13381 results for ""pdc"+"heritage+language"+census+study"

in 67.60 milliseconds.

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

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

  Dataset EGAD00001004606

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

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

  Dataset EGAD00001004605

• Genome and transcriptome sequence data from a non-small cell lung carcinoma patient

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

  Dataset EGAD00001004596

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

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

  Dataset EGAD00001004604

• Genome and transcriptome sequence data from a metastatic basal cell carcinoma patient

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

  Dataset EGAD00001004630

• Genome and transcriptome sequence data from a metastatic breast cancer ER+ patient

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

  Dataset EGAD00001004631

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

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

  Dataset EGAD00001004632

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

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

  Dataset EGAD00001004633

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

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

  Dataset EGAD00001004634

• PPIL4 is essential for brain angiogenesis and implicated in intracranial aneurysm in humans

  Rupture of intracranial aneurysms (IAs) leads to subarachnoid hemorrhage (SAH), a sudden-onset disease often causing severe disability or death. Using whole exome sequencing, we identified significant enrichment of rare, deleterious mutations in PPIL4 in both index and familial IA cases. Ppil4 depletion causes intracerebral hemorrhage, defects in cerebrovascular morphology, and impaired Wnt signaling in vivo. Wild type, but not IA-mutant PPIL4, potentiates Wnt signaling by binding JMJD6, a known angiogenesis regulator and Wnt activator. These findings identify a novel PPIL4-dependent Wnt signaling mechanism involved in brain-specific angiogenesis and maintenance of cerebrovascular integrity, and implicate PPIL4 gene variation in the pathogenesis of human IA.

  Study EGAS00001005518

• Single-cell RNA-seq data of the tumor microenvironment of lymphocyte-rich Hodgkin lymphoma and other Hodgkin lymphoma subtypes

  Lymphocyte-rich classic Hodgkin lymphoma (LR-CHL) is a rare subtype of Hodgkin lymphoma. Recent technical advances have allowed for the characterization of specific crosstalk mechanisms between malignant Hodgkin Reed-Sternberg (HRS) cells and different normal immune cells in the tumor microenvironment (TME) of CHL. However, the TME of LR-CHL has not yet been characterized at single cell resolution. Here, using single cell RNA sequencing, we examined the immune cell profile of 8 cell suspension samples of LR-CHL in comparison to 20 samples of the mixed cellularity (9 cases) and nodular sclerosis (11 cases) subtypes of CHL, as well as 5 reactive lymph node controls.

  Study EGAS00001005541

• Origins and timing of emerging lesions in advanced renal cell carcinoma

  Renal cell carcinoma (RCC) with venous tumor thrombus (VTT) arising from the primary tumor occurs in ~10% of cases and is thought to represent more advanced disease. RCC with VTT and distant metastasis provides unique opportunities to examine the origins and relative timing of tumor lesion emergence and to identify molecular correlates with disease state. We performed multi-region exome and RNA sequencing analysis of a clinical cohort of 16 RCC patients with VTT, with eight patients also having sequenced metastasis, to examine which genomic alterations, biological pathways, and evolutionary processes contribute to VTT and metastasis, and to ask whether metastasis typically arises directly from VTT or is independent of VTT.

  Study EGAS00001005897

• Case Report: Precision medicine target revealed by in-vitro modelling of relapsed, refractory ALL from a child with neurofibromatosis

  Children with neurofibromatosis have a higher risk of developing juvenile myelomonocytic leukaemia and acute myeloid leukaemia, but rarely develop B-cell acute lymphoblastic leukaemia (B-ALL). Through in-vitro modelling, a novel NF1 p.L2467 frameshift (fs) mutation identified in a relapsed/refractory Ph-like B-ALL patient with neurofibromatosis demonstrated cytokine independence and increased RAS signalling, indicative of leukaemic transformation. Furthermore, these cells were sensitive to the MEK inhibitors trametinib and mirdametinib. Bi-allelic NF1 loss of function may be a contributing factor to relapse and with sensitivity to MEK inhibitors, suggests a novel precision medicine target in the setting of neurofibromatosis patients with B-ALL.

