3906 results for "*geneti*"

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• Genomic and transcriptomic landscape of T-cell lymphoblastic lymphoma compared to T-cell acute lymphoblastic leukemia: similar subtypes and different fusions

  Due to the lower incidence of T-LBL and difficulties in obtaining diagnostic T-LBL material, extensive research on T-LBL has been hampered whereas genetic aberrations in T-ALL are thoroughly characterized. Given the similarities and differences between T-LBL and T-ALL, the question has been raised whether T-LBL and T-ALL represent two different diseases or different manifestations of the same disease. This study aims to identify the genomic and transcriptomic landscape of T-LBL and compare the findings to what is found T-ALL. Comparison of the molecular aberrations between T-LBL and T-ALL can provide insights into the overlap and differences in malignant development between the two entities, which could lead to improved risk stratification in T-LBL in order to eventually adapt T-LBL treatment protocols based on molecular-genetic prognostic factors.

  Study EGAS00001007767

• This study aims to evaluate the relationship between cardiometabolic risk factors and the most common genetic variation (SNPs)

  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 Axiom™ 2.0 Precision Medicine Research Array in the Thermo Fisher Scientific laboratory (Affymetrix Inc, Santa Clara, CA).

  Study EGAS00001007818

• Phosphoproteomics adds value to treatment recommendations in molecular tumor boards

  Precision oncology approaches employing genomics-guided targeted therapies for individual patients have provided significant survival benefits in several cancer types. However, low response rates in most solid malignancies, many patients without actionable genomic lesions, and increasing evidence that non-genomic mechanisms may play an important role in tumors indicate that genomics alone is often insufficient to inform and guide the clinical care of patients. Here, we show for the first time that comprehensive (phospho)proteome profiling is feasible and informative in a real-world prospective precision oncology setting. We developed a novel tumor pathway activity (TUPAC) scoring methodology that provides a holistic perspective on dysregulated receptor tyrosine kinase (RTK) signaling in individual patients. Based on 919 tumor tissue profiles of patients enrolled in the national NCT/DKTK MASTER study and the INFORM registry trial, we illustrate how TUPAC scoring can be used to uncover individual tumor biology in rare cancers and demonstrate that TUPAC methodology identifies EGFR-driven sarcomas despite the absence of genetic EGFR alterations. Overall, our work demonstrates the utility of the additional phosphoproteome data layer to enhance therapeutic recommendations in molecular tumor boards.

  Study EGAS00001007891

• The University of Hong Kong Intestinal Metaplasia Organoids Study

  Background: Gastric intestinal metaplasia (IM) is a pre-cancerous stage spanning a morphological spectrum that is poorly represented by human cell line models. Objective: We aim to establish and characterize human IM cell models to better understand IM progression along the cancer spectrum. Design: A large human gastric IM organoid (IMO) cohort (n=28), their clonal derivatives and normal gastric organoids (n=42) for comparison were established. Comprehensive multi-omics profiling and functional characterization were performed. Results: Single-cell transcriptomes revealed IMO cells spanning a spectrum from hybrid gastric/intestinal to advanced intestinal differentiation. Their lineage trajectories connected different cycling and quiescent stem and progenitors, highlighting differences in gastric to IM transition and the potential origin of IM from STMN1 cycling isthmus stem cells. Hybrid IMOs showed impaired differentiation potential, high lineage plasticity beyond gastric or intestinal fates, and reactivation of a fetal gene program. Cell populations in gastric IM and cancer tissues were highly similar to those derived from IMOs and exhibited a fetal signature. Genomically, IMOs showed elevated mutation burden, frequent chromosome 20 gain, and epigenetic de-regulation of many intestinal and gastric genes. Functionally, IMOs were FGF10 independent and showed downregulated FGFR2. Several IMOs exhibited a cell-matrix adhesion independent (CMi) subpopulation that displayed chromosome 20 gain but lacked key cancer driver mutations, potentially representing the earliest neoplastic precursor of IM-induced gastric cancer. Conclusions: Overall, our IM organoid biobank captured the heterogeneous nature of IM, revealing mechanistic insights on IM pathogenesis and progression, offering an ideal platform for studying early gastric neoplastic transformation and chemoprevention.

