Search Results - EGA European Genome-phenome Archive

Tobacco exposure and somatic mutations in normal human bronchial epithelium

That tobacco smoking causes lung cancer is well-established, but we lack quantitative understanding of its effects on genomes of normal bronchial epithelium. We sequenced whole genomes of 632 colonies derived from single bronchial epithelial cells across 16 subjects. Tobacco smoking is the major influence on mutation burden, adding 1000-10,000+ mutations/cell, massively increasing both between-subject and within-subject variance, and generating several distinct signatures of substitutions and indels. A population of cells in subjects with smoking history had mutation burdens equivalent to that expected for never-smokers: these cells lacked tobacco-specific mutational signatures, were four-fold more frequent in ex-smokers than current smokers, and had significantly longer telomeres than their more mutated counterparts. Driver mutations increased in frequency with age, affecting 4-14% of cells in middle-aged never-smokers. In current smokers, ≥25% of cells carried driver mutations and 0-6% cells had 2 or even 3 drivers. Thus, tobacco smoking increases mutation burden, cell-to-cell heterogeneity and driver mutations, but quitting promotes replenishment of bronchial epithelium from mitotically quiescent cells that have avoided tobacco mutagenesis.

Dataset EGAD00001005193

The Precision Medicine in Liver Cancer across an Asia-pacific NETwork (PLANET) - Intratumoural immune heterogeneity

The clinical relevance of immune landscape intratumoural heterogeneity (immune-ITH) and its role in tumour evolution remain largely unexplored. Here, we uncover significant spatial and phenotypic immune–ITH from multiple tumour sectors and decipher its relationship with tumour evolution and disease progression in hepatocellular carcinomas (HCC). Immune–ITH is associated with tumour transcriptomic-ITH, mutational burden, and distinct immune microenvironments. Tumours with low immune–ITH experience higher immunoselective pressure and escape via loss of heterozygosity in human leukocyte antigens and immunoediting. Instead, the tumours with high immune-ITH evolve to a more immunosuppressive/exhausted microenvironment. This gradient of immune pressure along with immune-ITH represents a hallmark of tumour evolution, which is closely linked to the transcriptome-immune networks that contributes to disease progression and immune inactivation. Remarkably, high immune-ITH and its transcriptomic signature are predictive for worse clinical outcome in HCC patients. This in-depth investigation of ITH provides evidence on tumour-immune co-evolution along HCC progression.

Dataset EGAD00001006570

Single-cell gene expression data from CD8+ T cells from two Austrian COVID19 patients stimulated with wildtype and mutant SARS-Cov-2 peptides

The data contains single-cell gene sequencing data (10x Genomics) from FACS-purified CD8 T lymphocytes from two Austrian patients. The cells were stimulated with one MHC class I peptides obtained from a common (wild type) variant and an emerging mutant variant of the SARS-Cov-2 virus. Then the samples were multiplexed using hashtag oligos. We provide the raw and aligned sequence data for: i. The single-cell experiments ii. The PCR-amplified samples for enrichment of the hashtag oligo multiplexing barcodes iii. The PCR-amplified samples for enrichment of the T Cell Receptor (TCR) VDJ region for immuno-profiling. The samples and libraries were processed and obtained in collaboration between St. Anna Children's Cancer Research Institute (CCRI), CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, and the Medical University of Vienna. The cell barcodes and processed data has been submitted to the GEO database with GEO accession GSE166651.

Dataset EGAD00001006995

Dataset for the Pearl study

Biomarkers to identify patients without benefit from adding everolimus to endocrine treatment in metastatic breast cancer (MBC) are needed. We report the results of the Pearl trial conducted in five Belgian centers assessing 18F-FDG-PET/CT non-response (n=45) and ctDNA detection (n=46) after 14 days of exemestane-everolimus (EXE-EVE) to identify MBC patients who will not benefit. Metabolic non-response rate was 66.6%. Median PFS in non-responding patients (using as cut-off 25% for SUVmax decrease) was 3.1 months compared to 6.0 months in those showing response (HR: 0.77, 95% CI: 0.40-1.50, p=0.44). Difference was significant when using a “post-hoc” cut-off of 15% (PFS 2.2 months vs 6.4 months). ctDNA detection at D14 was associated with PFS: 2.1 months vs 5.0 months (HR-2.5, 95% CI: 1.3-5.0, p=0.012). Detection of ctDNA and/or the absence of 18F-FDG-PET/CT response after 14 days of EXE-EVE identifies patients with a low probability of benefiting from treatment. Independent validation is needed.