  Study EGAS00001006187

• Intra-prostatic tumour evolution, steps in metastatic spread and histogenomic associations revealed by integration of multi-region whole genome sequencing with histopathological features

  We performed whole genome sequencing on 42 prostate cancer samples from the prostate, seminal vesicles and regional lymph nodes of five treatment-naive patients with locally advanced disease who underwent radical prostatectomy. Using cancer cell fractions computed from single nucleotide variants and copy number alterations, we reconstructed the tumour phylogenies, which in turn allowed us to infer key molecular steps in the progression of prostate cancer in these individuals. We mapped the clonal composition of cancer sampled across the prostate in each individual and inferred the routes of spread of cancer cells within the prostate and to seminal vesicles and lymph nodes.

  Study EGAS00001007438

• Genomic profiling of IBC

  We collected matched pretreatment blood and tumor samples from 19 patients with primary TN-IBC enrolled in a phase II clinical trial (NCT02876107). Patients were treated with neoadjuvant chemotherapy (NAC) or the anti-EGFR antibody panitumumab (PmAb) plus NAC (PmAb/NAC). We conducted whole-exome sequencing, RNA sequencing, and CIBERSORT analyses for these TN-IBC samples and compare the genetic and molecular profiles with similarly analyzed stage III TN-non-IBC patient samples. We also compared the genetic and molecular characteristics of TN-IBC in patients who had a pathologic complete response (pCR) to NAC or PmAb/NAC treatment, a suitable surrogate endpoint for IBC, with those who did not have pCR (non-pCR).

  Study EGAS00001007520

• 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.

  Study EGAS00001008051

• Next Generation Sequencing platform for targeted Personalized Therapy of Leukemia - Acute myeloid leukemia

  The advent of high-throughput next generation sequencing (NGS) technologies that are revolutionizing genomics and transcriptomics by providing a single base resolution tool for a unified deep analysis of diseases complexity allows a fast and cost-efficient fine-scale assessment of the genetic variability hidden within cohorts of patients affected by the same leukemia. That being so, by potentially highlighting inter-individual differences that may play a role in the differential success of diverse therapeutic interventions, they promise to be crucial for selecting the most appropriate medical treatments. The project aims at the identification of novel prognostic biomarkers for acute myeloid leukemia (AML) and studied the molecular differences between aneuploid and euploid AML.

  Study EGAS00001005464

• Detection and genomic analysis of BRAF fusions in Juvenile Pilocytic Astrocytoma through the combination and integration of multi-omic data

  Juvenile Pilocytic Astrocytoma (JPAs) are highly vascular tumors and show pervasive immune infiltration, which can lead to low tumor cell purity in clinical samples. In some instances, this results in gene fusions that are difficult to detect with conventional omics approaches including RNA-Seq. To this effect, we applied RNA-Seq as well as linked-read whole-genome sequencing and in situ Hi-C as new approaches to detect and characterize low-frequency gene fusions at the genomic, transcriptomic and spatial level. Overall, we demonstrate the power of integrating multi-omic datasets to identify low frequency fusions and characterize the JPA genome at high resolution.

  Study EGAS00001006388

• Time-dependent characterization of CNS response in COVID-19

  Coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 primarily affects the respiratory system, but the observation of diverse neurological symptoms indicates that other organs, including the brain, may be involved. The pathophysiological mechanisms of COVID-19-associated effects on the central nervous system (CNS) have become clearer during the past two years. Nevertheless, the precise CNS-specific molecular mechanisms are still elusive and raise several questions. To further elucidate the host response at brain tissue level, we profiled single-nucleus transcriptomes and performed proteomics from olfactory mucosa, olfactory bulb, medulla oblongata and cerebellum at different timepoints of the disease in individuals who died of COVID-19 and underwent rapid autopsy.

  Study EGAS00001006442

• T cell reactivity of MHC epitopes

  By using >36,000 immunogenicity assay results, we developed a method to identify peptide-MHC complexes whose structural alignment facilitates T cell reaction. Our method accurately predicted neoepitopes for MHC II as well as MHC I that were responsive to checkpoint blockade when applied to >1,200 samples of various tumor types and on-therapy melanoma samples. To investigate selection by spontaneous immunity at the single epitope level, we analyzed the frequency spectrum of >25 million mutations in >9,000 treatment-naïve tumors in association with >100 immune phenotypes. MHC II immunogenicity specifically lowered variant frequencies in tumors under high immune pressure particularly with high TCR clonality and MHC II expression.

