8252 results for "canc*"

in 55.37 milliseconds.

• Whole-exome sequencing data from head and neck cancer patients

  This dataset contains paired-end whole-exome sequencing data (2x50 bp) from the normal samples, the primary tumors and the recurrences/metastases of 8 head and neck cancer patients.

  Dataset EGAD00001011278

• Clinical and genetic factors associated with tumor response to neoadjuvant (chemo)radiotherapy, survival and recurrence risk in rectal cancer

  Dataset consists of 216 samples, with each sample having a BAM, BAI and VCF file.

  Dataset EGAD00001011297

• Neoantigen Immunogenicity Landscapes and Evolution of Tumor Ecosystems During Immunotherapy with Nivolumab

  We performed Whole Exome (WXS) and RNASeq sequencing on samples obtained from the same site before and during therapy from our prospective clinical trial (CA209-153, NCT02066636) of nivolumab in advanced Non-small cell lung cancer (NSCLC) patients that progressed on chemotherapy. There are 58 pre and 42 on therapy WXS samples and 24 pre and 12 on therapy RNASeq samples. All WXS tumor samples have matching normal samples.

  Dataset EGAD00001011302

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 8a)

  Whole genome sequencing data of 26 high-grade serous carcinoma (HGSC) patients (87 samples) sequenced with MGISEQ-2000 and HiSeq X Ten.

  Dataset EGAD00001011304

• INSPIRE multi-timepoint cfMeDIP dataset

  This dataset contains raw sequencing data from multi-timepoint cell-free methylated DNA immunoprecipitation and sequencing (cfMeDIP-seq) of plasma samples from the INSPIRE study (NCT02644369). Details about the study, including inclusion/exclusion criteria and interventions are available at https://clinicaltrials.gov/study/NCT02644369. Briefly, five cohorts were included, INS-A (head & neck squamous cell carcinoma), INS-B (triple-negative breast cancer), INS-C (high-grade serous ovarian cancer), INS-D (melanoma), and INS-E (mixed solid tumors). All patients in the study were diagnosed with advanced cancer and received treatment with pembrolizumab. Plasma samples were collected at baseline and every 3 cycles until disease progression, death, loss of follow-up, or completion of the study. Plasma samples were first processed for cell-free DNA mutations and remaining samples were then processed by cfMeDIP-seq, prioritizing baseline and post-cycle 3 samples. In total, data from 204 timepoints from 87 distinct patients are deposited.

  Dataset EGAD00001011312

• Genome and transcriptome sequence data from a clear low grade adenocarcinoma of the lower rectum patient

  Genome and transcriptome sequence data from a clear low grade adenocarcinoma of the lower rectum patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001016568

• Genome and transcriptome sequence data from a metastatic high grade small cell neuroendocrine ca nasal cavity patient

  Genome and transcriptome sequence data from a metastatic high grade small cell neuroendocrine ca nasal cavity patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001016569

• Genome and transcriptome sequence data from a low grade serous ovarian cancer patient

  Genome and transcriptome sequence data from a low grade serous ovarian cancer patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001016570

• Genome and transcriptome sequence data from a metastatic gastric cancer patient

  Genome and transcriptome sequence data from a metastatic gastric cancer patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001016571

• Genome and transcriptome sequence data from a mixed histology adenocarcinoma high grade neuroendocrine carcinoma of the ge junction patient

  Genome and transcriptome sequence data from a mixed histology adenocarcinoma high grade neuroendocrine carcinoma of the ge junction patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001016572

• Genome and transcriptome sequence data from a peritoneal mesothelioma patient

  Genome and transcriptome sequence data from a peritoneal mesothelioma patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001016573

• Genome and transcriptome sequence data from a angiosarcoma of right breast patient

  Genome and transcriptome sequence data from a angiosarcoma of right breast patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001016574

• Genome and transcriptome sequence data from a metastatic rectal cancer patient

  Genome and transcriptome sequence data from a metastatic rectal cancer patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001016575

• Genome and transcriptome sequence data from a metastatic colorectal cancer patient

  Genome and transcriptome sequence data from a metastatic colorectal cancer patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001016576

• ICGC Prostate UK EPICSeq methylation sequencing data BAMs

  This dataset contains aligned BAM files generated from DNA methylation sequencing of prostate cancer and morphologically normal tissue samples from the ICGC Prostate UK cohort. Libraries were prepared using the Illumina TruSeq Methyl Capture EPIC (EPIC-Seq) assay and sequenced on the Illumina HiSeq 4000 platform. Sequence reads were aligned to the reference genome using Bismark v0.22.1.

  Dataset EGAD00001016579

• Dataset for Genomic and fragmentomic landscapes of cell-free DNA in aging and disease : MICA Morbidity Cohort

  This dataset contains 570 cram files from whole genome next-generation sequencing on the Illumina NovaSeq 6000 with 1-2x coverage. The samples analyzed include plasma samples from non-cancer patients from MICA cohort.