Dataset EGAD00001007979

Whole genome sequencing

Whole genome sequencing of high-grade serous ovarian cancer (HGSC) tumours and matched normals from 15 patients with homologous recombination deficiencies. The dataset includes fastq files from 56 HGSC tumours (1 primary, 1 relapse, 54 end-stage) and 15 matched normals. Sequence libraries were generated from tumour and matched normal genomic DNA using the KAPA HyperPrep PCR-free library preparation kit (Roche), or the Illumina TruSeq DNA Nano kit according to manufacturer’s instructions. Sequencing was carried out by the Kinghorn Centre for Clinical Genomics Sequencing Laboratory (Sydney, Australia) on the HiSeq X Ten System (Illumina) or by the Australian Genome Research Facility (Melbourne, Australia) on an Illumina NovaSeq to a minimum base coverage of 30-fold for normal DNA and 60-fold for tumour DNA samples.

Dataset EGAD00001009746

Distinct embryonic phylogenies and driver events of infant Wilms tumor - DNA

Cancers of adults typically arise through progressive rounds of clonal diversification and intratumoral selective sweeps which generate a long mutational trunk with shorter subclonal branches. Here, we investigated whether tumors of young children exhibit the same phylogenetic configuration. We studied three infants, including two newborns, with the childhood kidney cancer, Wilms tumour, through whole genome sequencing of bulk tissues, of single cell derived organoids, and of microdissections. All three cancers exhibited unusual driver events, with tumours of newborns harbouring FOXR2 rearrangements, delineating a distinct variant of Wilms tumour. Phylogenetic analyses suggest that tumors were seeded in an early, possibly confined window of development. Unusually, following seeding there was extensive polyclonal diversification with little evidence of clonal sweeps, leading to a distinct phylogenetic configuration more reminiscent of normal tissues rather than of adult cancers. These findings indicate that some childhood cancers may diversify via unorthodox phylogenetic pathways.

Dataset EGAD00001009812

Development, maturation and maintenance of human prostate inferred from somatic mutations

Stem cells within prostate epithelium frequently undergo malignant transformation, but there is limited information on their clonal dynamics and mutation burden in healthy human prostates. We sequenced whole genomes from 409 microdissections of prostate epithelium across 8 donors, using phylogenetic reconstruction with spatial mapping in a 59-year-old man’s prostate to provide high-resolution reconstruction of tissue dynamics across the lifespan. Somatic mutation burden increases linearly with age, at ~16 mutations/year/clone, and is higher in peripheral than peri-urethral regions. The 24-30 independent glandular subunits are established as rudimentary ductal structures during fetal development by 5-10 embryonic cells each. Puberty induces formation of further side branches and terminal acini by local stem cells disseminated through the rudimentary ducts during development. During adult tissue maintenance, clonal expansions are small, with limited geographic scope and minimal migration. Driver mutations are rare in normal ageing prostate epithelium, but the one canonical driver we did observe generated a sizable intraepithelial clonal expansion. By resolving unbiased, continuously occurring lineage-marking mutations, we define stem cell dynamics through embryogenesis, puberty and ageing, with relevance for prostate cancer.

Dataset EGAD00001006591

Genomic Profiling Reveals Spatial Intra-tumour Heterogeneity in Follicular Lymphoma

