10161 results for "cancer rna-seq"

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• Robust methylation-based classification of brain tumours using nanopore sequencing

  Background: DNA methylation-based classification of cancer provides a comprehensive molecular approach to diagnose tumours. In fact, DNA methylation profiling of human brain tumours already profoundly impacts clinical neuro-oncology. However, current implementations using hybridization microarrays are time-consuming and costly. We recently reported on shallow nanopore whole-genome sequencing for rapid and cost-effective generation of genome-wide 5-methylcytosine profiles as input to supervised classification. Here, we demonstrate that this approach allows to discriminate a wide spectrum of primary brain tumours. Results: Using public reference data of 82 distinct tumour entities, we performed nanopore genome sequencing on N=382 tissue samples covering 46 brain tumour (sub)types. Using bootstrap sampling in a cohort of N = 56 cases, we find that a minimum set of 1,000 random CpG features is sufficient for high-confidence classification by ad hoc random forests. We implemented score recalibration as confidence measure for interpretation in a clinical context and empirically determined a platform-specific threshold in a randomly sampled discovery cohort (N = 185). Applying this cut-off to an independent validation series (N = 184) yielded 148 classifiable cases (sensitivity 80.4%) and demonstrated 100 % specificity. Cross-lab validation demonstrated robustness with concordant results across four laboratories in 10/11 (90.9%) cases. In a prospective benchmarking (N = 15), median time to results was 21.1 hours. Conclusions: In conclusion, nanopore sequencing allows robust and rapid methylation-based classification across the full spectrum of brain tumours. Platform-specific confidence scores facilitate clinical implementation for which prospective evaluation is warranted and ongoing.

  Study EGAS00001006540

• Oncogenic fate conversion by PRDM16s causes acute myeloid leukemia

  Oncogenic mutations confer aberrant replicative capacity to cells with little or no replicative capacity, generating cancer stem cells that perpetuate the tumor through extensive self-replication and differentiation blockade. However, whether oncogenes disrupt the cellular identity ofcancer stem cell by altering the developmental potential is unknown. Fate conversion has been demonstrated by ectopic expression of master transcriptional regulators, such as PU.1 and C/EBP alpha that confers myeloid cell fate to other cell types, and PRDM16 that confers brown adipose fate to white adipocytes or myoblasts. Here we show that a transcriptional regulator overexpressed in human myeloid malignancies, PRDM16s, causes oncogenic fate conversion, by transforming cells fated to form platelets and erythrocytes into myeloid leukemia-initiating cells (LICs). Prdm16s expression in hematopoietic progenitor cells caused a myelodysplastic syndrome (MDS)-like disease that progressed to acute myelogenous leukemia (AML). The myeloid diseases caused by Prdm16s exhibited expansion of megakaryocyte-erythroid progenitors (MEPs) but not granulocyte-macrophage progenitors. MEPs from Prdm16s-induced leukemia possessed LIC potential, and expression of Prdm16s in normal MEPs was sufficient to convert them to myeloid LICs and blocked megakaryocytic/erythroid potential. Prdm16s induced the expression of myeloid master regulators, including PU.1 and C/EBP alpha, by interacting with their super enhancers. Ablation of myeloid master regulators attenuated the myeloid potential and reinstalled the megakaryocytic/erythroid potential of leukemic-MEPs in mouse models and in human AML with PRDM16 rearrangement. Our study demonstrates that oncogenic Prdm16 expression converts the fate of MEPs to a malignant myeloid fate by activating myeloid master transcription factors.

  Study EGAS00001003235

• Healthspan and lifespan extension by fecal microbiota transplantation in progeroid mice

  The gut microbiome is emerging as a key regulator of several metabolic, immune and neuroendocrine pathways. Gut microbiome deregulation has been implicated in major conditions such as obesity, type 2 diabetes, cardiovascular disease, non-alcoholic fatty acid liver disease or cancer, but its precise role in aging remains to be elucidated. Here, we characterize the gut microbiome profile of accelerated aging and show that its external modulation is sufficient to extend healthspan and lifespan. We found that two different mouse models of progeria present with intestinal dysbiosis, which is characterized, among other alterations, by an increment in proteobacteria, cyanobacteria and a loss in verrucomicrobia, whereas long-lived humans (i.e., centenarians) exhibit a remarkable increase in verrucomicrobia and a reduction in proteobacteria. Fecal microbiota transplantation proved to be effective to enhance healthspan and lifespan in both progeroid mouse models and, more importantly, the solely transplantation with the verrucomicrobia Akkermansia muciniphila was sufficient to exert beneficial effects. Our results demonstrate that intestinal dysbiosis is a phenotype associated with accelerated aging and its correction provides health benefits. Moreover, metabolomic analysis of ileal content points to the restoration of secondary bile acids as a possible mechanism for the beneficial outcome of reestablishing a healthy microbiome. Our results suggest the existence of a link between gut aging and the microbiota, and can help to gain insight into the rationale for microbiome-based interventions against age-related diseases. Mouse sequence data have been deposited in ENA (https://www.ebi.ac.uk/ena) under accession number PRJEB34214

