6048 results for "canc*"

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• Sequencing data for oesophageal and related samples - Mourikis et al (WGS)

  Data supporting: "Patient-specific detection of cancer genes reveals recurrently perturbed processes in esophageal adenocarcinoma." Mourikis et al. WGS (BAM files) 521 samples

  Dataset EGAD00001004775

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

  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. RNAseq (BAM files)

  Dataset EGAD00001006353

• WES data of colorectal cancer patients

  35 samples from individuals with colorectal tumors, exome sequencing

  Dataset EGAD00001007745

• WGS data of colorectal cancer patients

  36 samples from individuals with colorectal tumors, whole genome sequencing

  Dataset EGAD00001007746

• Sequencing data for oesophageal and related samples - OACs 496 release (WGS)

  Data from 496 OCCAMS (Oesophageal Cancer Clinical And Molecular Stratification) cases. WGS BAM files 496x oesophageal adenocarcinoma samples 496x normal samples

  Dataset EGAD00001007785

• CPC-GENE primary prostate benign and tumour tissue Hi-C sequencing reads

  This dataset contains the raw sequencing data, in FASTQ format, for Hi-C assays from 17 primary prostate tissue samples. The sequencing data is paired-end, 150 bp sequencing data from an Illumina NovaSeq 6000 machine, and contains 5 benign tissue samples and 12 primary tumour samples from the Canadian Prostate Cancer Genome Network (CPC-GENE) project. Tumour samples have IDs starting with the "CPCG" prefix, and benign tissue samples have IDs starting with the "BP" suffix.

  Dataset EGAD00001008024

• Dataset for hematopoietic_malignancy-EXON

  Rare cancer sequencing data of 91 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008882

• WCDT deep RNA-seq

  This dataset includes fastq files for total RNAseq of 104 patient biopsies with metastatic castration resistant prostate cancer. The RNAseq libraries were rRNA depleted and sequenced at 150bp paired-end on Illumina Novaseq.

  Dataset EGAD00001008799

• cell-free DNA Whole Genome Sequencing of 3784 samples on MGI and Illumina platform

  The dataset of Integrative modeling of tumor genomes and epigenomes for enhanced cancer diagnosis by cell-free DNA includes 3784 whole genome sequencing bam files on the MGI and Illumina platform. The analyzed samples include plasma samples from normal individuals and patients with cancer.

  Dataset EGAD00001009335

• CCMA

  This dataset has the processed WGS data for the cancer models in CCMA.

  Dataset EGAD00001009633

• Human primary and metastatic colorectal cancer (CRC) samples

  Bank of human both primary and metastastic colorectal cancer sample RNAseq

  Dataset EGAD00001009712

• Tumor Educated Platelets (TEPs) for breast cancer detection

  The TEP dataset consists of 549 Fastq samples which are divided into two experiments: a training data cohort, used to train the classifier, and a validation data cohort, used to assess classifier performance

  Dataset EGAD00001009790

• Single-cell RNA-sequencing of CD19 Chimeric Antigen Receptor (CAR) T-cells (CD19 CAR T-cells) from a Phase I clinical study in paediatric ALL: CARPALL

  Chimeric antigen receptor (CAR)-modified T-cells have become established as an effective treatment of haematological cancers. In the context of relapsed and refractory childhood pre-B cell acute lymphoblastic leukaemia (B ALL), CD19 targeting CAR T-cells often induce durable remissions. Previously, we generated a novel low-affinity CAR incorporating a CD19-specific single-chain variable fragment (scFV) called CAT, displaying a faster off-rate of interaction than the FMC63 CD19 binder used in prior clinical studies. Here, we systematically analysed CD19 CAR T-cells of ten children with relapsed or refractory B ALL enrolled in the CARPALL trial (NCT02443831). To characterize persisting CD19 CAR T-cells, we performed high throughput single-cell gene expression and T-cell receptor (TCR) sequencing of infusion products and serial blood and bone marrow samples up to five years post-infusion. We isolated CAR T-cells from peripheral blood or bone marrow by flow cytometry for CD3 and CAR expression, prior to single cell sequencing (Chromium 10X) platform.