Follicular lymphoma (FL) is an incurable indolent non-Hodgkin’s lymphoma (NHL) that behaves heterogeneously and is synonymous with the reciprocal translocation t(14;18)(q32;q21), leading to aberrant constitutive over-expression of BCL2 [ref]. High risk groups with poor overall survival include patients that transform to a high grade lymphoma, most commonly diffuse large B cell lymphoma (DLBCL) or progress early (within 2 years) of receiving treatment. Recently several studies have shed light on the diverse genomic landscape of FL, with frequently mutated genes including those involved in chromatin remodelling, (CREBBP, KMT2D, EZH2, EP300), immune modulation (TNFRSF14), JAK-STAT (STAT6, SOCS1), NF-ĸB (CARD11, MYD88, TNFAIP3) and mTORC1 signalling (RRAGC) [ref]. To date, the majority of these studies have either focussed on inter-patient genetic heterogeneity or established the extent of clonal heterogeneity as a patient’s tumour evolves over time. Furthermore, these temporal studies have alluded to the existence of a tumour-repopulating population (referred to as the common progenitor cell (CPC)) that evades treatment and acts as a reservoir, seeding each subsequent relapse and transformation event. Although these previous studies have illuminated the longitudinal clonal dynamics that occur in FL, our understanding of the degree of spatial or intra-tumour heterogeneity (ITH) that exists within an individual patient thus far remains limited. Earlier studies have predominantly focused on differences in cytological grade and immunophenotype between spatially separated lymph nodes and bone marrow, the most common site of extra-nodal involvement in FL, with genomic profiling restricted to examining somatic hypermutation patterns in IgVH genes [ref]. In contrast next generation sequencing has been increasingly utilised in solid organ malignancies to derive comprehensive genomic profiles from spatially separated sites. The seminal study by Gerlinger et al revealed profound differences in the genetic make-up between individual primary and metastatic sites of renal cell carcinoma [ref]. Significant heterogeneity has since been demonstrated both between and within lesions in the same patient in lung, pancreas and breast cancer with presumed driver mutations distributed within the “branches” of the evolutionary phylogenetic tree, suggesting that a single biopsy is incapable of capturing the full genomic heterogeneity of an individual’s malignancy [ref]. This geographical heterogeneity not only adds to the diverse pool of tumour subclones that may contribute to drug resistance mechanisms but importantly, presents a major obstacle for precision-based approaches focussed on targeting specific lesions within a single biopsy. In FL, the exponential increase in clinical trials using novel agents such as EZH2, PI3K and BTK inhibitors reflects this shift in cancer care and along with the development of molecular prognostic scores such as the m7-FLIPI highlights the clinical need to accurately define genomic alterations with clinical relevance. As the majority of FL patients manifest disseminated tumour involvement, we sought to uncover the extent and clinical importance of spatial heterogeneity in FL by comprehensively genetically profiling 22 synchronously removed spatially separated biopsies from 9 patients. Using a combination of whole exome and targeted deep sequencing, our results inferred the complex subclonal architecture within these tumours and the mutational differences between anatomical sites, demonstrating cases with significant intrinsic genetic diversity.

Study EGAS00001002492

Molecular Biomarkers Predicting Lung Cancer Response Phenotypes

We have used a "chemistry first" approach to discover druggable acquired vulnerabilities that arised in the pathogenesis of non-small cell lung cancer (NSCLC). We screened chemical libraries (~200,000 compounds) for chemical toxins that killed subsets of NSCLC but not normal human lung epithelial cells (HBECs). We first screened a panel of 12 NSCLC lines that represented a variety of known oncogenotypes and identified chemicals with large Z scores and appropriate properties including re-supply, chemistry, and reproducible drug response phenotypes. This was then narrowed down to a list of 202 chemicals and 18 drugs with known targeting (henceforth called "Precision Oncology Probe Set", or POPS). These, and a panel of 30 clinically available drugs, targeted therapies, and drug combinations, already in use or in trials for NSCLC treatment, were then tested on a panel of 96 NSCLC lines for their drug response phenotypes in 12-point dose response curves. This information was analyzed using scanning ranked KS (Kolmogorov-Smirnov) and elastic net biostatistics approaches to identify molecular biomarkers (mutations, mRNA expression, copy number variation, protein expression, and metabolomics) which could predict for sensitivity or resistance to a particular chemical toxin or treatment regimen. From this we have discovered that: our approach identifies already known molecular biomarker of drug sensitivities (e.g. EGFR mutations and EGFR TK inhibitors); many clinically available chemotherapy agents have molecular biomarkers predicting preclinical model drug responses; the POP set of chemical toxins provides novel drug response phenotype patterns in the large NSCLC panel different from those found with clinically available agents including a therapeutic window; many of the POP toxins only hit a small percentage (~5%) of the NSCLC panel but the POP set as a whole provides "coverage" of the entire NSCLC panel; there are simple, one or 2 component molecular biomarkers (mutations, mRNA expression) that predict responses to the different chemical toxins in the NSCLC panel; and that the molecular biomarkers provide some information on the targets and pathways involved in response to the chemical toxins. Thus, we have identified a group of chemical toxins with selectivity for subsets of NSCLC and associated tumor molecular biomarkers to facilitate their development for precision medicine, and also, in some cases, information on the targets and pathways interdicted by these chemical compounds. In addition, we have discovered NSCLC predictive biomarkers for clinically available agents.

