7406 results for "canc*"

in 67.90 milliseconds.

• 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 - copy number variants (Mutographs)

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

  Dataset EGAD00001015390

• 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

• Characterising the evolutionary dynamics of cancer proliferation in single-cell clones with SPRINTER

  Characterising the evolutionary dynamics of cancer proliferation in single-cell clones with SPRINTER

  Dataset EGAD00001015411

• 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

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

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

  Dataset EGAD00001015400

• PD-L1 blockade immunotherapy rewires cancer-induced emergency myelopoiesis

  HSPCs were sorted as CD34+ cells from bone marrow of patients with Hodgkin Lymphoma (HL). Control samples were isolated before initiating treatment.These were compared to samples from two additional HL patients who had relapsed and were being treated with nivolumab. Nivolumab was administered at a dose of 240 mg every two weeks, with BM samples collected the day before the scheduled dose. The patients receiving nivolumab were in remission at the time of BM collection. RNA was extracted using Arcturus™ PicoPure™ RNA Isolation Kit (Thermo Fisher Scientific, #12204-01) ` instructions. Paired-end sequencing was reads were generated for each sample in the Illumina Novaseq 6000 system.

  Dataset EGAD00001015403

• 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

• WES data for Early evolutionary branching across spatial domains predisposes to clonal replacement under chemotherapy in neuroblastoma

  Neuroblastoma (NB) is one of the most lethal childhood cancers due its propensity to treatment resistance. By spatial mapping of subclone geographies before and after chemotherapy across 89 tumor regions from 12 NBs, we find that densely packed territories of closely related subclones present at diagnosis are replaced under effective treatment by islands of distantly related survivor subclones, originating from a different most recent ancestor compared to lineages dominating before treatment. Conversely, in tumors that progressed under treatment, ancestors of subclones dominating later in disease are present already at diagnosis. Chemotherapy treated xenografts and cell culture models replicates these two contrasting scenarios and shows branching evolution to be a constant feature of proliferating NB cells. Phylogenies based on whole genome sequencing of 505 individual NB cells indicate that a rich repertoire of parallel subclones, emerges already with the first oncogenic mutations and lays the foundation for clonal replacement under treatment.

  Dataset EGAD00001015413

• scDNA-seq for 'Early evolutionary branching across spatial domains predisposes to clonal replacement under chemotherapy in neuroblastoma'

  Neuroblastoma (NB) is one of the most lethal childhood cancers due its propensity to treatment resistance. By spatial mapping of subclone geographies before and after chemotherapy across 89 tumor regions from 12 NBs, we find that densely packed territories of closely related subclones present at diagnosis are replaced under effective treatment by islands of distantly related survivor subclones, originating from a different most recent ancestor compared to lineages dominating before treatment. Conversely, in tumors that progressed under treatment, ancestors of subclones dominating later in disease are present already at diagnosis. Chemotherapy treated xenografts and cell culture models replicates these two contrasting scenarios and shows branching evolution to be a constant feature of proliferating NB cells. Phylogenies based on whole genome sequencing of 505 individual NB cells indicate that a rich repertoire of parallel subclones, emerges already with the first oncogenic mutations and lays the foundation for clonal replacement under treatment.

  Dataset EGAD00001015414

• 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

• 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

• HCA Organoids | Colon - Cancer, Multiome Sequencing Data

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

  Dataset EGAD00001015504

• A spatiotemporal cancer cell trajectory underlies glioblastoma heterogeneity

  Abstract: Cancer cells display highly heterogeneous and plastic states in glioblastoma, an incurable brain tumour. However, how these malignant states arise and whether they follow a tractable cellular trajectory across tumours is poorly understood. Here, we generated a deep single cell and spatial multi-omic atlas of human glioblastoma that pairs transcriptomic, epigenomic and genomic profiling of 12 tumours across multiple regions. We identify that glioblastoma heterogeneity is driven by spatially-patterned transitions of cancer cells from developmental-like states towards those defined by a glial injury response and hypoxia. This cancer cell trajectory regionalizes tumours into distinct tissue niches and manifests in a conserved manner across tumours as well as genetically distinct tumour subclones. Moreover, using a new deep learning framework to jointly map cancer cell states and clones in situ, we show that tumour subclones are finely spatially intermixed through glioblastoma tissue niches. Finally, we show that this cancer cell trajectory is intimately linked to myeloid heterogeneity and unfolds across regionalised myeloid signalling environments. Our findings define a stereotyped trajectory of cancer cells in glioblastoma and unify glioblastoma tumour heterogeneity into a tractable cellular and tissue framework.

