3735 results for "*oma"

in 54.10 milliseconds.

• Melanoma post mortem analysis

  These are 21 metastatic melanoma exomes matched with 7 germlines from 7 multisite metastatic melanoma cases.

  Dataset EGAD00001005421

• Melanoma multi site metastases

  These are caveman, pindel, battenberg and brass calls for index patients' metastatic melanoma genomes within this study.

  Dataset EGAD00001005483

• Melanoma multi site metastases

  These are caveman, pindel and sequenza calls for the metastatic melanoma exomes within this study.

  Dataset EGAD00001005487

• MBD4 targeted sequencing in pool experiment

  Targeted sequencing of MBD4 of either tumor and germline DNA from Uveal Melanoma assembled by pool (germline pool or tumor pool).

  Dataset EGAD00001006989

• Whole genome bisulfite sequencing on 10 multiple myeloma cases

  Whole genome bisulfite sequencing on 10 multiple myeloma cases. Data quality control and adaptor-trimmed were performed with the Trimomatic tool. Paired-reads were mapped to the hg19 human reference with methylCtools aligner.

  Dataset EGAD00001007821

• Neuroblastoma sequencing data

  This dataset contains tumor and normal whole exome DNA sequence data for a patient with neuroblastoma

  Dataset EGAD00001008120

• MBD4 targeted sequencing

  We sequenced a gene of interest, MBD4, in both germline (n=1099) and tumor (n=192) sample from Uveal Melanoma patients.

  Study EGAS00001005012

• Whole genome bisulfite sequencing on 10 multiple myeloma cases

  Data quality control and adaptor-trimmed were performed with the Trimomatic tool. Paired-reads were mapped to the hg19 human reference with methylCtools aligner.

  Study EGAS00001004346

• Neuroblastoma sequencing data

  This study shares tumor and normal DNA for a patient with neuroblastoma

  Study EGAS00001005602

• Melanoma post mortem analysis

  This is the affymetrix gene expression data of the metastatic tumours related to this study.

  Dataset EGAD00010001717

• Integrated genomic, transcriptional and epigenomic analyses in germinal center-cell lymphomas link the mutation landscape with differential DNA methylation in Burkitt lymphoma

  Biologically and clinically diverse B-cell neoplasms, including Burkitt, follicular and diffuse large B-cell lymphoma, show features of germinal center (GC) B-cells. Here we present a comprehensive analysis of the epigenetic landscape of GC-B-cell lymphomas using whole genome bisulfite sequencing paired with genome and transcriptome sequencing from 29 primary tumor samples and four normal GC-B-cell samples. All lymphomas studied showed extensive genome-wide methylation losses as well as intragenic regions where DNA methylation levels were strongly correlated with expression of associated genes. Pathway analysis revealed that these intragenic regions were enriched in signaling networks differentially activated in Burkitt and follicular lymphomas and affected regulatory mechanisms deregulated by recurrent mutations in a large fraction of Burkitt lymphomas (including the ID3/TCF3 complex, the SWI/SNF remodeling complex and the inhibitory GI signaling pathway). Taken together, these results provide a global picture of Burkitt lymphoma pathomechanism and demonstrate a tight connection between epigenetic regulation and other levels of regulatory control in these tumors.

  Study EGAS00001001067

• HYPERMUTATION AND MALIGNANT PROGRESSION IN LOW-GRADE GLIOMA PATIENTS

  While patients with primary glioblastoma (GBM) have benefited from increased overall survival due to treatment with the alkylating chemotherapy temozolomide (TMZ), the benefit ofTMZ for patients with diffuse low-grade gliomas (LGG) remains unknown. To further explore the relationships among TMZ treatment, hypermutation and malignant progression, we studied tumor evolution in an expanded cohort of untreated and TMZ-treated patients by exome-sequencing of paired IDH1/2-mutant LGGs and their post-TMZ recurrences. Together, these findings further our understanding of the molecular features and clinical behavior of hypermutated clones.

  Study EGAS00001002368

• Whole genome sequencing of multiple myeloma identifies novel structural and non-coding mutations.

  The coding region of the myeloma genome is well understood with key mutations having been identified. However, the non-coding regions of the myeloma genome are yet to be analyzed. Here we have performed whole genome sequencing of myeloma patient samples to identify structural abnormalities including chromothripsis and chromoplexy, as well as gene dysregulation through super-enhancer juxtaposition with key oncogenes. We have also identified non-coding region hotspots of mutation, especially in promoter regions, that affect gene expression.

  Study EGAS00001003164

• RNA sequencing of multiple myeloma identifies genes dysregulated by structural variants.

  Multiple myeloma is a disease of structural changes brought about by copy number abnormalities and translocations. Many of these changes result in super-enhancers being placed next to key oncogenes. Here, we have investigated which genes are commonly dysregulated by these changes.

  Study EGAS00001003411

• noninvasive lung cancer subtyping

  Accurate diagnosis of lung cancer is important for treatment decision-making. Currently, the gold standard for diagnosing histological subtypes of lung cancer relies on tumor biopsies. Recently, liquid biopsy, particularly cell-free DNA (cfDNA), has shown promising results in cancer detection and classification. In this study, we investigated the potential of cfDNA methylome for the noninvasive classification of lung cancer histological subtypes. Specifically, we focused on the two most prevalent lung cancer subtypes, lung adenocarcinoma and lung squamous cell carcinoma. Using a fragment-based marker discovery approach, we identified robust subtype-specific methylation markers from tumor samples. These markers were successfully validated in independent cohorts and associated with subtype-specific transcription activity. Leveraging these markers, we constructed a subtype classification model using cfDNA methylation profiles, achieving an AUC of 0.808 in the cross-validation and an AUC of 0.747 in the independent validation. Additionally, tumor copy number variations inferred from cfDNA methylome analysis revealed potential implications for treatment selection. In summary, our study demonstrates the potential of cfDNA methylome analysis for noninvasively lung cancer subtyping, offering insights for cancer monitoring and early detection.