  Study EGAS00001006445

• Subtype-associated epigenomic landscape and 3D genome structure in bladder cancer

  We determine the genome-wide transcriptome, enhancer landscape and transcription factor binding profiles of FOXA1 and GATA3 in luminal and basal subtypes of bladder cancer. Furthermore, we report the first-ever mapping of genome-wide chromatin interactions by Hi-C in both bladder cancer cell lines and primary patient tumors. We show that subtype-specific transcription is accompanied by specific open chromatin and epigenomic marks, at least partially driven by distinct transcription factor binding at distal-enhancers of luminal and basal bladder cancers. Finally, we identify a novel clinically relevant transcription factor, Neuronal PAS Domain Protein 2 (NPAS2), in luminal bladder cancers that regulates other subtype-specific genes and influences cancer cell proliferation and migration.

  Study EGAS00001005071

• Identification and functional characterisation of a rare MTTP variant underlying familial non-alcoholic fatty liver disease

  We identified a rare causal variant in MTTP, c.1691T>C p.I564T (rs745447480) encoding microsomal triglyceride transfer protein (MTP) causing progressive non-alcoholic fatty liver disease with cirrhosis and hepatocellular carcinoma unrelated to metabolic syndrome, without manifestations of abetalipoproteinemia, in a four generation family with South Asian ancestry. Variant-expressing hepatocyte-like-cells (HLCs) derived from human induced pluripotent stem cells generated from homozygous donor skin fibroblasts had lower lipoprotein ApoB secretion, compared to wild type cells. Cytoplasmic triglyceride accumulation in HLCs triggered endoplasmic reticulum stress, secretion of pro-inflammatory mediators, production of reactive oxygen species, delineating the progression of disease associated with homozygosity for MTTP p.I564T

  Study EGAS00001005254

• Chip_seq_oesophageal_adenocarcinoma_

  There is complex interplay between underlying genetic sequence and epigenetic factors, however this interplay is still illusive. Massively reconstructed cancer genomes can be used in order to better understand this relationship. Six oesophageal adenocarcinoma organoids will be sequenced using long read sequencing technologies and will be profiled for a range of epigenetic marks. Combination of genetic and epigenetic data will allow the thorough characterisation of reference cancer genomes and will provide novel insights into mechanisms of gene regulation. Description: Chip-seq Sequencing of 5 patient derived organoid cell models. Each model was derived from a piece of patient tumour taken following surgical rescetion of the tumour. All model derivations took place with the CGaP facility in Sanger.

  Study EGAS00001007180

• Human data for chromatin accessibility (ATAC-Seq and scATAC-Seq) and transcriptome (RNA-Seq and scRNA-Seq) in eight B-cell precursors, from HSC to Naive B cells

  We generated paired transcriptomic (RNA-Seq) and chromatin accessibility (ATAC-Seq) profiles from 8 immune cell populations representing the early lymphoid hematopoietic differentiation stages along the B cell lineage: HSC, CLP, pro-B, pre-B, Immature B, Transitional B, Naive B CD5-, Naive B CD5+. Cell populations were isolated from healthy adult human bone marrow precursors and peripheral blood (n=13) following a predefined sorting strategy. For each donor, a subset of different cell type populations was obtained. Additionally, to explore the continuous dynamic of RNA and ATAC, we generated a single-cell sample of human CD34+ B cell precursors.

  Study EGAS00001007296

• Single-cell RNA-seq of peripheral blood mononuclear cells in classic Hodgkin lymphoma

  Classic Hodgkin lymphoma (cHL) is a largely MHC class I-negative tumor with recurrent 9p24.1/ PD-L1/ PD-L2 copy gains and the highest reported response rates to PD-1 blockade. We utilized scRNA sequencing to characterize the peripheral immune response to PD-1 blockade and more broadly define non-CD8+ dependent mechanisms of immune evasion in cHL. Peripheral blood mononuclear cells were obtained from 20 patients with relapsed/refractory (R/R) cHL treated with PD-1 blockade (nivolumab) on the CheckMate 205 clinical trial (paired samples from cycle 1 day 1 [C1D1] and cycle 4 day 1 [C4D1]), 11 patients with newly diagnosed, previously untreated cHL and 13 healthy donors.

