15152 results for "cancer studies using rna-seq"

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• Whole-genome sequencing of high-grade serous ovarian cancer (HGSC) tumours and matched normals from long-term survivors.

  Whole-genome sequencing of high-grade serous ovarian cancer (HGSC) tumours and matched normals from long-term survivors performed as part of the Multidisciplinary Ovarian Cancer Outcomes Group (MOCOG) study. The dataset includes fastq files from 58 HGSC tumours (53 primary tumours and 5 recurrent tumours) and 53 matched normals from 53 long-term survivor patients. Sequence libraries were generated from tumour and matched normal genomic DNA using the KAPA HyperPrep PCR-free library preparation kit (Roche) according to manufacturer’s instructions. Sequencing was carried out by the Kinghorn Centre for Clinical Genomics Sequencing Laboratory (Sydney, Australia) on the HiSeq X Ten System (Illumina) to a minimum base coverage of 30-fold for normal DNA and 60-fold for tumour DNA samples.

  Dataset EGAD00001009398

• Bioinformatic Methods and Bridging of Assay Results for Reliable Tumor Mutational Burden Assessment in Non-Small Cell Lung Cancer

  Tumor mutational burden (TMB) has emerged as a predictive biomarker of response to immune checkpoint inhibitors. Standardization of TMB measurement is essential for implementing diagnostic tools to guide treatment. Here we evaluate bioinformatic TMB analysis by whole exome sequencing (WES) in formalin-fixed, paraffin-embedded samples. In CheckMate 026, TMB was retrospectively assessed in 312 patients with non-small cell lung cancer (58% of the intent-to-treat population) who received first-line nivolumab treatment or chemotherapy. We examined the sensitivity of TMB assessment to bioinformatic filtering methods and assessed concordance between TMB data derived by WES and the FoundationOne CDx™ assay. TMB scores comprising synonymous, indel, frameshift, and nonsense mutations (all mutations) were 3.1-fold higher than data including missense mutations only, but values were highly correlated (Spearman’s r = 0.99). Scores from CheckMate 026 samples including missense mutations only were similar to those generated from data in The Cancer Genome Atlas, but those including all mutations were generally higher. Using databases for germline subtraction (instead of matched controls) showed a trend for race-dependent increases in TMB scores. Parameter variation can therefore impact TMB calculations, highlighting the need for standardization. Encouragingly, WES and FoundationOne CDx outputs were highly correlated (Spearman’s r = 0.90) and differences could be accounted for by empirical calibration, suggesting that reliable TMB assessment across assays, platforms and centers is achievable.

  Dataset EGAD00001005035

• Linked-Read Whole Genome Sequencing Profiles Structural Variant Landscape of Gliomas with Barcode-Level Evidence

  Structural variants (SVs) play essential roles in glioma oncogenesis and offer prognostic insights, yet the SV landscape of gliomas has not been completely characterized due to previous technological limitations. To comprehensively profile the SV landscape of gliomas, we performed linked-read whole genome sequencing (LR-WGS) on 31 tumour samples from 20 glioma patients. Using barcode-level evidence, we validated known SVs and identified the presence of extrachromosomal DNA containing the EGFR sequence, which correlates with elevated EGFR expression. Additionally, we uncovered rare SVs affecting genes typically mutated by single nucleotide variants (SNVs), including those in the SWI/SNF chromatin remodeling complex. Our analysis also reveals selective chromosomal vulnerabilities to SVs, highlighting certain chromosomes as hotspots for SV accumulation. Collectively, our results demonstrate the utility of LR-WGS in accurately detecting SVs and thoroughly profiling SV landscapes using barcode-level evidence. The insights gained into the synergistic effects of SNVs and SVs on oncogenes further underscore the importance of integrating SV analysis when examining mutations in gliomas.