  Study EGAS00001007717

• Oesophageal adenocarcinoma RNAseq from LUD2015-005 study (NCT02735239, EudraCT 2015-005298-19)

  This dataset contains bulk transcriptomes from the inoperable cohorts of the LUD2015-005 study (NCT02735239, EudraCT 2015-005298-19). Transcriptomes were prepared from pre-treatment oesophageal tumour biopsies using a ribodepletion approach in order to assess both previously reported (e.g. PD-L1 expression) and novel predictive expression-based biomarkers for immunochemotherapy treatment in this setting. On-treatment and post-treatment biopsies were generated as well to characterize response to therapy, and samples were also prepared from paired normal GI tissues for a subset of patients. scRNA-seq based deconvolution was also applied to bulk transcriptomes in this study to estimate the cell composition of tumour biopsies and assess the link between the presence of specific cell types with immunochemotherapy outcomes.

  Dataset EGAD00001009399

• Oesophageal adenocarcinoma WGS from LUD2015-005 study (NCT02735239, EudraCT 2015-005298-19)

  This dataset contains whole genome sequencing (WGS) generated from the inoperable cohorts of the LUD2015-005 study (NCT02735239, EudraCT 2015-005298-19). WGS data were generated with the aim to assess previously reported (e.g. tumour mutational burden) and novel predictive genomic markers for immunochemotherapy treatment in this setting. Using these data, mutation and copy number profiles were generated for the LUD2015-005 study, which were assessed for correlation with patient outcomes from this trial.

  Dataset EGAD00001009400

• A Risk Score Incorporating Low Pass Whole Genome Sequencing of Cell Free DNA from Patients Receiving CD19 CAR T-Cell Therapy for Large B-Cell Lymphoma

  Study EGAS00001006308

• Low Pass Whole Genome Sequencing of Cell Free DNA from Patients Receiving CD19 CAR T-Cell Therapy for Large B-Cell Lymphoma

  Low Pass Whole Genome Sequencing of Cell Free DNA from Patients Receiving CD19 CAR T-Cell Therapy for Large B-Cell Lymphoma consisting of 123 samples with FASTQs with hg19 aligned BAM/BAI files.

  Dataset EGAD00001009175

• MD Anderson Lymphoma & Myeloma Data Access Committee

  Dac EGAC00001002706

• Machine learning guided signal enrichment for ultrasensitive plasma tumor burden monitoring

  In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole genome sequencing (WGS). We now introduce MRD-EDGE, a composite machine learning-guided WGS ctDNA single nucleotide variant (SNV) and copy number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGESNV uses deep learning and a ctDNA-specific feature space to increase SNV signal-to-noise enrichment in WGS by 300X compared to previous WGS error suppression. MRD-EDGECNV also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1 Gb to 200 Mb, thereby expanding its applicability to a wider range of solid tumors. We harness the improved performance to identify MRD following surgery in multiple cancer types, track changes in tumor burden in response to neoadjuvant immunotherapy in non-small cell lung cancer (NSCLC) and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal-to-noise enrichment in MRD-EDGESNV enables de novo mutation calling in melanoma and small cell lung cancer (SCLC) without matched tumor, yielding clinically informative TF monitoring for patients on immune checkpoint inhibition (ICI).

  Study EGAS00001007545

• Machine Learning Signal Enrichment for Ultrasensitive Plasma Tumor Burden Monitoring

  In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole genome sequencing (WGS). We now introduce MRD-EDGE, a composite machine learning-guided WGS ctDNA single nucleotide variant (SNV) and copy number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGESNV uses deep learning and a ctDNA-specific feature space to increase SNV signal-to-noise enrichment in WGS by 300X compared to previous WGS error suppression. MRD-EDGECNV also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1 Gb to 200 Mb, thereby expanding its applicability to a wider range of solid tumors. We harness the improved performance to identify MRD following surgery in multiple cancer types, track changes in tumor burden in response to neoadjuvant immunotherapy in non-small cell lung cancer (NSCLC) and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal-to-noise enrichment in MRD-EDGESNV enables de novo mutation calling in melanoma and small cell lung cancer (SCLC) without matched tumor, yielding clinically informative TF monitoring for patients on immune checkpoint inhibition (ICI).

  Study EGAS00001007451

• Biomarker Screen for Efficacy of Oncolytic Virotherapy in Patient-derived Pancreatic Cancer Cultures

  Pancreatic ductal adenocarcinoma (PDAC) is a tumour entity with unmet medical need. To assess the therapeutic potential of oncolytic virotherapy (OVT) against PDAC, different oncolytic viruses (OVs) are currently investigated in clinical trials. However, systematic comparisons of these different OVs in terms of efficacy against PDAC and biomarkers predicting therapeutic response are lacking. We screened fourteen patient-derived PDAC cultures for their sensitivity to five clinically relevant OVs, namely serotype 5 adenovirus Ad5-hTERT, herpes virus T-VEC, measles vaccine strain MV-NIS, reovirus jin-3, and protoparvovirus H 1PV using live cell analysis, quantification of viral genome/gene expression, cell viability as well as cytotoxicity assays. Sensitivity was correlated with transcriptome profiles to identify potential predictive biomarkers for response to OVT. Patient-derived PDAC cultures showed individual response patterns to OV treatment. Twelve of fourteen cultures were responsive to at least one OV, with no single OV proving superior or inferior across all cultures. Known host factors for distinct viruses were retrieved as potential biomarkers. Compared to the basal-like molecular subtype, the quasi-mesenchymal subtype of PDAC was more sensitive to H-1PV, jin-3, and T-VEC. Expression of viral entry receptors did not correlate with sensitivity to OV treatment. Rather, cellular pathways controlling immunological, metabolic, and proliferative signalling appeared to determine outcome. For instance, high baseline expression of interferon-stimulated genes (ISGs) correlated with relative resistance to oncolytic measles virus, whereas cGAS expression was associated with exceptional response. Combination treatment of MV-NIS with a cGAS inhibitor improved tumour cell killing in several PDAC cultures.