  Dataset EGAD00001010018

• Treated and control Patient Derived Xenografts of colorectal cancer (CRC) samples

  Bank of treateed and control PDXs metastastic colorectal cancer sample RNAseq

  Dataset EGAD00001010022

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 5)

  Whole genome sequencing data of 19 high-grade serous carcinoma (HGSC) patients (47 samples) sequenced with HiSeq X Ten.

  Dataset EGAD00001010029

• CCMA-RNA

  This dataset has the raw RNA sequencing data for the cancer models in CCMA.

  Dataset EGAD00001010034

• FFPE, buffycoat and cell free DNA from N. German esophagus cancer patients - 2021

  28 patients. Cell-free DNA and leukocyte DNA, both from before any neoadjuvant treatment. Tumor FFPE tissue (plus metastasic tissue for some patients) from after any neoadjuvant treatment. Some cfDNA from follow-up time points (e.g. after neodj. treatment or in the clinical course). IDT xgen Pan-Cancer panel for hybridisation capture. Illumina TruSeq library prep for cfDNA and leukocyte DNA, Illumina DNA Prep for FFPE DNA. n=150 libraries in total.

  Dataset EGAD00001010081

• untargeted whole genome sequencing - Evaluation and correction of GC biases in cell-free DNA at the fragment level

  These are aligned paired-end reads from Illumina NovaSeq 6000 whole-genome sequencing of 4 cfDNA samples extracted from blood plasma (plasma-Seq). Three samples from patients with breast cancer, prostate cancer, or colorectal cancer and one sample from a healthy individual were aligned to GRCh38 (GCA_000001405.15_GRCh38_no_alt_plus_hs38d1_analysis_set). The observed GC bias is different in each of these cfDNA samples which leads to different average GC content per sample. This bias is corrected using the GCparagon commandline tool.

  Dataset EGAD00001010100

• RNAseq analysis on primary sites Colorectal Cancer xenografts (PRX) samples

  Bank of primary sites (PRs) colorectal cancer of Patient Derived Xenografts (PDXs)

  Dataset EGAD00001010101

• Sequencing data for the manuscript "Early on-treatment changes in circulating tumor DNA fraction and response to enzalutamide or abiraterone in metastatic castration-resistant prostate cancer"

  This submission contains gzipped fastq files from paired-end targeted sequencing.

  Dataset EGAD00001010105

• MutWP5: CRUK Mutographs of Cancer: Breast: Reduction Mammoplasty (WG)

  Sequencing of LCM-derived microbiopsies from 10 women who underwent reduction mammoplasty. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. 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 women who had breast cancer and those who are BRCA 1/2 carriers. This dataset contains all the data available for this study on 2023-03-08.

  Dataset EGAD00001010109

• MutWP5: CRUK Mutographs of Cancer: Breast: Reduction Mammoplasty (Exome)

  Sequencing of LCM-derived microbiopsies from 10 women who underwent reduction mammoplasty. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Exome data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequently be sent for whole-genome sequencing. Results from this portion of the study will be compared to women who are BRCA1/2 germline carriers and those with cancer. . This dataset contains all the data available for this study on 2023-03-08.

  Dataset EGAD00001010110

• MutWP5: CRUK Mutographs of Cancer: Lung: PD43291_Novaseq (WG)

  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 mutaiton 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 poriton 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 2023-03-08.

  Dataset EGAD00001010111

• MutWP5: CRUK Mutographs of Cancer: BRCA Carriers (WG)(Novaseq)

  Sequencing of LCM-derived microbiopsies from 20 women who underwent risk-reducing reduction mastecomies due to germline BRCA1/2. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Exome data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequenctly be sent for whole-genome sequencing. Results from this poriton of the study will be compared to women who had cosmetic breast reduction surgeries and those with cancer. . This dataset contains all the data available for this study on 2023-03-08.

