12454 results for "cancer studies using rna-seq"

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• Whole-genome sequences of single-cell derived clonal samples and bulk blood samples from human

  Human single cells were clonally expanded by culture and whole-genome sequenced. This dataset includes 334 clonal samples and 7 blood bulks from seven individuals (DB2, DB3, DB5, DB6, DB8, DB9, DB10). We extracted genomic DNA materials from clonally expanded cells and matched peripheral blood using DNeasy Blood and Tissue kits (Qiagen) according to the protocol. DNA libraries for WGS were generated by an Accel-NGS 2S Plus DNA Library Kit (Swift Biosciences) from 1 µg of genomic DNA materials. WGS was performed on either the Illumina HiSeq X platform or the NovaSeq 6000 platform to generate mean coverage of 25.2X for 374 clonally expanded cells and 94.8X for 7 matched blood tissues.

  Dataset EGAD00001007032

• DNA methylation sequencing profiles of 1538 breast tumors and 244 normal breast tissues

  DNA methylation sequencing profiles of 1538 breast tumors and 244 normal breast tissues. Libraries were prepared using a custom Reduced Representation Bisulfite Sequencing pipeline. Sequencing was performed on the Illumina HiSeq 2500 (v4 chemistry), with single-end reads of 125 bp length. Multiplexing was conducted at the level of 8 samples per lane. FASTQ files are provided for 1538 breast tumors and 244 normal breast tissues. Reference: Batra et al. (2021). DNA methylation landscapes of 1538 breast cancers reveal a replication-linked clock, epigenomic instability and cis-regulation.

  Dataset EGAD00001007976

• IYDP Indonesian Y chromosome Diversity Project

  The IYDP dataset includes BAM files of 126 Y chromosomes extracted from whole genome sequences. These are from individuals from a broad range of Indonesian islands - communities close to mainland Asia through to New Guinea. The original whole genome sequencing libraries were prepared using TruSeq DNA PCR-Free and TruSeq Nano DNA HT kits depending on DNA quantity. 150 bp paired-end sequencing was performed on the Illumina HiSeq X sequencer. Individuals were sequenced to expected mean depth of 30x, with an achieved median depth of raw reads across samples of 43x.

  Dataset EGAD00001008573

• Leiomyosarcoma Whole Genome Sequencing

  DNA was extracted from fresh frozen LMS material for 29 untreated tumors (24 primary tumors, 5 metastatic 13 relapses) and 13 tumors treated with radiation (7 primaries, 6 metastatic relapses). DNA from matched blood was used as a normal reference. Whole-genome sequencing was performed using established protocols on Illumina instruments.

  Dataset EGAD00001007722

• Comprehensive single-cell genome analysis at nucleotide resolution using the PTA Analysis Toolbox

  We developed a comprehensive bioinformatic workflow, called the PTA Analysis Toolbox (PTATO), to accurately detect single base substitutions, insertions-deletions (indels) and structural variants in PTA-based WGS data. PTATO includes a machine learning approach and filtering based on recurrency to distinguish PTA-artefacts from true mutations with high sensitivity (up to 90%), outperforming existing bioinformatic approaches. Our results show that PTATO enables studying somatic mutagenesis in the genomes of single cells with unprecedented sensitivity and accuracy.

  Study EGAS00001007288

• Characterizing Disease-Causing Variants Using Personal Genomes with Large Recurrent Deletions

  Individuals with recurrent genomic deletions are known to present variable clinical phenotypes, despite the apparent identical range of the genomic segments being affected in their genomes. We propose to study the phenotypic variability and the molecular polymorphism in individuals with the recurrent 17q12 deletions or the recurrent 1q21.1 deletions, with the objective to establish causal relationship between the genotypes and the incompletely penetrant clinical phenotypes. Genome sequencing and phenotypic data from individuals with the deletions and their relatives are included in this submission.

  Study phs002613

• Genomics and Modification of Pain: A peripheral component identified using iPSCs with the S241T mutation

  We have capitalized on inherited erythromelalgia (IEM) as a well-characterized genetic model of chronic pain, and studied IEM patients carrying Nav1.7 mutations which affect channel activation and often produce hyperexcitability of DRG neurons. Whole exome sequencing was used to discover multiple gene variants that might contribute to neuronal excitability and that might serve as modifiers of sensory neuron firing, and identified the Kv7.2 channel as a contributor to differences in pain profiles between individuals.

  Study phs001724

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  Documentation tools

• Integrated analysis of relapsed B-cell precursor Acute Lymphoblastic Leukemia identifies subtype-specific cytokine and metabolic signatures

  Recent efforts reclassified B-Cell Precursor Acute Lymphoblastic Leukemia (BCP-ALL) into more refined subtypes. Nevertheless, outcomes of relapsed BCP-ALL remain unsatisfactory, particularly in adult patients where the molecular basis of relapse is still poorly understood. To elucidate the evolution of relapse in BCP-ALL, we established a comprehensive multi-omics dataset including DNA-sequencing, RNA-sequencing, DNA methylation array and proteome MASS-spec data from matched diagnosis and relapse samples of BCP-ALL patients (n = 50) including the subtypes DUX4, Ph-like and two aneuploid subtypes. Relapse-specific alterations were enriched for chromatin modifiers, nucleotide and steroid metabolism including the novel candidates FPGS, AGBL and ZNF483. The proteome expression analysis unraveled deregulation of metabolic pathways at relapse including the key proteins G6PD, TKT, GPI and PGD. Moreover, we identified a novel relapse-specific gene signature specific for DUX4 BCP-ALL patients highlighting chemotaxis and cytokine environment as a possible driver event at relapse. This study presents novel insights at distinct molecular levels of relapsed BCP-ALL based on a comprehensive multi-omics integrated data set including a valuable proteomics data set. The relapse specific aberrations reveal metabolic signatures on genomic and proteomic levels in BCP-ALL relapse. Furthermore, the chemokine expression signature in DUX4 relapse underscores the distinct status of DUX4-fusion BCP-ALL.

  Study EGAS00001002856

• Transcriptomic analysis of Acute Myeloid Leukemia stem cells

  Acute Myeloid Leukemia (AML) is characterized by the accumulation of clonal myeloid blast cells unable to differentiate into mature leukocytes. Chemotherapy induces remission in the majority of patients, but relapse rates are high and lead to poor clinical outcomes. Since this is primarily caused by chemotherapy-resistant leukemic stem cells (LSCs), it is essential to eradicate LSCs to improve patient survival. LSCs have predominantly been studied at the transcript level, thus lacking information about post-transcriptionally regulated genes and associated networks. Here we extend our previous report on LSC proteomes to healthy age-matched hematopoietic stem and progenitor cells (HSPCs) and correlate the proteomes to the corresponding transcriptomes. By comparing LSCs to leukemic blasts and healthy HSPCs, we validate candidate LSC markers and highlight novel and potentially targetable proteins that are absent or only lowly expressed in HSPCs. In addition, our data provides strong evidence that LSCs harbor a characteristic energy metabolism, adhesion molecule composition, as well as RNA processing properties. Furthermore, correlating proteome and transcript data of the same individual samples highlights the strength of proteome analyses, which are particularly potent in detecting alterations in metabolic pathways. In summary, our study provides a comprehensive proteomic and transcriptomic characterization of functionally validated LSCs, blasts and healthy HSPCs, representing a valuable resource helping to design LSC-directed therapies.

  Study EGAS00001004402