  Dataset EGAD00001016584

• Genome and transcriptome sequence data from a colon adenocarcinoma patient

  Genome and transcriptome sequence data from a colon adenocarcinoma patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001016602

• Genome and transcriptome sequence data from a metastatic chondrosarcoma patient

  Genome and transcriptome sequence data from a metastatic chondrosarcoma patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001016595

• Genome and transcriptome sequence data from a metastatic ovarian cancer patient

  Genome and transcriptome sequence data from a metastatic ovarian cancer patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001016596

• Genome and transcriptome sequence data from a poorly differentiated gastric adenocarcinoma patient

  Genome and transcriptome sequence data from a poorly differentiated gastric adenocarcinoma patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001016597

• Genome and transcriptome sequence data from a gastric adenocarcinoma patient

  Genome and transcriptome sequence data from a gastric adenocarcinoma patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001016598

• Genome and transcriptome sequence data from a metastatic colorectal cancer patient

  Genome and transcriptome sequence data from a metastatic colorectal cancer patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001016599

• Genome and transcriptome sequence data from a metastatic low grade rectosigmoid adenocarcinoma patient

  Genome and transcriptome sequence data from a metastatic low grade rectosigmoid adenocarcinoma patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001016600

• Genome and transcriptome sequence data from a glioblastoma patient

  Genome and transcriptome sequence data from a glioblastoma patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001016601

• Genome and transcriptome sequence data from a malignant peripheral nerve sheath tumour patient

  Genome and transcriptome sequence data from a malignant peripheral nerve sheath tumour patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001016603

• Genome and transcriptome sequence data from a rectosigmoid adenocarcinoma patient

  Genome and transcriptome sequence data from a rectosigmoid adenocarcinoma patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001016604

• Genome and transcriptome sequence data from a metastatic pancreatic adenocarcinoma patient

  Genome and transcriptome sequence data from a metastatic pancreatic adenocarcinoma patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001016605

• Genome and transcriptome sequence data from a metastatic dedifferentiated liposarcoma patient

  Genome and transcriptome sequence data from a metastatic dedifferentiated liposarcoma patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001016606

• Genome and transcriptome sequence data from a metastatic malignant melanoma patient

  Genome and transcriptome sequence data from a metastatic malignant melanoma patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001016607

• Genome and transcriptome sequence data from a metastatic small bowel cancer patient

  Genome and transcriptome sequence data from a metastatic small bowel cancer patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001016608

• Genome and transcriptome sequence data from a prostate adenocarcinoma, and small cell carcinoma of the prostate patient

  Genome and transcriptome sequence data from a prostate adenocarcinoma, and small cell carcinoma of the prostate patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001016609

• Genome and transcriptome sequence data from a metastatic goblet cell adenocarcinoma patient

  Genome and transcriptome sequence data from a metastatic goblet cell adenocarcinoma patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001016610

• Genome and transcriptome sequence data from a metastatic adenocarcinoma of lung patient

  Genome and transcriptome sequence data from a metastatic adenocarcinoma of lung patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001016611

• Genome and transcriptome sequence data from a malignant perivascular epithelioid cell tumor patient

  Genome and transcriptome sequence data from a malignant perivascular epithelioid cell tumor patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001016612

• Genome and transcriptome sequence data from a dedifferentiated endometrial cancer patient

  Genome and transcriptome sequence data from a dedifferentiated endometrial cancer patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001016613

• Genome and transcriptome sequence data from a colorectal cancer patient

  Genome and transcriptome sequence data from a colorectal cancer patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001016614

• Genome and transcriptome sequence data from a thymoma ab patient

  Genome and transcriptome sequence data from a thymoma ab patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001016615

• Genome and transcriptome sequence data from a metastatic hepatocellular carcinoma patient

  Genome and transcriptome sequence data from a metastatic hepatocellular carcinoma patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001016616

• Genome and transcriptome sequence data from a upper rectum adenocarcinoma patient

  Genome and transcriptome sequence data from a upper rectum adenocarcinoma patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001016617

• Genome and transcriptome sequence data from a small bowel adenocarcinoma patient

  Genome and transcriptome sequence data from a small bowel adenocarcinoma patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001016618

• Genome and transcriptome sequence data from a squamous cell carcinoma nos patient

  Genome and transcriptome sequence data from a squamous cell carcinoma nos patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001016619

• Genome and transcriptome sequence data from a clear cell carcinoma of peritoneal origin patient

  Genome and transcriptome sequence data from a clear cell carcinoma of peritoneal origin patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001016620

• Genome and transcriptome sequence data from a metastatic colorectal cancer patient

  Genome and transcriptome sequence data from a metastatic colorectal cancer patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001016621

• Genome and transcriptome sequence data from a metastatic pancreatic adenocarcinoma patient

  Genome and transcriptome sequence data from a metastatic pancreatic adenocarcinoma patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001016622

• Genome and transcriptome sequence data from a urachal adenocarcinoma patient

  Genome and transcriptome sequence data from a urachal adenocarcinoma patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001016623

• Genome and transcriptome sequence data from a uterine leiomyosarcoma patient

  Genome and transcriptome sequence data from a uterine leiomyosarcoma patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001016624

• Genome and transcriptome sequence data from a epithelioid angiosarcoma of liver patient

  Genome and transcriptome sequence data from a epithelioid angiosarcoma of liver patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001016625

• Data for noninvasive lung cancer subtyping study

  This dataset included cfMethyl-Seq data of 15 plasma cfDNA samples from 15 lung cancer patients and RRBS data of 58 lung tumor tissue samples from 58 lung cancer patients. The data were generated following the standard protocols.

