for 1,995 Japanese breast cancer patients

  This dataset consists of 106 bam files. Each sample from 10-20 consecutive patient extractions were combined into one DNA pool, generating a total of 106 DNA pools. We sequenced 11 genes implicated in hereditary breast cancer using the SureSelect Custom kit.

  Dataset EGAD00001006368

• Detection of ctDNA in Plasma of Patients with Clinically Localised Prostate Cancer is Associated with Rapid Disease Progression

  Whole genome sequencing of tumour-normal pairs in eight patients with clinically localised disease undergoing prostatectomy. A bespoke DNA capture and amplification panel against the highest prevalence, highest confidence aberrations for each individual was designed and used to interrogate ctDNA isolated from plasma prospectively obtained pre- and post- (24 hours and 6 weeks) surgery. Tagged-amplicon deep sequencing (TAm-Seq) across the TP53 gene in ctDNA in a cohort of 189 individuals.

  Dataset EGAD00001006369

• sWGS for genome-wide copy number profiling

  Shallow whole-genome sequencing (sWGS) data for the identification of somatic copy number alterations (SCNA) and the estimation of tumor fractions in plasma DNA of metastatic colorectal cancer patients (mCRC).

  Dataset EGAD00001006384

• Copy number profiling of tissue and plasma samples from high grade serous epithelial ovarian cancer patients

  This dataset includes 289 samples from 46 high grade serous epithelial ovarian cancer patients. Data are from both tissue samples (either primary tumor, or synchronous metastases) and circulating cell-free DNA (cfDNA) of plasma samples taken during therapy and follow-up.

  Dataset EGAD00001006422

• Pre-clinical evolution of haematological malignancies_WGS

  Leukaemia and related blood cancers occur due to genetic changes that typically accumulate over many years. This study will employ targeted next-generation sequencing to retrace the preclinical evolution of several types of haematological malignancy. Investigating the progression of the earliest pre-malignant ancestral clones promises to offer valuable insights into early leukaemia evolution and therapeutic vulnerabilities of leukaemia stem cells.

  Dataset EGAD00001006423

• Illumina TSO500 RNA Dataset for Manuscript titled: Evaluation of Endobronchial Ultrasound-Guided Transbronchial Needle Aspiration (EBUS-TBNA) Samples from Advanced Non-Small Cell Lung Cancer for Whole Genome, Whole Exome and Comprehensive Panel Sequencing

  Illumina TSO500 RNA Dataset for Manuscript titled: Evaluation of Endobronchial Ultrasound-Guided Transbronchial Needle Aspiration (EBUS-TBNA) Samples from Advanced Non-Small Cell Lung Cancer for Whole Genome, Whole Exome and Comprehensive Panel Sequencing

  Dataset EGAD00001015397

• WGS and WES of Advance Prostate Cancer

  The dataset consists of BAM files of 2 pairs of matched tumor/normal samples of a men with advanced prostate cancer. One pair is whole genome sequencing: WGS_T/WGS_N for tumor and normal samples, respectively; and the other pair is whole exome sequencing: WES_T/WES_N for tumor and normal specimens, respectively. Details can be found at the publication titled: "Molecular Medicine Tumor Board: Whole Genome Sequencing to Inform on Personalized Medicine for a Man with Advanced Prostate Cancer"

  Dataset EGAD00001006487

• Lung cancers from admixed Latin American populations (2)

  Raw data from cancer panel sequencing of lung adenocarcinomas from admixed Latin American populations, predominantly samples without known oncogene mutations (n=532).

  Dataset EGAD00001006571

• Somatic variants in 344 colorectal cancer samples

  The dataset contains somatic variants in 344 colorectal cancer samples. Variants are called with Mutect2 (GRCh38). Important: VCF-files include also variants, which have been annotated as "str_contraction" and "panel_of_normals". Please, use only "PASS" variants in studies, which are not microsatellite repeat related. Samples are sequenced with Novaseq 6000, HiSeq 2000, and HiSeq X Ten instruments (average coverage depth ~30+). The dataset consists of 257 MSS, 58 MSI, 25 MSS IBD, and 4 POLE mutant CRCs.

  Dataset EGAD00001006572

• Prognostic and immunomodulatory consequences of ERV expression in ovarian cancer

  The dataset contains transcriptional data obtained using total RNA sequencing on a Illumina machin. 59 samples are from the Hammersmith Hospital (HH) cohort of human primary ovarian tumours and 20 samples are from ovarian cancer cell lines Kuramochi (3 replicates) and Ovsaho (2 replicates) treated with 1 uM DNMTi guadecitabine or vehicle, at an early (day 5) or late (day 8) timepoint.

