12345 results for "cancer rna-seq"

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• Transcriptomic profiling of RIRCD patient skeletal muscle, comparing muscle during affected phase to healthy control, and affected patient with and without additional EARS2 mutations.

  Illumina Nextseq total RNA sequencing profiles of skeletal muscle biopsies of 5 affected patients (F3/2M, F4/1F, F5/1M, F2/2F, F2/1M) compared to 6 control (Control040500, Control3509, Control3934, Control3949, Control4994, Control5106) and comparing 3 patients with additional EARS2 mutations (F2/2F, F2/1M, F5/1M) to 2 patients without (F3/2M, F4/1F). Illumina MiSeq total RNA sequencing profiles of skeletal muscle biopsies from patient F3/1M during affected disease phase (4 replicates: F3-1M_Affected_1, F3-1M_Affected_2, F3-1M_Affected_3, F3-1M_Affected_4) compared to recovered phase (F3-1M_Recovered_1, F3-1M_Recovered_2, F3-1M_Recovered_3, F3-1M_Recovered_4).

  Dataset EGAD00001006381

• Oxford Nanopore targeted RNA-based amplicon data of 12 classical HLA genes

  The dataset consists of Oxford Nanopore targeted RNA-based amplicon data of 12 classical HLA genes (HLA-A, -B, -C, -DRA, -DRB1, -DRB3, -DRB4, -DRB5, -DQA1, -DQB1, -DPA1, and DPB1) of 50 healthy individuals. The 12 classical genes were sequenced in two separate gene pools on R9.4 flowcells using MinION sequencer. Per individual, gene pool 1 contains HLA-A, -B, -C, -DRB1, -DRB3, -DRB4, -DRB5, and -DPB1 and gene pool 2 HLA-DRA, -DQA1, -DQB1, and -DPA1. The dataset includes 100 fastq files of Oxford Nanopore 2D reads (50 for gene pool 1 and 50 for gene pool 2).

  Dataset EGAD00001006814

• Whole genome and RNA-sequencing in T-cell acute lymphoblastic leukemia

  Dataset includes whole genome and transcriptomic sequencing data from five T-cell acute lymphoblastic leukemia (T-ALL) patients. Whole genome sequencing has performed from both diagnostic (T-ALL sample) and control (remission sample) samples. RNA-sequencing has performed from diagnostic samples. Samples has been taken from the bone marrow or peripheral blood.

  Dataset EGAD00001008658

• Human Liver Cohort (HLC)

  The Human Liver Cohort (HLC) study aimed to characterize the genetic architecture of gene expression in human liver using genotyping, gene expression profiling, and enzyme activity measurements of Cytochrom P450. The HLC was assembled from a total of 780 liver samples screened. DNA samples were genotyped on the Affymetrix 500K SNP and Illumina 650Y SNP genotyping arrays. Only data from those samples which were collected postmortem are accessible through this submission. These 228 samples represent a subset of the 427 samples included in the Human Liver Cohort Publication (Schadt, Molony et al. 2008, PMID: 18462017). RNA samples were profiled on a custom Agilent 44,000 feature microarray composed of 39,280 oligonucleotide probes targeting transcripts representing 34,266 known and predicted genes, including high-confidence, noncoding RNA sequences. Gene Expression data for the samples from which it could be obtained is available in GEO under accession number GSE9588. Results and networks will be made available for download from Sage Bionetworks.

  Study phs000253

• Functional Genomic Landscape of Acute Myeloid Leukemia

  The implementation of targeted therapies for acute myeloid leukemia has been challenged by complex mutational patterns within and across patients as well as a dearth of pharmacologic agents for most mutational events. The initial findings from the Beat AML program were from a cohort of 672 tumor specimens collected from 562 patients. Additional patients have been added in subsequent versions. We assessed these specimens using whole exome sequencing, RNA-sequencing, and ex vivo drug sensitivity analyses. Our data reveal novel mutational events not previously detected in AML. We show association of drug response with mutational status, including instances of drug sensitivity that are specific to combinatorial mutational events. Integration with RNA-sequencing also revealed gene expression signatures, which predict a role of specific gene networks in drug response. Collectively, this report offers a dataset, accessible by the Beat AML data viewer (www.vizome.org), that can be leveraged to address clinical, genomic, transcriptomic, and functional inquiries into the biology of AML.

  Study phs001657

• Unraveling the heterogeneity of multiple myeloma identifies therapy resistant subpopulation with vulnerability to the splicing pathway intervention

  Intra-tumor heterogeneity underlies the therapy resistance of multiple myeloma (MM). However, its details remain unknown. Here, we performed single-cell RNA sequencing coupled with VDJ targeted sequencing on highly purified bone marrow lineage marker-negative CD38+ MM cells from patients at diagnosis and in remission. This approach successfully subdivided MM cells into distinct clusters, unraveling their heterogeneity and plasticity on the axis of cell surface CD138 expression. Notably, unique clusters were identified in the minor CD138-negative population that resisted therapies. CRISPR/Cas9 screening of upregulated genes in the resistant population identified their vulnerability to the splicing pathway inhibition, among which RNA-binding protein 39 (RBM39) appeared to be overexpressed in the resistant population and involved in aberrant splicing. Genetic and pharmacological inhibition of RBM39 exerted a profound synthetic lethal effect on them. Our results unveil an uncharacterized subpopulation associated with therapy resistance and provide a novel therapeutic strategy targeting the splicing pathway in MM.