  Dataset EGAD00001015344

• Targeted and shallow whole genome sequencing identifies therapeutic opportunities in p53abn endometrial cancers

  Targeted panel sequencing of 188 formalin-fixed paraffin-embedded p53abn endometrial cancer samples.

  Dataset EGAD00001015349

• The somatic mutation landscape of normal gastric epithelium - TGS

  The landscapes of somatic mutation in normal cells inform on the processes of mutation and selection operative throughout life, permitting insight into embryogenesis, normal ageing and the earliest stages of cancer development. Here, by whole-genome sequencing and targeted panel sequencing of microdissections from 30 individuals, including 18 with gastric cancer, we elucidate the developmental trajectories of normal and malignant gastric epithelium.

  Dataset EGAD00001015352

• The somatic mutation landscape of normal gastric epithelium - WGS

  The landscapes of somatic mutation in normal cells inform on the processes of mutation and selection operative throughout life, permitting insight into embryogenesis, normal ageing and the earliest stages of cancer development. Here, by whole-genome sequencing and targeted panel sequencing of microdissections from 30 individuals, including 18 with gastric cancer, we elucidate the developmental trajectories of normal and malignant gastric epithelium.

  Dataset EGAD00001015351

• Timing the Philadelphia chromosome and trajectory to chronic myeloid leukaemia

  We sequence >1000 whole genomes from 9 patients with CML, providing the largest sequencing dataset for this cancer. We reconstruct phylogenetic trees using somatic mutations and infer BCR::ABL1 timing and tumour growth rates. We correlate mutation landscapes and clonal trajectories with clinical features.

  Dataset EGAD00001015353

• FASTQ file for paper titled "Discovery of immunotherapy targets for pediatric solid and brain tumors by exon-level expression"

  This data set includes 27 full-length transcript sequence generated from PacBio IsoSeq that were used for verify the cancer-specific exons identified in three genes: FN1, COL6A3 and TNC. The data were generated from PDX models of osteosarcoma patients.

  Dataset EGAD00001015356

• NEOPREDICT-Lung: longitudinal whole exome sequencing of non-small cell lung cancers under immunotherapy

  In 43 patients pretreatment tumor biopsies, resected tumors and normal tissue of sufficient quality and quantity were obtained to longitudinally explore the mutational profiles of a comprehensive set of cancer-related genes. For tumor samples, one to four FFPE sections (10 µm thickness, number depending on sample size) were lysed for genomic DNA isolation. Isolation was performed semi-automatically on the Maxwell purification system (Maxwell RSC DNA FFPE Kit, AS1450, Promega) as specified by the manufacturer. DNA was eluted in 50 µl RNase-free water and quantified fluorescently for library preparation using a Qubit 2.0 fluorometer (Life Technology) with its appertaining DNA broad-range assay. Corresponding normal DNA was isolated from blood or PBMCs using routinely available QIAGEN technology. DNA was stored at -20°C before use. Whole-exome sequencing (WES) was performed using the Twist Human Core + RefSeq + Mitochondrial Panel (Twist Bioscience), and 2 x 100 bp fragment sizes were sequenced using a NovaSeq6000 (Illumina). Demultiplexing of sequenced reads was achieved using bcl2fastq (version 2.2).

  Dataset EGAD00001015362

• Sequencing data for "Replication timing alterations are associated with mutation acquisition during tumour evolution in breast and lung cancer"

  Repli-seq data for "Replication timing alterations are associated with mutation acquisition during tumour evolution in breast and lung cancer"

  Dataset EGAD00001015363

• Colorectal cancer – unmapped reads (Mutographs)

  Colorectal cancer – unmapped reads (Mutographs)

  Dataset EGAD00001015364

• To profile the landscape of sebaceous tumours_WES

  Sebaceous tumours are a rare cutaneous cancer with potential for aggressive behaviour. However, limited information is available on these cancers with few published cases. Here we wish to exome sequence these cancers to define the first genomic landscape for this malignancy. We will extract DNA from formalin-fixed, paraffin-embedded (FFPE) cores. Cores may be obtained from lesional and non-lesional tissues of primaries as well as matching metastases. The extracted DNA will be used for exome sequencing. Please note that the dataset was last revised on October 16, 2025.

  Dataset EGAD00001015367

• To profile the landscape of sebaceous tumours_RNAseq

  Sebaceous tumours are a rare cutaneous cancer with potential for aggressive behaviour. However, limited information is available on these cancers with few published cases. Here we wish to exome sequence these cancers to define the first genomic landscape for this malignancy. We will extract RNA from formalin-fixed, paraffin-embedded (FFPE) cores. Cores may be obtained from lesional and non-lesional tissues of primaries as well as matching metastases. The extracted RNA will be used for RNA sequencing.

