5731 results for "canc*"

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• Whole Exome sequencing of Gingivo-buccal Cancer - ICGC India Project Batch04

  This dataset pertains to whole exome sequencing of paired DNA samples of Gingivo-buccal oral cancer patient.DNA was isolated from the tumor and blood tissues of 47 patients (94 samples).We have performed Nextera exome capture and sequenced exome libraries in Illumina HiSeq platform.We have uploaded BWA-ALN aligned BAM files.

  Dataset EGAD00001003987

• 20180221_EGA_OESO

  Illumina platform sequencing of whole genome libraries prepared from normal, Barrett's oesophagus and oesophageal cancer samples from 44 donors

  Dataset EGAD00001003996

• Single-cell RNA sequencing on 12346 single T cells from 14 non-small cell lung cancer (NSCLC) patients

  Deep single-cell RNA sequencing data for 12346 T cells from tumour, adjacent normal tissue and peripheral blood of treatment-naïve NSCLC patients

  Dataset EGAD00001003999

• Whole Genome Sequencing of HCC

  The present series corresponds to 24 whole genome sequencing (12 Tumoral/Non-tumoral pairs). Hepatocellular carcinoma (HCC) accounts for more than 90% of liver cancers, and is a major health problem. It is the 3rd cause of cancer-related mortality. Advances in genomic analyses have formed a comprehensive understanding of different underlying pathobiological layers resulting in hepatocarcinogenesis. Thus, the development of next-generation sequencing technologies has made it possible to generate more comprehensive catalogues of somatic alteration events (single nucleotide substitutions, structural variations, and epigenetic changes) in liver cancer genome than ever before.

  Dataset EGAD00001003994

• Lung cancer organoids

  Organoids are self-organizing 3D structures grown from stem cells that recapitulate essential aspects of organ structure and function. Here we describe a method to establish long-term culture conditions of human airway epithelial organoids that contain all major cell populations and allow personalized human disease modelling. We collected macroscopically inconspicuous lung tissue from non-small-cell lung cancer (NSCLC) patients undergoing medically indicated surgery and isolated epithelial cells to engineer 3D organoids. We exploit the potential to derive sub-clones from AOs to demonstrate the feasibility of CRISPR gene editing. Finally, we show that AOs readily allow modelling of viral infections such as RSV and for the first time demonstrate the possibility to study neutrophil-epithelium interaction in an organoid model. Taken together, we anticipate that human AOs will find broad applications in the study of adult human airway epithelium in health and disease.

  Dataset EGAD00001004013

• Cancer Genomics of the Kidney

  The aim of CAGEKID is to carry out comprehensive detection of DNA markers for conventional (clear cell) renal carcinoma. The project includes complete analysis of somatic and constitutional DNA variation, methylation patterns and expression in a large number of constitutional/tumor pairs. CAGEKID is a part of the International Cancer Genome Consortium, ICGC.

  Dataset EGAD00001004018

• 2014 sequenced Korean WES-Lung Cancer sample 36 pair

  This data is belong to WES-Lung Cancer patients' genome data which is aligned to human reference(human_g1k_v37.fasta). There are 36 paired tumor/normal samples from Samsung Hospital. All samples has passed QC and recalibration steps while aligning to reference.

  Dataset EGAD00001004027

• HBV-associated hepatocellular carcinoma

  Fastq files of whole-genome bisulfite sequence of non-cancerous tissue of HBV-associated hepatocellular carcinoma

  Dataset EGAD00001004032

• Molecular diagnosis of albinism (2018-03-14)