  Study EGAS00001007899

• Northern Ireland COhort for the Longitudinal study of Ageing

  The Northern Ireland COhort for the Longitudinal study of Ageing (NICOLA) is a representative sample of ~8,500 people from across Northern Ireland. The study, which was set up in 2012, aims to understand what it is like to grow older in Northern Ireland. • NICOLA has a strong focus on molecular biomarkers so there is complementary genetic, epigenetic and transcriptomic data available for a subset of individuals. • We inherit much of our DNA from our parents while a small amount of this material changes as we get older. In NICOLA we have 551,839 directly genotyped and 18,148,478 imputed Single Nucleotide Polymorphisms (SNPs) currently available for 2969 participants. • Summary statistics for the association of these gene polymorphisms with ~30 phenotypes were generated. • Epigenetics provides a link between our inherited DNA and environmental influences from a person’s diet, medication and lifestyle. NICOLA has the epigenetic quality controlled profiles of 1984 individuals arising from variations in DNA methylation at 862,927 genetic sites.

  Study EGAS00001007915

• Transcriptomics-driven classification of ALAL

  Acute leukemia of ambiguous lineage (ALAL) is a rare, poor-prognosis subtype of acute leukemia that cannot be assigned to a single hematopoietic lineage. Although ALAL patients are typically treated with acute myeloid leukemia (AML) or acute lymphoblastic leukemia (ALL) regimens, optimal treatment choice is hindered by their lineage ambiguity. Therefore, we investigated the added value of transcriptomics for improving lineage assignment, currently based mainly on surface markers. First, we used an in-house pipeline to comprehensively detect genetic lesions in RNA-sequencing data (n=23) with a sensitivity >90%, as confirmed by targeted DNA sequencing. Second, we compared ALAL gene expression profiles (GEPs) with representative AML (n=145), B-ALL (n=223) and T-ALL (n=85) cases. In a principal component analysis, ALALs did not form a separate group, but clustered with AML, B-ALL or T-ALL. Accordingly, a machine learning classifier trained with GEPs of acute leukemias segregated 20/23 ALALs into myeloid-, B- or T-lymphoid leukemia. These 20 cases harbored genetic abnormalities consistent with the classifier-assigned leukemia. Furthermore, ALAL GEPs were deconvoluted with single-cell transcriptional profiles of normal hematopoietic cells using CIBERSORTx, revealing enrichment for signatures of lineages corresponding to the leukemic type predicted by our algorithm. The classifier was validated on an external ALAL cohort (n=24), assigning 75% of the patients to a lineage matching their immunophenotypic and methylation profiles. In conclusion, integrative analysis of RNA-sequencing data can accurately classify most ALAL cases. The pipeline and classifier developed in our study are valuable tools to improve ALAL diagnosis and guide therapeutic decisions.

  Study EGAS00001007967

• Single-cell atlas of > 1.5 million PBMC with multi-layer omics data in Japanese

  Osaka Atlas of Immune Cells (OASIS) is multi-omics immune cell atlas from 235 Japanese including COVID-19 patients and healthy subjects. The 5’ single-cell transcriptomics data profiled over 1,500,000 peripheral blood mononuclear cells (PBMCs). OASIS links these single-cell transcriptomics data with host genetics, plasma proteomics, and metagenomics data.

  Study EGAS00001008016

• Patient-derived tumoroids from CIC::DUX4 rearranged sarcoma identify MCL1 as a therapeutic target

  High-risk sarcomas, such as metastasized and relapsed Ewing and CIC-rearranged sarcomas, currently lack effective curative systemic treatment options. Precision medicine approaches offer hope and among them ex vivo drug response profiling of patient-derived tumor cells emerges as a promising novel tool to identify effective drugs for individual patients. Here, we established ex vivo culture conditions to propagate Ewing and CIC::DUX4-sarcomas as tumoroids in a co-clinical manner. These models retained their original molecular and functional characteristics, including recurrent ARID1A mutations, and serve as tumor avatars suitable for large-scale drug testing. Indeed, screening a large drug library on a small living biobank of such tumors not only revealed distinct response differences between the two entities, but also identified an exceptional dependency of CIC::DUX4-sarcoma cells on MCL1. Mechanistically. MCL1 was identified as a direct target gene of the CIC::DUX4 fusion protein. Genetic and pharmacological inhibition of MCL1 induced rapid apoptosis in CIC::DUX4-sarcoma cells and inhibited tumor growth in a xenograft model. Thus, MCL1 represents a potential novel therapeutic target for CIC::DUX4-sarcoma. Overall, our study highlights the feasibility of co-clinical drug response profiling for individual sarcoma cases and suggests that prospective tests, to evaluate its clinical benefit are highly warranted.