  Dataset EGAD00001015368

• A non-canonical lymphoblast in refractory childhood T cell leukaemia

  Refractory cancers may arise either through the acquisition of resistance mechanisms by cancer cells or represent distinct diseases. The origin of childhood T-cell acute lymphoblastic leukaemia (T-ALL) that does not respond to initial treatment, i.e. refractory disease, is unknown. Refractory T-ALL carries a poor prognosis and cannot be predicted at diagnosis. Here, we performed single cell mRNA sequencing of T-ALL from children who did or did not respond to initial treatment. We identified a transcriptionally distinctive blast population, exhibiting features of innate-like lymphocytes, as the major source of refractory disease. Evidence of such blasts at diagnosis heralded refractory disease across independent datasets and was associated with survival in a large, contemporary trial cohort. Our findings portray refractory T-ALL as a distinct disease. They may have immediate clinical utility.

  Dataset EGAD00001015381

• The University of Hong Kong Gastric Cancer XClone Study WES Data

  Exome capturing was performed using xGen Exome Research Panel v1.0 based on standard protocols. Paired-end sequencing (2 x 151 bp) was performed using Illumina NovaSeq6000.

  Dataset EGAD00001015382

• The University of Hong Kong Gastric Cancer XClone Study Single Cell CNV Data

  Single cell encapsulation and DNA libraries were prepared by Chromium™ Single Cell DNA Reagent Kits and Chromium™ Single Cell C and D Chip Kits.

  Dataset EGAD00001015383

• 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

• The complexity of tobacco smoke induced mutagenesis in head and neck cancer - patient metadata files (Mutographs)

  The complexity of tobacco smoke induced mutagenesis in head and neck cancer - patient metadata files (Mutographs)

  Dataset EGAD00001015387

• The complexity of tobacco smoke induced mutagenesis in head and neck cancer - filtered vcf files (Mutographs)

  The complexity of tobacco smoke induced mutagenesis in head and neck cancer - filtered vcf files (Mutographs)

  Dataset EGAD00001015388

• The complexity of tobacco smoke induced mutagenesis in head and neck cancer - structural variation vcf files (Mutographs)

  The complexity of tobacco smoke induced mutagenesis in head and neck cancer - structural variation vcf files (Mutographs)

  Dataset EGAD00001015389

• The complexity of tobacco smoke induced mutagenesis in head and neck cancer - copy number variants (Mutographs)

  The complexity of tobacco smoke induced mutagenesis in head and neck cancer - copy number variants (Mutographs)

  Dataset EGAD00001015390

• DNA WGS Short Read Sequence (Illumina NovaSeq) for manuscript titled: "Performance of Somatic Structural Variant Calling in Lung Cancer using Oxford Nanopore Sequencing Technology"

  DNA WGS Short Read Sequence (Illumina NovaSeq) for manuscript titled: "Performance of Somatic Structural Variant Calling in Lung Cancer using Oxford Nanopore Sequencing Technology"

  Dataset EGAD00001015399

• DNA Whole Exome Sequence 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

  DNA Whole Exome Sequence 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 EGAD00001015395

• Illumina TSO500 DNA 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 DNA 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 EGAD00001015396

• 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

• Cancer-independent, second somatic NF1 mutation of normal tissues in neurofibromatosis type 1

  Cancer predisposition syndromes mediated by recessive cancer genes generate tumours via somatic variants (second hits) in the unaffected allele. Second hits may or may not be sufficient for neoplastic transformation. Here, we performed whole genome and exome sequencing on 479 tissue biopsies from a child with neurofibromatosis type 1, a multi-system cancer-predisposing syndrome mediated by constitutive monoallelic NF1 inactivation. We identified multiple independent NF1 driver variants in histologically normal tissues, but not in 610 biopsies from two non-predisposed children. We corroborated this finding using targeted duplex sequencing, including a further nine adults with the same syndrome. Overall, truncating NF1 mutations were under positive selection in normal tissues from individuals with neurofibromatosis type 1. We demonstrate that normal tissues in neurofibromatosis type 1 commonly harbour second hits in NF1, the extent and pattern of which may underpin the syndrome's cancer phenotype.

  Dataset EGAD00001015398

• Somatic mutation in edited cholangiocyte organoids

  Primary human cells cultured in organoid format have great promise as potential regenerative cellular therapies. However, their immunogenicity and mutagenic profile remain unresolved, impeding effective long-term translation to the clinic. In this study we report, for the first time, the generation of human leukocyte antigen (HLA)-I and HLA-II knock-out human expandable primary cholangiocyte organoids (PCOs) using CRISPR-Cas9 as a potential ‘universal’ low-immunogenic therapy for bile duct disorders. HLA-edited PCOs (ePCOs) displayed the same phenotypic and functional characteristics as parental unedited PCOs. Despite minimal off-target edits, duplex sequencing approaches demonstrated that ePCOs and PCOs acquire mutations in culture at similar rates, but without evident selection for cancer-driver mutations. ePCOs induced reduced T cell-mediated immunity and donor-dependent NK cell cytotoxicity in vitro and evaded cytotoxic responses with increased graft survival in humanized mice in vivo. Our findings have important implications for assessment of safety and immunogenicity of primary cell-derived organoid cellular therapies.