  Albinism is genetically heterogeneous rare genetic condition affecting 1:17000 in the Western world (but more frequent in Africa) whose main feature is a profound visual impairment, characterised by foveal hypoplasia, abnormal chiasmatic connections, nystagmus and photofobia. All these features result in severly altered visual acuity (<0,1), absent depth perception and poor night vision. People with albinism are primarily visually handicapped. In addition, for some types of albinism, the visual phenotype can be presented with partial or total hypopigmentation, hence resulting in a secondary phenotype which can lead to skin cancer if skin is not adequately protected. Recently a new syndrome has been described, FHONDA, with the same visual abnormalities of albinism but without pigment alteration. The traditional classification differentiates Oculoculatenous albinism (OCA), where hypopigmentation involves hair, skin and eyes versus Ocular Albinism (OA), where hypopigmentation only affects the eyes. These are non-sydrimic types of albinism. Some syndromic forms (Hermansky-Pudlak=HPS, Chediak-Higashi=CHS) affect cells beyond pigment cells, present in the lungs, immune system, platelets and intestines, resulting in more severe phenotypes that can be fatal. Mutations in at least 19 genes are assocaited with the corresponding types of albinism. Most hospitals will only diagnose the most frequent cases using traditional Sanger, MLPA approaches. Some will use CGH arrays. We aim to diagnose all cases of albinism through the Albinochip proposal, which combines a Sequenom first step of known mutations combined with subsequent NGS approaches. In some cases we fail to find a second mutation, these are good candidates for further full exome analyses. 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/ . This dataset contains all the data available for this study on 2018-03-14.

  Dataset EGAD00001004039

• CLL targeted exome sequencing (2018-03-14)

  Aim to characterise cancer gene landscape in CLL, particularly in cases with mutated POT1 gene. Treatment-naive CLL cases will be interrogated by targeted exome sequencing using a cancer gene panel. . This dataset contains all the data available for this study on 2018-03-14.

  Dataset EGAD00001004037

• Exome sequencing of 142 gastric cancer and matched normal from Japanese cohorts (UT)

  As a contribution to the International Cancer Genome Consortium, exome sequencing of 142 Japanese gastric cancer with various histological subtypes have been conducted. This study aims to identify unique and common driver genes and molecular subtypes in Japanese gastric cancer. Please refer ICGC website for detail: http://icgc.org/icgc/cgp/69/420/1012357

  Dataset EGAD00001004041

• Exome sequencing of 102 gastric cancer and matched normal from Japanese cohorts (YCU)

  As a contribution to the International Cancer Genome Consortium, exome sequencing of 102 Japanese gastric cancer with various histological subtypes have been conducted. This study aims to identify unique and common driver genes and molecular subtypes in Japanese gastric cancer. Please refer ICGC website for detail: http://icgc.org/icgc/cgp/69/420/1012357

  Dataset EGAD00001004042

• Exome sequencing files for "A single mutant clone populates the pancreatic ductal system to generate coexisting neoplastic lesions"

  Files from whole exome sequencing of eight tumors from eight pancreatic cancer patients along with matched PanIN precursor lesion(s) and a matched normal tissue.

  Dataset EGAD00001004044

• Reference Epigenomes and Regulatory Landscape of CLL

  Analysis of the reference epigenomes and regulatory landscape of CLL as a whole and its major clinico-biological subtypes (with mutated and unmutated IGHV) in the light of the normal B-cell differentiation. We have extensively characterized the reference epigenomes of seven primary chronic lymphocytic leukemia samples (CLLs) with mutated (n=5) and unmutated IGHV (n=2) as well as several mature B-cell subpopulations (naive B cells from blood and tonsil, germinal center B cells, memory B cells and plasma cells from tonsil) using genome-wide maps of six histone marks (H3K4me3, H3K4me1, H3K27ac, H3K36me3, H3K9me3 and H3K27me3), DNA accessibility (ATAC-seq), DNA methylation (whole-genome bisulfite sequencing) and gene expression (RNA-seq). Furthermore, we have mapped the regulatory chromatin landscape of 100 additional CLL cases using chIP-seq of H3K27ac and ATAC-seq and linked these data to additional layers of information (whole-genome and/or whole-exome sequencing (WGS/WES), RNA-seq and DNA methylation microarrays) studied in the context of the International Cancer Genome Consortium (ICGC).