  Study EGAS00001007569

• RNA-seq study of human long-term and short-term hematopoietic stem cells from umblical cord blood with lentiviral overexpression of S1PR3

  To investigate the molecular and biological pathways altered by S1PR3OE in human hematopoietic stem cells (HSC), we performed RNA-sequencing (RNA-seq) of LT- and ST-HSC 3 days after transduction with control or S1PR3 overexpression (OE) lentiviral vectors. LT-HSC and ST-HSC from 3 pool of CB lin- were FACS-purified, cells were prestimulated for 4 hours and transduced with lentiviral vectors. At day 3, 2000-5300 BFP+ cells were FACS-purified for RNA isolation with a PicoPure kit. We were able to isolate only 1600-1800 BFP+ cells from LT-HSC control samples as opposed to 4000-5400 BFP+ cells from S1PR3OE samples. Thus, we pooled all control BFP+ LT-HSC cells into one sample for RNA-seq analysis. BFP- LT-HSC from control vector transduction were purified from CB1 as an additional LT-HSC control. Nextera libraries generated from 10 ng RNA from 5 LT-HSC samples (2 controls, 3 S1PR3OE) and 6 ST-HSC samples (3 controls, 3 S1PR3OE) were subjected to 125 bp, paired-end RNA-sequencing on the Illumina HiSeq 2500 with an average of 50 million reads/sample at the Center for Applied Genomics, Sick Kids Hospital.

  Dataset EGAD00001006582

• 33 patients with Monoclonal Gammopathy of Undetermined Significance (MGUS)

  Monoclonal gammopathy of undetermined significance (MGUS) is a premalignant precursor of multiple myeloma (MM) with a 1% risk of progression per year. Although targeted analyses have shown the presence of specific genetic abnormalities such as IGH translocations, RB1 deletion, 1q gain, hyperdiploidy or RAS genes mutations, little is known about molecular mechanism of malignant transformation. We have performed whole exome sequencing together with SNP array analysis in 33 flow-cytometry separated abnormal PC samples of MGUS patients to describe somatic gene mutations and chromosome changes at the genome-wide level. Non-synonymous mutations (NS-SNVs) and copy number alterations (CNAs) were present in 97.0% and in 63.6% of cases, respectively. Importantly, the number of somatic mutations was significantly lower in MGUS compared to MM (p<10-4) and we have identified 6 myeloma significantly mutated genes which are KRAS, NRAS, DIS3, HIST1H1E, EGR1 and LTB in the MGUS dataset. We also found a positive correlation with increasing chromosome changes and somatic mutations. IGH translocations were present in 27.3% of cases comprising t(4;14), t(11;14), t(14;16) or t(14;20) and were in a similar frequency to MM, which corresponded with primary lesion hypothesis. Data from this study showed MGUS is a genetically comprehensive disease, however overall genetic instability is significantly lower compared to MM.

  Dataset EGAD00001001901

• Paroxysmal Neurological Disorders 2

  We are sequencing the exomes of patients with paroxysmal neurological disorders mainly focusing on migraine and epilepsy. Cases are collected from performance sites of members of the International Headache Genetics consortium and EuroEPINOMICS. Most cases have a strong family history. The study sample will include both cases and controls.

  Dataset EGAD00001000407

• A study of the molecular pathogenesis of Splenic Marginal Zone and Diffuse Large B-Cell Lymphoma

  We will perform exome sequencing on selected cases of splenic marginal zone lymphoma (SMZL) and diffuse large B-cell lymphoma (DLBCL) in order to characterise their genetic makeup and identify biomarkers for prognosis and prediction of treatment response.

  Dataset EGAD00001000410

• Paroxysmal neurological Disorders

  We are sequencing the exomes of patients with paroxysmal neurological disorders mainly focusing on migraine and epilepsy. Cases are collected from performance sites of members of the International Headache Genetics consortium and EuroEPINOMICS. Most cases have a strong family history. The study sample will include both cases and controls.