  Dataset EGAD00001015456

• Somatic mutation in edited cholangiocyte organoids

  Primary human cells cultured in organoid format have great promise as potential regenerative cellular therapies. However, their immunogenicity and mutagenic profile remain unresolved, impeding effective long-term translation to the clinic. In this study we report, for the first time, the generation of human leukocyte antigen (HLA)-I and HLA-II knock-out human expandable primary cholangiocyte organoids (PCOs) using CRISPR-Cas9 as a potential ‘universal’ low-immunogenic therapy for bile duct disorders. HLA-edited PCOs (ePCOs) displayed the same phenotypic and functional characteristics as parental unedited PCOs. Despite minimal off-target edits, duplex sequencing approaches demonstrated that ePCOs and PCOs acquire mutations in culture at similar rates, but without evident selection for cancer-driver mutations. ePCOs induced reduced T cell-mediated immunity and donor-dependent NK cell cytotoxicity in vitro and evaded cytotoxic responses with increased graft survival in humanized mice in vivo. Our findings have important implications for assessment of safety and immunogenicity of primary cell-derived organoid cellular therapies.

  Dataset EGAD00001015457

• Geographic and age-related variations in mutational processes in colorectal cancer - copy number variants (Mutographs)

  Geographic and age-related variations in mutational processes in colorectal cancer - copy number variants (Mutographs)

  Dataset EGAD00001015487

• Combination Immune Checkpoint Inhibition in Australian Rare Cancers_WES

  Combination immune checkpoint inhibition (ICI) with anti-CTLA-4 and anti-PD-1 blockade has demonstrated significant clinical activity across tumour types. Rare cancer patients have limited treatment options due to the scarcity of studies of novel treatment options, so they are often offered chemotherapies untested in their disease. ONJ2016-001/CA209-538 is a prospective, multicentre clinical trial of combination ICI (ipilimumab and nivolumab) in patients with advanced rare cancers, including biliary tract, adrenocortical, rare gynaecological and neuroendocrine cancers (https://clinicaltrials.gov/ct2/show/NCT02923934). The primary endpoint is clinical benefit rate (complete response + partial response + stable disease >3 months) by RECIST 1.1. This study involves generation and analysis of pre-treatment formalin fixed paraffin embedded (FFPE) tumour DNA sequencing data, paired with germline DNA sequencing data, to potentially identify genomic biomarkers that may associate with clinical benefit or other clinical efficacy / toxicity metrics.

  Dataset EGAD00001015465

• A Tumour Organoid Biobank for Mapping Cancer Cell Vulnerabilities - TGS

  Targeted gene sequencing data from cancer patient-derived organoids and their matched tumour tissue samples. Part of a study to include genomic and transcriptomic sequencing data, along with CRISPR screening data from cancer patient-derived organoids and matched tumour tissues. Some organoids were developed as part of the Human Cancer Models Initiative (HCMI) in collaboration with Cancer Research UK (CRUK). The study includes organoids derived from colorectal, oesophageal, ovarian, pancreatic, and stomach cancer samples.

  Dataset EGAD00001015468

• A Tumour Organoid Biobank for Mapping Cancer Cell Vulnerabilities - WGS

  Whole genome sequencing data from cancer patient-derived organoids and their matched tumour tissue samples. Part of a study to include genomic and transcriptomic sequencing data, along with CRISPR screening data from cancer patient-derived organoids and matched tumour tissues. Some organoids were developed as part of the Human Cancer Models Initiative (HCMI) in collaboration with Cancer Research UK (CRUK). The study includes organoids derived from colorectal, oesophageal, ovarian, pancreatic, and stomach cancer samples.

  Dataset EGAD00001015469

• A Tumour Organoid Biobank for Mapping Cancer Cell Vulnerabilities - RNA

  RNA sequencing data from cancer patient-derived organoids. Part of a study to include genomic and transcriptomic sequencing data, along with CRISPR screening data from cancer patient-derived organoids and matched tumour tissues. Some organoids were developed as part of the Human Cancer Models Initiative (HCMI) in collaboration with Cancer Research UK (CRUK). The study includes organoids derived from colorectal, oesophageal, ovarian, pancreatic, and stomach cancer samples.

  Dataset EGAD00001015470

• The earliest stages of neoplastic transformation in Familial Adenomatous Polyposis

  Familial Adenomatous Polyposis (FAP) is caused by constitutional inactivating mutations in APC, the central gatekeeper gene of colorectal cancer, and is associated with a substantially increased lifetime-risk of colorectal cancer. To investigate the earliest stages of neoplastic change due to APC inactivation we microdissected and individually whole-genome sequenced 522 normal and abnormal colorectal crypts from 16 individuals with FAP. Colorectal crypts were isolated by laser capture microdissection and individually whole genome sequenced: 192 normal crypts; 34 crypts with regenerative changes; 23 crypts from 9 bifurcating crypts; 86 crypts from 17 aberrant crypt aggregates; 2 monocryptal adenomas which represent the simplest dysplastic crypt structures we were able to identify; 29 crypts from 9 oligocryptal adenomas; 156 crypts from 23 adenomatous polyps including 135 from 20 diminutive polyps and 21 from three large polyps.