  Study EGAS00001008039

• Genetic origins of the Kiritimati population from central-eastern Micronesia

  The migration of Austronesian-speaking populations through Oceania has intrigued researchers for decades. The Kiribati islands, situated along the boundaries of Micronesia and Polynesia, provide a crucial link in this migration. We analyzed the genome-wide data of the Kiritimati population of Kiribati to uncover their genetic origins and connections with other Oceanian groups. Our study reveals that the Kiritimati population primarily exhibits Remote Oceanian-related ancestry associated with ancient Lapita and present-day Polynesian populations. In addition, our identity-by-descent analysis identifies populations from Philippines as their closest relatives in Island Southeast Asia. The genetic links between Kiritimati, ancient Lapita, and modern Polynesians underscore the shared ancestry and continuous gene flow across these regions. This genetic continuity and ongoing links are supported by linguistic and cultural evidence, illustrating a complex history of migration and admixture in Oceania.

  Study EGAS00001008060

• Epi2Diag

  Genomic DNA was extracted from whole blood and bisulfite converted using the EZ DNA Methylation Lightning Kit (Zymo research). DNA methylation profile was then derived using Illumina’s Infinium EPIC array v2.0. in accordance with the manufacturer’s protocol at the ASGARD-Rouen genomic platform (Inserm U1245, University of Rouen and Rouen University Hospital, Rouen France) on an Illumina NextSeq550 scanner.

  Study EGAS00001008070

• Dataset with genome-wide array data from Algerian Amazigh (Chaoui and Mozabite) and non-Amazigh individuals

  In this study we perform a genetic characterization of different Amazigh populations in Algeria and assess the impact of recent demography on their genomes.

  Study EGAS00001007235

• Single cell TCRseq data fromTIL and non-TIL expanded TRACERx samples in the manuscript Bulk TCRseq from TRACERx samples from 'Subclonal immune evasion in non-small cell lung cancer'

  Immune checkpoint blockade in non-small cell lung cancer (NSCLC) rarely leads to complete tumour remission, suggesting that tumours harbour subpopulations of cancer cells that can escape immune predation. However, while tumours consist of multiple genetically distinct clones, the extent to which separate tumour subclones differ intrinsically in their functional capacity for immune evasion remains largely unexplored. This has been challenging to address due to an inability to isolate and propagate individual tumour subclones from human cancers. Here, we leverage the multi-region TRACERx lung cancer evolution study to generate a patient-derived platform that allows the functional analysis of immune escape at single clone resolution. We generated libraries of >20 separate NSCLC organoid lines per patient by isolating individual (clonal) organoids established from multiple spatially separated tumour regions. Each organoid subline was co-cultured with autologous tumour infiltrating lymphocytes (TIL) to evaluate their capacity to elicit a T cell response. Organoid lines derived from separate tumour regions, or from single clones within individual regions, differ vastly in their capacity to elicit a T cell response, showing the coexistence of intrinsically immune evading (‘cold) and non-evading (‘hot) clones in the same primary tumour. Organoid lines escaping T cell recognition represent genetically and transcriptionally unique subclones with a distinct evolutionary history, showing that evolutionary sculpting of subclonal diversity can have functional consequences for anti-tumour immunity. Notably, the identification of immune-evasive subclones would not have been possible using computational approaches alone, highlighting the unique value of functional co-culture platforms. This patient-derived functional co-culture platform reveals that tumour evolution can give rise to distinct cancer clones with intrinsic differences in immune evasion capacity and provides an approach to prospectively identify, isolate and characterise immune evading subclones from patients with cancer.

  Study EGAS00001008161

• OMKar

  The whole genome karyotype refers to the sequence of large chromosomal segments that make up an individuals genotype. karyotype analysis, which includes descriptions of aneuploidies and other rearrangements is crucial for understanding genetic risk factors, for diagnosis, treatment decisions, and genetic counseling linked to constitutional disorders. The current karyotyping standard is based on microscopic examination of chromosomes, a complex process that requires high expertise and offers Mb scale resolution. Optical Genome Mapping (OGM) technology can identify large DNA lesions in a cost-effective manner. In this paper, we developed OMKar, a method that uses OGM data to create a virtual karyotype. OMKar processes Structural (SV) and Copy Number (CN) Variants as inputs and encodes them into a compact breakpoint graph. It recomputes copy numbers using Integer Linear Programming to maintain CN balance and then identifies constrained Eulerian paths representing entire donor chromosomes. In tests using 38 whole genome simulations of constitutional disorders, OMKar reconstructed the karyotype with 88% precision and 95% recall on SV concordance and 95% Jaccard score on CN concordance. We applied OMKar to 50 prenatal, 41 postnatal, and 63 parental samples from ten different sites. OMKar reconstructed the correct karyotype in 144 out of 154 samples, covering 25 of 25 aneuploidies, 32 of 32 balanced translocations, and 72 of 82 unbalanced variations. Detected constitutional disorders included Cri-du-chat, Wolf-Hirschhorn, Prader-Willi deletions, Down, and Turner syndromes. Importantly, it identified a plausible genetic mechanism for five cases of constitutional disorder that were not detected by other technologies. Together, these results demonstrate the robustness of OMKar for OGM-based karyotyping.