  Study EGAS00001003656

• Neoadjuvant immunotherapy leads to pathological responses in MMR proficient and MMR deficient early stage colon cancers

  PD-1 plus CTLA-4 blockade is highly effective in advanced-stage, mismatch repair (MMR)-deficient (dMMR) colorectal cancers, yet not in MMR-proficient (pMMR) tumors. We postulated a higher efficacy of neoadjuvant immunotherapy in early-stage colon cancers. In the exploratory NICHE study (ClinicalTrials.gov: NCT03026140), patients with dMMR or pMMR tumors received a single dose of ipilimumab and two doses of nivolumab before surgery, the pMMR group with or without celecoxib. The primary objective was safety and feasibility; 40 patients with 21 dMMR and 20 pMMR tumors were treated, and 3 patients received nivolumab monotherapy in the safety run-in. Treatment was well tolerated and all patients underwent radical resections without delays, meeting the primary endpoint. Of the patients who received ipilimumab + nivolumab (20 dMMR and 15 pMMR tumors), 35 were evaluable for efficacy and translational endpoints. Pathological response was observed in 20/20 (100%; 95% exact confidence interval (CI): 86–100%) dMMR tumors, with 19 major pathological responses (MPRs, ≤10% residual viable tumor) and 12 pathological complete responses. In pMMR tumors, 4/15 (27%; 95% exact CI: 8–55%) showed pathological responses, with 3 MPRs and 1 partial response. CD8+PD-1+ T cell infiltration was predictive of response in pMMR tumors. These data indicate that neoadjuvant immunotherapy may have the potential to become the standard of care for a defined group of colon cancer patients when validated in larger studies with at least 3 years of disease-free survival data.

  Study EGAS00001004160

• Non-viral precision T cell receptor replacement for personalized cell therapy

  The T cell receptor (TCR) provides the fine specificity of T cells to recognize mutations in cancer cells 1-3. We developed a clinical-grade approach based on CRISPR/Cas9 non-viral precision genome editing to simultaneously knock-out the two endogenous TCR genes, TCRα (TRAC) and TCRβ (TRBC), and insert in the TRAC locus the two chains of a neoantigen-specific TCR (neoTCR), isolated from the patient’s own circulating T cells using a personalized library of soluble predicted neoantigen-HLA capture reagents. Sixteen patients with refractory solid cancers received up to three distinct neoTCR-transgenic cell products, each expressing a patient-specific neoTCR, in a cell dose-escalation, first-in-human phase 1 clinical trial (NCT03970382). One patient had grade 1 cytokine release syndrome, and one grade 3 encephalitis. All had the expected side effects from the lymphodepleting chemotherapy. Five patients had stable disease, and the other 11 had disease progression as best response on therapy. NeoTCR-transgenic T cells were detected in tumour biopsies post-infusion at frequencies higher than the native TCRs pre-infusion. This study demonstrates the feasibility of isolating and cloning multiple TCRs recognizing mutational neoantigens, the simultaneous knock-out of the endogenous TCR and knock-in of the neoTCRs using single-step, non-viral precision genome editing, the manufacturing of neoTCR engineered T cells at clinical grade, the safety of infusing up to three gene edited neoTCR T cell products, and the ability of the transgenic T cells to traffic to the patients’ tumours.