  Dataset EGAD00001015516

• GBM-Space: Spatial Transcriptomic Profiling of Glioblastoma (10x Genomics - Visium)

  Cancer cells display heterogeneous and dynamic states in glioblastoma, but how these malignant states arise and whether they follow a tractable cellular trajectory across tumours is poorly understood. Here, we generate a deep single cell and spatial multi-region atlas of 12 isocitrate dehydrogenase wild-type (IDH-wt) primary glioblastomas that integrates transcriptomic, epigenomic and genomic analysis to comprehensively characterise their tumour heterogeneity. The datasets in this study include sequencing data from Visium spatial transcriptomic (10x Genomics) profiling of these tumours. Note: 2 new samples were added to the dataset on 2026-05-19.

  Dataset EGAD00001015527

• Citrate synthase novel variant rewires TCA cycle to promote colorectal cancer progression

  H3K4me3, IgG, and Input ChIP-seq in overexpression of pLV Control, CS-FL and CS-ΔEx4 in SW1116 cells

  Dataset EGAD00001015543

• RRBS data from TRACERx non-small cell lung cancer (NSCLC) tumours and matched normal adjacent tissue.

  TRACERx (TRAcking Cancer Evolution through therapy (Rx)) is a prospective cohort study designed to investigate intratumor heterogeneity (ITH) in relation to clinical outcome, and to determine the clonal nature of driver events and evolutionary processes in early stage non-small cell lung cancer (NSCLC).

  Dataset EGAD00001015534

• HCA Organoids | Colon - Cancer, WES

  HCA Organoids | Colon - Cancer, Whole Exome Sequencing (WES)

  Dataset EGAD00001015548

• A standardised framework for robust fragmentomic feature extraction from cell-free DNA sequencing data

  Fragmentomic features of cell-free DNA represent promising non-invasive biomarkers for cancer diagnosis. However, a lack of systematic evaluation of biases in feature quantification has hindered the adoption of such applications. We compared features derived from whole-genome sequencing of ten healthy donors using nine library kits and ten data-processing routes, and validated them in 1,182 plasma samples from published studies. Our results clarify the variations resulting from library preparation and feature quantification methods. We designed the Trim Align Pipeline and the cfDNAPro R package as unified interfaces for data pre-processing, feature extraction, and visualisation, aiming to standardise multimodal feature engineering and integration for machine learning.

  Dataset EGAD00001015535

• HCA Organoids | Colon - Cancer, Nanopore Sequencing Data

  Nanopore Sequencing Data

  Dataset EGAD00001015536

• Raw molecular data for "Subclonal immune evasion in non-small cell lung cancer"

  Whole exome, RNA sequencing and TCR sequencing of organoid samples derived from TRACERx patients. The dataset also includes whole exome sequencing from the tumour samples from which the organoids were generated, as well as whole exome sequencing from PDX derived from said tumours.

  Dataset EGAD00001015537

• The dataset for "Validation of cfDNA fragmentome analyses for early detection of liver cancer"

  The dataset for “Validation of cfDNA fragmentome analyses for early detection of liver cancer” includes 380 cram files from whole genome next-generation sequencing on the Illumina NovaSeq 6000 with 10x coverage. The samples analyzed include plasma samples from patients with cancer and liver disease.