  Dataset EGAD00001010112

• MutWP5: CRUK Mutographs of Cancer: Breast: Reduction Mammoplasty (WG)(Novaseq)

  Sequencing of LCM-derived microbiopsies from 10 women who underwent reduction mammoplasty. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Exome data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequenctly be sent for whole-genome sequencing. Results from this poriton of the study will be compared to women who are BRCA1/2 germline carriers and those with cancer. . This dataset contains all the data available for this study on 2023-03-08.

  Dataset EGAD00001010113

• MutWP5: CRUK Mutographs of Cancer: Cancer Mastectomy (WG)(Novaseq)

  Sequencing of LCM-derived microbiopsies from 40 women who underwent mastecomies due to breast cancer. LCM and sequencing will be conducted on both normal, unaffected breast, and, where possible, tumour tissue. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue, and compare findings between the normal and associated cancer tissues. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this poriton of the study will be compared to women who had cosmetic breast reduction surgeries and those who are BRCA carriers. . This dataset contains all the data available for this study on 2023-03-08.

  Dataset EGAD00001010114

• MutWP5: CRUK Mutographs of Cancer: Breast: Reduction Mammoplasty (Exome)(Novaseq)

  Sequencing of LCM-derived microbiopsies from 10 women who underwent reduction mammoplasty. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Exome data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequenctly be sent for whole-genome sequencing. Results from this poriton of the study will be compared to women who are BRCA1/2 germline carriers and those with cancer. . This dataset contains all the data available for this study on 2023-03-08.

  Dataset EGAD00001010116

• MutWP5: CRUK Mutographs of Cancer: BRCA Carriers (Exome)(Novaseq)

  Sequencing of LCM-derived microbiopsies from 20 women who underwent risk-reducing reduction mastecomies due to germline BRCA1/2. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Exome data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequenctly be sent for whole-genome sequencing. Results from this poriton of the study will be compared to women who had cosmetic breast reduction surgeries and those with cancer. . This dataset contains all the data available for this study on 2023-03-08.

  Dataset EGAD00001010115

• MutWP5: CRUK Mutographs of Cancer: Cancer Mastectomy (Exome)(Novaseq)

  Sequencing of LCM-derived microbiopsies from 40 women who underwent mastecomies due to breast cancer. LCM and sequencing will be conducted on both normal, unaffected breast, and, where possible, tumour tissue. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue, and compare findings between the normal and associated cancer tissues. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this poriton of the study will be compared to women who had cosmetic breast reduction surgeries and those who are BRCA carriers. . This dataset contains all the data available for this study on 2023-03-08.

  Dataset EGAD00001010117

• Somatic mutation and clonal evolution normal breast tissue WGS

  Cancer is a genetic disease caused by an accumulation of mutations, however many of these mutations have been identified in pathologically normal tissue. We aim to use laser-capture microscopy (LCM) to sample individual clones from breast tissue to identify whether cancer-associated mutations appear in this normal tissue, assess the mutational burden present, and identify the mutational processes causing these mutations. We will sample from a wide age range of individuals (<20 to >70 years old) to determine whether these processes differ in pre- and post-menopausal women. We will also be comparing the tissue from healthy individuals (samples from breast reduction surgery) to those at elevated risk of breast cancer (mastectomy from BRCA1/2 patients) and those who have breast cancer (adjacent normal, distal normal, and tumour tissue from mastectomy). This will allow us to determine how these processes are different between these groups of individuals, and gain insight into the earliest stages of tumour development. . This dataset contains all the data available for this study on 2023-03-09.

  Dataset EGAD00001010123

• Breast cancer topographs

  Whole genome sequencing to identify subclonal variants for subsequent mapping back to fixed tissue specimens. . This dataset contains all the data available for this study on 2023-03-09.

  Dataset EGAD00001010124

• Genomics of acral lentiginous melanoma

  Melanoma is the most aggressive type of skin cancer, causing about 75% of dermatological cancer deaths. Acral lentiginous melanoma (ALM) is the most common subtype of melanoma in admixed Latin American populations, but very few tumour genomes and exomes, all from European-descent individuals, have been analysed across several studies. Because of this, the genomic landscape of ALM is mostly unknown. Our aim in this project is to define this landscape and identify driver somatic alterations by whole-exome sequencing a collection of ALM germline/tumour paired FFPE samples from the National Cancer Institute of Mexico. . This dataset contains all the data available for this study on 2023-03-09.