  Study EGAS50000000947

• Exome-wide analysis identifies three low-frequency missense variants associated with pancreatic cancer risk in Chinese populations

  Germline coding variants have not been systematically investigated for pancreatic ductal adenocarcinoma (PDAC). Here, we report an exome-wide investigation using the Illumina Human Exome Beadchip with 943 PDAC cases and 3,908 controls in the Chinese population, followed by two independent replicate samples including 2,142 cases and 4,697 controls. We identify three low-frequency missense variants associated with the PDAC risk: rs34309238 in PKN1 (OR = 1.77, 95% CI: 1.48-2.12, P = 5.35 X 10-10), rs2242241 in DOK2 (OR = 1.85, 95% CI: 1.50-2.27, P = 4.34 X 10-9) and rs183117027 in APOB (OR = 2.34, 95% CI: 1.72-3.16, P = 4.21 X 10-8).

  Study EGAS00001003040

• Liver biopsy derived induced pluripotent stem cells provide an unlimited supply for the generation of patient-specific hepatocyte-like cells

  Background: Hepatocyte-like cells (HLCs) differentiated from induced pluripotent stem cells (iPSCs) have emerged as a promising cell culture model to study metabolism, biotransformation, viral infections and genetic liver diseases. However the derivation of iPSCs is restricted by ethical and procedural constraints. Furthermore, incomplete HLC differentiation remains a major challenge. iPSC may carry-on a tissue of origin dependent expression memory influencing iPSC differentiation into different cell types. If liver derived iPSCs (Li-iPSCs) maintain a liver specific gene expression profile is not known. It is also not known, if Li-iPSCs would allow the generation of more fully differentiated HLCs.Methods: Primary liver cells (PLCs) were expanded from liver needle biopsies and reprogrammed into Li-iPSCs using a non-integrative Sendai virus-based system. Li-iPSCs were differentiated into HLCs using established differentiation protocols. The HLC phenotype was characterized at the protein, functional and transcriptional level. RNA sequencing data were generated from the originating liver biopsies, the Li-iPSCs, fibroblast derived iPSCs, and differentiated HLCs, and used to characterize and compare their transcriptome profiles.Results: PLCs were obtained from small pieces of liver biopsies and could be reprogrammed into Li-iPSCs. Li-iPSCs indeed retain a liver specific transcriptional footprint. Li-iPSCs can be propagated to provide an unlimited supply of cells for differentiation into Li-HLCs. Similar to HLCs derived from fibroblasts, Li-HLCs could not be fully differentiated into hepatocytes. Relative to the originating liver, Li-HLCs showed lower expression of liver specific transcription factors and increased expression of genes involved in the differentiation of other tissues.Conclusions: PLCs and Li-iPSCs obtained from small pieces of human needle liver biopsies constitute a novel unlimited source for the production of HLCs. Despite the preservation of a liver specific gene expression footprint in Li-iPSCs, the generation of fully differentiated hepatocytes cannot be achieved with the current differentiation protocols.

  Study EGAS00001002676

• T-cell receptor sequencing of tumor-infiltrating lymphocytes (TIL) in breast cancer

  The spatial distribution of tumor-infiltrating lymphocytes (TIL) predicts breast cancer outcome and response to systemic therapy, highlighting the importance of an intact tissue structure for characterizing patients’ tumors. Here, we present ST-FFPE, a spatial transcriptomics method for the analysis of formalin-fixed paraffin-embedded samples, which opens the possibility of interrogating widely available archival tissue. The method involves extraction, exome capture and sequencing of RNA from different tumor compartments microdissected by laser-capture, and can be used to study the cellular composition of various tumor environments. Focusing on triple-negative breast cancer (TNBC), we characterized T cells, B cells, dendritic cells, fibroblasts and endothelial cells in both stromal and intra-epithelial compartments. We found a highly variable spatial distribution of immune cell subsets among tumors. This analysis revealed that the immune repertoires of intra-epithelial T and B cells were consistently less diverse than those of stromal T and B cells. T-cell receptor (TCR) sequencing confirmed a reduced diversity and revealed higher clonality of intra-epithelial T cells relative to the corresponding stromal T cells. Analysis of the top ten dominant clonotypes in the two compartments showed a majority of shared but also some unique clonotypes both in stromal and intra-epithelial T cells. Hyperexpanded clonotypes were more abundant among intra-epithelial than stromal T cells. These findings validate the ST-FFPE method and suggest an accumulation of antigen-specific T cells within tumor core. Because ST-FFPE is readily applicable for analysis of previously collected tissue samples, it could be useful for rapid assessment of intratumoral cellular heterogeneity in multiple disease and treatment settings.