  Dataset EGAD00001015538

• Sperm sequencing reveals extensive positive selection in the human germline -WGS

  Mutations that occur during human ageing in the cell lineages of sperm or eggs have the potential to be transmitted to offspring. In males, positive selection of driver mutations during spermatogenesis is known to increase the birth prevalence of certain developmental disorders and cancer predisposition syndromes. However, direct observation of the scope of this selection in sperm has been limited by the error rates of sequencing technologies. Using the duplex sequencing method known as NanoSeq, we sequenced bulk sperm samples from individuals aged 24 to 75 years. Our findings revealed a linear accumulation mutations per year and mutational signatures consistent with pedigree studies. Deep targeted and deep exome NanoSeq of sperm samples identified genes subject to significant positive selection in the male germline, which are linked to diverse cellular pathways including RAS/MAPK and BMP signaling. Strikingly, nearly all positively selected genes are associated with developmental or cancer predisposition disorders in children. We find that this effect drives an elevated risk of known likely disease-causing mutations in sperm across a wide age range. This implies that the disorders attributed to these genes likely exhibit elevated birth prevalence in human populations, particularly among older fathers. These findings shed light on the dynamics of germline mutations and highlight an increased disease risk for children born to fathers of advanced age.

  Dataset EGAD00001015592

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

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

  Dataset EGAD00001015583

• Sperm sequencing reveals extensive positive selection in the human germline -NanoSeq

  Mutations that occur during human ageing in the cell lineages of sperm or eggs have the potential to be transmitted to offspring. In males, positive selection of driver mutations during spermatogenesis is known to increase the birth prevalence of certain developmental disorders and cancer predisposition syndromes. However, direct observation of the scope of this selection in sperm has been limited by the error rates of sequencing technologies. Using the duplex sequencing method known as NanoSeq, we sequenced bulk sperm samples from individuals aged 24 to 75 years. Our findings revealed a linear accumulation mutations per year and mutational signatures consistent with pedigree studies. Deep targeted and deep exome NanoSeq of sperm samples identified genes subject to significant positive selection in the male germline, which are linked to diverse cellular pathways including RAS/MAPK and BMP signaling. Strikingly, nearly all positively selected genes are associated with developmental or cancer predisposition disorders in children. We find that this effect drives an elevated risk of known likely disease-causing mutations in sperm across a wide age range. This implies that the disorders attributed to these genes likely exhibit elevated birth prevalence in human populations, particularly among older fathers. These findings shed light on the dynamics of germline mutations and highlight an increased disease risk for children born to fathers of advanced age.

  Dataset EGAD00001015590

• Sperm sequencing reveals extensive positive selection in the human germline -TargetedNanoSeq

  Mutations that occur during human ageing in the cell lineages of sperm or eggs have the potential to be transmitted to offspring. In males, positive selection of driver mutations during spermatogenesis is known to increase the birth prevalence of certain developmental disorders and cancer predisposition syndromes. However, direct observation of the scope of this selection in sperm has been limited by the error rates of sequencing technologies. Using the duplex sequencing method known as NanoSeq, we sequenced bulk sperm samples from individuals aged 24 to 75 years. Our findings revealed a linear accumulation mutations per year and mutational signatures consistent with pedigree studies. Deep targeted and deep exome NanoSeq of sperm samples identified genes subject to significant positive selection in the male germline, which are linked to diverse cellular pathways including RAS/MAPK and BMP signaling. Strikingly, nearly all positively selected genes are associated with developmental or cancer predisposition disorders in children. We find that this effect drives an elevated risk of known likely disease-causing mutations in sperm across a wide age range. This implies that the disorders attributed to these genes likely exhibit elevated birth prevalence in human populations, particularly among older fathers. These findings shed light on the dynamics of germline mutations and highlight an increased disease risk for children born to fathers of advanced age.

  Dataset EGAD00001015591

• RNA-seq dataset of Characterization of UV DNA damage in B-cell precursor acute lymphoblastic leukemia

  Extensive characterization of mutational signature SBS7a in B-cell precursor acute lymphoblastic leukemia (BCP-ALL) samples. We aimed to describe the presentation of SBS7a in BCP-ALL, identify other pediatric cancers presenting with SBS7a, look into the link of SBS7a and UV-light in the context of BCP-ALL and cancers with provable UV exposure, and pinpoint when SBS7a was acquired.