  Dataset EGAD00001010126

• patient-derived head and neck cancer organoids

  patient-derived head and neck cancer organoids

  Dataset EGAD00001010134

• Ither2 WXS dataset - Implementation of pediatric precision oncology into clinical practice: The individualized Therapies for Children with cancer program “iTHER”

  iTHER is a prospective national precision oncology program aiming to define tumor molecular profiles in children and adolescents with primary very high-risk, relapsed, or refractory pediatric tumors in order to identify relevant aberrations to inform treatment.

  Dataset EGAD00001010178

• sWGS data of Pap test smears and tumor tissues

  Shallow whole-genome sequencing data divided into three groups: - sWGS data from Pap smears of patients with confirmed high grade serous ovarian cancer - sWGS data from matched tumor tissue (at diagnosis) from the same patients - sWGS data from Pap tests smears of healthy women

  Dataset EGAD00001010141

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0175_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0175_001 for Triple negative breast cancer patient-derived xenograft SA535X6XB03101

  Dataset EGAD00001011224

• WES and RNA-seq data of 11 cancer patients with multiple cancer types

  This dataset includes WES and RNAseq from 11 patients with metastatic melanoma, lung, kidney, and stomach cancers, enrolled in phase I clinical trials of TIL ACT (NCT03475134 & NCT04643574). WES was performed on matched cancer and healthy samples, whereas RNAseq was performed on cancer tissues, using Illumina HiSeq 2500/4000 and Illumina NextSeq 550 systems. Paired-end reads are provided in fastq format.

  Dataset EGAD00001010169

• Ither2 RNA-Seq dataset - Implementation of pediatric precision oncology into clinical practice: The individualized Therapies for Children with cancer program “iTHER”

  iTHER is a prospective national precision oncology program aiming to define tumor molecular profiles in children and adolescents with primary very high-risk, relapsed, or refractory pediatric tumors in order to identify relevant aberrations to inform treatment.

  Dataset EGAD00001010179

• Somatic L1 retrotransposition in normal colorectal epthelium

  Throughout an individual’s lifetime, genomic alterations accumulate in somatic cells. However, the mutational landscape induced by retrotransposition of long interspersed nuclear element-1 (L1), a widespread mobile element in the human genome, is poorly understood in normal cells. Here, we explored the whole-genome sequences of 406 normal colorectal clones, 12 MUTYH-associated adenomatous clones, and 19 matched colorectal cancer tissues. In addition, we analyzed promoter DNA methylation status of retrotransposition-competent L1 (in 139 clones) and read-through RNA expression profiles (in 116 clones) to investigate the epigenetic regulation of L1 activity.

  Dataset EGAD00001010183

• CRUK-ICGC Prostate DNA Methylation Sequencing Dataset (Prostatectomy Batches 1-6)

  This dataset includes Illumina EPIC Capture Sequencing Data of 376 samples from 188 men with prostate cancer. Samples were taken from primary tissue obtained at prostatectomy, with matched pathologically assessed non-cancer control material. This DNA methylation data includes donors and samples included in previously published WGS datasets (from CRUK-ICGC batches 1 to 3 [EGAD00001001116] and batches 4 to 6 [EGAD00001003225]; including the majority of donors used in Wedge et al, Nature Genetics 2018 [PMID: 29662167]). The targeted DNA methylation sequencing data in this EGA dataset were generated using the Illumina TruSeq methyl capture method (EPICseq), covering over 3.3 million CpGs in the human genome, representing a total targeted hybridisation capture panel of 107Mbp. According to the EPICseq protocol, DNA samples extracted from prostatectomy tissue samples were enriched for target regions using hybridisation capture, prior to bisulfite conversion, amplification and sequencing in pools of 12 samples (150 single end reads over two Illumina HiSeq4000 lanes). This approach generated DNA methylation profiles from prostate cancer and control samples at base-pair resolution across millions of CpGs in the human genome.