  Dataset EGAD00001000412

• Investigation of mutational signatures associated with DNMT3A deficiency (2019-04-03)

  Mutational signatures have been shown to be attributable to specific genetic contexts, such as mutations in DNA repair genes. DNMT3A is a DNA methyltransferase that helps maintain the DNA methylation pattern in a site-specific manner and may participate in DNA repair or the stress response. We have identified an adult individual who is a germline mosaic for a DNMT3A mutation. We have obtained clonal lymphoblastoid cells (LCLs) from the subject representing both WT and mutant lines grown in the same individual for >50 years. These clones represent a unique opportunity to examine the mutational impact of the DNMT3A mutation in a well-controlled setting. Our goal is to perform WGS on whole blood, representing the pool, as well as several WT and several mutant clones, in order to investigate the contribution of DNMT3A to mutation rates and signatures. . This dataset contains all the data available for this study on 2019-04-03.

  Dataset EGAD00001004889

• Genome and transcriptome sequence data from a metastatic adenoid cystic carcinoma of the breast patient

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

  Dataset EGAD00001004921

• Genome and transcriptome sequence data from a squamous cell carcinoma of the alveolar ridge patient

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

  Dataset EGAD00001004934

• Extreme phenotypes define epigenetic and metabolic signatures in cardiovascular diseases

  Improving the understanding of cardiometabolic syndrome pathophysiology and its relationship with thrombosis are ongoing healthcare challenges. Using plasma biomarkers analysis coupled with the transcriptional and epigenetic characterisation of cell types involved in thrombosis, obtained from two extreme phenotype groups (obese and lipodystrophy) and comparing these to lean individuals and blood donors, the present study identifies the molecular mechanisms at play, highlighting patterns of abnormal activation in innate immune phagocytic cells and shows that extreme phenotype groups could be distinguished from lean individuals, and from each other, across all data layers. The characterisation of the same obese group, six months after bariatric surgery shows the loss of the patterns of abnormal activation of innate immune cells previously observed. However, rather than reverting to the gene expression landscape of lean individuals, this occurs via the establishment of novel gene expression landscapes. Netosis and its control mechanisms emerge amongst the pathways that show an improvement after surgical intervention. Taken together, by integrating across data layers, the observed molecular and metabolic differences form a disease signature that is able to discriminate, amongst the blood donors, those individuals with a higher likelihood of having cardiometabolic syndrome, even when not presenting with the classic features.

  Dataset EGAD00001005197

• Fetal origins of malignant germ cell tumours

  Germ cell tumours (GCTs) are a collection of benign and malignant neoplasms derived from primordial germ cells (PGCs). They are uniquely able to generate embryonic and extraembryonic tissues, which in malignant GCTs carries prognostic and therapeutic significance. The developmental pathways underpinning GCT initiation and histogenesis are incompletely understood. Here, we studied the phylogenetic and transcriptional diversity of 15 malignant gonadal GCTs and four normal testis biopsies by sequencing 131 whole genomes and 416 transcriptomes from 14 gonadal histologies, excised by laser capture microdissection. Our findings demonstrate that tumours were initiated by whole genome duplication likely in embryogenesis, within ~5-8 cell divisions post-PGC specification, followed by chromosome 12p gains associated with invasive disease. Of note, 12p imbalances were not only generated through GCT-typical isochromosomes, but also through non-isochromosomic configurations. Whilst tumours developed along homogenous phylogenetic pathways, they spawned manifold tissues independent of genetic subclonal diversification. A key feature of GCT tissues was the expression of fetal-specific genes. The transcriptional diversity notwithstanding, we found universal transcriptional elements correlated with hallmark 12p gains. Overall, our study reveals stereotyped phylogenies and transcriptomes underpinning the development of GCT that originate in fetal life and may lend themselves to therapeutic manipulation.

  Dataset EGAD00001007038

• Integrated single-cell profiling dissects cell-state-specific enhancer landscapes of human tumor infiltrating T cells.