Study phs001823

Whole Exome Sequencing of Chronic Lymphocytic Leukemia

The somatic genetic basis of chronic lymphocytic leukemia (CLL), a common and clinically heterogenous adult leukemia, remains poorly understood. Massively parallel sequencing technology now provides a method for systematic discovery of genetic alterations that underlie disease, and for uncovering new therapeutic targets and biomarkers. In study version 2 we presented a dataset consisting of DNA sequencing from 169 CLL samples (with matched germline controls). Samples were collected from patients displaying a wide range of characteristics representing the broad clinical spectrum of CLL. Understanding the mutational landscape of CLL provides a starting point for systematic analyses to address fundamental questions in CLL, including how mutated genes alter cellular networks and phenotypes, and thereby contribute to disease heterogeneity. Intratumoral heterogeneity plays a critical role in tumor evolution. To define the contribution of DNA methylation to heterogeneity within tumors, we performed genome-scale bisulfite sequencing of >100 primary chronic lymphocytic leukemias (CLLs; data presented in study version 3). Compared with 26 normal B cell samples, CLLs consistently displayed higher intrasample variability of DNA methylation patterns across the genome, which appears to arise from stochastically disordered methylation in malignant cells. Transcriptome analysis of bulk and single CLL cells revealed that methylationdisorder was linked to low-level expression. Disordered methylation was further associated with adverse clinical outcome. We therefore propose that disordered methylation plays a similar role to that of genetic instability, enhancing the ability of cancer cells to search for superior evolutionary trajectories.

Study phs000435

Small Intestine Neuroendocrine Tumors (Carcinoid Tumors)

The diagnosed incidence of small bowel neuroendocrine tumors (NETs) is increasing. While patients with localized disease can be treated surgically, those with metastatic disease currently have few treatment options. The success of biologically targeted therapies in other malignancies has led to interest in the molecular alterations underlying the pathogenesis of these NETs. To identify genetic aberrations in small intestine NETs, we generated copy number profiles from 31 primary and metastatic tumors and performed whole-exome sequencing on a subset of 29 primary small intestine NETs and 24 metastatic NETs in parallel with normal blood DNA. Whole-genome sequencing data was generated on 15 tumor/normal pairs and 5 primary/metastasis/normal trios. The global genetic landscape of small bowel NETs is relatively quiet. Consistent with previous studies, the overwhelming majority of tumors were characterized by loss of chromosome 18 and, to a lesser extent, other chromosome arm gains and losses. In stark contrast to arm-level alterations, recurrent high-level focal amplifications and deletions were much less prevalent in these tumors. High-throughput mutation screening and exome sequencing revealed similarly low rates of somatic mutation in NETs (median of 0.77 non-silent mutations per megabase (Mb) of coding DNA) compared to other recent cancer exome sequencing efforts. Our analysis of this cohort identified only a single, statistically significant recurrent somatic mutation targeting the cyclin-dependent kinase inhibitor gene, CDKN1B, encoding p27.

Study phs000579

Clinical Sequencing Exploratory Research (CSER): Clinical sequencing in cancer: Clinical, ethical, and technological studies

The Clinical Sequencing Exploratory Research (CSER) program supports multi-disciplinary projects that bring together clinicians, bioinformaticians, and ethicists to research the challenges of utilizing genomic sequence data in the clinic in the routine practice of medicine. The challenges are many and not disease-specific. Important aims of the research include: development of technical specifications and standards for sequencing in a clinical setting, investigation of methods to transmit genome-scale data to physicians in a fashion and timescale that fits the normal clinical workflow, exploration of regulatory requirements for applying genomic sequence data to patient care, study of physician and patient preferences regarding presentation of genomic information, and study of the ethical implications of returning unanticipated findings. More information about CSER and the investigators and institutions who comprise the CSER consortium can be found at http://www.genome.gov/27546194. The NEXT (New Exome Technology) Medicine Study utilizes a randomized controlled trial (RCT) structure to compare usual care (UC) practice in Medical Genetics Clinics with the introduction of a powerful research tool of whole exome sequencing plus UC practices for Colorectal Cancer and Polyposis (CRCP) in adults. In doing so, the study aims to explore the practical, economic, and ethical implications of identifying and returning incidental findings ("extra" whole exome genetic risk results not associated with CRCP that includes pharmacogenetic variants) to patients. The study will also attempt to identify novel causal genes for CRCP by studying relatives of selected research subjects.