  Dataset EGAD00001004046

• Genomic analysis of Japanese gastric cancer

  fastq of 345 Japanese gastric cancer

  Dataset EGAD00001004051

• nanostring analysis

  mRNA expression profile of kidney cancer

  Dataset EGAD00010001535

• CNVs analysis

  kidney cancer tissue sample

  Dataset EGAD00010001536

• Single-cell transcriptome sequencing of regulatory and conventional T cells in breast cancer patients and healthy individuals.

  Identification of tumor-specific effects on gene expression profile of regulatory T cells and conventional T cells in humans, investigation of the clonal origin of regulatory T cells and impact analysis of tumor-specific conversion of conventional T cells into induced regulatory T cells on the peripheral regulatory T cell repertoire in humans.

  Dataset EGAD00001004069

• Low-coverage Whole Genome Sequencing, Colorectal advanced adenomas, NKI-AvL TGO COCOS series

  For this tissue dataset, we applied low-pass whole genome sequencing to 96 advanced adenomas. Advanced adenomas were classified as lesions with low-risk or high-risk of progression, according to the presence of specific DNA copy number changes (Carvalho et al, CancerPrevRes, 2018).

  Dataset EGAD00001004078

• Mutational consequences of precancerous liver disease

  Clonally expanded liver adult stem cell clones of healthy liver and cirrhotic liver (due to alcohol abuse, NASH and PSC), as well as biopsies of liver cancers were subjected to whole genome sequencing to determine the mutational impact of precancerous liver disease

  Dataset EGAD00001004105

• Cancer gene panel (T200.1) sequencing analysis of adult type ovarian granulosa cell tumors (Validation cohort from Hillman, et al)

  Cancer gene panel (T200.1) sequencing data from tumor/normal pairs for adult type ovarian granulosa cell tumor sequencing project. This data set contains 55 tumor panel sequencing data and 44 matched normal panel sequencing data generated using the MD Anderson Cancer Center T200.1 cancer gene hybrid capture platform, with sequencing performed on an Illumina HiSeq 2000. This dataset contains BAM files generated by aligning paired-end reads to the hg19 reference genome.

  Dataset EGAD00001004091

• Chip-exo and Chip-nexus for five TFs in three colorectal cancer cell lines

  Chip-exo and Chip-nexus for FOXA1, HNF4A, KLF5, MYC, and TCF7L2 in colorectal cancer cell lines LoVo, GP5D, COLO320DM

  Dataset EGAD00001004099

• Spatial Maps of Prostate Cancer Transcriptomes

  A total of 14 samples that has been analyzed with the Spatial Transcriptomics method. H&E stain can be sent if requested.

  Dataset EGAD00001004121

• The spatio-temporal evolution of lymph node spread in early breast cancer

  Set of multi-region sequenced breast cancer primary samples, lymph nodes and ctDNA. We collected samples from 11 breast cancer patients with lymph node involvement but no sign of distant metastasis. We performed a mix of whole-exome sequencing, targeted capture sequencing, and whole-genome sequencing of primary tumour samples and lymph nodes, as well as targeted capture sequencing of circulating tumour DNA.

  Dataset EGAD00001004122

• Structural rearrangements generate cell-specific, gene-independent CRISPR-Cas9 loss of fitness effects.

  CRISPR-Cas9 genome editing is widely used to study gene function, from basic biology to biomedical research. Structural rearrangements are a ubiquitous feature of cancer cells and their impact on the functional consequences of CRISPR-Cas9 gene-editing has not yet been assessed. Utilizing CRISPR-Cas9 knockout screens for 250 cancer cell lines, we demonstrate that targeting structurally rearranged regions, in particular tandem or interspersed amplifications, is highly detrimental to cellular fitness in a gene independent manner. In contrast, amplifications caused by whole chromosomal duplications have little to no impact on fitness. This effect is cell line specific and dependent on the ploidy status. We devise a copy-number ratio metric that substantially improves the detection of gene-independent cell fitness effects in CRISPR-Cas9 screens. Furthermore, we develop a computational tool, called Crispy, to account for these effects on a single sample basis and provide corrected gene fitness effects. Our analysis demonstrates the importance of structural rearrangements in mediating the effect of CRISPR-Cas9-induced DNA damage, with implications for the use of CRISPR-Cas9 gene-editing in cancer cells.