  Study EGAS00001007001

• ExomeSeq Neoantigen Immunogenicity Landscapes

  Immune checkpoint blockade (ICB) therapy is a cornerstone of oncologic treatment for patients with advanced stage non-small cell lung cancer (NSCLC) and other malignancies. Neoantigen immunoediting drives ICB efficacy, yet the fundamental physiochemical characteristics of neoantigens and how neoantigen immunogenicity shapes treatment response remains poorly understood. To help address these questions, a prospective clinical trial of NSCLC patients treated with nivolumab was conducted. We assessed genomic alterations in tumors from 58 patients and performed large-scale neoepitope immunogenicity analyses, before and during treatment (CheckMate153, CA209-153). Tumors were analyzed by whole-exome and transcriptome sequencing. In responding patients, loss of mutation and neoantigen burden early during therapy associated with clinical benefit. We evaluated the immunogenicity of 1,453 candidate neoantigens and identified 502 neopeptides that bound to MHC I and 196 neopeptides that were immunogenically recognized by T cells in the setting of nivolumab treatment. These T cell reactive neoantigens were differentially present in clonal populations that underwent distinctive evolutionary trajectories across responders and nonresponders. Mapping these neoantigens to tumor clonal dynamics and clinical response revealed strong selection against immunogenic neoantigen harboring clones compared to non-immunogenic clones. Using this large collection of neoantigens, we identified position specific amino acid features related to immunogenicity, which we used to develop and validate an immunogenicity score. Changes in the genomic and neoantigen immunogenicity landscapes were accompanied by temporal changes in the tumor microenvironment. Nivolumab-induced microenvironmental evolution in NSCLC shared some similarities with that in melanoma, yet critical differences in immunologic programs were apparent from comparative network analysis between tumor types. This study provides unprecedented molecular portraits of the neoantigen landscapes underlying nivolumab’s mechanism of action.

  Study EGAS00001007508

• RNASeq Neoantigen Immunogenicity Landscape

  Immune checkpoint blockade (ICB) therapy is a cornerstone of oncologic treatment for patients with advanced stage non-small cell lung cancer (NSCLC) and other malignancies. Neoantigen immunoediting drives ICB efficacy, yet the fundamental physiochemical characteristics of neoantigens and how neoantigen immunogenicity shapes treatment response remains poorly understood. To help address these questions, a prospective clinical trial of NSCLC patients treated with nivolumab was conducted. We assessed genomic alterations in tumors from 58 patients and performed large-scale neoepitope immunogenicity analyses, before and during treatment (CheckMate153, CA209-153). Tumors were analyzed by whole-exome and transcriptome sequencing. In responding patients, loss of mutation and neoantigen burden early during therapy associated with clinical benefit. We evaluated the immunogenicity of 1,453 candidate neoantigens and identified 502 neopeptides that bound to MHC I and 196 neopeptides that were immunogenically recognized by T cells in the setting of nivolumab treatment. These T cell reactive neoantigens were differentially present in clonal populations that underwent distinctive evolutionary trajectories across responders and nonresponders. Mapping these neoantigens to tumor clonal dynamics and clinical response revealed strong selection against immunogenic neoantigen harboring clones compared to non-immunogenic clones. Using this large collection of neoantigens, we identified position specific amino acid features related to immunogenicity, which we used to develop and validate an immunogenicity score. Changes in the genomic and neoantigen immunogenicity landscapes were accompanied by temporal changes in the tumor microenvironment. Nivolumab-induced microenvironmental evolution in NSCLC shared some similarities with that in melanoma, yet critical differences in immunologic programs were apparent from comparative network analysis between tumor types. This study provides unprecedented molecular portraits of the neoantigen landscapes underlying nivolumab’s mechanism of action.

  Study EGAS00001007509

• Exploring the driver events of eccrine poromas and porocarcinomas: A retrospective, cross-institutional study of 90 cases

  Eccrine poroma (EP) and porocarcinoma (EPC) are rare benign and malignant adnexal neoplasms of the terminal sweat gland duct, respectively. Both can arise de novo, however, EPCs can also arise from a pre-existing EP. To-date, genetic investigation of these tumors has involved studies with small sample sizes and/or limited analyses. To comprehensively compare the driver events and mutational landscape of these tumors, we performed a retrospective multi-institutional whole-exome sequencing and RNA sequencing study on the largest cohort of EPs and EPCs to-date (n=90). We uncovered novel events and delineated different pathways of tumorigenesis underlying these tumors, with EPs driven largely by fusion genes, and EPCs driven largely by somatic mutations, with rare YAP1 and frequent PAK gene novel fusions.

  Dataset EGAD00001015376

• Exploring the driver events of eccrine poromas and porocarcinomas: A retrospective, cross-institutional study of 90 cases

  Eccrine poroma (EP) and porocarcinoma (EPC) are rare benign and malignant adnexal neoplasms of the terminal sweat gland duct, respectively. Both can arise de novo, however, EPCs can also arise from a pre-existing EP. To-date, genetic investigation of these tumors has involved studies with small sample sizes and/or limited analyses. To comprehensively compare the driver events and mutational landscape of these tumors, we performed a retrospective multi-institutional whole-exome sequencing and RNA sequencing study on the largest cohort of EPs and EPCs to-date (n=90). We uncovered novel events and delineated different pathways of tumorigenesis underlying these tumors, with EPs driven largely by fusion genes, and EPCs driven largely by somatic mutations, with rare YAP1 and frequent PAK gene novel fusions.

  Dataset EGAD00001015377

• Exploring the driver events of eccrine poromas and porocarcinomas: A retrospective, cross-institutional study of 90 cases

  Eccrine poroma (EP) and porocarcinoma (EPC) are rare benign and malignant adnexal neoplasms of the terminal sweat gland duct, respectively. Both can arise de novo, however, EPCs can also arise from a pre-existing EP. To-date, genetic investigation of these tumors has involved studies with small sample sizes and/or limited analyses. To comprehensively compare the driver events and mutational landscape of these tumors, we performed a retrospective multi-institutional whole-exome sequencing and RNA sequencing study on the largest cohort of EPs and EPCs to-date (n=90). We uncovered novel events and delineated different pathways of tumorigenesis underlying these tumors, with EPs driven largely by fusion genes, and EPCs driven largely by somatic mutations, with rare YAP1 and frequent PAK gene novel fusions.