  Study EGAS00001006898

• CINECA_synthetic_cohort_EUROPE_UK1 referencing fake samples

  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 This 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. The 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 EGAD00001006673

• Human genomic and phenotypic synthetic data for the study of rare diseases

  The purpose of this dataset is to facilitate development of technical implementations for rare disease data integration, analysis, discovery, and federated access. This synthetic dataset includes clinical and genomic data from 6 rare disease cases. It consists of 18 whole genomes (6 index cases with their parents) which have genetic background based on public human data sequenced in the context of the Illumina Platinum initiative (Eberle, MA et al. (2017)) and made available by the HapMap project (https://www.genome.gov/10001688/international-hapmap-project). In each of the cases, real causative variants correlating with the phenotypic data provided were spiked-in. The cases included in this synthetic dataset correspond to the following type of disorders: CASE 1- Congenital myasthenic syndrome (Autosomal Dominant -de novo variant) CASE 2- Macular dystrophy (Autosomal Dominant) CASE 3- Muscular dystrophy (Autosomal Recessive-compound heterozygous variants) CASE 4- Mitochondrial disorder (Autosomal Recessive-consanguineous case - homozygous variant) CASE 5- Breast cancer (Autosomal Dominant) CASE 6- Similar as case 1 for patient matchmaking tests: Congenital myasthenic syndrome (Autosomal Dominant-de novo variant) For each case you will be able to download the following data: clinical information (phenopackets per individual and pedigree per family), raw genomic data (FASTQ and BAMs) and processed genomic data (vcfs). When using the data, the following should be acknowledged: the RD-Connect GPAP (https://platform.rd-connect.eu/), EC H2020 project EJP-RD (grant # 825575), EC H2020 project B1MG (grant # 951724) and Generalitat de Catalunya VEIS project (grant # 001-P-001647).

  Study EGAS00001005702

• STAMPEED: Whole Genome Association Analysis of Hematopoietic Cell Transplant (HCT) Outcomes

  This retrospective cohort study was designed to identify single nucleotide polymorphisms (SNPs) that are associated with complications after allogeneic hematopoietic cell transplantation (HCT). Validated discoveries provide information to improve risk assessment, counseling and treatment planning and to direct future mechanistic studies of the genes and pathways that influence outcomes, thereby providing insight and rationale for new targeted therapies. The study was conducted with the use of 3 different approaches. (1) We used GWAS discovery and replication analyses to identify SNPs variants associated with outcomes after HCT. (2) We tested SNP alleles in HLA-matched sibling donors and recipients to determine whether mismatching in the recipient is associated with graft-versus-host disease (GVHD) or the risk of recurrent malignancy after HCT. Such associations would suggest that the peptide encoded by the SNP allele functions as a minor histocompatibility antigen. (3) We performed in silico candidate SNP studies to determine the validity of previously published results showing associations with outcomes after HCT. The study population represents a large cohort from the Fred Hutchinson Cancer Research Center and consists of 4,471 recipients and 4,628 donors containing 4,258 recipient-donor pairs. Recipients suffered from a hematologic malignancy or myelodysplastic syndrome and were treated in a highly structured clinical research environment with comprehensive monitoring and systematic data recording. We used proportional hazards analyses to test for associations with acute and chronic GVHD, acute kidney injury, gram-negative bacteremia, invasive fungal disease, CMV infection and disease, recurrent malignancy, death not attributable to recurrent malignancy, and death after recurrent or progressive malignancy.

  Study phs001918

• eMERGE: Genetics of Complex Pediatric Disorders from the Center for Applied Genomics

  The Center for Applied Genomics (CAG) is a specialized Center of Emphasis at the Children's Hospital of Philadelphia (CHOP) with the primary goal of translating basic research findings to medical innovations. The mission of CAG is to develop new and better ways to diagnose and treat children affected by rare and complex medical disorders. We aim to discover genetic causes for the most prevalent diseases of childhood including asthma, autism, diabetes, epilepsy, obesity, schizophrenia, pediatric cancer, and a range of rare diseases. Ultimately, our objective is to generate new diagnostic tests and to guide physicians to the most appropriate therapies. The CAG is one of the world's largest genetics research programs in pediatrics, and the only center at a pediatric hospital to have established a large-scale biobank of genotyped samples. The electronic Medical Records and Genomics (eMERGE) Network is a consortium of 9 clinical sites with EMR linked DNA biobanks, including Northwestern University and its NUgene biobank, funded by the NHGRI (National Human Genome Research Institute) to investigate the use of electronic medical record systems for genomic research. The goal of eMERGE is to conduct genome-wide association studies in approximately 100,000 individuals using EMR-derived phenotypes and DNA from linked biorepositories. Using electronic phenotyping methods, the consortium has been and is using DNA samples from all participating sites to explore the genetic determinants of approximately 80 phenotypes, including both diseases and traits, for which the electronic phenotyping algorithms have or are being published on PheKB.org.

  Study phs001165

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

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

  Study EGAS00001007464