Study phs000999

Genetic Basis for Clinical Response to CTLA-4 Blockade in Melanoma

Immune checkpoint inhibitors are effective cancer treatments, but molecular determinants of clinical benefit are unknown. Ipilimumab and tremelimumab are antibodies against cytotoxic T-lymphocyte antigen 4 (CTLA-4). Anti-CTLA-4 treatment prolongs overall survival in patients with melanoma. CTLA-4 blockade activates T cells and enables them to destroy tumor cells. We obtained tumor tissue from patients with melanoma who were treated with ipilimumab or tremelimumab. Whole-exome sequencing was performed on tumors and matched blood samples. Somatic mutations and candidate neoantigens generated from these mutations were characterized. Neoantigen peptides were tested for the ability to activate lymphocytes from ipilimumab-treated patients. Malignant melanoma exomes from 64 patients treated with CTLA-4 blockade were characterized with the use of massively parallel sequencing. A discovery set consisted of 11 patients who derived a long-term clinical benefit and 14 patients who derived a minimal benefit or no benefit. Mutational load was associated with the degree of clinical benefit (P = 0.01) but alone was not sufficient to predict benefit. Using genomewide somatic neoepitope analysis and patient-specific HLA typing, we identified candidate tumor neoantigens for each patient. We elucidated a neo-antigen landscape that is specifically present in tumors with a strong response to CTLA-4 blockade. We validated this signature in a second set of 39 patients with melanoma who were treated with anti-CTLA-4 antibodies. Predicted neoantigens activated T cells from the patients treated with ipilimumab.

Study phs001041

MAP Kinase-Mutant Hematologic Malignancies and Their Therapeutic Resistance

The Mitogen-Activated Protein Kinase (MAPK) signaling pathway has been critically important in understanding pathology and developing targeted therapy for many cancers, but high frequency mutations in this pathway in hematopoietic malignancies were unknown until a series of sequencing studies from our group and others revealed a high frequency of activating mutations in BRAF (GeneID:673), MAP2K1 (GeneID:5604), and other key components of the MAPK pathway in two groups of rare and poorly studied blood cancers: hairy cell leukemia (HCL) and the systemic histiocytoses (SH). Although HCL and the SH both share common gene mutations in BRAF (BRAFV600E) and MAP2K1, these are distinct blood cancers with different clinical behaviors; however, their actual developmental cellular origins, genomic, and pathogenic differences are poorly understood, which led to our project goal of determining how BRAFV600E, MAP2K1, and other MAPK pathway mutations contribute to the pathogenesis of distinct blood cancers and affect their clinical responses to MAPK pathway inhibitors. This study proposal seeks to advance our understanding of the actual cells of origin of cancer-causing MAPK mutations in HCL and the SH, to determine why BRAFV600E and MAP2K1 mutations can cause two distinct blood cancers, and to understand how these mutations in HCL and SH influence responses to MAPK pathway inhibitor drugs and other receptor tyrosine kinase (RTK) inhibitors such as RET and ALK inhibitors that could potentially become effective therapy for these poorly understood blood cancers.

Study phs001864

MP2PRT: Comprehensive Genomic Profiling to Identify Alterations Associated with Relapse for NCI Standard Risk (SR) B-Lineage ALL and NCI High Risk (HR) B-Lineage ALL with Favorable Genetic Features

The Molecular Profiling to Predict Response to Treatment (MP2PRT) program is part of the NCI's Cancer Moonshot Initiative. The aim of this program is the retrospective characterization and analysis of biospecimens collected from completed NCI-sponsored trials of the National Clinical Trials Network and the NCI Community Oncology Research Program. This study, titled "Comprehensive Genomic Profiling to Identify Alterations Associated with Relapse for NCI Standard Risk (SR) B-Lineage ALL and NCI High Risk (HR) B-Lineage ALL with Favorable Genetic Features," is one of the selected studies under this program. For this study, genomic characterization (WGS 30X, WXS, Total RNAseq) was performed on NCI Standard Risk B-lineage ALL patients who relapse and subsets of NCI High Risk B-lineage ALL patients who relapse as well as two non-relapse control cases for each relapse case. It was hypothesized that the comprehensive characterization of these sample sets will allow the identification of somatic genetic features that will facilitate early intervention to improve cure rates for those enrolled on future trials. Data were generated and genetic subtype was integrated with clinical variables, including age, presenting white blood cell count, sex, race, and levels of minimal residual disease at the end of induction. Additional secondary alterations were identified and included if they occurred in more than 10 patients. The study has been completed and a manuscript has been prepared.