  Study JGAS000723

• Somatic mutations in ALS genes in the motor cortex of sporadic ALS patients

  Several lines of evidence suggest that amyotrophic lateral sclerosis (ALS) pathology starts focally and spreads within the central nervous system (CNS). We leveraged DNA and RNA sequencing data from ALS autopsy tissue to explore the presence of somatic mosaic variants in sporadic ALS (sALS) cases. Deep targeted sequencing of known ALS disease genes from motor cortex tissue revealed enrichment of somatic variants in sALS compared to familial ALS (fALS) with a monogenic cause and an increased pathogenicity of mosaic mutations in known ALS mutational hot spots. Experimental validation of the variants identified that the somatic FUS variant p.E516X leads to nucleo-cytoplasmic mislocalization and aggregation. Additionally, somatic variant calling from single-cell RNA-sequencing data of sALS tissue showed an accumulation of somatic variants in excitatory neurons. Collectively, using a multi-modal approach, our findings suggest that somatic mutations within the motor cortex, especially in excitatory neurons, may contribute to the development of sALS.

  Study EGAS00001008104

• Recurrent somatic mutations in POLR2A define a distinct subset of meningiomas

  RNA polymerase II mediates the transcription of all protein-coding genes in eukaryotic cells, a process that is fundamental to life. Genomic mutations in this enzyme have not been previously linked to any pathology in humans, a testament to its indispensable role in cell biology. Based on a combination of next-generation genomic analyses of 775 meningiomas, we report that recurrent somatic p.Gln403Lys or p.Leu438_His439del mutations in POLR2A, which encodes the catalytic subunit of RNA polymerase II1, are sufficient to hijack this essential enzyme and drive neoplasia. POLR2A mutant tumors reveal dysregulation of key meningeal identity genes, including WNT6 and ZIC1/ZIC42,3. In addition to POLR2A, NF2, SMARCB1, TRAF7, KLF4, AKT1, PIK3CA and SMO4-8, we also report somatic mutations in AKT3, PIK3R1, PRKAR1A, and SUFU in meningiomas. Our results identify a role for essential transcriptional machinery in driving tumorigenesis and define mutually exclusive meningioma subgroups with distinct clinical and pathological features.

  Study EGAS00001001916

• Linking the epigenetic landscape in chronic lymphocytic leukemia to deregulated chromatin networks

  Aberrant chromatin features and epigenetic signaling emerge as an important part of the tumor disease state in chronic lymphocytic leukemia (CLL). However, an integrative analysis of the malignant chromatin landscape is currently missing. Here, we mapped DNA-methylation, nucleosome position, 7 histone modifications, ATAC-seq and the transcriptome in primary CD19+ sorted B-cells from the peripheral blood of CLL patients in comparison to non-malignant lymphocytes of healthy donor reference samples. On the > 50 kb scale we identified global differences with respect to DNA methylation, nucleosome positioning and histone modifications in CLL. Furthermore, a chromatin state annotation was developed to identify deregulated chromatin features of promoters and enhancers in CLL. By integrating these findings with an ATAC-seq based transcription factor binding analysis we identified a set of promoters and enhancers specific to CLL that were enriched in certain transcription factors binding motifs and genes of the BCR signaling pathway. Thus, our study provides an in-depth map of the CLL chromatin landscape and links chromatin state changes at promoters and enhancers to deregulated pathways.

  Study EGAS00001002518

• A Single-cell Atlas of Progressive TKI Resistance in Chronic Myeloid Leukemia

  High-dimensional scRNA seq and CyTOF were used to identify features predictive of treatment outcome at diagnosis. An optimal TKI response was characterised by erythroid lineage skewing of the CD34+ HSPC compartment. While TKI-resistant CP was reminiscent of a BC-like state, where HSPCs were enriched for inflammation, stemness and quiescence. We designed a machine-learning approach which assessed the prognostic potential of all 32 sub-populations of our scRNA seq dataset. LSCs and NK populations harboured the highest prognostic power at diagnosis. Within the LSCs, erythroid lineage priming and MYC activation were features of an optimal and poor TKI responses, respectively. With the NK cell compartment, apart from a higher abundance of NK cells in TKI optimal responders, a memory-like HLA-DR+ adaptive NK and KLRC1+ NK populations were hallmarks of an optimal and poor TKI responses, respectively. Mechanistically, both cell intrinsic and extrinsic mechanisms contributed towards the higher sensitivity of EPs to TKI therapy. In summary, our high-dimensional single-cell atlas of TKI resistance highlights pivotal transcriptional features associated with TKI-resistance disease, some of which have the potential to be exploited as biomarkers.

  Study EGAS00001005509