  Dataset EGAD00001006589

• EORTC RP1335 SPECTA Lung cancer data - Oncomine

  EORTC RP1335 SPECTA Lung cancer data - Oncomine dataset

  Dataset EGAD00001006594

• Validated Single-cell RNA sequencing in early breast cancer

  Single-cell RNA and VDJ sequencing of early breast cancer

  Dataset EGAD00001006608

• CINECA_synthetic_cohort_EUROPE_UK1 referencing fake samples

  Please note: This synthetic data set (with cohort “participants” / ”subjects” marked with FAKE) has no identifiable data and cannot be used to make any inference about cohort data or results. The purpose of this dataset is to aid development of technical implementations for cohort data discovery, harmonization, access, and federated analysis. In support of FAIRness in data sharing, this dataset is made freely available under the Creative Commons Licence (CC-BY). Please ensure this preamble is included with this dataset and that the CINECA project (funding: EC H2020 grant 825775) is acknowledged. For any questions please contact isuru@ebi.ac.uk or cthomas@ebi.ac.uk This dataset (CINECA_synthetic_cohort_EUROPE_UK1) consists of 2521 samples which have genetic data based on 1000 Genomes data (https://www.nature.com/articles/nature15393), and synthetic subject attributes and phenotypic data derived from UKBiobank (https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001779). These data were initially derived using the TOFU tool (https://github.com/spiros/tofu), which generates randomly generated values based on the UKBiobank data dictionary. Categorical values were randomly generated based on the data dictionary, continuous variables generated based on the distribution of values reported by the UK Biobank showcase, and date / time values were random. Additionally we split the phenotypes and attributes into 4 main classes - general, cancer, diabetes mellitus, and cardiac. We assigned the general attributes to all the samples, and the cardiac / diabetes mellitus / cancer attributes to a proportion of the total samples. Once the initial set of phenotypes and attributes were generated, the data data was checked for consistency and where possible dependent attributes were calculated from the independent variables generated by TOFU. For example, BMI was calculated from height and weight data, and age at death generated by date of death and date of birth. These data were then loaded to the development instance of Biosamples (https://www.ebi.ac.uk/biosamples/) which accessioned each of the samples. The genetic data are derived from the 1000 Genomes Phase 3 release (https://www.internationalgenome.org/category/phase-3/). The genotype data consists of a single joint call vcf files with call genotypes for all 2504 samples, plus bed, bim, fam, and nosex files generated via plink for these samples and genotypes. The genotype data has had a variety of errors introduced to mimic real data and as a test for quality control pipelines. These include gender mismatches, ethnic background mislabelling and low call rates for a randomly chosen subset of sample data as well as deviations from Hardy Weinberg equilibrium and low call rates for a random selection of variants. Additionally 40 samples have raw genetic data available in the form of both bam and cram files, including unmapped data. The gender of the samples in the 1000 genomes data has been matched to the synthetic phenotypic data generated for these samples. The genetic data was then linked to the synthetic data in BioSamples, and submitted to EGA.

  Dataset EGAD00001006673

• RNA-seq assessment of the impact of fasting-mimicking diet on tumor tissue specimens from early-stage breast cancer patients

  RNA-seq data (44 samples) from tumor tissue specimens pre and post fasting-mimicking diet from 22 early-stage breast cancer patients.

  Dataset EGAD00001006860

• PIK3CA SiMSen-Seq

  Simple, Multiplexed, PCR-based barcoding of DNA for Sensitive mutation detection using Sequencing (SiMSen-Seq) of 11 PIK3CA hotspot mutations in plasma DNA of breast cancer patients.ng

  Dataset EGAD00001006897

• Single cell sequencing of ovarian cancer

  Single cell sequencing of 12 ovarian cancer biopsies from 7 patients.

  Dataset EGAD00001006898

• MutWP5: CRUK Mutographs of Cancer: Lung: PD38233 (WG) (2021-02-02)

  Sequencing of LCM-derived microbiopsies from explanted lung from COPD patient. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Deep sampling throughout multiple regions of the lung will determine whether there are differences in smoking-related mutation burden in different portions of the lung. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this portion of the study will be compared to other individuals with smoking-related diseases (COPD, pulmonary fibrosis, lung cancer), and normal, non-smoking lungs. . This dataset contains all the data available for this study on 2021-02-02.

  Dataset EGAD00001006930

• MicroRNA profiling by next-generation sequencing for colorectal cancer screening

  The dataset contains raw miRNA sequencing data of plasma samples from 20 newly diagnosed colorectal cancer cases and 20 controls free of colorectal neoplasms matched by age and sex. It includes files in the FASTQ compressed (.gz) format.