  Study EGAS00001008245

• H3Africa - Deciphering Developmental Disorders in Africa

  Developmental disorders are typically rare conditions, causing an impairment in physical, learning, language, or behavioural areas. Genetic heterogeneity and highly variable clinical manifestations make diagnosing developmental disorders particularly challenging. Developmental disorders are increasing in prevalence in low- and middle-income countries, partly due to effective prevention and treatment of infectious diseases leading to a decrease in childhood mortality. New sequencing technologies are used effectively in the diagnosis of rare diseases and results can impact clinical practice significantly. Despite this international trend, very little implementation of these new approaches has taken place in low-resource settings, especially in Africa. The Deciphering Developmental Disorders in Africa (DDD-Africa) study aims to take advantage of an unbiased genotype-driven approach to improve healthcare services for patients. The study aims to recruit and perform detailed clinical phenotyping and exome sequencing (ES) on 500 African patients with a developmental disorder in whom a genetic diagnosis has not been confirmed. Where available, parents are also included in sequencing efforts. The project has two active research sites in Johannesburg (South Africa) and Kinshasa (Democratic Republic of Congo) representing diversity in geography, clinical, socio-economic, genetic and environmental factors.

  Study EGAS00001008319

• Genome-wide methylation detection and episignature analysis using PacBio long-read sequencing

  Study EGAS00001008250

• Blueprint: A human variation panel of genetic influences on epigenomes and transcriptomes in three immune cell types, (ChIP-Seq for CD14-positive, CD16-negative classical monocyte, on genome GRCh37)

  ChIP-Seq data for 172 CD14-positive, CD16-negative classical monocyte sample(s). 572 run(s), 345 experiment(s), 340 analysis(s) on human genome GRCh37. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/blueprint_Epivar/protocols/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002672

• A comprehensive characterisation and analysis of human breast cancers through whole-genome sequencing

  We propose to definitively characterise the somatic genetics of breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing.

  Dataset EGAD00001002740

• Fetal origins of malignant germ cell tumours

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

  Dataset EGAD00001007037

• IBD Whole Genome Sequencing (2019-04-01)

  We will sequence at 15X coverage the genomes of 1536 IBD patients. These samples are currently onsite at Sanger and made available for sequencing via our collaboration with the UK IBD Genetics consortium. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ . This dataset contains all the data available for this study on 2019-04-01.

  Dataset EGAD00001004880

• Exome Sequencing to Identify Causes of Leukaemia Predisposing Congenital Neutropenias (2019-08-19)

  The objective of this study is to identify the causative genes in two unrelated congenital neutropenia families. We aim to whole exome sequence the affected individuals, unaffected siblings and parents in both cases in an effort to idenitfy the causative genetic mutation. Exome capture will be performed using Agilent SureSelect system. Subsequently, exome libraries will sequenced using the Illumina HiSeq platform. Sequence variant calling will be done in house and common variants excluded using public databases and data from unaffected family members. . This dataset contains all the data available for this study on 2019-08-19.

  Dataset EGAD00001005264

• Survival Benefit and Genetic Profile of Pemetrexed as Initial Chemotherapy in Selected Chinese Patients with Advanced Lung Adenocarcinoma

  NGS data of 12 patients enrolled in the Chinese Patient Assistance Program from multiple centers who received pemetrexed alone or combined with platinum as initial chemotherapy and continued pemetrexed maintenance therapy for advanced lung adenocarcinoma from November 2014 to June 2017.

  Dataset EGAD00001006287

• Phylogenetic reconstruction of adult blood cancer reveals early origins and lifelong evolution - WGS