  Study EGAS00001007125

• scATAC-seq of sorted CD45+ cells from blood and tissues

  scATAC-seq by 10xGenomics Droplet Sequencing from two human donors. scATAC sequences are available for FACS-sorted CD45+ cells from blodd, skin and vat (visceral adipose tissue)

  Dataset EGAD50000000510

• Cell subtypes subsets from subcortical MS snRNA-seq atlas

  Curated subsetting of cell subtypes derived from the 9 principal cell types within our subcortical Multiple Sclerosis (MS) lesions snRNA-seq atlas.

  Dataset EGAD50000000522

• A distinct monocyte cellular state links systemic immune dysregulation to pulmonary impairment in long COVID

  single cell multiome dataset (snRNA-seq + snATAC-seq) from PBMC of patients with long COVID disease.

  Dataset EGAD50000001729

• ATAC-seq dataset

  This dataset contains ATAC-seq data performed in MM.1S cell line in ETOH (control) or Dexamethasone condition (Treatment)

  Dataset EGAD00001011135

• UCSF brain tumor data

  Single Nuclei ATAC seq data from GBM tumor samples. NovaSeq6000 was used for ATAC seq. The files uploaded are bam files created with grch38 reference.

  Dataset EGAD00001005314

• 4C-seq data

  4C-seq data was generated for regions of interest to confirm enhancer-gene promoter interactions

  Dataset EGAD00001001847

• Whole-genome-sequencing, Whole-exome-sequencing and RNA-sequencing in Sporadic ALS

  To identify the genetic cause and modifiers of Sporadic ALS, we performed Whole-genome-sequencing, Whole-exome-sequencing and RNA-sequencing of Sporadic ALS patients.

  Study JGAS000393

• ICR_RNASeq_pHGG

  RNA sequencing of paediatric high grade gliomas and diffuse intrinsic pontine gliomas. RNA was sequenced from fresh frozen surgical material or from primary cells cultured under stem cell conditions. RNA was subjected to Illumina whole transcriptome paired end sequencing. Data is provided as paired-end FASTQ files

  Dataset EGAD00001004116

• Human embryo ATAC+RNA single cell sequencing samples DAC (Linnarsson)

  DAC for human embryo ATAC+RNA single cell sequencing samples

  Dac EGAC50000000657

• TARGET-seq+ single-cell genotyping

  Single-cell genotyping data for bone marrow samples from 9 cases with clonal hematopoiesis and 1 control sample. The TARGET-seq+ protocol was used to generate plate-based 3' transcriptome data. For details on cell sorting and the TARGET-seq+ protocol see the methods section of the manuscript. One FASTQ file is provided per cell. Cells are named with their plate and well IDs and the subject ID. Empty wells (no-cell controls) are named "blank". Corresponding transcriptome files use the same naming with the "_transcriptome" suffix.

  Dataset EGAD00001011150

• BLUEPRINT September 2016, ChIP-Seq for conventional dendritic cell from cord blood, on Genome GRCh38

  ChIP-Seq data for 1 sample(s) for conventional dendritic cell from cord blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001002948

• BLUEPRINT September 2016, ChIP-Seq Acute Lymphocytic Leukemia for precursor B cell from venous blood, on Genome GRCh38

  ChIP-Seq data for 1 sample(s) Acute Lymphocytic Leukemia for precursor B cell from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001002949

• BLUEPRINT September 2016, ChIP-Seq for memory B cell from venous blood, on Genome GRCh38

  ChIP-Seq data for 1 sample(s) for memory B cell from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001002950

• BLUEPRINT September 2016, ChIP-Seq T-cell Acute Lymphocytic Leukemia from capillary blood, on Genome GRCh38

  ChIP-Seq data for 4 sample(s) T-cell Acute Lymphocytic Leukemia from capillary blood, on Genome GRCh38. 7 run(s), 7 experiment(s), 7 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001002952