  Dataset EGAD00001004124

• Normal prostatectomy project analysis and leftovers

  Data collected as part of the Normal prostatectomy project analysis. Whole genome sequencing (WGS, targeted at 30X for normal tissue and 50X for tumour tissue) was performed on morphologically normal tissue samples from 30 patients with prostate cancer. In addition, seven prostate tissue samples were sequenced from 7 non-cancer patients: two collected after a cystoprostatectomy and five from samples collected at autopsy. Matched blood controls were included for all patients. An extra five samples were sequenced from the stroma of cell cultured fibroblasts. In addition a few tumour samples obtained at prostatectomy and their blood matched controls are included in this dataset from the main study that are not included elsewhere.

  Dataset EGAD00001004125

• Anaplastic Thyroid Cancer aligned sequence data

  Sequence data in fastq format was aligned to the GRCH38 reference genome. Aligned sequence was preprocessed with GATK for Indel Realignment and Base Quality Score Recalibration. Duplicates were marked with Picard Mark Duplicates. Aligned sequence is in bam format. Details of the alignment can be found int he bam header. In total, data generated from 174 tumour samples 102 matched blood normal controls was aligned. Tumour samples were classified as Anaplastic Thyroid, Poorly-differentiated or well-differentiated cancers.

  Dataset EGAD00001004126

• Anaplastic Thyroid Cancer germline variants

  Sequence was aligned to the GRCH38 reference genome. Aligned sequence was analyzed with GATK Haplotype Caller, to generate germline variant calls across the SureSelect All Exon V5+UTR target region. Variant calls are in VCF format. In total there are samples from 173 donors. 101 donors have calls generated from both normal and tumour samples tumour samples, 94 of which have a matched normal. Details for the call can be found in the vcf headers.

  Dataset EGAD00001004127

• Anaplastic Thyroid Cancer somatic variants (SomaticSniper)

  Sequence was aligned to the GRCH38 reference genome. Aligned sequence was analyzed with SomaticSniper. Somatic variant calls are in VCF format. In total there are 94 tumour samples, each with a matched normal.

  Dataset EGAD00001004128

• Anaplastic Thyroid Cancer somatic variants (MuTect)

  Sequence was aligned to the GRCH38 reference genome. Aligned sequence was analyzed with GATK/MuTect, to generate somatic variant calls across the SureSelect All Exon V5+UTR target region. Somatic variant calls are in VCF format. In total there are 166 tumour samples, 94 of which have a matched normal. Somatic variants for tumours without a matched normal, were called against a panel of normals. Details for the mutect call can be found in the vcf header.

  Dataset EGAD00001004129

• Pheno-seq profiles of single clonal tumor spheroids derived from a patient with colorectal cancer

  Pheno-seq is a new approach that integrates high-throughput imaging and transcriptomic profiling of clonal spheroids/organoids to dissect functional tumor cell heterogeneity in 3D cell culture systems. The method is based on the iCELL8 technology (TakaraBio) that uses barcoded nanowells and a micro-solenoid valve dispenser. The CRC_spheroid dataset contains demultiplexed RNA-sequencing profiles (FASTQ file format, NextSeq 500) of 95 clonal tumor spheroids derived from a patient with colorectal cancer.

  Dataset EGAD00001004131

• Epigenetic profiling of colorectal cancer initiating cells (CC-ICs) and investigation of changes in transcriptome following EZH2 inhibition using RNA-seq.