  Dataset EGAD00001015471

• The earliest stages of neoplastic transformation in Familial Adenomatous Polyposis

  Familial Adenomatous Polyposis (FAP) is caused by constitutional inactivating mutations in APC, the central gatekeeper gene of colorectal cancer, and is associated with a substantially increased lifetime-risk of colorectal cancer. To investigate the earliest stages of neoplastic change due to APC inactivation we microdissected and individually whole-genome sequenced 522 normal and abnormal colorectal crypts from 16 individuals with FAP. Colorectal crypts were isolated by laser capture microdissection and individually whole genome sequenced: 192 normal crypts; 34 crypts with regenerative changes; 23 crypts from 9 bifurcating crypts; 86 crypts from 17 aberrant crypt aggregates; 2 monocryptal adenomas which represent the simplest dysplastic crypt structures we were able to identify; 29 crypts from 9 oligocryptal adenomas; 156 crypts from 23 adenomatous polyps including 135 from 20 diminutive polyps and 21 from three large polyps.

  Dataset EGAD00001015477

• DERMATLAS: Hidradenoma papilliferum_RNAseq

  Virtually no other tumour type is associated with so many different forms as skin cancer. Histologically, tumours of the skin may arise from epithelium, including epidermis, hair follicle, sebaceous or sweat gland, melanocytes, dermal-associated mesenchymal structures or tissue resident immune cells, making for a diversity of clinical presentations. Importantly, many skin tumour types have an extremely poor prognosis. Many skin tumour subtypes have never undergone molecular profiling, or if they have, targeted sequencing has been used and the number of cases analyzed has been so limited that deriving firm conclusions about the profile of driver genes, DNA mutational signatures and germline alleles has not been possible.For 70 key skin tumour subtypes defined by the World Health Organization, that have not undergone extensive genetic analysis previously, we propose to perform whole exome and transcriptome sequencing, from a range of body sites, to build a genomic atlas of dermatological tumours, including detailed maps of SNVs, copy number alterations, genome-wide methylation and expression profiles.

  Dataset EGAD00001015480

• DERMATLAS: Hidradenoma papilliferum_WES

  Virtually no other tumour type is associated with so many different forms as skin cancer. Histologically, tumours of the skin may arise from epithelium, including epidermis, hair follicle, sebaceous or sweat gland, melanocytes, dermal-associated mesenchymal structures or tissue resident immune cells, making for a diversity of clinical presentations. Importantly, many skin tumour types have an extremely poor prognosis. Many skin tumour subtypes have never undergone molecular profiling, or if they have, targeted sequencing has been used and the number of cases analyzed has been so limited that deriving firm conclusions about the profile of driver genes, DNA mutational signatures and germline alleles has not been possible.For 70 key skin tumour subtypes defined by the World Health Organization, that have not undergone extensive genetic analysis previously, we propose to perform whole exome and transcriptome sequencing, from a range of body sites, to build a genomic atlas of dermatological tumours, including detailed maps of SNVs, copy number alterations, genome-wide methylation and expression profiles.

  Dataset EGAD00001015481

• Geographic and age-related variations in mutational processes in colorectal cancer - sequence data (Mutographs)

  Geographic and age-related variations in mutational processes in colorectal cancer - sequence data (Mutographs)

  Dataset EGAD00001015485

• Geographic and age-related variations in mutational processes in colorectal cancer - filtered vcf files (Mutographs)

  Geographic and age-related variations in mutational processes in colorectal cancer - filtered vcf files (Mutographs)

  Dataset EGAD00001015486

• HCA Organoids | Colon - Cancer, Multiome Sequencing Data

  Multiome sequencing of patient tissue and patient derived organoids in colon cancer

  Dataset EGAD00001015504

• Somatic mutation and selection at epidemiological scale - TwinsUK_TargetedEMSeq_Blood

  Development of a targeted methylation assay to determine the cell-type composition of a sample. As we age, many tissues become colonised by microscopic clones carrying somatic driver mutations. Some of these clones represent a first step towards cancer whereas others may contribute to ageing and other diseases. However, our understanding of the clonal landscapes of human tissues, and their impact on cancer risk, ageing and disease, remains limited due to the challenge of detecting somatic mutations present in small numbers of cells. Here, we introduce a new version of nanorate sequencing (NanoSeq), a duplex sequencing method with error rates of less than 5 per billion base pairs, which is compatible with whole-exome and targeted gene sequencing. Deep sequencing of polyclonal samples with single-molecule sensitivity enables the simultaneous detection of mutations in large numbers of clones, yielding accurate somatic mutation rates, mutational signatures and driver mutation frequencies in any tissue. Applying targeted NanoSeq to 1,042 non-invasive samples of oral epithelium and 371 samples of blood from a twin cohort, we found an unprecedentedly rich landscape of selection, with 46 genes under positive selection driving clonal expansions in the oral epithelium, over 62,000 driver mutations, and evidence of negative selection in some genes. The high number of positively selected mutations in multiple genes provides high-resolution maps of selection across coding and non-coding sites, a form of in vivo saturation mutagenesis. Multivariate regression models enable mutational epidemiology studies on how carcinogenic exposures and cancer risk factors, such as age, tobacco or alcohol, alter the acquisition and selection of somatic mutations. Accurate single-molecule sequencing has the potential to unveil the polyclonal landscape of any tissue, providing a powerful tool to study early carcinogenesis, cancer prevention and the role of somatic mutations in ageing and disease.

