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• WES data for HGSC patient-derived organoids (Kallunki)

  The dataset contains whole exome sequencing (WES) data of organoids from 10 high-grade serous carcinoma (HGSC) patients. The 31 samples are sequenced with Novaseq6000. The files provided are paired fastq files.

  Dataset EGAD50000002216

• MutWP4__CRUK_Grand_Challenge_Mutographs_of_Cancer__Gastric_Organoids

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, Kings College London will characterise the mutational signatures induced by putative human carcinogens in order to identify the origins of mutational signatures found in human cancers. To achieve this human organoid cell cultures will be exposed to a representative catalogue of known or suspected human carcinogens and mutagens and, using whole genome sequencing, the patterns of mutations induced by them will be determined. Somatic mutational signatures will be subsequently extracted by non-negative matrix factorisation methods and correlated with exposure data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Study EGAS00001003151

• MutWP4__CRUK_Grand_Challenge_Mutographs_of_Cancer__Pancreatic_Organoids

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, Kings College London will characterise the mutational signatures induced by putative human carcinogens in order to identify the origins of mutational signatures found in human cancers. To achieve this human organoid cell cultures will be exposed to a representative catalogue of known or suspected human carcinogens and mutagens and, using whole genome sequencing, the patterns of mutations induced by them will be determined. Somatic mutational signatures will be subsequently extracted by non-negative matrix factorisation methods and correlated with exposure data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Study EGAS00001003520

• MutWP4__CRUK_Grand_Challenge_Mutographs_of_Cancer__organoid_control_WGS

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, Kings College London will characterise the mutational signatures induced by putative human carcinogens in order to identify the origins of mutational signatures found in human cancers. To achieve this human organoid cell cultures will be exposed to a representative catalogue of known or suspected human carcinogens and mutagens and, using whole genome sequencing, the patterns of mutations induced by them will be determined. Somatic mutational signatures will be subsequently extracted by non-negative matrix factorisation methods and correlated with exposure data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Study EGAS00001005449

• MutWP4__CRUK_Grand_Challenge_Mutographs_of_Cancer__Mutagen_treated_organoids

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, Kings College London will characterise the mutational signatures induced by putative human carcinogens in order to identify the origins of mutational signatures found in human cancers. To achieve this human organoid cell cultures will be exposed to a representative catalogue of known or suspected human carcinogens and mutagens and, using whole genome sequencing, the patterns of mutations induced by them will be determined. Somatic mutational signatures will be subsequently extracted by non-negative matrix factorisation methods and correlated with exposure data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Study EGAS00001004873

• Exome_sequencing_of_Congenital_Heart_Disease_families_Leuven

  This project aims to study at least 90 exomes from families with congenital heart disease. The samples have been selected in Leuven in collaboration with Koen Devriendt. Ethic approval has been sought for in Leuven, Belgium and a HDMMC agreement for submitting these samples is in place at the WTSI. The phenotype we wil primarily focus our analysis is severe Left Ventricular Outflow Tract Obstructions (LVOTO) and Atrioventricular Septal Defect (AVSD). The indexed Agilent whole exome pulldown libraries will be sequenced on 75bp PE HiSeq (Illumina).

  Study EGAS00001000185

• An Organoid Biobank of Rare Human Neuroendocrine Neoplasms Enables Genotype-Phenotype Mapping

  We performed whole genome sequencing and RNA-sequencing of neuroendocrine neoplasm. The aim of this study was to provide genetic landscape of neuroendocrine neoplasm, to construct available animal models, and to engineer neuroendocrine neoplasm from normal colon epithelium. The reference genomes used are GRCh37 for whole genome sequencing and GRCh38 for RNA-sequencing.

  Study JGAS000237

• Capture-based Methods for Transcriptomic Profiling of FFPE material

  This dataset includes all FASTQ files for 11 samples where different capture-based methods for transcriptome profiling have been tested. Specifically, we have the 'traditional' RNA-seq experiment with fresh frozen (FF) material, and 3 different capture methods for the matching formalin-fixed paraffin-embedded samples: Agilent (AGI), IDT, and Twist Biosciences (TBS). In total, there are 43 samples with paired-end FASTQ files (1 sample did not have sufficient material to test all methods). Samples are identified by the R01-R11 IDs with a suffix that indicates the capture method used (or FF for fresh frozen).

  Dataset EGAD00001007655

• Autism Post-Mortem Brain RNA-Sequencing: SRRM4 Splicing Study

  Purpose: The goal of this study was to assess the status of splicing changes in microexons in the cortex of individuals with autism. Methods: We performed RiboZero Gold (rRNA depleted) 50bp PE RNA-seq in a larger set of case and control samples to define 12 autism and 12 control samples showing the greatest global differential gene expression change. These samples, which show differential expression of the splicing regulator SRRM4, were used to evaluate global splicing changes. Results: Within these samples, 126 of 504 (30%) detected alternative microexons display, a mean ΔPSI > 10 between ASD and control subjects of which 113 (90%) also display neural-differential regulation. By contrast, only 825 of 15,405 (5.4%) longer (i.e. > 27 nt) exons show such misregulation, of which 285 (35%) correspond to neural-regulated exons. Notably, we also observe significantly higher correlations between microexon inclusion and nSR100 mRNA expression levels across the stratified ASD samples and controls, for those microexons regulated by nSR100 relative to those microexons that are not regulated by this factor (p=1.4x10-7, Wilcoxon Sum Rank test). Conclusions: These data suggest microexon regulation is a potentially important mechanism underlying ASD and likely other neurodevelopmental disorders.

  Study phs000872

• Integrated copy number and expression analysis identifies profiles of whole-arm chromosomal alterations and subgroups with favorable outcome in ovarian clear cell carcinomas

  Ovarian clear cell carcinoma (CCC) is generally associated with chemoresistance and poor clinical outcome, even with early diagnosis; whereas high-grade serous carcinomas (SCs) and endometrioid carcinomas (ECs) are commonly chemosensitive at advanced stages. Although an integrated genomic analysis of SC has been performed, conclusive views on copy number and expression profiles for CCC are still limited. In this study, we performed single nucleotide polymorphism arrays in 57 (31 CCCs, 14 SCs, and 12 ECs) and expression microarrays in 55 epithelial ovarian cancers (25 CCCs, 16 SCs, and 14 ECs), and then evaluated PIK3CA mutations and ARID1A expression in CCCs. SNP array analysis classified 13% of CCCs into a cluster with high frequency and focal range of copy number alterations (CNAs), significantly lower than for SCs (93%, P < 0.01) and ECs (50%, P = 0.017). The ratio of whole-arm to all CNAs was higher in CCCs (46.9%) than SCs (21.7%) (P < 0.0001). SCs with loss of heterozygosity (LOH) of BRCA1 (85%) also had LOH of NF1 and TP53, and LOH of BRCA2 (62%) coexisted with LOH of RB1 and TP53. Microarray analysis classified CCCs into three clusters. One cluster (CCC-2, n = 10) showed more favorable prognosis than the others (CCC-1and CCC-3) (P = 0.041). Coexistent alterations of PIK3CA and ARID1A were more common in CCC-1 and CCC-3 (7/11, 64%) than in CCC-2 (0/10, 0%) (P < 0.01). Being in cluster CCC-2 was an independent favorable prognostic factor in CCC. In conclusion, CCC was characterized by a high ratio of whole-arm CNAs; whereas CNAs in SC were mainly focal, but preferentially caused LOH of well-known tumor suppressor genes. As such, expression profiles might be useful for sub-classification of CCC, and might provide useful information on prognosis.

  Study JGAS000022