  Dataset EGAD00001015378

• Exploring the driver events of eccrine poromas and porocarcinomas: A retrospective, cross-institutional study of 90 cases

  Eccrine poroma (EP) and porocarcinoma (EPC) are rare benign and malignant adnexal neoplasms of the terminal sweat gland duct, respectively. Both can arise de novo, however, EPCs can also arise from a pre-existing EP. To-date, genetic investigation of these tumors has involved studies with small sample sizes and/or limited analyses. To comprehensively compare the driver events and mutational landscape of these tumors, we performed a retrospective multi-institutional whole-exome sequencing and RNA sequencing study on the largest cohort of EPs and EPCs to-date (n=90). We uncovered novel events and delineated different pathways of tumorigenesis underlying these tumors, with EPs driven largely by fusion genes, and EPCs driven largely by somatic mutations, with rare YAP1 and frequent PAK gene novel fusions.

  Dataset EGAD00001015379

• Pediatric Low-Grade Glioma RNA and Targeted Sequencing

  Pediatric low-grade gliomas (pLGG) are frequently driven by genetic alterations in the RAS/MAPK pathway yet show unexplained variability in their clinical outcome. To address this, we characterized a cohort of >1,000 clinically annotated pLGG. 84% of cases harbored a driver alteration, while those without an identified alteration also often exhibited up-regulation of the RAS/MAPK pathway. pLGG could be broadly classified based on their alteration type. Rearrangement-driven tumors were diagnosed at a younger age, enriched for WHO grade I histology, infrequently progressed, and rarely resulted in death as compared to SNV-driven tumors. Further sub-classification of clinical-molecular correlates stratified pLGG into risk categories. These data highlight the biological and clinical differences between pLGG subtypes and opens avenues for future treatment refinement.

  Study EGAS00001004242

• DIPG RNA and exome sequencing

  DIPG is a paediatric high-grade glioma that diffusely infiltrates the brainstem and is the leading cause of paediatric brain tumour death. Here we performed RNA and whole exome sequencing on DIPG and control samples to analyse transcriptomic and genetic alterations associated with this devastating disease, and to understand the relationship between them.

  Study EGAS00001004749

• Alternative lengthening of telomeres in childhood neuroblastoma from genome to proteome

  Telomere maintenance by telomerase activation or alternative lengthening of telomeres (ALT) is a major determinant of poor outcome in neuroblastoma. Here, we screen for ALT in primary and relapsed neuroblastomas and characterize its features using multi-omics profiling. We aim to deepen the knowledge about the biology and clinical features of ALT-positive neuroblastomas by enriching ALT tumors in the study cohort independent of ATRX mutation status. Using a combination of genomic, transcriptomic and proteomic profiling, we provide evidence that this subgroup is clinically and molecularly distinct.

  Study EGAS00001004349

• IDH mutant Glioma methylation analysis and prognostic signatures

  Study EGAS00001006961

• Pediatric HGG WES and RNA-Seq

  Paediatric high-grade glioma (pHGG) is the leading cause of paediatric brain tumour death. Here we performed RNA and whole exome sequencing on pHGG samples to analyse transcriptomic and genetic alterations associated with this devastating disease, and to understand the relationship between them.

  Study EGAS00001005687

• Shot-gun stool metagenomics and colorectal cancer risk.

  This study aims to identify metagenomics biomarkers in colorectal cancer (CRC). The study includes 156 samples of shot-gun stool metagenomics, corresponding to 51 patients with CRC, 54 patients with high-risk adenoma, and 51 healthy controls. The sequencing libraries were prepared with 2 µg of total DNA using the Nextera XT DN Sample Prep Kit (Illumina, San Diego, CA, USA). Sequencing was performed at 150 nucleotides, paired-end, using an Illumina HiSeq 4000 platform.

  Study EGAS00001007025

• Multiple Myeloma follow-up sequencing study

  A total of 40 Multiple Myeloma (MM) patients at clinical relapse who progressed during Proteasome Inhibitors (PIs) or Immunomodulating Drugs (IMiDs)-based therapies and who are assigned to antiCD38-based salvage treatments, will be enrolled. We will collect bone marrow (BM) and peripheral blood (PB) samples from patients at specific timepoints: baseline (BM, PB and buccal swab) every 3 month (PB) achievement of response (≥ Very Good Partial Response (VGPR)) (BM and PB) relapse or refractory status to antiCD38-based treatments (BM and PB) Samples will be processed and stored in the "Hematological Laboratory" located in the University of Turin (Italy) for various proposed analyses: at specific time-points CD138+ (Plasma Cells-PCs) awill be immunomagnetically enriched from the BM mononuclear cells and frozen as viable cells in dimethyl sulfoxide (DMSO); PB mononuclear cells (PBMCs) will be isolated from whole blood by density-gradient centrifugation, and frozen as above; plasma fraction from PB and BM will be obtained by centrifugation and stored frozen; Neutrophils will be obtained at the time of enrollment as a source of control germline DNA and stored frozen.

  Study EGAS00001007092

• Histological Transformation and Progression in Follicular Lymphoma: a Clonal Evolution Study

  Background: Follicular lymphoma (FL) is an indolent, yet incurable B-cell malignancy. A subset of patients experience increased mortality rate driven by two distinct clinical end points: histological transformation and early progression after immuno-chemotherapy. The nature of tumor clonal dynamics leading to these clinical endpoints is poorly understood and previously determined genetic alterations do not explain the majority of transformed cases or accurately predict early progressive disease. We contend that detailed knowledge of the expansion patterns of specific cell populations plus their associated mutations would provide insight into therapeutic strategies and disease biology over the timecourse of FL clinical histories. Methods and Findings: Using a combination of whole genome sequencing, targeted deep sequencing and digital droplet PCR on matched diagnostic and relapse specimens, we deciphered the constituent clonal populations in n=15 transformation patients and n=6 progressors, and measured their change in abundance over time. We observed widely divergent patterns of clonal dynamics in transformed cases relative to progressed cases. Transformation specimens were generally composed of clones that were rare or absent in diagnostic specimens, consistent with dramatic clonal expansions that came to dominate the transformation specimen. This pattern was independent of time to transformation and treatment modality. By contrast, progression specimens were composed of clones that were already present in the diagnostic specimens and exhibited only moderate clonal dynamics, even in the presence of immuno-chemotherapy. Analysis of somatic mutations impacting 94 genes was undertaken in a validation cohort consisting of 395 samples from 277 patients in order to decipher disrupted biology in the two clinical endpoints. We found 12 genes were more commonly mutated in transformed samples than in preceding FL, including TP53, B2M, CCND3, GNA13, S1PR2 and P2RY8. Moreover, 10 genes were more commonly mutated in diagnostic specimens of early progressors including TP53, BTG1, MKI67 and XBP1. Conclusions: Our results illuminate contrasting modes of evolution shaping the clinical histories of transformation and progression. They have implication for interpretation of evolutionary dynamics in the context of treatment-induced selective pressures, and indicate that transformation and progression will require different clinical management strategies.