  Dataset EGAD00001010184

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 6)

  Whole genome sequencing data of 31 high-grade serous carcinoma (HGSC) patients (101 samples) sequenced with HiSeq X Ten and BGISEQ-500

  Dataset EGAD00001010202

• Spatial TCR sequencing in breast cancer

  Spatial characterization by TCR sequencing in tumor core and matched stroma in seven cases of triple negative breast cancer.

  Dataset EGAD00001010203

• Mechanism of action and resistance to Trastuzumab Deruxtecan in patients with metastatic breast cancer: the DAISY trial

  198 exome sequencing samples

  Dataset EGAD00001009853

• WGS

  Whole-genome sequencing of pancreatic cancer organoids and matched germline controls.

  Dataset EGAD00001010835

• Genomic data used in "ACT-Discover: identifying karyotype heterogeneity in pancreatic cancer evolution using ctDNA"

  Genomic data used in "ACT-Discover: identifying karyotype heterogeneity in pancreatic cancer evolution using ctDNA"

  Dataset EGAD00001010250

• lymphoma plasma cfRNA

  Dataset contains total RNA sequencing data from plasma of 65 different human donors: 30 diffuse large B-cell lymphoma (DLBCL) and 13 primary mediastinal large B-cell lymphoma (PMBCL) patients, and 22 cancer-free controls. Samples were sequenced on a NovaSeq 6000 and are provided in FASTQ format.

  Dataset EGAD00001010259

• Massive genomic rearrangement acquired in a single catastrophic event during cancer development

  Massive genomic rearrangement acquired in a single catastrophic event during cancer development

  Dataset EGAD00001000002

• Sebaceous carcinoma tumor/normal exome sequencing and transcriptome sequencing. Transcriptome sequencing of

  Sebaceous carcinomas (SeC) are cutaneous malignancies that, in rare cases, metastasize and prove fatal. Here we report whole exome sequencing on 32 SeC, revealing distinct mutational classes that explain both cancer ontogeny and clinical course. A UV-damage signature predominated 10/32 samples, while 9 were instead defined by microsatellite instability (MSI) mutations. UV-damage SeC exhibited poorly differentiated, infiltrative histopathologycompared to MSI signature SeC (p = 0.003), features previously associated with dissemination. Strikingly, UV-damage SeC transcriptomes and anatomic distributionclosely resembling those of cutaneous squamous cell carcinomas (SCC), implicating sun-exposed keratinocytes as a cell of origin. Like SCC, this UV-damage subclass harbors a high somatic mutation burden with >50 mutations/Mb, predicting immunotherapeutic response. In contrast, ocular SeC acquire far fewer mutations without a dominant signature, but show frequent truncating mutations in the ZNF750 epidermal differentiation regulator. Our data exemplify how different mutational processes convergently drive histopathologically related but clinically distinct cancers.

  Dataset EGAD00001004016

• Tumour evolvability metrics predict recurrence in advanced localised prostate cancer (tumour data)

  There is a need for quantitative measurements of evolutionary metrics in controlled clinical trials with long term follow-up information. This is particularly true in advanced localised prostate cancer, which can recur more than a decade after diagnosis. Here we mapped genomic intra-tumour heterogeneity in 642 tumour samples from 114 patients who took part in the IMRT and DELINEATE clinical trials, for which full clinical information and 12y median follow-up was available. We concomitantly assessed phenotypic (morphological) heterogeneity using Deep Learning in 1,923 histological sections from 250 IMRT patients (fully overlapping with the genetic set). This study shows that combining genomics with AI-aided histopathology in clinical trials leads to novel clinical biomarkers. This EGA repository contains data produced from tumour samples using low coverage whole genome sequencing and a prostate cancer specific gene panel data following compression of unique molecular identifiers.

  Dataset EGAD00001010274

• Methylation profiles in blood (breast cancer cases)

  Raw methylation data from blood samples in breast cancer cases.

  Dataset EGAD00010002470