  Dataset EGAD00001015598

• WGS dataset of Characterization of UV DNA damage in B-cell precursor acute lymphoblastic leukemia

  Extensive characterization of mutational signature SBS7a in B-cell precursor acute lymphoblastic leukemia (BCP-ALL) samples. We aimed to describe the presentation of SBS7a in BCP-ALL, identify other pediatric cancers presenting with SBS7a, look into the link of SBS7a and UV-light in the context of BCP-ALL and cancers with provable UV exposure, and pinpoint when SBS7a was acquired.

  Dataset EGAD00001015599

• WGS dataset of Characterization of UV DNA damage in B-cell precursor acute lymphoblastic leukemia

  We characterized B-cell precursor acute lymphoblastic leukemia (BCP-ALL) patients that present with the mutational signature SBS7a. We found clear subtype specificity, but presence of SBS7a did not seem linked to heterogeneity within subtypes. To further distinguish the incidence of SBS7a in pediatric cancer we analyzed a pan-cancer WGS cohort and identified frequent SBS7a in anaplastic large cell lymphomas. As SBS7a is commonly found in skin cancers and has been linked to UV-light induced DNA damage, we compared the features of UV-light induced DNA damage in skin cancer and SBS7a in ALL, and found high similarity. We found no defects in UV damage response pathways in SBS7a-positive samples, indicating no additional UV vulnerability. Additionally, transcriptomic data showed no differences between samples with and without SBS7a. Finally we looked into the moment of exposure to the source of SBS7a by deep sequencing of diagnosis-relapse pairs and single cell whole genome sequencing of diagnosis samples with high SBS7a.

  Dataset EGAD00001015600

• scWGS dataset of Characterization of UV DNA damage in B-cell precursor acute lymphoblastic leukemia

  Extensive characterization of mutational signature SBS7a in B-cell precursor acute lymphoblastic leukemia (BCP-ALL) samples. We aimed to describe the presentation of SBS7a in BCP-ALL, identify other pediatric cancers presenting with SBS7a, look into the link of SBS7a and UV-light in the context of BCP-ALL and cancers with provable UV exposure, and pinpoint when SBS7a was acquired.

  Dataset EGAD00001015601

• RNAseq of human breast cancer tumors from the PEARL study

  Formalin fixed, paraffin-embedded human breast cancer tumor samples had RNA extracted using the Thermo Scientific KingFisher Flex instrument and the Applied Biosystems MagMAX FFPE DNA/RNA Ultra Kit; Total RNA libraries were created using the Bravo Automated Liquid-Handling Platform and the TruSeq Stranded Total RNA Library Prep Gold Kit; libraries were sequenced on the Illumina NovaSeq 6000 machine using a 2x50 bp paired-end configuration to target a read depth of 120 million clusters per library.

  Dataset EGAD00001015613

• WGS and WTS data for manuscript titled: Pathologist-initiated whole genome and transcriptome sequencing demonstrates diagnostic utility in resolving difficult-to-diagnose tumors

  Illumina platform sequencing of whole genome libraries prepared from normal and cancer samples and whole transcriptome libraries from cancer samples from 45 donors

  Dataset EGAD00001015615

• Mutational signatures of environmental carcinogens in human tissue organoids

  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 EGAD00001015616

• Somatic mutation and selection at epidemiological scale - TwinsUK_TargetedNanoSeq_Buccal

  Targeted NanoSeq in buccal epithelium obtained longitudinally from a number of donors. A custom-designed panel of ~200 genes will be used to achieve high depth coverage (aiming for ~1000X at panel sites).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 55 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 EGAD00001015618

• Somatic mutation and selection at epidemiological scale - TwinsUK_TargetedNanoSeq_Blood

  Utilising Targeted NanoSeq, we hope to explore the driver landscape in unprecedented detail in donors from TwinsUK. These donors have paired buccal swabs and data from this will help contextualise that work. 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 EGAD00001015619

• Somatic mutation and selection at epidemiological scale - TwinsUK_ExomeNanoSeq_Buccal

  Exome NanoSeq in buccal swab samples obtained from patients with a wide range of clinical phenotypes. 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 EGAD00001015620

• Somatic mutation and selection at epidemiological scale - TwinsUK_RENanoSeq_Buccal

