14970 results for "cancer studies using rna-seq"

in 21.06 milliseconds.

• The long term effects of chemotherapy on normal blood - WGS dataset

  In developed countries, ~10% of individuals are exposed to systemic chemotherapy for cancer and other diseases. Many chemotherapeutic agents act by increasing DNA damage in cancer cells, hence triggering cell death. However, there is limited understanding of the extent and consequences of collateral DNA damage to normal tissues. To investigate the impact of chemotherapy on mutation burdens and cell population structure of a normal tissue we sequenced blood cell genomes from 23 individuals, aged 3-80 years, treated with a range of chemotherapy regimens. Substantial additional mutation loads with characteristic mutational signatures were imposed by some chemotherapeutic agents, but there were differences in burden between different classes of agent, different agents of the same class and different blood cell types. Chemotherapy also induced premature changes in the cell population structure of normal blood, similar to those of normal ageing. The results constitute an initial survey of the long-term biological consequences of cytotoxic agents to which a substantial fraction of the population is exposed during the course of their disease management, raising mechanistic questions and highlighting opportunities for mitigation of adverse effects.

  Dataset EGAD00001015339

• RNA sequencing of CCO- and CCO+ human hepatocytes

  RNAseq data from Passman et al 2023. Clonal CCO-deficient hepatocyte patches and nearby CCO-proficient hepatocytes were identified in morphologically normal human livers and sampled at varying distances along the PT-CV axis. Samples are named according to their location within the liver lobule, with "PT" denoting samples abutting the portal triad, "CV" denoting samples abutting the central hepatic vein, and "Mid" sampled acquired midway between these structures. Normal human liver is thought to be generally quiescent, however clonal hepatocyte expansions have been observed but neither their cellular source nor their expansion dynamics have been determined. Knowing the hepatocyte cell of origin, and their subsequent dynamics and trajectory within the human liver will provide an important basis to understand disease-associated dysregulation. Here we use in vivo lineage tracing and a combination of methylation sequence analysis to demonstrate normal human hepatocyte ancestry. We exploit next generation mitochondrial sequencing to determine hepatocyte clonal expansion dynamics across spatially-distinct areas of laser-capture microdissected clones, in tandem with computational modelling in morphologically-normal human liver.

  Study EGAS00001006984

• NHLBI GO-ESP: Family Studies (Mendelian Lipid Disorders)

  The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. In this study, we seek to identify the genetic cause of two monogenic lipid disorders-severe hypercholesterolemia and familial hypoalphalipoproteinemia. Monogenic severe hypercholesterolemia is clinically characterized by elevated total and low-density lipoprotein (LDL) cholesterol levels in plasma. Elevated LDL-cholesterol levels lead to excessive deposition of cholesterol in arterial walls, which eventually results in accelerated atherosclerosis and premature cardiovascular disease (CVD). Monogenic hypercholesterolemia has a prevalence of approximately one in 500 individuals, making it one of the most common inherited disorders. To date, mutations in the LDL receptor (LDLR) ligand-binding domains of APOB and PCSK9 have been shown to cause hypercholesterolemia. While mutations in these genes can explain a large percentage of clinically diagnosed patients, the underlying molecular determinant in a substantial fraction of patients remains unknown. Familial hypoalphalipoproteinemia (low HDL-C) is defined by an HDL-C below the age- and sex- specific 10th percentile. ABCA1, LCAT, and APOA1 are known to cause familial hypoalphalipoproteinemia. We hypothesize that: (1) additional novel genes responsible for Mendelian forms of low HDL-C exist; and (2) the causal gene and mutation(s) in each family may be discovered with exome analysis of just a few affected individuals in each pedigree.

  Study phs000587

• FEGA FAQs: a summary of the Q+A session from the FEGA workshop at ELIXIR AHM 2024