  Dataset EGAD00001015623

• Somatic mutation and selection at epidemiological scale - Sanger_NanoSeq_RandD

  Bottleneck sequencing of human tissue including neurons, cord blood, sperm 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/. As we age, many tissues become colonised by microscopic clones carrying somatic driver mutations. Some of these clones represent a first step towards cancer whereas others may contribute to ageing and other diseases. However, our understanding of the clonal landscapes of human tissues, and their impact on cancer risk, ageing and disease, remains limited due to the challenge of detecting somatic mutations present in small numbers of cells. Here, we introduce a new version of nanorate sequencing (NanoSeq), a duplex sequencing method with error rates of less than 5 per billion base pairs, which is compatible with whole-exome and targeted gene sequencing. Deep sequencing of polyclonal samples with single-molecule sensitivity enables the simultaneous detection of mutations in large numbers of clones, yielding accurate somatic mutation rates, mutational signatures and driver mutation frequencies in any tissue. Applying targeted NanoSeq to 1,042 non-invasive samples of oral epithelium and 371 samples of blood from a twin cohort, we found an unprecedentedly rich landscape of selection, with 46 genes under positive selection driving clonal expansions in the oral epithelium, over 62,000 driver mutations, and evidence of negative selection in some genes. The high number of positively selected mutations in multiple genes provides high-resolution maps of selection across coding and non-coding sites, a form of in vivo saturation mutagenesis. Multivariate regression models enable mutational epidemiology studies on how carcinogenic exposures and cancer risk factors, such as age, tobacco or alcohol, alter the acquisition and selection of somatic mutations. Accurate single-molecule sequencing has the potential to unveil the polyclonal landscape of any tissue, providing a powerful tool to study early carcinogenesis, cancer prevention and the role of somatic mutations in ageing and disease.

  Dataset EGAD00001015624

• Dataset for Manuscript: Cancer genome standards for long-read sequencing using cancer cell line mixtures

  Dataset for Manuscript: Cancer genome standards for long-read sequencing using cancer cell line mixtures

  Dataset EGAD00001015628

• Mutational signatures of environmental carcinogens in human tissue organoids – WGS Bulk Normals

  Whole genome sequencing of human tumours has revealed distinct patterns (signatures) of mutations that provide clues to the causative origins of cancer. Some signatures have been attributed to endogenous processes, some to exogenous agents, while a substantial proportion are of unknown origin. Generation of mutational signatures induced in experimental systems can verify the signature assignments and shed light on their origins and mechanisms. We have investigated mutational signatures of environmental carcinogens in human tissue organoid cultures. These 3-dimensional systems retain some of the architecture and functions of the organs from which they are derived, affording the opportunity to observe the effects of carcinogens in both target and non-target organs. There was a lesser requirement for an exogenous metabolizing system, as the cultures were, in most cases, capable of activating test agents. Duplex sequencing eliminated PCR amplification errors from mutational profiles and removed the need to clone carcinogen-treated cultures. Gastric, colon, liver, pancreas and kidney organoids were exposed to benzo[a]pyrene (BaP), aflatoxin B1 (AFB1), aristolochic acid (AAI) and 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP). All four agents induced single-base substitution (SBS) signatures, BaP and AAI induced double-base substitution (DBS) signatures and indel (ID) signatures, and PhIP also induced an ID signature. These signatures were the same in all five organoid types, although there were quantitative differences. A further 13 environmental carcinogens were investigated in human gastric organoids, and signatures were obtained for seven of them: ethylnitrosourea (ENU), methylazoxymethanol acetate (MAM), N-methyl-N′-nitro-N-nitrosoguanidine (MMNG), potassium bromate, glycidamide, styrene oxide and propylene oxide, providing additional insights into processes underlying the causes of human cancer.