  Study EGAS00001001709

• SPECIAL: Dissecting the melanoma ecosystem one cell at the time during immunotherapy

  The aim of this study was to identify potential biomarkers of response to immunotherapy (anti-PD1-based) as well as gain understanding of the biological mechanism of therapy resistance (either intrinsic or acquired) in melanoma patients. Single cell RNA sequencing was performed from pre- and on-treatment (2-3 weeks after immunotherapy) metastatic biopsies from stage III and IV melanoma patients.

  Study EGAS00001006488

• RNA sequencing of in vitro generated suppressive myeloid cells using parental and Sialidase expressing A549 cancer cell lines

  Fresh peripheral blood mononuclear cells of four human donors were cultured together with either lung adenocarcinoma A549 cancer cells or A549-expressing H1N1 Sialidase cancer cells. These treatments induced the differentiation of donor cells into immunosuppressive MDSC-like cells, which were further subjected to bulk RNA sequencing. RNA-seq TruSeq libraries were generated from polyA-enriched mRNA isolated from the samples, and sequenced in paired-end mode on 4 lanes of an Illumina NextSeq 500 flow-cell

  Dataset EGAD00001012437

• ISA Nutrition 2015

  Comprehensive data on lifestyle-related modifiable factors, sociodemographic, anthropometric, economic, biochemical, and genetic markers related to the occurrence of cardiometabolic diseases as part of the observational cross-sectional survey (2015 Health Survey of Sao Paulo with Focus on Nutrition (2015 ISA-Nutrition), a population-based study. Data of 805218 SNPs for 841 individuals was genotyped using the Axioma 2.0 Precision Medicine Research Array in the Thermo Fisher Scientific laboratory (Affymetrix Inc, Santa Clara, CA).

  Dataset EGAD00010002678

• MutWP1__CRUK_Grand_Challenge_Mutographs_of_Cancer__head___neck

  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, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute. Non-tumour DNA is also studied for some cancer types. Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors 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 EGAS00001005450

• Leeds Melanoma Cohort (LMC) gene expression study

  Array-based profiling (whole genome DASL HT12.4, Illumina Inc) in over 700 FFPE tumour blocks from the population-based Leeds Melanoma cohort recruited in the North of England, with a long follow up. Data used in tumour immune micro-environment investigation (Nsengimana et al 2018, J Clin Invest doi: 10.1172/JCI95351).

  Study EGAS00001002922

• Whole genome sequencing of patients with or at risk for HCC

  Liver cancer is a major cause of cancer mortality worldwide. Screening individuals at high risk, including those with cirrhosis and viral hepatitis, provides an avenue for improved survival, but current screening methods are inadequate. In this study, we used whole-genome cell-free DNA (cfDNA) fragmentome analyses to evaluate 724 individuals from the United States, the European Union, or Hong Kong with hepatocellular carcinoma (HCC) or who were at average or high-risk for HCC. Using a machine learning model that incorporated multifeature fragmentome data, the sensitivity for detecting cancer was 88% in an average-risk population at 98% specificity and 85% among high-risk individuals at 80% specificity. We validated these results in an independent population. cfDNA fragmentation changes reflected genomic and chromatin changes in liver cancer, including from transcription factor binding sites. These findings provide a biological basis for changes in cfDNA fragmentation in patients with liver cancer and provide an accessible approach for noninvasive cancer detection.

  Study EGAS00001007249

• Stratifying and Targeting Pediatric Medulloblastoma through Genomics

  In this project, genomic analyses of pediatric medulloblastoma samples, obtained through the international medulloblastoma consortium, will be performed. RNA and miRNA expression profiles of 1000 samples, representing all four subgroups (Wnt, Shh, Group C, and D), will be studied to identify novel subtypes within each subgroup. The resulting subtype-specific expression profiles will support the development of reliable and robust biomarkers to more accurately and reliably classify medulloblastomas for treatment in clinical trials. For that purpose, two assays will be developed: an antibody-based immunohistochemical assay and an orthogonal nucleic acid-based hybridization assay. Additional genomic DNA analysis of the 300 high risk subgroup cases will support the discovery of subgroup specific somatic mutations in order to inform current clinical trials of targeted therapies, and to identify genes and pathways already targeted in other diseases. Such therapies could be rapidly transitioned to Phase II trials in medulloblastoma. Furthermore, the discovery of somatic mutations could be used for developing as well as validating specific biomarkers. The project team will also try to identify risk factors that predispose children to this type of cancer.

  Study EGAS00001000273

• Failure of Differentiation of the Rhombic Lip Constitutes Medulloblastoma

  We used single-cell transcriptomics to study cells from the developing human cerebellum, and show that different molecular subgroups of medulloblastoma resemble distinct glutamatergic progenitors.

  Study EGAS00001005826

• Molecular profiling of acinar cell carcinoma of the salivary glands

  Samples of acinar cell carcinoma (AciCC) of the salivary glands and paired normal salivary gland tissue were analyzed by whole transcriptome RNA-seq (n=10), whole genome sequencing (n=6), whole genome bisulfite sequencing (n=3) and ChIP-seq (H3K27ac, H3K4me3, H3K27me3, NR4A3, CTCF).

