2965 results for "愛の戦士完全破壊2-re-imagination-version-鞭首絞め・電撃・ヘソか"

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• Single-cell DNA amplicon sequencing reveals clonal heterogeneity and evolution in T-cell acute lymphoblastic leukemia

  T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive leukemia that is most frequent in children and is characterized by the presence of few chromosomal rearrangements and 10 to 20 somatic mutations in protein-coding regions at diagnosis. The majority of T-ALL cases harbor activating mutations in NOTCH1 together with mutations in genes implicated in kinase signaling, transcriptional regulation or protein translation. To obtain more insight in the level of clonal heterogeneity at diagnosis and during treatment, we used single-cell targeted DNA sequencing with the Tapestri platform. We designed a custom ALL panel and obtained accurate single-nucleotide variant and small insertion-deletion mutation calling for 305 amplicons covering 110 genes in about 4400 cells per sample and time point. A total of 108,188 cells were analyzed for 25 samples of 8 T-ALL patients. We typically observed a major clone at diagnosis (>35% of the cells) accompanied by several minor clones of which some were less than 1% of the total number of cells. Four patients had >2 NOTCH1 mutations some of which present in minor clones, indicating a strong pressure to acquire NOTCH1 mutations in developing T-ALL cells. By analyzing longitudinal samples, we detected the presence and clonal nature of residual leukemic cells as well as clones with a minor presence at diagnosis that evolved to clinically relevant major clones at later disease stages. Single-cell DNA amplicon sequencing is a sensitive assay to detect clonal architecture and evolution in T-ALL.

  Study EGAS00001004440

• Prediction and quantification of splice events from RNA-seq data

  Analysis of splice variants from short read RNA-seq data remains a challenging problem. Here we present a novel method for the genome-guided prediction and quantification of splice events from RNA-seq data, which enables the analysis of unannotated and complex splice events. Splice junctions and exons are predicted from reads mapped to a reference genome and are assembled into a genome-wide splice graph. Splice events are identified recursively from the graph and are quantified locally based on reads extending across the start or end of each splice variant. We assess prediction accuracy based on simulated and real RNA-seq data, and illustrate how different read aligners (GSNAP, HISAT2, STAR, TopHat2) affect prediction results. We validate our approach for quantification based on simulated data, and compare local estimates of relative splice variant usage with those from other methods (MISO, Cufflinks) based on simulated and real RNA-seq data. In a proof-of-concept study of splice variants in 16 normal human tissues (Illumina Body Map 2.0) we identify 249 internal exons that belong to known genes but are not related to annotated exons. Using independent RNA samples from 14 matched normal human tissues, we validate 9/9 of these exons by RT-PCR and 216/249 by paired-end RNA-seq (2 x 250 bp). These results indicate that de novo prediction of splice variants remains beneficial even in well-studied systems. An implementation of our method is freely available as an R/Bioconductor package SGSeq.

  Study EGAS00001001026

• 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

• The genomic landscape of pediatric acute lymphoblastic leukemia

  Acute lymphoblastic leukemia (ALL) is the most common pediatric cancer and arises from B- or T-lineage lymphocyte precursors. ALL comprises dozens of subtypes, and genomic analyses have largely been performed within these subtypes. Here we analyze pediatric ALL genomes across all subtypes, including 768 whole genomes, 1,729 exomes, and 1,889 transcriptomes in 2,754 patients. Most ALL subtypes harbor 4 or more driver alterations per sample, similar to adult cancers, despite low mutation burdens. Hyperdiploid B-ALL copy gains are likely acquired early and synchronously, with copy gains occurring before ultraviolet-induced mutations. By contrast, ultraviolet-induced mutations precede copy gains in iAMP21 B-ALL. Overall, we identified 378 putative ALL driver genes. Most driver alterations vary in prevalence across ALL subtypes, with B-ALL enriched for Ras and B-lineage-related alterations, and T-ALL enriched for PI3K, JAK, and cell cycle alterations. Most B-ALL (54.3%) and T-ALL (51.2%) samples bear at least one rare driver gene alteration (present in less than 2% of samples), including 30 putative novel cancer driver genes associated with ubiquitination, SUMOylation, non-coding, and other functions. Known or novel alterations associated with poor outcomes in specific subtypes include TBL1XR1 alterations in ETV6-RUNX1 patients, CREBBP in Ph-like-CRLF2, SETD2 in hyperdiploid, and PTEN in TAL1 patients. Intriguingly, DUX4 and KMT2A subtypes separate into CEBPA/FLT3- or NFATC4-expressing subgroups with potential clinical implications. Together, these results deepen understanding of ALL etiology and outcomes, and facilitate ALL model development.

