22992 results for "ega"

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• DNTR sequencing data of paediatric acute lymphoblastic leukemia

  This study used the DNTR-seq method in leukaemia samples to profile the whole-genome and mRNA jointly in single cells. Direct tagmentation is used in a collection of single-cell whole genome sequencing (scWGS) methods, including DNTR-seq, which provide high quality data at ultra-low to low coverage. The overall goal was to characterize the genetic and transcriptional heterogeneity of cancer samples. To infer clonal structure and evolutionary history, copy number analysis based workflows were implemented. Bone marrow mononuclear cells from pediatric acute lymphoblastic leukemia samples were FACS sorted into 384 plates to generate the DNA and RNA profiles.

  Study EGAS50000001247

• MorphoITH: A Framework for Deconvolving Intra-Tumor Heterogeneity Using Tissue Morphology

  This study introduces MorphoITH, a framework for deconvolving intra-tumor heterogeneity (ITH) in clear cell renal cell carcinoma (ccRCC) based on tissue morphology from histopathological slides. The study tested MorphoITH's ability to capture different aspects of morphology and to reflect genetic ITH. The data deposited here is derived from a morphology guided multi-regional sequencing dataset used to study the relationship between morphology and genetic evolution. This dataset consists of whole exome sequencing of tumor from multiple sites and adjacent normal samples which were collected from two patients treated in affiliated hospitals of the University of Texas Southwestern Medical Center (UTSW), including Parkland Hospital.

  Study EGAS50000001064

• Whole genome sequencing data of pediatric hypodiploid acute lymphoblastic leukemia

  Hypodiploid acute lymphoblastic leukemia (ALL) is a rare subtype of B-cell ALL characterized by chromosome number < 45 , encompassing near-haploid (24–29 chromosomes) and low-hypodiploid (30–39 chromosomes) subgroups. These subgroups display distinct genetic landscapes, including Ras and receptor tyrosine kinase pathway alterations in near-haploid ALL, and frequent IKZF2, RB1, and germline TP53 alterations in low-hypodiploid ALL. Clinically, hypodiploid ALL is associated with dismal prognosis, with 5-year overall survival rates often between 50-70% in children and markedly worse in adults. Despite advances in risk stratification and MRD-guided therapy, allogeneic stem cell transplantation remains the current standard recommendation for affected patients.

  Study EGAS50000001305

• Multi-omics analysis of treated cancer samples

  We treated patient-derived cell lines with effective drug inhibitors that we discovered. To understand the mechanisms behind how the inhibitor can effectively inhibit tumor growth, we performed a series of RNA-Seq, Histone ChIP-Seq, TF ChIP-Seq and ATAC-Seq profiling for samples with and without treatment with the inhibitor. There are 18 RNA-Seq, 20 ATAC-Seq and 182 ChIP-Seq experiments performed. This includes 2 biological replicates. Novaseq 6000 was used to sequence the samples. Library preparation was performed in house for ChIP-Seq and ATAC-Seq, using NEB indexes, while libraries for RNA-Seq were constructed by the sequencing company hired. Total RNA was sequenced. Sequencing parameters used are PE150, bi-directional sequencing. For ATAC-Seq, sequencing was performed up to 40M reads, for ChIP-Seq, sequencing was performed up to 20M reads and for RNA-Seq, sequencing was performed up to 20M to 40M reads. Fastq files are uploaded here.

  Dataset EGAD50000000349

• Long-read single-cell RNA sequencing uncovers cell-type specific transcript regulation in COVID-19

  SARS-CoV-2 infection leads to extensive host transcriptomic changes, but the role of alternative splicing in shaping the immune response remains underexplored. Here, we present the first application of long-read single-cell RNA sequencing on nasopharyngeal swabs from COVID-19 patients and healthy controls to resolve transcript-level changes across cell types. Leveraging the strengths of long-read sequencing, we characterize alterations in both gene and isoform expression within cell populations of the upper respiratory tract—the primary site of SARS-CoV-2 entry. This approach provides new insights into how transcriptional regulation and splicing shape host immune responses to viral infection.

  Study EGAS50000001290

• Whole genome sequencing data of paediatric T cell acute lymphoblastic leukemia (T-ALL)

  T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive hematologic malignancy accounting for approximately 15–25% of pediatric and adult ALL cases. Despite significant therapeutic improvements over the last decade, the prognosis of T-ALL remains less favorable than that of B-ALL, with 5-year EFS and OS of around 76–82% and 80–88%, respectively, depending on the treatment protocol used. T-ALL patients often suffer from failure of induction therapy or early relapse, which is associated with a dismal prognosis. Approximately 10–15% of T-ALL patients experience relapse, and survival after relapse is poor.

  Study EGAS50000001387

• Multi-modal spatial characterization of tumor-immune microenvironments in diffuse large B-cell lymphoma

  We have leveraged spatial transcriptomics together with proteomic and genomic analysis to investigate the spatial immunology and pathobiology of DLBCL. We define distinct cellular niches that differ in frequency across tumors, related to both Epstein-Barr virus (EBV) infection status and the anatomical site of the tumor, and show that residence within different cellular niches is associated with divergent functional states of T-cells and tumor B-cells due to different patterns of cell-cell communication. This provides a framework for understanding stereotyped patterns of spatial organization in DLBCL and immunological interactions associated with heterogeneity in immune cell infiltration and function across patients.

  Study EGAS50000001146

• CLUSTER RNAseq Study of Juvenile Idiopathic Arthritis patients in methotrexate cohort

  CLUSTER aims to discover novel disease mechanisms and biomarkers in children suffering from Juvenile idiopathic arthritis (JIA). Currently, little is known about the pathological disease mechanisms of JIA and there are no validated tools capable of predicting response or non-response to treatment. The study aims to identify biomarkers for treatment response using RNAseq technology. The samples used in this study comes from blood samples that were collected prior to patients receiving methotrexate treatment (naive). These samples were then processed for PBMC isolation followed by sorting cells into 4 different immune cell types. All of these samples were then sequenced by NovaSeq6000.

  Study EGAS50000000995

• scRNAseq analysis of CD8 T cells infiltrating the bladder and tumor of 4 non-muscle-invasive bladder cancer patients, before and after BCG treatment.

  We performed scRNAseq analysis of CD8 T cells infiltrating the bladder and tumor of 4 non-muscle-invasive bladder cancer patients, before and after BCG treatment. In order to identify tumor-specific T cells, we selected CD8 T cells that were enriched in the tumor of the patient. We also selected CD8 T cells appearing in the bladder after BCG treatment, with the hypothesis that BCG treatment stimulates tumor-specific CD8 T cells. Next, we cloned the TCR of these T cells in a Jurkat cell line and tested these TCR for recognition of tumor-specific antigens.

  Study EGAS50000001384

• CLUSTER Read-counts matrix of RNAseq Datasets of JIA in methotrexate cohort

  CLUSTER aims to discover novel disease mechanisms and biomarkers in children suffering from Juvenile idiopathic arthritis (JIA). Currently, little is known about the pathological disease mechanisms of JIA and there are no validated tools capable of predicting response or non-response to treatment. The study aims to identify biomarkers for treatment response using RNAseq technology. The samples used in this study comes from blood samples that were collected prior to patients receiving methotrexate treatment (naive). These samples were then processed for PBMC isolation followed by sorting cells into 4 different immune cell types. All of these samples were then sequenced by NovaSeq6000.

  Study EGAS50000001501