  Epigenetic profiling of colorectal cancer initiating cells (CC-ICs) to identify bivalently marked genes (H3K4me3 and H3K27me3 ChIP-seq), and investigation of changes in transcriptome following EZH2 inhibition using RNA-seq.

  Dataset EGAD00001004133

• RNA-seq analysis of transcriptome variation with human ESC subclones

  Many studies over the past 10 years, culminating in the recent report of the International Stem Cell Initiative (ISCI, 2011) have shown that hPSC acquire genetic and epigenetic changes during their time in culture. Many of the genetic changes are non-random and recurrent, probably because they provide a selective growth advantage to the undifferentiated cells. Some are shared by embryonal carcinoma cells, the malignant counterparts of ES cells. The origins of these growth advantages are poorly understood, but may come from altered cell cycle dynamics, resistance to apoptosis or altered patterns of differentiation. Less is known about the nature and consequences of epigenetic changes, but it is likely that these similarly affect hPSC behaviour; e.g., enhanced expression of DLK1, an imprinted gene, is associated with altered hPSC growth (Enver et al 2005). Inevitably, these genetic and epigenetic changes will impact on our ability to use hPSC for regenerative medicine, either because malignant transformation of the undifferentiated cells or their differentiated derivatives to be used for transplantation compromises safety, or because they impede the function of those differentiated derivatives, or because they affect the efficiency with which the undifferentiated cells can be expanded and differentiated into desired cell types. Focusing initially upon the existing clinical grade hESC lines, later moving to iPSC, we will Consolidate and extend knowledge of the rate, type and functional impact of the genetic variations that occur during hPSC culture. We will use whole genome and exome sequencing as well as SNP arrays, together with clonal analysis and other cytogenetics techniques. Common changes will be compared with those found in the normal human population, at low frequency in the original cell population or observed during iPSC generation in the HIPSCI project currently based at the WTSI. These studies will provide a better understanding of the range of genetic changes that occur in hPSC beyond the CNVs already identified. In conjunction with cancer genome resources and expertise at WTSI, bioinformatic analyses of these hPSC data will allow us to assess potential impact on hPSC behaviour pertinent to applications in regenerative medicine, notably the likelihood that specific changes arising in undifferentiated PSC cultures may be associated with potential malignant transformation of differentiated progeny 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/ .

  Dataset EGAD00001004266

• ICR639 CPG NGS Validation series

  The dataset includes sequencing data generated using the TruSight Cancer Panel (TSCP) a targeted NGS assay for analysis of CPGs and orthogonally generated data supporting at least one pathogenic variant in a CPG for a total of 645 pathogenic CPG variants. The set of pathogenic CPG variants includes strong representation of some of the most challenging types of pathogenic variants, with 339 indels, including 16 complex indels and 24 insertions or deletions with length greater than 5bp, and 74 exon CNVs, including 23 single exon CNVs. There are 502 pathogenic variants in BRCA1 or BRCA2, making this an important first-line validation dataset for laboratories performing NGS testing of BRCA1 and BRCA2.

  Dataset EGAD00001004134

• SS18-SSX-mediated hijacking of BAF complexes drives synovial sarcoma

  Synovial sarcoma (SS) is defined by a recurrent t(x;18) chromosomal translocation, which produces the hallmark SS18-SSX oncogenic fusion. Incorporation of SS18-SSX into BAF complexes renders BAF complexes aberrant in two distinct manners: the addition of 78aa of SSX onto SS18, and concomitant loss of BAF47 assembly. However, the importance and functional contributions of each of these perturbations on BAF complex targeting and gene expression regulation remain unclear. Here we use an integrative set of genomic approaches in human cancer cell lines and primary tumor samples to define the mechanistic consequences of the SS18-SSX fusion oncoprotein. We find that SS18-SSX hijacks BAF complexes to broad polycomb domains to activate bivalent genes, driving a unique gene expression program distinct from other loss-of-function BAF complex malignancies. Importantly, restoration of BAF47 rescues enhancer activation but is dispensable for proliferative arrest in cell lines. These results demonstrate that gain-of-function SS18-SSX-mediated BAF complex targeting and gene activation is the driving event in SS, and present a mechanism by which distinct functions of BAF complexes can be co-opted to drive oncogenesis.