  Utilising restriction enzyme NanoSeq, we hope to explore the somatic mutation burden and mutational signatures in buccal cells from TwinsUK donors. Some donors have paired blood samples and data from this will help contextualise that work. All donors have paired Targeted NanoSeq data from buccal swabs. 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 EGAD00001015621

• Somatic mutation and selection at epidemiological scale - TwinsUK_TargetedEMSeq_Buccal

  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 EGAD00001015622

• 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

• WGS/WES analysis refines molecular subtypes of hepatocellular carcinoma

  This work aims to identify homogeneous and robust molecular subtypes in HCC based on a large, homogenous and well-annotated cohort. We performed whole genome/exome sequencing (WGS/WES) on 529 HCC from 461 patients collected mainly in France. Based on the genomic data, we identified 9 robust HCC subtypes primarily driven by key mutations. We further characterized these subtypes using genomic and clinicopathological features. Among the 9 subtypes, 5 belonged to chromosome instable tumors, while 3 belonged to chromosome stable tumors. Our subtypes were associated with prognosis and showed distinct distributions across features like etiology and gender. This study offers a comprehensive molecular classification of HCC, enhancing our understanding of hepatocarcinogenesis and supporting the development of genome-based precision medicine for liver cancer.

  Dataset EGAD00001015428

• SGCC GASCAD-II dataset

  The GASCAD-II dataset from the Singapore Gastric Cancer Consortium includes paired tumor-blood whole exome sequencing data for 209 gastric cancer (GC) patients, along with whole transcriptome sequencing data for 125 GC samples. Whole exome sequencing was conducted using Agilent SureSelect Human All Exon V6 kits. For RNA sequencing, total RNA was isolated using the RNeasy Mini Kit, and libraries were prepared with the TruSeq Stranded Total RNA with Ribo-Zero Gold protocol (Illumina). Aligned BAM files for both exome and RNAseq data are included in this dataset

  Dataset EGAD00001015433

• Sequencing data for oesophageal and related samples - Linossi et al

  Data supporting: "Utility of ctDNA assessment after six weeks of immunotherapy to predict radiological response in advanced oesophageal cancer" Linossi et al

  Dataset EGAD00001015434

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

  Geographic and age-related variations in mutational processes in colorectal cancer - patient metadata files (Mutographs)

  Dataset EGAD00001015437

• RNA sequencing of Hepatoblastoma cell lines and drug-treated HepG2 xenograft tumors

  RNA sequencing was performed on 7 pediatric liver cancer cell lines, complementing a panel of 8 cell lines previously described (Hirsch, Cancer Discov. 2021) and on 16 HepG2 xenograft tumors treated with cisplatin, low-dose elimusertib, elimusertib at MTD, or elimusertib/cisplatin compared to vehicle-treated controls.

  Dataset EGAD00001015439

• RNA-Seq Dataset of Organoid drug profiling identifies methotrexate as a therapy for SCCOHT, a rare pediatric cancer

  We generated and characterized tumoroids from small cell carcinoma of the ovary, hypercalcemic type. Furthermore, we identified a drug that is selective and effective against SCCOHT tumoroids.

  Dataset EGAD00001015441

• WGS Dataset of Organoid drug profiling identifies methotrexate as a therapy for SCCOHT, a rare pediatric cancer

  We generated and characterized tumoroids from small cell carcinoma of the ovary, hypercalcemic type. Furthermore, we identified a drug that is selective and effective against SCCOHT tumoroids.

  Dataset EGAD00001015442

• A developmental cell atlas of the human thyroid gland - WGS

  The thyroid gland produces hormones essential for health from embryogenesis to adulthood. Thyroid disorders, including congenital hypothyroidism and thyroid carcinoma, are prevalent and pose significant health challenges. Congenital hypothyroidism often results from thyroid dysgenesis or impaired hormone synthesis, is particularly prevalent in trisomy 21 (T21), while thyroid carcinoma is the most frequent endocrine malignancy, affecting both paediatric and adult populations. Understanding the molecular basis of these conditions requires deeper insights into fetal thyroid development. We generated a spatiotemporal atlas of the human thyroid during early pregnancy, revealing key cell types, including hormone-producing thyrocytes. Thyroid follicular cells are heterogeneous, with two functional cell states (fTFC1, fTFC2) that persist into adulthood, with fTFC2 characterised by elevated PAX8 expression. We demonstrated that T21 thyroids displayed dysgenesis with disrupted follicular morphology, and altered extracellular matrix interactions, and that the fTFC2 signature was enriched in paediatric papillary thyroid cancer compared to adults. These findings uncover thyrocyte heterogeneity across the lifespan, advancing understanding of thyroid development and disease.