  Study EGAS00001002795

• Comprehensive molecular profiling identifies novel genetic drivers and subtypes underlying medulloblastoma

  Current therapies for medulloblastoma (MB), a highly malignant childhood brain tumor, impose debilitating effects on the developing child, warranting the development of molecularly targeted treatments with reduced toxicities. Prior studies have failed to disclose the full spectrum of driver genes and molecular processes operative in MB or adequately explain heterogeneity among molecular subgroups. Herein, we detail the somatic landscape across 491 sequenced MBs and molecular heterogeneity amongst 1,256 epigenetically analyzed cases, identifying subgroup-specific mutational signatures, driver genes, and pathway alterations including previously unappreciated actionable therapeutic targets. Integrative approaches for assigning driver genes to subgroups explained >65-70% of Group 3 and Group 4, doubling previous knowledge. Novel subtypes underlying Group 3 and Group 4 were differentially enriched for specific driver events, including hotspot in-frame indels targeting KBTBD4 and ‘enhancer hijacking’ driving activation of PRDM6. Thus, application of integrative genomics to an unprecedented cohort of clinical samples derived from a single childhood cancer entity has disclosed a series of new cancer genes and biologically relevant subtype diversity that represent attractive therapeutic targets for treating MB.

  Study EGAS00001001953

• Molecular Profiling Reveals Unique Immune and Metabolic Features of Melanoma Brain Metastases

  There is a critical need to improve our understanding of the pathogenesis of -melanoma brain metastases (MBM). Thus, we performed RNA sequencing on 88 resected MBMs and 42 patient-matched extracranial metastases; tumors with sufficient tissue also underwent whole-exome sequencing, T-cell receptor sequencing, and IHC. MBMs demonstrated heterogeneity of immune infiltrates that correlated with prior radiation and post-craniotomy survival. Comparison with patient-matched extracranial metastases identified significant immunosuppression and enrichment of oxidative phosphorylation (OXPHOS) in MBMs. Gene-expression analysis of intracranial and subcutaneous xenografts, and a spontaneous MBM model, confirmed increased OXPHOS gene expression in MBMs, which was also detected by direct metabolite profiling and [U-13C]-glucose tracing in vivo IACS-010759, an OXPHOS inhibitor currently in early-phase clinical trials, improved survival of mice bearing MAPK inhibitor-resistant intracranial melanoma xenografts and inhibited MBM formation in the spontaneous MBM model. The results provide new insights into the pathogenesis and therapeutic resistance of MBMs.

  Study EGAS00001003672

• Single-cell analysis for metastatic gastric adenocarcinoma

  Intra-tumoral heterogeneity (ITH) is the fundamental property of cancer, however, the origins of ITH remain poorly understood. Here we performed single-cell RNA sequencing of peritoneal carcinomatosis (PC) from patients with advanced gastric adenocarcinoma (GAC), constructed a transcriptome map of 45,048 PC cells, profiled the transcriptome states of diverse tumor cell lineages and types, incisively explored ITH of PC tumor cells, and identified significant correlates with patient survival.

  Study EGAS00001004443

• Telomerase activation by genomic rearrangements in high-risk neuroblastoma

  Neuroblastoma is a malignant pediatric tumor of the sympathetic nervous system1. Roughly half of these tumors regress spontaneously or are cured by limited therapy. By contrast, high-risk neuroblastomas have an unfavorable clinical course despite intensive multimodal treatment, and their molecular basis has remained largely elusive2-4. We have performed whole-genome sequencing of 56 neuroblastomas (high-risk, n=39; low-risk, n=17) and discovered recurrent genomic rearrangements affecting a chromosomal region (5p15.22) proximal of the telomerase reverse transcriptase gene (TERT). These rearrangements occurred only in high-risk neuroblastomas (12/39, 31%) in mutually exclusive fashion with MYCN amplifications and ATRX mutations, which are known genetic events in this tumor type1,2,5. In an extended case series (n=217), TERT rearrangements defined a subgroup of high-risk tumors with particularly poor outcome. Despite the large diversity of these rearrangements, they all induced massive transcriptional upregulation of TERT. In the remaining high-risk tumors, TERT expression was also elevated in MYCN-amplified tumors, whereas alternative lengthening of telomeres was present in neuroblastomas without TERT or MYCN alterations, suggesting that telomere lengthening represents a central mechanism defining this subtype. The 5p15.22 rearrangements juxtapose the TERT coding sequence to strong enhancer elements, resulting in massive chromatin remodeling and DNA methylation of the affected region. Supporting a functional role of TERT, neuroblastoma cells bearing rearrangements or amplified MYCN exhibited both upregulated TERT expression and enzymatic telomerase activity. In summary, our findings show that remodeling of the genomic context abrogates transcriptional silencing of TERT in high-risk neuroblastoma and places telomerase activation in the center of transformation in a large fraction of these tumors.

  Study EGAS00001001308

• Whole genome and whole exome sequencing of serial biopsies of relapsed/refractory diffuse large B-cell lymphoma.

  Purpose: Diffuse large B-cell lymphoma (DLBCL) is cured in more than 60% of patients, but outcomes remain poor for patients experiencing disease progression or relapse (refractory or relapsed DLBCL [rrDLBCL]), particularly if these events occur early. Although previous studies examining cohorts of rrDLBCL have identified features that are enriched at relapse, few have directly compared serial biopsies to uncover biological and evolutionary dynamics driving rrDLBCL. Here, we sought to confirm the relationship between relapse timing and outcomes after second-line (immuno)chemotherapy and determine the evolutionary dynamics that underpin that relationship. Patients and methods: Outcomes were examined in a population-based cohort of 221 patients with DLBCL who experienced progression/relapse after frontline treatment and were treated with second-line (immuno)chemotherapy with an intention-to-treat with autologous stem-cell transplantation (ASCT). Serial DLBCL biopsies from a partially overlapping cohort of 129 patients underwent molecular characterization, including whole-genome or whole-exome sequencing in 73 patients. Results: Outcomes to second-line therapy and ASCT are superior for late relapse (>2 years postdiagnosis) versus primary refractory (<9 months) or early relapse (9-24 months). Diagnostic and relapse biopsies were mostly concordant for cell-of-origin classification and genetics-based subgroup. Despite this concordance, the number of mutations exclusive to each biopsy increased with time since diagnosis, and late relapses shared few mutations with their diagnostic counterpart, demonstrating a branching evolution pattern. In patients with highly divergent tumors, many of the same genes acquired new mutations independently in each tumor, suggesting that the earliest mutations in a shared precursor cell constrain tumor evolution toward the same genetics-based subgroups at both diagnosis and relapse. Conclusion: These results suggest that late relapses commonly represent genetically distinct and chemotherapy-naïve disease and have implications for optimal patient management.