  Dataset EGAD00001006966

• UROMOL 2020 - RNA-seq data validation

  For this project about non-muscle invasive bladder cancer (NMIBC), we analysed total RNA-seq data from 47 patients used for validation. Sequencing of total RNA was performed using KAPA RNA HyperPrep Kit with RiboErase HMR (Roche). RNA input was 100 to 500 ng. The dataset is composed of 94 fastq files.

  Dataset EGAD00001006967

• Targeted sequencing of Human esophageal epithelium microbiopsies

  NOTCH1 mutant clones occupy the majority of normal human esophagus by middle age, but are comparatively rare in esophageal cancers, suggesting NOTCH1 mutations may promote clonal expansion but impede carcinogenesis. Here we test this hypothesis. Visualizing and sequencing NOTCH1 mutant clones in aging normal human esophagus, reveals frequent biallelic mutations that block NOTCH1 signaling.  In mouse esophagus, heterozygous Notch1 mutation confers a competitive advantage over wild type cells, an effect enhanced by loss of the second allele.  Notch1 loss alters transcription but has minimal effects on epithelial structure and cell dynamics. In a carcinogenesis model, Notch1 mutations were less prevalent in tumors than normal epithelium. Deletion of Notch1 reduced tumor growth, an effect recapitulated by anti-NOTCH1 antibody treatment.  We conclude that Notch1 mutations in normal epithelium are beneficial as wild type Notch1 promotes tumor expansion. NOTCH1 blockade has therapeutic potential in esophageal squamous tumors.

  Dataset EGAD00001006969

• Clinical phenotype data

  Clinical data corresponding to the patients with ovarian cancer studied using scRNA-seq and bulk RNA-seq. Variables include molecular subtype, predicted immune phenotype, reviewing pathologist comment, final immune phenotype, histology characterization, and tumor stage.

  Dataset EGAD00001006973

• Bulk RNAseq fastq files

  RNAseq FASTq files from 15 samples from patients with ovarian cancer, 5 samples for each of the 3 tumor immune phenotypes (Infiltrated, Excluded and Desert).

  Dataset EGAD00001006975

• HER2-negative primary breast cancers WES

  Temporal HER2-negative breast cancers WES

  Dataset EGAD00001006980

• Single-cell RNA-seq data from metastatic ovarian cancer for quality control study

  This study includes treatment-naïve fresh tissue sample from 4 HGSOC patients.

  Dataset EGAD00001006984

• WES_SCLC_MDACC

  To identify genomic drivers present in limited-stage small cell lung cancer (LS-SCLC); To determine the overall tumor mutational burden in LS-SCLC; To determine genomic intratumor heterogeneity (ITH) in LS-SCLC.

  Dataset EGAD00001007004

• Cryopreservation of human cancers conserves tumour heterogeneity for single-cell multi-omics analysis

  Single-cell RNA-Sequencing of three primary breast cancers, two primary prostate cancers, and a metastatic melanoma sample from Wu et al. (2021) Genome Medicine study. Each tumour was sequenced across different cryopreservation conditions including Fresh Tissue (FT), cryopreserved single-cell suspensions (CCS), cryopreserved solid tissue fragments (CT) and a cryopreserved after overnight cold storage (CO). Data was generated using the Chromium controller (10X Genomics) and sequenced on the NextSeq platform.

  Dataset EGAD00001007030

• Geographic variation of mutagenic exposures in kidney cancer genomes – structural variation vcf files (Mutographs)

  Geographic variation of mutagenic exposures in kidney cancer genomes – structural variation vcf files ( Mutographs )

  Dataset EGAD00001013726

• Geographic variation of mutagenic exposures in kidney cancer genomes – copy number variants (Mutographs)

  Geographic variation of mutagenic exposures in kidney cancer genomes – copy number variants (Mutographs)

  Dataset EGAD00001013727

• Single cell resolution landscape of hypomutated childhood cancers

  A paradigm of childhood cancers is that they have a low mutation burden, with some ostensibly bearing fewer mutations than the normal tissues from which they derive. We set out to resolve this paradox by examining paediatric renal cancers with exceptionally few mutations using high resolution, high depth sequencing approaches. We found that apparent hypomutation was the result of unusual clonal architecture due to a normal tissue-like mode of tumour evolution, raising the possibility that the mutation burden of some cancers has been systematically misjudged.

  Dataset EGAD00001015406

• The complexity of tobacco smoke induced mutagenesis in head and neck cancer - sequence data (Mutographs)

  The complexity of tobacco smoke induced mutagenesis in head and neck cancer - sequence data (Mutographs)

  Dataset EGAD00001015386