  Dataset EGAD00001015630

• Single-Cell Data from "Spatiotemporal T-cell tracking for personalized T-cell receptor T-cell therapy designs in childhood cancer"

  This dataset contains the FASTQ files from the Single-Cell GEx+TCR 10X Genomics data from the study "Spatiotemporal T-cell tracking for personalized T-cell receptor T-cell therapy designs in childhood cancer" (EGAS00001008174)

  Dataset EGAD00001015632

• WXS dataset of Oncogenic and immunological targets for matched therapy of pediatric blood cancer patients: Dutch iTHER study experience

  WXS dataset of Oncogenic and immunological targets for matched therapy of pediatric blood cancer patients: Dutch iTHER study experience

  Dataset EGAD00001015638

• RNA-seq dataset of Oncogenic and immunological targets for matched therapy of pediatric blood cancer patients: Dutch iTHER study experience

  RNA-seq dataset of Oncogenic and immunological targets for matched therapy of pediatric blood cancer patients: Dutch iTHER study experience

  Dataset EGAD00001015639

• Detection of human brain cancers using genomic and immune cell characterization of cerebrospinal fluid through CSF-BAM

  Detection of human brain cancers using genomic and immune cell characterization of cerebrospinal fluid through CSF-BAM

  Dataset EGAD00001015645

• Low-Coverage Whole-Genome Sequencing Data (Tissue and Buffy coat Samples)

  This dataset contains low-coverage whole-genome sequencing (lcWGS) data based on genomic DNA from 8 fresh-frozen prostate cancer tissue samples and matched buffy coat samples from 8 prostate cancer patients.

  Dataset EGAD00001015652

• Methylated DNA Immunoprecipitation Sequencing Data (Tissue and Buffy coat Samples)

  This dataset contains methylated DNA immunoprecipitation sequencing (MeDIP-seq) data based on genomic DNA from 8 fresh-frozen prostate cancer tissue samples and matched buffy coat samples from 8 prostate cancer patients.

  Dataset EGAD00001015653

• Single cell characterization of T-cell lymphoma: RNA (2025-07-31)

  Lymphomas are types of blood cancer derived from lymphocytes, and can be classified into two main categories, Hodgkin's lymphomas (HL) and non-Hodgkin lymphomas (NHL). T-cell lymphoma is a type of NHL that develops from T lymphocytes and accounts for 10-15% of total NHL cases. As a rare disease, T-cell lymphoma is functionally, pathologically, and clinically complex and heterogeneous. The 2016 revision of the WHO classification has listed 29 subtypes of mature T/NK-cell neoplasms, among which over 25 are T lymphocyte in origin. These subtypes of T-cell lymphomas have different biological behaviours and clinical prognosis. Clinically, T-cell lymphoma ranges from indolent (slow-growing) to aggressive (fast-growing and spreading) disease. According to the guideline booklet provided by the Lymphoma Research Foundation (https://lymphoma.org/aboutlymphoma/nhl/), indolent T-cell lymphoma subtypes include adult T-cell leukaemia/lymphoma (ATLL), cutaneous T-cell lymphoma (CTCL), and mycosis fungoides (MF), while the aggressive subtypes include anaplastic large cell lymphoma (ALCL), angioimmunoblastic T-cell lymphoma (AITL), peripheral T-cell lymphoma (PTCL), and T lymphoblastic lymphoma (TLBL). PTCL and ALCL represent the most common subtypes of aggressive T-cell lymphoma whereas TLBL is a rare and aggressive subtype mostly diagnosed in children. In this study, we will use single cell RNA sequencing and single cell multiomic methods three aggressive T-cell lymphoma subtypes (ALCL, PTCL and TLBL) and try to gain a deeper insight into the genotypic and phenotypic features of these T-cell lymphomas. . This dataset contains all the data available for this study on 2025-07-31.

  Dataset EGAD00001015669

• A non-canonical lymphoblast in refractory childhood T-cell leukaemia

  Refractory cancers may arise either through the acquisition of resistance mechanisms or represent distinct disease states. The origin of childhood T-cell acute lymphoblastic leukaemia (T-ALL) that does not respond to initial treatment, i.e. refractory disease, is unknown. Refractory T-ALL carries a poor prognosis and cannot be predicted at diagnosis. Here, we perform single cell mRNA sequencing of T-ALL from 58 children (84 samples) who did, or did not respond to initial treatment. We identify a transcriptionally distinctive blast population, exhibiting features of innate-like lymphocytes, as the major source of refractory disease. Evidence of such blasts at diagnosis heralds refractory disease across independent datasets and is associated with survival in a large, contemporary trial cohort. Our findings portray refractory T-ALL as a distinct disease with the potential for immediate clinical utility. This dataset contains 56 single-cell RNA sequencing data files with corresponding single-cell T cell receptor sequencing data files. The data here form the validation cohort in our paper.

  Dataset EGAD00001015673

• Colorectal Microenvironment Spatial Mapping Dataset

  Two samples derived from a colorectal cancer female patient - tumor tissue and normal adjacent tissue analyzed via Visium Spatial Gene Expression.

  Dataset EGAD00001015675

• Additional RNAseq data of metastatic breast cancer samples

  Paired-end RNA sequencing data from 33 metastatic breast cancer samples. Sequencing was performed on the Illumina NovSeq 6000 using NEBNext Single Cell and Low Input RNA Library Prep Kit for Illumina.

  Dataset EGAD00001015678

• Whole exome sequencing data for paired non-serous endometrial and ovarian carcinomas from 27 patients with concurrent tumours.

  Dataset for Synchronous Endometrial and Ovarian Cancer

  Dataset EGAD00001015680