  Study EGAS00001007053

• Whole genome sequencing and somatic mutation profiles and whole genome transcription files of pediatric medulloblastoma

  Fastq, Mutect (SNVs), Platypus (indels), and InfoGenomeR (SVs and CNAs) calls from whole genome sequencing data and fastq files of whole genome transcription data of five patients with pediatric medulloblastoma.

  Dataset EGAD00001009507

• Spatiotemporal evolution and inter-patient heterogeneity in primary and recurrent/metastatic head and neck squamous cell carcinoma

  Head and neck cancer squamous cell carcinomas (HNSCCs) are heterogeneous in terms of origin and aetiology. In addition, there is uncertainty about the spatiotemporal genetic evolution from initial diagnosis to recurrence/metastasis (R/M) after primary treatments and further disease progression following systemic treatment. Changes in the genetic profile have implications on the selection of appropriate treatments for patients, especially in the era of targeted therapies and immunotherapies. Here, we analysed a cohort of 11 HNSCC patients with metachronous R/M, among whom nine had paired primary and R/M samples suitable for next-generation sequencing (multiple R/M samples collected at different time points were available for some of the patients). At the genomic level, the R/M samples shared a fraction of the somatic single nucleotide variants (SNVs) with the index primary tumours, but they also acquired many additional mutations, while losing only a few others. A similar behaviour was also observed when examining the changes of mutational signatures between primary and R/M samples. Overall, R/M appeared thus more genetically diverse than the respective primary tumours. The transcriptomic analysis showed that R/M samples had lower immune cell infiltration and several genes related to immune response were significantly downregulated compared to the primary samples. Our results underline the importance of analysing multiple samples per patient to obtain a more complete picture of the patient’s tumour and advocates a re-biopsy in the event of R/M and treatment failure, in order to select the most appropriate therapeutic strategy.

  Study EGAS00001007464

• H3.3G34R/V-transformed interneuron progenitors co-opt PDGFRA for gliomagenesis

  Histone H3.3 glycine 34 to arginine/valine (H3.3G34R/V) mutations occur in deadly hemispheric high-grade gliomas. These tumors show exquisite regional and temporal specificity, suggesting a developmental context permissive to the effects of G34R/V mutations. Here we present the molecular landscape of G34R/V gliomas (n=85) and show that 50% bear activating mutations in PDGFRA, with strong selection pressure for PDGFRAMUT clones at recurrence. We show that G34R/V tumors arise in interneuron progenitors of the foetal ventral forebrain expressing GSX2 and the DLX family of homeobox transcription factors, where terminal neuronal differentiation is impaired through aberrant G34R/V-mediated H3K27me3. Frequent co-occurrence of G34R/V & PDGFRAMUT is facilitated in this interneuron lineage-of-origin as PDGFRA forms an aberrant chromatin loop with the adjacent GSX2, hijacking its active chromatin conformation. At the single-cell level, G34R/V tumours entirely lack oligodendroglial transcriptional programs prominent in other glioma entities, and instead harbour dual neuronal and astroglial compartments. CRISPR-removal of H3.3G34R/V does not impact tumorigenicity suggesting this mutation becomes dispensable, while PDGFRAMUT are potently oncogenic regardless of G34 mutation. Collectively, our results suggest that G34R/V gliomas arise in foetal interneuron progenitors unable to undergo terminal differentiation, enabling co-option of PDGFRA through inappropriate expression and activating mutations to promote gliogenesis and oncogenicity. Reliance on PDGFRA for oncogenesis may be of therapeutic opportunity in G34R/V glioma.

  Study EGAS00001004301

• NanoString Cancer

  RCC files of 17 Cartridges from metastatic melanoma

  Dataset EGAD00010002432

• 3D-GSC_expression_profiles

  In this study, we used RNA-sequencing gene expression profiling in order to characterize specific phenotypic traits in DIPG-derived glioma stem cell (GSC) models. Twenty-two primary GSC models derived from biopsies collected at diagnosis were cultured in an ECM-mimicking compound before for RNA extraction and subsequent rRNA-depletion and sequencing .

  Study EGAS00001007182

• 3D-GSC_expression_profiles

  In this study, we used RNA-sequencing gene expression profiling in order to characterize specific phenotypic traits in DIPG-derived glioma stem cell (GSC) models. Twenty-two primary GSC models derived from biopsies collected at diagnosis were cultured in an ECM-mimicking compound before for RNA extraction and subsequent rRNA-depletion and sequencing .

  Dataset EGAD00001011079

• Genomic characterization of hepatocellular carcinoma in Hispanic patients

  The genomic DNA was extracted from paired tumor and adjacent non-tumor samples of 27 Hispanic HCC patients. The TruSeq Rapid Exome Library Prep kit (Illumina, CA) was used to capture the coding regions of the human genome. The 100 bp paired-end sequencing of every 6-plex whole exome library pool was performed on an Illumina HiSeq 3000 system according to the manufacturer’s recommended protocol to achieve an average coverage of ~100X. The paired-end reads were aligned to the human reference genome (hg19) with decoy sequences (as used in the 1000 Genomes Project) using BWA software. The duplicate reads were marked and removed using Picard and SAMtools, respectively. Local realignment around insertions/deletions (indels) and base quality recalibration were performed using GATK.

  Study EGAS00001007431

• Whole exome sequencing data of Hispanic hepatocellular carcinoma

  The paired-end reads were aligned to the human reference genome (hg19) with decoy sequences (as used in the 1000 Genomes Project) using BWA (v0.7.5a) software. The duplicate reads were marked and subsequently removed using Picard (v1.140) (https://broadinstitute.github.io/picard/) and SAMtools (v0.1.19), respectively. Local realignment around insertions/deletions (indels) and base quality recalibration were performed using GATK (v3.6).

  Dataset EGAD00001011158

• Chromatin landscape of medulloblastoma reveals context dependent driver

  In this study, we defined subgroup specific chromatin landscape (H3K27ac, H3K27me3, RNA-Seq, 27ac hichip, WGS) of medulloblastoma to identify pathogenic epigenetic alterations that regulate expression of a context dependent driver gene.