Study phs002005

A New Pipeline to Predict and Confirm Tumor Neoantigens Predicts Better Response to Checkpoint Blockade

Mutations that drive oncogenesis in cancer can generate neoantigens that may be recognized by the immune system. Identification of these neoantigens remains challenging due to the complexity of the major histocompatibility complex (MHC) antigen and T-cell receptor interaction. Here we describe the development of a systematic approach to efficiently identify and validate immunogenic neoantigens. Whole exome sequencing of tissue from a melanoma patient was used to identify nonsynonymous mutations, followed by MHC binding prediction and identification of tumor clonal architecture. The top 18 putative class I neoantigens were selected for immunogenicity testing via a novel in vitro pipeline in HLA-A201 healthy donor blood. Naive CD8 T cells from donors were stimulated with allogeneic dendritic cells pulsed with peptide pools and then with individual peptides. The presence of antigen-specific T cells was determined via functional assays. We identified one putative neoantigen that expanded T cells specific to the mutant form of the peptide and validated this pipeline in a subset of patients with bladder tumors treated with durvalumab (N = 5). Within this cohort, the top predicted neoantigens from all patients were immunogenic in vitro. Finally, we looked at overall survival in the whole durvalumab-treated bladder cohort (N = 37) by stratifying patients by tertile measure of tumor mutation burden (TMB) or neoantigen load. Patients with higher neoantigen and TMB load tended to show better overall survival.

Study phs002269

Search for new loci and low-frequency variants influencing glioma risk by exome-array analysis

To identify protein altering variants (PAVs) for glioma we analysed Illumina HumanExome BeadChip exome array data on 1,882 glioma cases and 8,079 controls from three independent European populations. In addition to single variant tests we incorporated information on the predicted functional consequences of PAVs and analysed sets of genes with a higher likelihood of having a role in glioma on the basis of the profile of somatic mutations documented by large-scale sequencing initiatives. Globally tThere was a strong relationship between effect size and SNPs predicted to be damaging (P=2.29x10-49); however, these variants which are most likely to impact on risk, are rare (MAF<5%). While no single variant showed an association which was statistically significant at the genomewide threshold a number of represented promising Notable associations - were seen with the BRCA2:c.9976A>T, p.(Lys3326Ter)BRCA2 p.Lys332X variant, which has been shown documented to influence breast and lung cancer risks (OR=2.3, P=4.00x10-4 for glioblastoma [GBM]) and IDH2:c.782G>A, p.(Arg261His)IDH2 p.Arg261His (OR=3.21, P=7.67x10-3, for non-GBM). Additionally, gene burden tests revealed a statistically significant association for HARS2 and risk of GBM (P=2.20x10-6). Genome scans of low frequency PAVs represent a complementary strategy to identify disease-causing variants compared with scans based on tagSNPs. Strategies to lessen the multiple testing burden by restricting analysis to PAVs with higher priors affords an opportunity to maximise study power.

Study EGAS00001001258

T cell receptor repertoire sequencing reveals chemotherapy-driven clonal expansion in colorectal liver metastases

Colorectal liver metastasis (CLM) is a leading cause of colorectal cancer mortality, and the response to immune checkpoint inhibition (ICI) in microsatellite stable CRC has been disappointing. Administration of cytotoxic chemotherapy may cause increased density of tumour infiltrating T cells, which has been associated with improved response to ICI. This study aimed to quantify and characterize T cell infiltration in CLM using T cell receptor (TCR) repertoire sequencing. Eighty-five resected CLM from patients included in the Oslo CoMet study were subjected to TCR repertoire sequencing. Thirty-five and 15 patients had received neoadjuvant chemotherapy (NACT) within a short or long interval, respectively, prior to resection, while 35 patients had not been exposed to NACT. T cell fractions were calculated, repertoire clonality was analysed based on Hill evenness curves, and TCR sequential convergence was assessed using network analysis. Increased T cell fractions (10.6% vs 6.3%) were detected in CLM exposed to NACT within a short interval prior to resection, while modestly increased clonality was observed in NACT exposed tumours independently of the timing of NACT administration and surgery. While private clones made up >90% of detected clones, network connectivity analysis revealed that public clones contributed the majority of TCR sequence convergence. TCR repertoire sequencing can be used to quantify T cell infiltration and clonality in clinical samples. This study provides evidence to support chemotherapy-driven T cell clonal expansion in CLM in a clinical context.

Study EGAS00001007136

ATRX mutant neuroblastoma is sensitive to EZH2 inhibition via modulation of neuronal differentiation.