  The ELIXIR All Hands Meeting (AHM) was held in Uppsala, Sweden this June. We at EGA always look forward to this meeting as a chance to see many of our partners and colleagues face-to-face. The Federated EGA (FEGA) is one initiative that always benefits from the AHM, and this year FEGA was in the spotlight, with several questions related to the advances we've made recently. We held this year's FEGA workshop a little differently, with most time for discussions on various “hot topics”. Organised in different breakouts, over 2 rounds, participants could choose which session they wanted to attend. One breakout was a general Q+A about FEGA and the path to join. We had a diverse range of participants, including experts from Central EGA (CEGA) and FEGA inaugural nodes, people from up and coming nodes at various stages of readiness, as well as participants not directly a part of FEGA but curious to learn more. It made for a great discussion! In this blog post, we highlight some of the questions for those who didn’t have a chance to be there. What is the FEGA Collaboration Agreement? It is a legal agreement between the node and Central EGA (CEGA) where both parties agree to certain responsibilities, like what services will be provided, sharing of public metadata with CEGA, interoperable technologies and more. The agreement is for 4 years, with the expectation of long-term sustainability. If a node is made up of multiple institutes, one institute must be the signatory. This could require a legal agreement within the node. CEGA is composed of CRG and EMBL-EBI (EGA itself has its own legal agreement between these institutes) Check the FEGA Collaboration Agreement What about purely medical data? Is this accepted in FEGA? CEGA only accepts data approved for secondary research use. We do accept medical data collected in this context, as do some nodes. Nodes are able to accept any data they like, as long as it is sensitive, thus in need of controlled access. What about other data types other than genomics? Like proteomics or images? They can be accepted, although CEGA is currently not designed with those formats in mind, so they might not fit with precision in the data model. The FEGA nodes are welcome to accept any data they want. Proteomic studies generating sensitive data are increasing, and specific work will likely be developed in the near future to adress this need. Does CEGA require a certain amount or type of data to be shared by the node? No, we do not and it's up to each node to decide what specific data types they accept and in what format. Nonetheless, a FEGA node has the duty to be open to data submission from any institution of their country, and can't be limited by design to a single or limited data source. Does CEGA and FEGA require a certain amount or type of details and description on the data to be submitted to the node? Data description (technical and biological), usually called metadata in this field, is crucial for the findability of the submitted data. Thus, we highly recommend including as much information as available to maximise the discoverability of the data. Specifical minimal metadata is defined in the submission schema, and thresholds are specified by the nodes. We are currently working towards a unified FEGA metadata model. What are the geographical borders of FEGA? FEGA should make the E for Everyone, because any institute worldwide could join and we indeed do have countries and use-cases worldwide. Some of them are very close to officially joining the federation. What are the main differences between FEGA and GDI? The two networks have a lot in common and also some critical differences. You can read all about this in one of our latest blog post. If you have more questions, please consider having a look at the FEGA onboarding webpage and, of course, don't miss our workshop at the ELIXIR AHM next year!

  Blog fega-faqs-elixir-ahm-2024

• High Resolution Maps of the HeLa 3D Genome Using Hi-C

  We use in situ Hi-C to probe the three-dimensional architecture of genomes, constructing haploid and diploid maps of nine cell types (including HeLa). The densest, in human lymphoblastoid cells, contains 4.9 billion contacts, achieving 1-kilobase resolution. We find that genomes are partitioned into contact domains (median length, 185kb), which are associated with distinct patterns of histone marks and segregate into six subcompartments. We identify ~10,000 loops. These loops frequently link promoters and enhancers, correlate with gene activation, and show conservation across cell types and species. Loop anchors typically occur at domain boundaries and bind CTCF. CTCF sites at loop anchors occur predominantly (>90%) in a convergent orientation, with the asymmetric motifs 'facing' one another. The inactive X-chromosome splits into two massive domains and contains large loops anchored at CTCF-binding repeats. The data for the other (non-HeLa) cell types has been uploaded to GEO.

  Study phs001010

• Genome-wide quantification of rare somatic mutations in normal human tissues using massively parallel sequencing

  We present Bottleneck Sequencing System (BotSeqS), a nextgeneration sequencing method that simultaneously quantifies rare somatic point mutations across the mitochondrial and nuclear genomes. BotSeqS combines molecular barcoding with a simple dilution step immediately prior to library amplification. We use BotSeqS to show age and tissue-dependent accumulations of rare mutations and demonstrate that somatic mutational burden in normal tissues can vary by several orders of magnitude, depending on biologic and environmental factors. We further show major differences between the mutational patterns of the mitochondrial and nuclear genomes in normal tissues. Lastly, the mutation spectra of normal tissues were different from each other, but similar to those of the cancers that arose in them. This technology can provide insights into the number and nature of genetic alterations in normal tissues and can be used to address a variety of fundamental questions about the genomes of diseased tissues.

  Study EGAS00001001838

• HSC_population_dynamics___KX007_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 EGAS00001004193

• HSC_population_dynamics_CBD_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 EGAS00001003091

• Single-cell atlas of penile cancer reveals TP53 mutations as driver for an aggressive phenotype, irrespective of HPV status, and provides clues for treatment personalization

  Our aim was to identify molecular differences in the microenvironment of penile squamous cell carcinoma (PSCC) stratified by TP53 loss-of-function (TP53LOF) mutations and HPV-status. Hence, we present a first single-cell transcriptomic atlas of PSCC. Stratification based on TP53 and HPV-status uncovered differences in CSS and underlying molecular pathways. Our data indicate that TP53LOF tumors are characterized by worse biological behavior regardless of HPV-status. These findings and further research are essential for trial design in PSCC, allowing us to move away from the current one-size-fits-all approach.