  Dataset EGAD00001015447

• A developmental cell atlas of the human thyroid gland - RNA

  The thyroid gland produces hormones essential for health from embryogenesis to adulthood. Thyroid disorders, including congenital hypothyroidism and thyroid carcinoma, are prevalent and pose significant health challenges. Congenital hypothyroidism often results from thyroid dysgenesis or impaired hormone synthesis, is particularly prevalent in trisomy 21 (T21), while thyroid carcinoma is the most frequent endocrine malignancy, affecting both paediatric and adult populations. Understanding the molecular basis of these conditions requires deeper insights into fetal thyroid development. We generated a spatiotemporal atlas of the human thyroid during early pregnancy, revealing key cell types, including hormone-producing thyrocytes. Thyroid follicular cells are heterogeneous, with two functional cell states (fTFC1, fTFC2) that persist into adulthood, with fTFC2 characterised by elevated PAX8 expression. We demonstrated that T21 thyroids displayed dysgenesis with disrupted follicular morphology, and altered extracellular matrix interactions, and that the fTFC2 signature was enriched in paediatric papillary thyroid cancer compared to adults. These findings uncover thyrocyte heterogeneity across the lifespan, advancing understanding of thyroid development and disease.

  Dataset EGAD00001015448

• 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 EGAD00001015455

• 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

• 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

  The succession of somatic genetic events associated with the conversion of a normal colorectal epithelial cell into a colorectal carcinoma constitutes a paradigmatic model of cancer development. 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 279 histologically normal and abnormal colorectal crypts from 15 individuals with FAP. Histologically normal crypts generally exhibited similar mutation burdens and mutational signatures to normal crypts from wild-type individuals of the same age, with 1/110 carrying a somatic inactivating APC mutation. By contrast, 9/18 aberrant crypt foci carried somatic APC mutations and exhibited modestly increased burdens of some mutational signatures found in normal crypts. 12/13 diminutive adenomatous polyps (less than 5mm diameter) showed somatic APC mutations and carried substantially increased mutation loads of most mutational signatures present in normal crypts. Phylogenetic trees of crypts from aberrant crypt foci and adenomatous polyps revealed that some had acquired their initiating somatic APC mutations decades previously during the first few years of life. The results catalogue the changes in somatic mutation rates, mutational processes and “driver” mutations in cancer genes during the earliest stages of colorectal neoplastic transformation initiated by APC inactivation and highlight the long periods of clonal evolution required for a cancer to develop.

  Dataset EGAD00001015471

• The earliest stages of neoplastic transformation in Familial Adenomatous Polyposis

  The succession of somatic genetic events associated with the conversion of a normal colorectal epithelial cell into a colorectal carcinoma constitutes a paradigmatic model of cancer development. 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 279 histologically normal and abnormal colorectal crypts from 15 individuals with FAP. Histologically normal crypts generally exhibited similar mutation burdens and mutational signatures to normal crypts from wild-type individuals of the same age, with 1/110 carrying a somatic inactivating APC mutation. By contrast, 9/18 aberrant crypt foci carried somatic APC mutations and exhibited modestly increased burdens of some mutational signatures found in normal crypts. 12/13 diminutive adenomatous polyps (less than 5mm diameter) showed somatic APC mutations and carried substantially increased mutation loads of most mutational signatures present in normal crypts. Phylogenetic trees of crypts from aberrant crypt foci and adenomatous polyps revealed that some had acquired their initiating somatic APC mutations decades previously during the first few years of life. The results catalogue the changes in somatic mutation rates, mutational processes and “driver” mutations in cancer genes during the earliest stages of colorectal neoplastic transformation initiated by APC inactivation and highlight the long periods of clonal evolution required for a cancer to develop.