Mutations and structural alterations of the SWI/SNF-like chromatin remodeler ATRX have been reported at high frequency in a number of adult and pediatric tumors1. However, the consequences of ATRX (Alpha Thalassemia/Mental Retardation, X-linked) mutations in cancer and their underlying epigenetic sensitivities remain ill defined. Particularly intriguing are the large N-terminal deletions of ATRX in neuroblastoma that generate in-frame fusion (IFF) proteins1–3 devoid of key chromatin interaction domains. Here we demonstrate that neuroblastoma cells harbouring ATRX IFFs have distinct gene expression programs compared to neuroblastoma cells that are wild type for ATRX. This is due in part to H3K27me3-mediated silencing of REST (RE1 Silencing Transcription Factor) target genes involved in neuronal differentiation. In turn, we find that ATRX IFF cells display exquisite sensitivity to EZH2 inhibition in both adherent and tumorsphere conditions, due in part to derepression of neurogenesis genes, including REST targets. Examination of the epigenomic landscape of a pediatric neuroblastoma tumor harboring an ATRX IFF revealed that H3K27me3 occupies a subset of REST target genes that are transcriptionally silenced, and are sensitive to EZH2 inhibition in our cell-based assays. Thus, our study greatly advances our understanding of indolent neuroblastoma and identifies EZH2 inhibition as a potential therapy for patients with ATRX mutant disease. Further, these studies may be applicable to other ATRX mutant pediatric malignancies, particularly those carrying similar structural alterations of ATRX.

Study EGAS00001002507

The Medical Genome Reference Bank: a whole genome data resource of 4,000 healthy elderly individuals.

Allele frequency data from human reference populations is of increasing value for filtering and assignment of pathogenicity to genetic variants. Aged and healthy populations are more likely to be selectively depleted of pathogenic alleles, and therefore particularly suitable as a reference populations for the major diseases of clinical and public health importance. However, reference studies of the healthy elderly have remained under represented in human genetics. We have developed the Medical Genome Reference Bank (MGRB), a large scale comprehensive whole genome dataset of confirmed healthy elderly individuals, to provide a publicly accessible resource for health related research, and for clinical genetics. It also represents a useful resource for studying the genetics of healthy aging. The MGRB comprises 4,000 healthy, older individuals with no reported history of cancer, cardiovascular disease or dementia, recruited from two Australian community based cohorts. DNA derived from blood samples will be subject to whole genome sequencing. The MGRB will measure genome wide genetic variation in 4,000 individuals, mostly of European decent, aged 60 to 95 years (mean age 75 years). The MGRB has committed to a policy of data sharing, employing a hierarchical data management system to maintain participant privacy and confidentiality, whilst maximizing research and clinical usage of the database. The MGRB will represent a dataset of international significance, broadly accessible to the clinical and genetic research community.

Study EGAS00001003511

CINECA_synthetic_cohort_ita_ingestion_test

Please note: This synthetic data set (with cohort “participants” / ”subjects” marked with FAKE) has no identifiable data and cannot be used to make any inference about cohort data or results. The purpose of this dataset is to aid development of technical implementations for cohort data discovery, harmonization, access, and federated analysis. In support of FAIRness in data sharing, this dataset is made freely available under the Creative Commons Licence (CC-BY). Please ensure this preamble is included with this dataset and that the CINECA project (funding: EC H2020 grant 825775) is acknowledged. For any questions please contact isuru@ebi.ac.uk or cthomas@ebi.ac.uk\n\nThis dataset (CINECA_synthetic_cohort_EUROPE_UK1) consists of 2521 samples which have genetic data based on 1000 Genomes data (https://www.nature.com/articles/nature15393), and synthetic subject attributes and phenotypic data derived from UKBiobank (https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001779). These data were initially derived using the TOFU tool (https://github.com/spiros/tofu), which generates randomly generated values based on the UKBiobank data dictionary. Categorical values were randomly generated based on the data dictionary, continuous variables generated based on the distribution of values reported by the UK Biobank showcase, and date / time values were random. Additionally we split the phenotypes and attributes into 4 main classes - general, cancer, diabetes mellitus, and cardiac. We assigned the general attributes to all the samples, and the cardiac / diabetes mellitus / cancer attributes to a proportion of the total samples. Once the initial set of phenotypes and attributes were generated, the data data was checked for consistency and where possible dependent attributes were calculated from the independent variables generated by TOFU. For example, BMI was calculated from height and weight data, and age at death generated by date of death and date of birth. These data were then loaded to the development instance of Biosamples (https://www.ebi.ac.uk/biosamples/) which accessioned each of the samples. \nThe genetic data are derived from the 1000 Genomes Phase 3 release (https://www.internationalgenome.org/category/phase-3/). The genotype data consists of a single joint call vcf files with call genotypes for all 2504 samples, plus bed, bim, fam, and nosex files generated via plink for these samples and genotypes. The genotype data has had a variety of errors introduced to mimic real data and as a test for quality control pipelines. These include gender mismatches, ethnic background mislabelling and low call rates for a randomly chosen subset of sample data as well as deviations from Hardy Weinberg equilibrium and low call rates for a random selection of variants. Additionally 40 samples have raw genetic data available in the form of both bam and cram files, including unmapped data. The gender of the samples in the 1000 genomes data has been matched to the synthetic phenotypic data generated for these samples. The genetic data was then linked to the synthetic data in BioSamples, and submitted to EGA.