  Despite extensive studies on the chromatin landscape of exhausted T cells, the transcriptional wiring underlying functional and dysfunctional states of human tumor infiltrating lymphocytes (TILs) is incompletely understood. Here, we identify tissue-specific and general gene-regulatory landscapes in the wide breadth of CD8+ TIL functional states covering four cancer entities using single-cell chromatin profiling. We map enhancer-promoter interactions in human TILs by integrating single-cell chromatin accessibility with single-cell RNA-seq data from tumor entity-matching samples and prioritize key elements by super enhancer analysis. Our analysis reveals a human core chromatin trajectory to TIL dysfunction and identifies key enhancers, transcriptional regulators, and deregulated target genes involved in this process. Finally, we validate enhancer regulation at loci encoding PD1, TCF1, and TIM3 by targeting non-coding regulatory elements with potent CRISPR activators and repressors. In summary, our study advances the understanding of molecular regulation of TIL (dys-)function and provides a framework for modulating immunotherapeutic relevant TIL genes via their enhancers.

  Dataset EGAD00001008662

• Targeted de novo phasing and long-range assembly by template mutagenesis

  Long-range sequencing with low error rate has been challenging. Sequence assembly and phasing usually require a high-quality reference genome for mapping, so working on highly-variable genomic regions or regions with no reference genome information would be difficult. In this study, we describe novel bench protocols and algorithms to obtain ultra-low-error-rate haplotype-phased sequence assemblies of regions 10 KB in length using a short-read sequencing platform that simultaneously solves the above two problems. We accomplish this by imprinting each template strand from a target region with a dense and unique mutation pattern. The mutation process randomly and independently converts ~50% of cytosines to uracils. Short-read sequencing libraries are made from both mutated and unmutated templates. A conservative de Bruijn graph approach seeds an assembly of the mutated templates, which we then extend by mapping paired-end reads. We next partition the template assemblies into two or more haplotypes after using the unmutated sequence library to recover almost all of the mutated bases. The final haplotype is assembled and corrected for residual template mutations and PCR errors. We obtain per-base-error rates below 10 9. We apply this method to a human family, correctly assembling and phasing three genomic intervals, including the highly polymorphic HLA-B gene.

  Dataset EGAD00001008444

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

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

  Dataset EGAD00001008925

• Genome and transcriptome sequence data from a lung adenocarcinoma patient

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

  Dataset EGAD00001008926

• Genome and transcriptome sequence data from a multiple myeloma patient

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

  Dataset EGAD00001008947

• Genome and transcriptome sequence data from a carcinoma of unknown primary patient

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

  Dataset EGAD00001008927

• Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient

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

  Dataset EGAD00001008928

• Genome and transcriptome sequence data from a hepatocellular carcinoma patient

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

  Dataset EGAD00001008929

• Genome and transcriptome sequence data from a adrenocortical carcinoma patient

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

  Dataset EGAD00001008930

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

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

  Dataset EGAD00001008931

• Genome and transcriptome sequence data from a mucosal melanoma patient

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

  Dataset EGAD00001008932

• Genome and transcriptome sequence data from a carcinoma of unknown primary patient

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

  Dataset EGAD00001008916

• Genome and transcriptome sequence data from a pancreatic acinar cell adenocarcinoma patient

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

  Dataset EGAD00001008934

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

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

  Dataset EGAD00001008915

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

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

  Dataset EGAD00001008914

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

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

  Dataset EGAD00001008913

• Genome and transcriptome sequence data from a metastatic synovial sarcoma patient

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

  Dataset EGAD00001008912

• Genome and transcriptome sequence data from a Ewing sarcoma patient

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

  Dataset EGAD00001008911

• Genome and transcriptome sequence data from a neuroendocrine tumor patient

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

  Dataset EGAD00001008910

• Genome and transcriptome sequence data from a colorectal cancer patient

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

  Dataset EGAD00001008909

• Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient

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

  Dataset EGAD00001008933

• Genome and transcriptome sequence data from a nasopharynx carcinoma patient

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

  Dataset EGAD00001008917

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

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

  Dataset EGAD00001008918

• Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient

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

  Dataset EGAD00001008919

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

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

  Dataset EGAD00001008920

• Genome and transcriptome sequence data from a endometrial carcinoma patient

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

  Dataset EGAD00001008921

• Genome and transcriptome sequence data from a intrahepatic cholangiocarcinoma patient