  Study EGAS50000000217

• HSC_population_dynamics___PX001_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 EGAS00001004146

• HSC_population_dynamics___KX009_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 EGAS00001004580

• HSC_population_dynamics___KX010_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 EGAS00001004581

• WES in muscle-invasive bladder cancer (MIBC) treated with durvalumab plus olaparib in the neoadjuvant setting: NEODURVARIB trial

  This submission contains the metadata derived from the whole exome sequencing of 70 samples from 26 patients who developed advanced urothelial carcinomas. The patients were enrolled in the Neodurvarib clinical trial, which compares the molecular profiles at diagnosis and after neoadjuvant treatment with Durvalumab and Olaparib. In this regard, the analyzed samples include: normal tissue and tumoral tissue obtained from the transurethral resection of the bladder (TURBT, a procedure performed prior to neoadjuvant therapy) from the 26 patients (52 samples), as well as tissue obtained from the radical cystectomy (a procedure performed after treatment with the aforementioned drugs; 18 samples).

  Study EGAS50000000791

• HSC_population_dynamics_KSP_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 EGAS00001002762

• GOSH_Paediatric_Tumour_23P108_WSSS_WGS_Managed_Access

  We have a case of two siblings (twins) who were born with nodular blue rashes over their body. The first twin had a large periorbital subcutaneous mass which was diagnosed as infantile undifferentiated sarcoma. This baby was too systematically unwell for chemotherapy and died at 12 days of age. The second sibling received two cycles of emergency chemotherapy however died due to disease progression and secondary haemorrhage at 2 months of age. Post-mortem normal and tumour samples have been taken. In addition to placental tissue and parental germline DNA, the goal will be to investigate intra-uterine transfer of sarcoma and the phylogenetic relationship of tumours in both twins.

  Study EGAS00001007536

• Multi-modal spatial characterization of tumor-immune microenvironments in diffuse large B-cell lymphoma

  We have leveraged spatial transcriptomics together with proteomic and genomic analysis to investigate the spatial immunology and pathobiology of DLBCL. We define distinct cellular niches that differ in frequency across tumors, related to both Epstein-Barr virus (EBV) infection status and the anatomical site of the tumor, and show that residence within different cellular niches is associated with divergent functional states of T-cells and tumor B-cells due to different patterns of cell-cell communication. This provides a framework for understanding stereotyped patterns of spatial organization in DLBCL and immunological interactions associated with heterogeneity in immune cell infiltration and function across patients.

  Study EGAS50000001146

• SS18-SSX-mediated hijacking of BAF complexes drives synovial sarcoma

  Synovial sarcoma (SS) is defined by a recurrent t(x;18) chromosomal translocation, which produces the hallmark SS18-SSX oncogenic fusion. Incorporation of SS18-SSX into BAF complexes renders BAF complexes aberrant in two distinct manners: the addition of 78aa of SSX onto SS18, and concomitant loss of BAF47 assembly. However, the importance and functional contributions of each of these perturbations on BAF complex targeting and gene expression regulation remain unclear. Here we use an integrative set of genomic approaches in human cancer cell lines and primary tumor samples to define the mechanistic consequences of the SS18-SSX fusion oncoprotein. We find that SS18-SSX hijacks BAF complexes to broad polycomb domains to activate bivalent genes, driving a unique gene expression program distinct from other loss-of-function BAF complex malignancies. Importantly, restoration of BAF47 rescues enhancer activation but is dispensable for proliferative arrest in cell lines. These results demonstrate that gain-of-function SS18-SSX-mediated BAF complex targeting and gene activation is the driving event in SS, and present a mechanism by which distinct functions of BAF complexes can be co-opted to drive oncogenesis.

  Dataset EGAD00001004135

• Integrative genome profiling in AML

  AML emerges as a consequence of accumulating independent genetic aberrations that direct regulation and/or dysfunction of genes resulting in aberrant activation of signalling pathways, resistance to apoptosis and uncontrolled proliferation. Given the significant heterogeneity of AML genomes, AML patients demonstrate a highly variable response rate and poor median survival in response to current chemotherapy regimens. For the past 4 years we have conducted gene expression profiling on purified bone marrow populations equating to normal haematopoietic stem and progenitor cells from healthy subjects and patients with de novo AML in order to identify AML signatures of aberrantly expressed genes in cancer versus normal. We are now applying a series of bioinformatic methodologies combined with clinical and conventional diagnostic data to establish novel genomics strategies for improved prognostication of AML. Additionally, we use our AML signatures to unravel oncogenic signalling pathway activities in AML patients and test inhibitory drugs for these pathways inn preclinical therapeutic programmes. We consider that superimposing GEP and clinical data for our AML patient cohort with additional data on their mutational status will significantly improve the prognostic power of the study as well as unravel yet unknown mutations associated with aberrant signalling activities of oncogenic pathways.

  Dataset EGAD00001001873

• HSC_population_dynamics___LEUK4_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 EGAS00001004247