  Dataset EGAD00001004135

• WES analysis of patients with USP8 wild-type corticotroph adenomas

  The overall goal of the Identification of recurrent mutations in Cushing’s disease project is to study the impact of whole-exome sequencing (WES) on the clinical care of cancer patients and oncology provider practices. The aims of Project are to implement and establish the feasibility of WES in patients with USP8 wild-type corticotroph adenomas; to develop a framework for the understanding of the molecular mechanism of the pathogenesis of corticotroph adenoma.

  Dataset EGAD00001004136

• Whole exome and targeted DNA sequencing data for formalin-fixed paraffin embedded tissue from de novo small cell prostatic carcinoma cases

  This dataset consists of 44 compressed paired fastq files, 15 of which are generated from whole exome sequencing, and 29 of which are generated from DNA sequencing using a targeted gene panel capturing the exonic regions of 73 prostate cancer driver genes. Targeted DNA sequencing was performed on an Illumina MiSeq (v3 600 cycle kit), and exome sequencing was done using an Illumina HiSeq 2500 (v4 250 cycle kit) machine. The fastq files are named in accordance with the sample aliases provided, which reflect the pathology of interest to this study (small cell prostatic carcinoma--SCPC), whether it was sequenced using an exome or targeted gene panel, whether the FFPE sample was sourced from tumor or benign tissue (labeled T or B, respectively), and whether there exists multiple samples belonging to a single patient.

  Dataset EGAD00001004139

• The dataset of breast cancer patients and benign breast tumor patients

  The dataset contains 438 plasma samples and 418 tissues samples from 102 breast cancer patients and 30 benign breast tumor patients. There are two kinds of file types: bam and fastq. Amplicon sequencing and Capture sequencing were used in our experiment.

  Dataset EGAD00001004175

• Whole exome profiling of spatial biopsies of high grade serous epithelial ovarian cancer patients

  This data set is comprised of data from seven distinct high grade serous epithelial ovarian cancer (HGS-EOC) partients, from whom multiple biopsies were taken at the time of surgery, from the ovary and from different locations in the peritoneal cavity. This data set contains 28 samples, sequenced with a whole exome sequencing approach.

  Dataset EGAD00001004154

• The evolving mutational landscape of normal human esophagus

  The extent to which cells in normal tissues accumulate mutations during life is poorly understood. Some mutant cells expand into clones that can be detected by genome sequencing. We mapped mutant clones in normal esophageal epithelium from nine donors aged 20-75. Somatic mutations accumulate with age and are mainly caused by intrinsic mutational processes. We found strong Darwinian selection of clones carrying mutations in 14 cancer genes, with tens to hundreds of such clones per square centimeter. By middle age, clones with cancer-associated mutations cover most of the epithelium, with NOTCH1 and TP53 mutations affecting 40% and 10% of all cells, respectively. Remarkably, the prevalence of NOTCH1 mutations in normal esophagus is several times higher than in esophageal cancers. The esophagus emerges as an evolving patchwork of mutant clones that colonize the majority of the epithelium, with implications for our understanding of cancer and ageing.

  Dataset EGAD00001004158

• The evolving mutational landscape of normal human esophagus

  The extent to which cells in normal tissues accumulate mutations during life is poorly understood. Some mutant cells expand into clones that can be detected by genome sequencing. We mapped mutant clones in normal esophageal epithelium from nine donors aged 20-75. Somatic mutations accumulate with age and are mainly caused by intrinsic mutational processes. We found strong Darwinian selection of clones carrying mutations in 14 cancer genes, with tens to hundreds of such clones per square centimeter. By middle age, clones with cancer-associated mutations cover most of the epithelium, with NOTCH1 and TP53 mutations affecting 40% and 10% of all cells, respectively. Remarkably, the prevalence of NOTCH1 mutations in normal esophagus is several times higher than in esophageal cancers. The esophagus emerges as an evolving patchwork of mutant clones that colonize the majority of the epithelium, with implications for our understanding of cancer and ageing.