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

  Dataset EGAD00001008922

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

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

  Dataset EGAD00001008923

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

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

  Dataset EGAD00001008924

• Genome and transcriptome sequence data from a clear cell adenocarcinoma patient

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

  Dataset EGAD00001008940

• Genome and transcriptome sequence data from a paraganglioma patient

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

  Dataset EGAD00001008935

• Genome and transcriptome sequence data from a thoracic cancer patient

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

  Dataset EGAD00001008936

• Genome and transcriptome sequence data from a salivary gland carcinoma patient

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

  Dataset EGAD00001008937

• Genome and transcriptome sequence data from a lung adenocarcinoma patient

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

  Dataset EGAD00001008938

• Genome and transcriptome sequence data from a neuroendocrine tumor patient

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

  Dataset EGAD00001008939

• Genome and transcriptome sequence data from a cholangiocarcinoma patient

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

  Dataset EGAD00001008941

• Genome and transcriptome sequence data from a breast carcinoma patient

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

  Dataset EGAD00001008942

• Genome and transcriptome sequence data from a melanoma patient

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

  Dataset EGAD00001008943

• Genome and transcriptome sequence data from a hematopoietic or lymphoreticular systems myeloma-multiple patient

  Genome and transcriptome sequence data from a hematopoietic or lymphoreticular systems myeloma-multiple patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001008944

• Genome and transcriptome sequence data from a carcinoma of unknown primary patient

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

  Dataset EGAD00001008945

• Genome and transcriptome sequence data from a neuroendocrine carcinoma patient

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

  Dataset EGAD00001008946

• Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient

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

  Dataset EGAD00001008948

• Single-cell RNA-sequencing of CD19 Chimeric Antigen Receptor (CAR) T-cells (CD19 CAR T-cells) from a Phase I clinical study in paediatric ALL: CARPALL

  Chimeric antigen receptor (CAR)-modified T-cells have become established as an effective treatment of haematological cancers. In the context of relapsed and refractory childhood pre-B cell acute lymphoblastic leukaemia (B ALL), CD19 targeting CAR T-cells often induce durable remissions. Previously, we generated a novel low-affinity CAR incorporating a CD19-specific single-chain variable fragment (scFV) called CAT, displaying a faster off-rate of interaction than the FMC63 CD19 binder used in prior clinical studies. Here, we systematically analysed CD19 CAR T-cells of ten children with relapsed or refractory B ALL enrolled in the CARPALL trial (NCT02443831). To characterize persisting CD19 CAR T-cells, we performed high throughput single-cell gene expression and T-cell receptor (TCR) sequencing of infusion products and serial blood and bone marrow samples up to five years post-infusion. We isolated CAR T-cells from peripheral blood or bone marrow by flow cytometry for CD3 and CAR expression, prior to single cell sequencing (Chromium 10X) platform.

  Dataset EGAD00001010018

• Duplexseq of the interstrand crosslinks_WGS

  One of the most dangerous forms of DNA damage are interstrand crosslinks (ICLs), which covalently crosslink the two strands of the DNA double helix. The repair of these lesions is crucial for cellular survival due to their ability to block transcription and DNA replication. Initially, the major pathway that has been described in ICL repair involves a network of 22 genes that are mutated in a severe human genetic disease known as Fanconi Anemia (FA). Using synthetic lethality screens in the near-haploid human HAP1 cell line, we recently identified two potentially novel regulators of ICL repair, C1orf112 and THAP12. Loss of C1orf112 and THAP12 causes hypersensitivity to ICL-inducing DNA damaging agents, such as Mitomycin C (MMC). Additionally, C1orf112-depleted cells show elevated levels of micronuclei and accumulation of DNA damage in S-phase. To better understand how C1orf112 and THAP12 mediate the repair of ICLs, we want to perform mutational signature analysis, using the BotSeq method. Therefore, WT, C1orf112 and THAP12 knockout cells were cultured in vehicle or MMC treated conditions for 10 days and the genomic DNA was isolated. FANCA and FANCD2 knockout cells are taken along as controls in this experimental setting. . This dataset contains all the data available for this study on 2023-04-20.

  Dataset EGAD00001010298

• 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 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 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