• Clonal fitness inferred from timeseries modeling of single cell cancer genomes

  Progress in defining genomic fitness landscapes in cancer by copy number alterations (CNA) has been impeded by lack of single cell and timeseries sampling. We generated 42,000 single cell whole genomes (scWGS) from breast epithelium and primary triple negative breast cancer (TNBC) patient-derived xenografts (PDX) collected during multi-year time series. Using a Wright-Fisher population genetics model, we inferred reproducible CNA-defined clonal fitness dynamics induced by TP53 mutation and cisplatin chemotherapy, with accurate forecasting of experimentally enforced clonal competition dynamics. Drug treatment in three long-term serially passaged TNBC PDX resulted in cisplatin resistant clones that had shown low fitness in the untreated setting. By contrast high fitness clones from treatment naive controls were eradicated reflecting an inversion of the fitness landscape. Upon drug release selective pressure dynamics were reversed indicating a fitness cost of treatment resistance. Taken together, our findings reveal clonal fitness dynamics linked to CNA and therapeutic resistance in polyclonal tumours.

  Study EGAS00001004448

• 41 fibroblast RNAseq samples of pediatric patients with childhood epilepsy and developmental delay

  We used RNA sequencing of patient fibroblasts to find a genetic diagnosis in patients with exome-negative childhood epilepsy. RNA extracted from 41 individuals' cultured fibroblasts (passage 3-6) was collected and sequenced at a depth of 90-110 paired reads per sample.

  Study EGAS50000000792

• Primary_DIPG_expression_profiles

  In this study, we used RNA-sequencing gene expression profiling in order to characterize specific phenotypic traits in DIPG. Seventeen primary tumor samples stereotactically biopsied at diagnosis by neurosurgeons in the Necker-Enfants Malades hospital (Paris, France) and snap-frozen for RNA extraction and subsequent poly-A mRNA purification.

  Study EGAS00001007181

• The mutational landscape of normal human endometrial epithelium - Additional Samples

  All normal somatic cells are thought to acquire mutations but understanding of the rates, patterns, causes and consequences of somatic mutation in normal cells is limited. Uterine endometrium adopts multiple physiological states over a lifetime and is lined by a gland-forming epithelium. Whole genome sequencing of normal endometrial glands from women aged 19 to 81 years showed them to be clonal cell populations derived from recent common ancestors, with total mutation burdens that increase with age at ~29 base substitutions/year and which are many-fold lower than endometrial cancers. Normal endometrial glands frequently carry driver mutations in cancer genes. Driver mutation burdens increase with age and correlate negatively with parity. Phylogenetic trees of normal endometrial glands constructed using whole genome sequences indicated that clones with drivers often originate during the first decades and spread to colonise the endometrial epithelial lining. The results show that driver mutation landscapes differ between normal cell types, perhaps shaped by differences in normal tissue physiology, and suggest that the procession of neoplastic changes leading to endometrial cancer is initiated early in life.

  Dataset EGAD00001005214

• cfDNA analysis reveals relation of POLR1D amplification to bevacizumab resistance in colorectal cancer patients

  Bevacizumab is an approved anti-angiogenic drug for patients with metastasized colorectal cancer (mCRC) targeting VEGF. The survival benefit of anti-VEGF therapy in mCRC patients is limited to a few months and acquired resistance mechanisms are greatly unknown. Using plasma DNA, we studied the evolution of tumor genomes in a cohort of patients with mCRC (n=150) and observed a recurrent focal amplification (8.7% of cases) on chromosome 13q12.2. Analysis of TCGA data (n=619) suggested an association with later stages, which we confirmed by longitudinal plasma analyses. We defined the minimally amplified region and studied the mechanistic consequences of copy number gain of the involved genes. The amplification of one gene, POLR1D, impacted cell proliferation, resulting in upregulation of VEGFA, an important regulator of angiogenesis which has been implicated in the resistance to bevacizumab. In several patients, we observed the emergence of this 13q12.2 amplicon under bevacizumab treatment, which was invariably associated with evolution of therapy resistance. Hence, we describe a novel resistance mechanism against a widely applied treatment in mCRC patients which will impact clinical management .

  Dataset EGAD00001005761