  Mutations in cancer-associated genes drive tumour outgrowth. However, the timing of driver mutations and dynamics of clonal expansion that lead to human cancers are largely unknown. We used 580,133 somatic mutations from whole-genome sequencing of 1013 clonal haematopoietic colonies to reconstruct the phylogeny of haematopoiesis, from embryogenesis to clinical disease, in 12 patients with myeloproliferative neoplasms which are blood cancers more common in older age. JAK2V617F, the pathognomonic mutation driving the majority of these cancers, was acquired in utero or childhood, with upper estimates of age of acquisition from 33 weeks gestation to 10.8 years, in all 5 patients in whom JAK2V617F was either the only or the first driver event.  Driver mutations associated with age-related clonal haematopoiesis occurred prior to or following JAK2V617F,  as independent clonal expansions in JAK2V617F-mutated patients, and as large clonal expansions in JAK2V617F-unmutated patients . These mutations were also acquired in utero or childhood, with DNMT3A mutations occurring by 8 weeks of gestation to 7.6 years across 4 patients, and PPM1D mutation occurring by age 5.8yrs in a patient with MPN lacking phenotypic driver mutations. Sequential driver mutation acquisition was common, separated by decades across life, and often outcompeted ancestral clones. The mean latency between JAK2V617F acquisition and clinical presentation was 30 years (range 11-54 years). Rates of clonal expansion were inferred from phylogenetic trees and varied substantially (3% to 190% expansion/year), were affected by additional driver mutations, and were predictive of latency to clinical presentation. Driver mutations and rates of expansion would have been detectable in blood one to four decades before clinical presentation. This study reveals how driver mutation acquisition early in life with life-long growth and evolution underlie adult myeloproliferative neoplasms, providing opportunities for early detection and intervention and a new paradigm for cancer development.

  Dataset EGAD00001007714

• Epigenetic, transcriptome and TF analysis of human NK cell and T cells

  RNA-seq 10 subsets; 5 donors. ATAC-seq 9 subsets, 4 donors; Histone modification profiling 10 subsets, 2 donors all using human NK cell and T cell subsets. TF ChIP-seq Bcl11b, Bach2, Runx2, Gata3, PLZF. Illuminia sequencing platform, ATAC-seq is Paired-end, RNA-seq/ChIP-seq is Single-end

  Dataset EGAD00001008449

• Phylogenetic reconstruction of adult blood cancer reveals early origins and lifelong evolution - TGS

  Mutations in cancer-associated genes drive tumour outgrowth. However, the timing of driver mutations and dynamics of clonal expansion that lead to human cancers are largely unknown. We used 580,133 somatic mutations from whole-genome sequencing of 1013 clonal haematopoietic colonies to reconstruct the phylogeny of haematopoiesis, from embryogenesis to clinical disease, in 12 patients with myeloproliferative neoplasms which are blood cancers more common in older age. JAK2V617F, the pathognomonic mutation driving the majority of these cancers, was acquired in utero or childhood, with upper estimates of age of acquisition from 33 weeks gestation to 10.8 years, in all 5 patients in whom JAK2V617F was either the only or the first driver event.  Driver mutations associated with age-related clonal haematopoiesis occurred prior to or following JAK2V617F,  as independent clonal expansions in JAK2V617F-mutated patients, and as large clonal expansions in JAK2V617F-unmutated patients . These mutations were also acquired in utero or childhood, with DNMT3A mutations occurring by 8 weeks of gestation to 7.6 years across 4 patients, and PPM1D mutation occurring by age 5.8yrs in a patient with MPN lacking phenotypic driver mutations. Sequential driver mutation acquisition was common, separated by decades across life, and often outcompeted ancestral clones. The mean latency between JAK2V617F acquisition and clinical presentation was 30 years (range 11-54 years). Rates of clonal expansion were inferred from phylogenetic trees and varied substantially (3% to 190% expansion/year), were affected by additional driver mutations, and were predictive of latency to clinical presentation. Driver mutations and rates of expansion would have been detectable in blood one to four decades before clinical presentation. This study reveals how driver mutation acquisition early in life with life-long growth and evolution underlie adult myeloproliferative neoplasms, providing opportunities for early detection and intervention and a new paradigm for cancer development.

  Dataset EGAD00001007715

• Novel de novo pathogenic variant in the GNAI1 as a cause of severe disorders of intellectual development with autistic features

  Our probands A and B are boys-monozygotic twins with the clinical diagnosis of severe intellectual impairment, developmental stagnation, and dysphasia. They were diagnosed at the Department of Medical Genetics and Genomics (University Hospital Brno). Parents provided written informed consent, which was approved by the Research Ethics Committee of Masaryk University and Ethics Committee of University Hospital Brno. Peripheral blood samples were collected in sterile heparinized tubes for cytogenetic analysis. Genomic DNA samples were obtained from 1 ml peripheral blood in EDTA, according to the standard DNA isolation process using the MagNaPure system (Roche Diagnostics, Basel, Switzerland). Quality and quantity were checked using a DeNovix DS-11 Spectrophotometer (DeNovix Inc., Wilmington, DE, USA) and Qubit® 2.0 (Thermo Fisher Scientific, Inc., Waltham, MA, USA).

  Dataset EGAD00001007736