  Study EGAS00001005250

• Phylogenetic analysis of treatment-naive metastases using whole exome and genome sequencing data

  Metastases are responsible for the majority of cancer related deaths and are often difficult to treat successfully. Even for metastases that occur subsequent to treatment, we do not know whether such relapsing metastases were originally heterogeneous or if the observed heterogeneity is a consequence of therapy. Given that treatment can influence evolutionary dynamics by selecting resistant clones, imposing bottlenecks on cancer cell populations, and even inducing novel somatic mutations, characterizing the prior standing variation among metastases remains an important goal to predict initial therapeutic response. To quantify the heterogeneity at clinical presentation of advanced disease, we surveyed the literature for patients in which at least two treatment-naïve metastases underwent genome/exome-wide sequencing. Across all cancer types surveyed, only 18 subjects were found to fulfill this requirement. Including previously unpublished data from two subjects, we analyzed data of 74 untreated metastases and inferred cancer phylogenies. Putative driver gene mutations were acquired at a 2-fold higher rate on the trunk of all metastases than on branches. Mutations in driver genes along the trunk were strongly enriched for predicted functional consequences. Using a stochastic mathematical model, we find that driver gene heterogeneity among metastases mostly occurs in slowly growing cancers for highly advantageous driver gene mutations. Seeding efficiency only weakly affects the heterogeneity among metastases. These results explain why functional driver gene heterogeneity is uncommon in advanced disease prior to treatment, thus providing optimism for future therapies that depend on mutations across metastases.

  Study EGAS00001002777

• 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

• Somatic mutations predict an aggressive phenotype in meningioma but do not drive grade progression

  A subset of meningiomas progress in histopathological grade and drivers of progression are poorly understood. We aimed to identify somatic mutations and copy number alterations (CNAs) associated with grade progression in a unique matched tumour dataset. Utilising a prospective database, we identified 10 patients with meningiomas that had undergone grade progression and for whom matched pre- and post-progression tissue (n=50 samples) was available for targeted next-generation sequencing. Mutations in NF2 were identified in 4/10 patients, 94% were non-skull base tumours. In one patient, three different NF2 mutations were identified in four tumours. NF2 mutated tumours showed large scale CNAs, with highly recurrent losses in 1p, 10, 22q, and frequent CNAs on chromosomes 2, 3 and 4. There was a correlation between grade and CNAs in a subset of patients. In two patients with sphenoid wing Grade III tumours without detected NF2 mutations, a STAT6-NAB2 inversion was identified. Two patients with tumours without detected NF2 mutations showed a combination of loss and high gain on chromosome 17q. Mutations in SETD2, TP53, TERT promoter and NF2 were not uniform across recurrent tumours and did not correspond with grade progression. Meningiomas that progress in grade generally have a mutational profile already detectable in the pre-progressed tumour, suggesting an aggressive phenotype . CNA profiling shows frequent alterations in NF2 mutated tumours compared to non NF2 mutated tumours and the pattern of CNAs may be associated with grade progression in a subset of cases.

