7412 results for "canc*"

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• 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