  Study EGAS00001006741

• H3K27ac/H3K27me3 landscape of medulloblastoma

  We profiled 111 patient medulloblastoma primary tumor samples by bulk RNA-seq (19 samples), 27ac (98 samples) / 27me3 (61 samples) ChIP-Seq, WGS (4 samples) and 27ac hichip (8 samples). Submitted data consists of data generated from previously unpublished tumors as well as complementary data for data sets already published for identical medulloblastoma tumors (ex: 27me3 ChIP-Seq and RNA-Seq data submitted for a tumor with publicly available WGS data). The raw fastqs and hg19 aligned RNA-Seq bams are provided.

  Dataset EGAD00001009709

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

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

  Dataset EGAD00001015403

• Targetable NOTCH1 rearrangements in reninoma - WGS

  Reninomas are exceedingly rare renin-secreting kidney tumours that derive from juxtaglomerular cells, specialised smooth muscle cells that reside at the vascular inlet of glomeruli. They are the central component of the juxtaglomerular apparatus which controls systemic blood pressure through the secretion of renin. We assessed somatic changes in reninoma and found structural variants that generate canonical activating rearrangements of NOTCH1, whilst removing its negative regulator, NRARP. Accordingly, in single reninoma nuclei we observed excessive renin and NOTCH1 signalling mRNAs, with a concomitant non-excess of NRARP expression. Re-analysis of previously published reninoma bulk transcriptomes further corroborates our observation of dysregulated Notch pathway signalling in reninoma. Our findings reveal NOTCH1 rearrangements in reninoma, therapeutically targetable through existing NOTCH1 inhibitors, and indicate that unscheduled Notch signalling may be a disease-defining feature of reninoma.

  Dataset EGAD00001010888

• Sebaceous carcinoma tumor/normal exome sequencing and transcriptome sequencing. Transcriptome sequencing of

  Sebaceous carcinomas (SeC) are cutaneous malignancies that, in rare cases, metastasize and prove fatal. Here we report whole exome sequencing on 32 SeC, revealing distinct mutational classes that explain both cancer ontogeny and clinical course. A UV-damage signature predominated 10/32 samples, while 9 were instead defined by microsatellite instability (MSI) mutations. UV-damage SeC exhibited poorly differentiated, infiltrative histopathologycompared to MSI signature SeC (p = 0.003), features previously associated with dissemination. Strikingly, UV-damage SeC transcriptomes and anatomic distributionclosely resembling those of cutaneous squamous cell carcinomas (SCC), implicating sun-exposed keratinocytes as a cell of origin. Like SCC, this UV-damage subclass harbors a high somatic mutation burden with >50 mutations/Mb, predicting immunotherapeutic response. In contrast, ocular SeC acquire far fewer mutations without a dominant signature, but show frequent truncating mutations in the ZNF750 epidermal differentiation regulator. Our data exemplify how different mutational processes convergently drive histopathologically related but clinically distinct cancers.

  Dataset EGAD00001004016

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

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

  Dataset EGAD00001015413

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

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

  Dataset EGAD00001015414

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

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

  Dataset EGAD00001002985

• Genome and transcriptome sequence data from a leiomyosarcoma patient

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

  Dataset EGAD00001002996

• Genome and transcriptome sequence data from a metastatic uterine leiomyosarcoma patient

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

  Dataset EGAD00001003010

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

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

  Dataset EGAD00001003023

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

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

  Dataset EGAD00001003642

• 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 EGAD00001003684

• Genome and transcriptome sequence data from a thymic carcinoma patient

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

  Dataset EGAD00001003700

• Genome and transcriptome sequence data from a metastatic myoepithelial carcinoma of parotid patient

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

  Dataset EGAD00001003701

• 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 melanoma patient

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

  Dataset EGAD00001004599

• 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 EGAD00001004602

• Genome and transcriptome sequence data from a metastatic squamous cell carcinoma of the cervix patient

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

  Dataset EGAD00001004616

• 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 uveal melanoma patient

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

  Dataset EGAD00001004647

• 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 EGAD00001004671

• Genome and transcriptome sequence data from a metastatic high-grade adenocarcinoma of the fallopian tubes patient

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

  Dataset EGAD00001004709

• Genome and transcriptome sequence data from a peritoneal mesothelioma patient

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

  Dataset EGAD00001001310

• Genome and transcriptome sequence data from a colorectal adenocarcinoma patient (Response to Angiotensin Blockade with Irbesartan in a Patient with Metastatic Colorectal Cancer)

  Genome and transcriptome sequence data from a colorectal adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study. These data are included in the manuscript entitled, "Response to Angiotensin Blockade with Irbesartan in a Patient with Metastatic Colorectal Cancer".

  Dataset EGAD00001001876

• Genome and transcriptome sequence data from an adrenal cortical carcinoma patient

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

  Dataset EGAD00001002049

• 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 EGAD00001002537

• Genome and transcriptome sequence data from an oligodendroglioma patient

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

  Dataset EGAD00001002539

• Genome and transcriptome sequence data from a uveal melanoma patient

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

  Dataset EGAD00001002566

• Genome and transcriptome sequence data from a clear cell carcinoma of ovary patient

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

  Dataset EGAD00001002604

• Genome and transcriptome sequence data from a superficial pleomorphic liposarcoma patient

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

  Dataset EGAD00001002616

• Genome and transcriptome sequence data from an adenoid cystic carcinoma of the trachea patient

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

  Dataset EGAD00001002627

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

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

  Dataset EGAD00001005844

• Genome and transcriptome sequence data from a tongue squamous cell carcinoma (head and neck) patient

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

  Dataset EGAD00001005865

• 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 EGAD00001005878

• Genome and transcriptome sequence data from an ovarian cystadenocarcinoma low grade patient

  Genome and transcriptome sequence data from an ovarian cystadenocarcinoma low grade patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005879

• Genome and transcriptome sequence data from an adenocarcinoma of right lung patient

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

  Dataset EGAD00001001967

• Genome and transcriptome sequence data from a recurrent glioma patient

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

  Dataset EGAD00001002043

• Genome and transcriptome sequence data from a liposarcoma patient

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

  Dataset EGAD00001002046

• Genome and transcriptome sequence data from a metastatic clear cell sarcoma patient

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

  Dataset EGAD00001003018

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

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

  Dataset EGAD00001003019