  Study EGAS00001006585

• Evaluation of EBUS-TBNA Aspirates from Advanced NSCLC for Comprehensive Sequencing Platforms Including Whole Genome Sequencing

  Endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) is often the only source of tumor tissue from patients with advanced, inoperable lung cancer. EBUS-TBNA aspirates are used for the diagnosis, staging, and genomic testing to inform therapy options. Here we extracted DNA and RNA from 220 EBUS-TBNA aspirates to evaluate their suitability for whole genome (WGS), whole exome (WES), and comprehensive panel sequencing. For a subset of 40 cases, the same nucleic acid extraction was sequenced using WGS, WES, and the TruSight Oncology 500 assay. Genomic features were compared between sequencing platforms and compared with those reported by clinical testing. A total of 204 aspirates (92.7%) had sufficient DNA (100 ng) for comprehensive panel sequencing, and 109 aspirates (49.5%) had sufficient material for WGS. Comprehensive sequencing platforms detected all seven clinically reported tier 1 actionable mutations, an additional three (7%) tier 1 mutations, six (15%) tier 2–3 mutations, and biomarkers of potential immunotherapy benefit (tumor mutation burden and microsatellite instability). As expected, WGS was more suited for the detection and discovery of emerging novel biomarkers of treatment response. WGS could be performed in half of all EBUS-TBNA aspirates, which points to the enormous potential of EBUS-TBNA as source material for large, well-curated discovery-based studies for novel and more effective predictors of treatment response. Comprehensive panel sequencing is possible in the vast majority of fresh EBUS-TBNA aspirates and enhances the detection of actionable mutations over current clinical testing.

  Study EGAS00001007708

• Targeted Myeloid DNA-Panelsequencing, MLL

  Sequencing data from a targeted myeloid DNA-Panelsequnencing at the MLL Dx, Munich lab. Targeted sequencing was performed using the Nextera DNA Flex library preparation kit, starting with 100ng of genomic DNA (Illumina, San Diego, CA, USA). The target regions were enriched by a custom xGen Lockdown panel using a hybridization capture workflow (IDT Integrated DNA Technologies, Coralville, IA, USA). All libraries were sequenced with 100bp paired-end reads on a NovaSeq6000 (Illumina) with a mean coverage of 3206x. Somatic variant calling was performed with Pisces and a sensitivity cut off of 2%. Large deletions and medium-sized insertions, as they are for example found in CALR and FLT3, were called with Pindel. Variant annotation considered the publicly available data bases Cosmic (v91), ClinVar (2020-03), gnomAd (non-cancer, v2.1.1), dbNSFP (v3.5) and UMD TP53 (2017_R2). Variants that are described as somatic, protein truncating or affecting splice sites were considered as mutations while variants with no or discrepant data base information were considered as variant of uncertain significance.

  Dataset EGAD00001008485

• RNA-seq study of human long-term and short-term hematopoietic stem cells from umblical cord blood with lentiviral overexpression of S1PR3

  To investigate the molecular and biological pathways altered by S1PR3OE in human hematopoietic stem cells (HSC), we performed RNA-sequencing (RNA-seq) of LT- and ST-HSC 3 days after transduction with control or S1PR3 overexpression (OE) lentiviral vectors. LT-HSC and ST-HSC from 3 pool of CB lin- were FACS-purified, cells were prestimulated for 4 hours and transduced with lentiviral vectors. At day 3, 2000-5300 BFP+ cells were FACS-purified for RNA isolation with a PicoPure kit. We were able to isolate only 1600-1800 BFP+ cells from LT-HSC control samples as opposed to 4000-5400 BFP+ cells from S1PR3OE samples. Thus, we pooled all control BFP+ LT-HSC cells into one sample for RNA-seq analysis. BFP- LT-HSC from control vector transduction were purified from CB1 as an additional LT-HSC control. Nextera libraries generated from 10 ng RNA from 5 LT-HSC samples (2 controls, 3 S1PR3OE) and 6 ST-HSC samples (3 controls, 3 S1PR3OE) were subjected to 125 bp, paired-end RNA-sequencing on the Illumina HiSeq 2500 with an average of 50 million reads/sample at the Center for Applied Genomics, Sick Kids Hospital.

  Dataset EGAD00001006582