Dataset EGAD50000000369

CM067 WES - Clinical Outcomes by Tumor Mutational Burden and Inflammatory Gene Expression With Combined Nivolumab and Ipilimumab or Monotherapy in Advanced Melanoma

Purpose Exploratory analyses of CheckMate 066 and 067 trials were conducted to investigate associations of tumor mutational burden (TMB), a 4-gene inflammatory gene expression signature, and BRAF mutation status with tumor response, progression-free survival (PFS), and overall survival (OS) in patients with advanced melanoma. Patients and Methods Patients with known programmed death ligand 1 (PD-L1) expression and BRAF mutation status received nivolumab (NIVO) or dacarbazine in CheckMate 066 and either NIVO, ipilimumab (IPI), or NIVO+IPI in CheckMate 067. Whole exome sequencing and RNA sequencing were used to determine TMB and inflammatory gene expression signature scores, respectively. These biomarkers were evaluated in terms of their association with PFS and OS. Results In the NIVO, NIVO+IPI, and IPI arms of CheckMate 067, longer survival was associated with high (> median) versus low (≤ median) TMB with hazard ratios (HRs) (95% confidence interval [CI]) for PFS of 0.45 (0.30–0.65), 0.55 (0.38–0.81), and 0.60 (0.43–0.82), and for OS of 0.46 (0.30–0.71), 0.53 (0.34–0.82), and 0.52 (0.36–0.74), respectively. For NIVO-treated patients, these results were confirmed in CheckMate 066. A survival benefit was observed with high TMB and absence of BRAF mutation. Survival was associated with high versus low inflammatory signature scores with HRs (95% CI) for PFS of 0.56 (0.34–0.94), 0.40 (0.23–0.72), and 0.43 (0.27–0.70), and for OS of 0.37 (0.20–0.66), 0.38 (0.19–0.74), and 0.46 (0.27–0.79), in the NIVO, NIVO+IPI, and IPI arms, respectively. Weak correlations were observed between PD-L1, TMB, and the inflammatory signature. Conclusions Combined assessment of TMB, inflammatory gene expression signature, and BRAF mutation status may be predictive for response to immunotherapy in advanced melanoma.

Dataset EGAD00001007573

HSC_population_dynamics___CB001_samples

My research project aims to use the clonal dynamics of spontaneously occurring somatic mutations to answer fundamental questions about human haematopoietic stem cell (HSC) biology. The four major questions I will address are: 1. How do age and aging affect normal human HSC dynamics in vivo? 2. How do in vivo perturbations, particularly chemotherapy and increased levels of reactive oxygen species, affect HSC population dynamics? 3. Is response to in vitro perturbation heritable and/or correlated with other features such as age of individual and contribution of the lineage to peripheral blood? 4. How are HSC dynamics altered in people with early driver mutations (clonal haematopoiesis)?

Study EGAS00001003397

Whole Genomes Define Concordance in Matched Primary, Xenograft, and Organoid Models of Pancreas Cancer

Pancreatic ductal adenocarcinoma (PDAC) has the worst prognosis of any common solid epithelial tumour. Multiple failed clinical trials necessitate newer approaches to understand the molecular etiology of this disease. Patient-derived xenografts (PDX) and patient-derived organoids (PDO) may serve as pre-clinical disease models; however, characterization remains largely unaddressed at the whole genome level. We conducted a comprehensive assessment of the genetic landscape of tumours and matched PDX and PDO from patients with PDAC. Our data show that PDX and PDO recapitulate PDAC tumourigenesis with respect to simple somatic mutations and copy number changes, and capture major structural variation events.

Study EGAS00001002597

WGS___Exploration_of__mutational_processes_in_human_cancer_cell_lines

Approximately 25 cell lines representative of 11 mutation signatures have been selected and will be grown from a single cell, referred to as parental clone, for a period of 3 months to allow accumulation of mutations. Following that period, we will obtain 2 subclones from each of the parental clone for analysis by exome-sequencing . In total we will therefore be sequencing 2 parental clones and 4 subclones per cell line for approximately 25 cell lines. Once the data has been analysed and the potential ongoing mutation processes determined, we will perform whole-genome sequencing of the parental clones and subclones of the candidate cell lines.

Study EGAS00001002680

9337 results for "cancer rna-seq"

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