  Dataset EGAD00001004159

• Undifferentiated sarcomas develop through distinct evolutionary pathways

  Undifferentiated sarcomas (USARC) of adults are diverse, rare and aggressive soft tissue cancers. Recent efforts have confirmed that USARC exhibit one of the highest burdens of structural aberrations across human cancer. Here, we sought to unravel the genomic basis of this structural complexity by integrating whole genome sequencing, ploidy analysis and methylation profiling of 53 USARC. We identified whole genome doubling as a prevalent and pernicious force in USARC tumourigenesis. Deconvolution of the complex copy number and rearrangement landscapes show distinct signatures associated with chromothripsis, early-haploidy, and successive whole-genome-doubling events, suggesting four divergent models of sarcoma development. We show similar distinct evolutionary tumourigenic pathways in different sarcoma subtypes from the Cancer Genome Atlas. Thirteen percent of tumours exhibited a hypermutator phenotype, opening new avenues for clinical management such as immunotherapy, whilst the period prior to and between genome doubling events may represent clinically relevant interventional points in USARC.

  Dataset EGAD00001004162

• Chromosome Segregation Errors Promote a Diverse Spectrum of Simple and Complex Genomic Rearrangements

  Cancer genomes are frequently characterized by numerical and structural karyotypic abnormalities. Here we combined an inducible centromere-specific inactivation approach with selection for a conditionally essential gene, a strategy we term ‘CEN-SELECT’, and show that single-chromosome missegregation during cell division can directly drive a broad spectrum of structural rearrangement types. Cytogenetic profiling revealed that missegregated chromosomes are 120-fold more susceptible to developing seven major categories of structural variants, including translocations, insertions, deletions, and reassembly into chromothriptically rearranged chromosomes. Whole-genome sequencing of clones with genetically propagatable derivative chromosomes identified complex rearrangements and copy-number alterations that can result in gene inactivation or extrachromosomal gene amplification. We conclude that chromosome segregation errors are sufficient to drive extensive structural variation that recapitulates those commonly associated with human cancers.

  Dataset EGAD00001004163

• Whole exome and transcriptome sequencing of gastric cancer patients

  Whole exome and RNA-seq of matched normal gastric mucosa (n=34) and gastric cancer tissues (n=34) from gastric cancer patients (n=34)

  Dataset EGAD00001004164

• The landscape of somatic mutation in normal colorectal epithelial cells

  The colorectal adenoma-carcinoma sequence has provided a paradigmatic framework for understanding the successive somatic genetic events and consequent clonal expansions leading to cancer. As for most cancer types, however, understanding of the earliest phases of colorectal neoplastic change, which may occur in morphologically normal tissue, is comparatively limited because of the difficulty of detecting somatic mutations in normal cells. Each colorectal crypt is a small clone of cells derived from a single recently-existing stem cell. Here, we sequenced hundreds of normal crypts from 42 individuals. Signatures of multiple mutational processes were revealed, some ubiquitous and continuous, others only found in some individuals, in some crypts or during some phases of the cell lineage from zygote to adult cell. Likely driver mutations were present in ~1% of normal colorectal crypts in middle-aged individuals, indicating that adenomas and carcinomas are rare outcomes of a pervasive process of neoplastic change across morphologically normal colorectal epithelium.

