11932 results for "cancer rna-seq"

in 12.90 milliseconds.

• Single cell RNA-seq of two rare cases of human glioblastoma at multiple sampling points

  Glioblastoma is characterized by large cellular diversity whose complexity and organizing principles are only starting to be uncovered. Both neurodevelopment-like and mesenchymal-like cell states have been described in glioblastoma but the nature of the mesenchymal-like cell states remains unresolved. Here, we performed deep single-cell RNA sequencing of two rare glioblastoma cases where tissue could be sampled from tumor core to macroscopically normal cortex with the aim of understanding these tumor cell states.

  Study EGAS50000001030

• RNA-seq profiling of NKX6.1 reporter iPSC lines for isolation and analysis of functionally relevant neuronal and pancreas populations

  We generated human induced pluripotent stem cell (iPSC) lines with a GFP reporter inserted in the endogenous NKX6.1 locus. Characterisation of the reporter lines demonstrated faithful GFP labelling of NKX6.1 expression during pancreas and motor neuron differentiation. We performed three independent in vitro differentiations towards the pancreatic endocrine lineage. We FACS-purified GFP positive and negative cells from stage 7 cultures, and generated Smart-Seq2 RNA-sequencing libraries for the pre-sorted cells, as well as the two GFP-sorted cell populations. Gene expression profiling by RNA-sequencing reveals that the NKX6.1-positive population closely resembles mature human beta cells and the functional evaluation of purified populations shows that the glucose-responsive beta-like cells are enriched within the NKX6.1-positive population. These reporter lines provide a valuable resource to the scientific community for the derivation of functional relevant pancreas and neuronal cell subtypes.

  Dataset EGAD00001003911

• IMCISION RNAseq

  RNA sequencing of 32 primary head and neck squamous cell carcinoma (HNSCC) samples prior to treatment with neoadjuvant anti-PD-1 (n=6) or anti-PD-1 + anti-CTLA-4 (n=26) immunotherapy, and 30 paired on-treatment HNSCC samples (i.e. after neoadjuvant immunotherapy). RNA quantity used: 10ng. Library Preparation Kit: SMART Stranded Total RNA Seq Kit (Takara). Sequencing parameters: NovaSeq 6000, 2x 100 bp. File type: fastQ

  Dataset EGAD00001008127

• RNA-seq dataset: Single-cell spatial analysis of pediatric high-grade glioma reveals a novel population of immunosuppressive and tumor-promoting SPP1+/GPNMB+ myeloid cells

  Our study utilizes two novel techniques, cyclical immunofluorescence imaging and single-cell spatial transcriptomics, to spatially map the tumor microenvironment of a large sample set of pediatric high-grade gliomas (pHGG). Using these methods, we have identified an abundant immunosuppressive myeloid cell population that has not been described in the context of pediatric high-grade gliomas. We validate our findings using an in vitro assay, spatial analysis on additional pHGG biopsies, independent spatial transcriptomic data, bulk RNA sequencing data of an expanded cohort of in-house patients, and publicly available bulk RNA sequencing data of an even larger cohort of pHGG patients.

  Dataset EGAD00001015450

• RNA sequencing of end-stage kidney disease patients with COVID-19

  This dataset contains paired RNA sequencing data for end-stage kidney disease (ESKD) patients on dialysis. There are two cohorts. The first includes 179 samples from 51 COVID-19 patients recruited during the initial phase of the COVID-19 pandemic (April-May 2020) and 55 non-infected ESKD patients as controls. 17 patients initially recruited as controls as part of the Wave 1 cohort were later infected with COVID-19 in January-March 2021. We acquired a total of 90 samples during the acute infection and convalescent samples for 12 of the 17 patients following the acute COVID-19 episode. RNA-seq counts and full clinical metadata for these cohorts are available without restriction from Zenodo (https://doi.org/10.5281/zenodo.6497251).

  Dataset EGAD00001009752

• SCNA-Seq of plasma DNA samples

  Low coverage whole genome sequencing for the identification of somatic copy number alterations (SCNA) and focal amplification mapping in plasma DNA of prostate cancer patients

  Dataset EGAD00001002149

• Diversity of U1 small nuclear RNAs and Evaluation of Diagnostic Methods for their Mutations

  U1 small nuclear RNA (snRNA) mutations are recurrent non-coding alterations found in various malignancies, including medulloblastoma, yet their identification has proven challenging due to their repetitive nature. To establish a robust DNA-based, and RNA-based method for detecting U1 snRNA mutations, we performed targeted DNA sequencing using our original gene panel for medulloblastoma and RNA-sequencing. As an RNA-based method, we developed a random forest classifier employing splicing patterns which were massively altered as a result of U1 snRNA mutations. By using both methods, we successfully detected U1 snRNA mutation in five DNA samples and four RNA samples.

  Study EGAS50000000693

• Circulating tumor DNA, pathological and immunologic responses to neoadjuvant nivolumab or nivolumab plus relatlimab and chemoradiotherapy in resectable esophageal/gastroesophageal junction cancer

  The dataset for the study “Circulating tumor DNA, pathological and immunologic responses to neoadjuvant nivolumab or nivolumab plus relatlimab and chemoradiotherapy in resectable esophageal/gastroesophageal junction cancer” includes 173 bam files from hybrid capture targeted error-correction next-generation sequencing (TEC-Seq) from plasma cell-free DNA and matched white blood cell DNA from 32 individuals with esophageal/gastroesophageal junction cancer, who received immunotherapy-containing regimens.

  Dataset EGAD00001011822

• Pancreatic islets PISA RNA-seq samples

  GWAS have identified more than 700 genetic signals associated with type 2 diabetes (T2D). To gain insight into the underlying molecular mechanisms, we created the Translational human pancreatic Islet Genotype tissue-Expression Resource (TIGER), aggregating >500 human islet RNA-seq and genotyping datasets. We imputed genotypes using 4 reference panels and meta-analyzed cohorts to improve coverage of expression quantitative trait loci (eQTL) and developed a method to combine allele-specific expression across samples (cASE). We identified >1 million islet eQTLs (56% novel), of which 53 colocalize with T2D signals (60% novel). Among them, a low-frequency allele that reduces T2D risk by half increases CCND2 expression. We identified 8 novel cASE colocalizations, among which an SLC30A8 T2D associated variant. We make all the data available through the open-access TIGER portal (http://tiger.bsc.es), which represents a comprehensive human islet genomic data resource to elucidate how genetic variation affects islet function and translate this into therapeutic insight and precision medicine for T2D.

  Study EGAS00001005535

• Spatially Resolved Tumor Ecosystems and Cell States in Gastric Adenocarcinoma Progression and Evolution

  Gastric cancer (GC) is a major cause of global cancer mortality with high levels of heterogeneity, and intratumoral heterogeneity (ITH) represents a significant barrier to GC patient outcomes. In this study, we applied GeoMx DSP technology to identify ITH in GC. We found spatially colocalized RNA-based intratumor subgroups within samples, each correlated with distinct spatially oriented TME and immune profiles. The findings broadening our understanding of the spatial and molecular complexity of GC ITH and offering a valuable data resource for future exploration and discovery.

  Study EGAS50000000345