  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

• Genome and transcriptome sequence data from a neuroblastoma tumor patient

  Genome and transcriptome sequence data from a neuroblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015264

• Genome and transcriptome sequence data from a neuroblastoma tumor patient

  Genome and transcriptome sequence data from a neuroblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015265

• Genome and transcriptome sequence data from a neurofibromatosis type 1 (NF1) tumor patient

  Genome and transcriptome sequence data from a neurofibromatosis type 1 (NF1) patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015266

• Genome and transcriptome sequence data from a neuroblastoma tumor patient

  Genome and transcriptome sequence data from a neuroblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015267

• Genome and transcriptome sequence data from a CNS sarcoma tumor patient

  Genome and transcriptome sequence data from a CNS sarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015268

• Genome and transcriptome sequence data from a ocular melanoma tumor patient

  Genome and transcriptome sequence data from a ocular Melanoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015269

• Genome and transcriptome sequence data from a osteosarcoma tumor patient

  Genome and transcriptome sequence data from a osteosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015270

• Genome and transcriptome sequence data from a fibrovascular brain tumor tumor patient

  Genome and transcriptome sequence data from a fibrovascular brain tumor patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015271

• Genome and transcriptome sequence data from a angiosarcoma tumor patient

  Genome and transcriptome sequence data from a angiosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015272

• Genome and transcriptome sequence data from a craniopharyngioma tumor patient

  Genome and transcriptome sequence data from a craniopharyngioma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015273

• Genome and transcriptome sequence data from a NHL large B cell tumor patient

  Genome and transcriptome sequence data from a NHL large B Cell patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015274

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

  Genome and transcriptome sequence data from a malignant granular cell tumor patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015275

• Genome and transcriptome sequence data from a papillary thyroid carcinoma tumor patient

  Genome and transcriptome sequence data from a papillary thyroid carcinoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015276

• Genome and transcriptome sequence data from a neuroblastoma tumor patient

  Genome and transcriptome sequence data from a neuroblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015277

• Genome and transcriptome sequence data from a osteosarcoma tumor patient

  Genome and transcriptome sequence data from a osteosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015278

• Genome and transcriptome sequence data from a aggressive fibromatosis tumor patient

  Genome and transcriptome sequence data from a aggressive fibromatosis patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015279

• Genome and transcriptome sequence data from a pineoblastoma tumor patient

  Genome and transcriptome sequence data from a pineoblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015280

• Genome and transcriptome sequence data from a multifocal glioblastoma multiforme tumor patient

  Genome and transcriptome sequence data from a multifocal glioblastoma multiforme patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015281

• Genome and transcriptome sequence data from a progressive facial plexiform neurofibroma tumor patient

  Genome and transcriptome sequence data from a progressive facial plexiform neurofibroma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015282

• Genome and transcriptome sequence data from a plexiform neurofibroma tumor patient

  Genome and transcriptome sequence data from a plexiform neurofibroma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015283

• Genome and transcriptome sequence data from a diffuse intrinsic pontine glioma tumor patient

  Genome and transcriptome sequence data from a diffuse Intrinsic Pontine Glioma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015284

• Genome and transcriptome sequence data from a acute lymphoblastic leukemia tumor patient

  Genome and transcriptome sequence data from a acute lymphoblastic leukemia patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015285

• Genome and transcriptome sequence data from a ewing sarcoma tumor patient

  Genome and transcriptome sequence data from a ewing sarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015286

• Genome and transcriptome sequence data from a ependymoma tumor patient

  Genome and transcriptome sequence data from a ependymoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015287

• Genome and transcriptome sequence data from a glioblastoma tumor patient

  Genome and transcriptome sequence data from a glioblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015288

• Genome and transcriptome sequence data from a NUT midline carcinoma tumor patient

  Genome and transcriptome sequence data from a NUT midline carcinoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015289

• Genome and transcriptome sequence data from a angiosarcoma tumor patient

  Genome and transcriptome sequence data from a angiosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015290