  Dataset EGAD00001004193

• Characterization of mutational signatures in human cancer cell lines reveals episodic APOBEC mutagenesis

  Multiple signatures of somatic mutations have been identified in human cancer genomes. To investigate whether mutational signatures continue to be generated, and if so their temporal patterns of activity, subsets of cell lines were cultured in vitro for extended periods and subjected to single cell cloning and whole genome or exome sequencing or directly to single cell whole genome sequencing. As expected, signatures of past exogenous exposures, such as tobacco smoke and ultraviolet light, were not generated in vitro. In contrast, signatures of normal and defective DNA repair and replication continued to be generated at essentially constant mutation rates. Signatures of APOBEC cytidine deaminase DNA-editing activity exhibited a distinctive pattern with substantial fluctuations in mutation rate over time and episodic bursts of mutations. The initiating factors for these bursts are unclear although retrotransposon mobilisation may play a role. This cell line set now constitutes a comprehensive resource of live experimental models of mutational processes of both known and unknown aetiologies potentially retaining the patterns of activity and regulatory influences operative in human cells in vivo.

  Dataset EGAD00001004201

• Dataset SNP tumours

  This dataset contains 30 idat files each from 15 SNP array runs on patient colitis-associated colorectal cancer tumours. All phenotypes are cancer. See Baker et al. 2018 Supplementary Table 2 for patient details of 12 tumours used in the analyses in the publication.

  Dataset EGAD00010001587

• Characterization of mutational signatures in human cancer cell lines reveals episodic APOBEC mutagenesis

  Multiple signatures of somatic mutations have been identified in human cancer genomes. To investigate whether mutational signatures continue to be generated, and if so their temporal patterns of activity, subsets of cell lines were cultured in vitro for extended periods and subjected to single cell cloning and whole genome or exome sequencing or directly to single cell whole genome sequencing. As expected, signatures of past exogenous exposures, such as tobacco smoke and ultraviolet light, were not generated in vitro. In contrast, signatures of normal and defective DNA repair and replication continued to be generated at essentially constant mutation rates. Signatures of APOBEC cytidine deaminase DNA-editing activity exhibited a distinctive pattern with substantial fluctuations in mutation rate over time and episodic bursts of mutations. The initiating factors for these bursts are unclear although retrotransposon mobilisation may play a role. This cell line set now constitutes a comprehensive resource of live experimental models of mutational processes of both known and unknown aetiologies potentially retaining the patterns of activity and regulatory influences operative in human cells in vivo.

  Dataset EGAD00001004202

• Characterization of mutational signatures in human cancer cell lines reveals episodic APOBEC mutagenesis

  Multiple signatures of somatic mutations have been identified in human cancer genomes. To investigate whether mutational signatures continue to be generated, and if so their temporal patterns of activity, subsets of cell lines were cultured in vitro for extended periods and subjected to single cell cloning and whole genome or exome sequencing or directly to single cell whole genome sequencing. As expected, signatures of past exogenous exposures, such as tobacco smoke and ultraviolet light, were not generated in vitro. In contrast, signatures of normal and defective DNA repair and replication continued to be generated at essentially constant mutation rates. Signatures of APOBEC cytidine deaminase DNA-editing activity exhibited a distinctive pattern with substantial fluctuations in mutation rate over time and episodic bursts of mutations. The initiating factors for these bursts are unclear although retrotransposon mobilisation may play a role. This cell line set now constitutes a comprehensive resource of live experimental models of mutational processes of both known and unknown aetiologies potentially retaining the patterns of activity and regulatory influences operative in human cells in vivo.

  Dataset EGAD00001004203

• Whole-exome sequencing of liver cancer organoids

  Whole-exome sequencing was performed from organoids derived from 10 liver cancer biopsies (7 hepatocellular carcinoma and 3 cholangiocarcinoma), corresponding liver and non-tumoral biopsies. For 3 of the organoids, both early and late passage organoids were sequenced. Whole-exome sequencing was performed using the Agilent Clinical Research Exome capture kit followed by Illumina sequencing. BAM files are provided in this dataset.

  Dataset EGAD00001004205