9295 results for "cancer rna-seq"

in 27.95 milliseconds.

• RNA-sequencing of blastic plasmacytoid dendritic cell neoplasm

  RNA sequencing of frozen tumor biopsies from patients with blastic plasmacytoid dendritic cell neoplasm. 4 samples. Illumina HiSeq 4000.

  Dataset EGAD00001005031

• sc-RNA and sc-BCR sequencing of multiple myeloma and precursors

  bam files of sc-RNA and sc-BCR sequencing of multiple myeloma and precursors from 65 samples

  Dataset EGAD00001009648

• Single-cell RNA and TCR sequencing of 40 advanced HCC biopsies.

  Single-cell RNA and TCR sequencing of 40 advanced HCC pre-treatment biopsies from 38 patients.

  Dataset EGAD00001011347

• Whole genome and RNA sequencing of cutaneous melanoma metastases

  Whole genome sequencing of cutaneous melanoma skin and brain metastases and matched normal DNA, as well as RNA sequencing of material from the skin and brain metastases. In addition, RNA sequencing was performed for Dabrafenib and Trametinib treated patient-derived xenografts, together with untreated and vehicle treated controls.

  Dataset EGAD00001004130

• RNA sequencing of a glioblastoma PDX cohort

  Patient-derived xenograft (PDX) models represent an essential tool for the preclinical evaluation of novel targeted therapies and their combinations. In this project, we molecularly characterized a comprehensive panel of glioma PDX models with well conserved molecular and pathological features over multiple passages. PDX samples were subjected to next generation sequencing (NGS). Characterization of cancer-relevant features including driver mutations or cellular processes was performed using mutational and gene expression data in order to identify potential biomarker or treatment targets in glioblastoma. In summary, we reported a newly established and molecularly characterized panel of glioma PDX models with high relevance for translational preclinical research.

  Study EGAS00001007119

• DNA Methylation and Microbiome Profiles from Colorectal Cancer Patients and Healthy Controls

  This dataset contains DNA methylation data and gut microbiome profiles derived from tumor biopsies, matched blood samples, and stool samples collected from 200 Swedish participants (150 colorectal cancer patients and 50 healthy controls) between 2020 and 2023. For DNA methylation profiling, genomic DNA was extracted from tumor tissues and blood samples using the Qiagen AllPrep DNA/RNA Kit and analyzed with the Illumina Infinium MethylationEPIC BeadChip. This approach captures more than 850,000 methylation sites across the genome. In parallel, stool samples were collected prior to treatment, and microbial DNA was extracted using the Qiagen QIAamp Fast DNA Stool Kit. 16S rRNA gene sequencing was performed on the Illumina MiSeq platform to characterize the gut microbiome composition in patients and controls. The resulting dataset includes: Methylation array data in IDAT format (~120 GB total) Normalized methylation matrices in CSV format (~15 GB) 16S rRNA microbiome data in FASTQ format (~250 GB total) Microbiome abundance tables in TSV format (~2 GB) All data are stored in FEGA Sweden under controlled access, and access requests will be reviewed by the Lund University RDO as the data controller. Ethical approval was obtained from the Swedish Ethical Review Authority (Dnr: 2023-04567).

  Dataset EGAD50000000156

• 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

• Genomic features of Helicobacter pylori-na��ve diffuse-type gastric cancer.

  Helicobacter pylori (HP) is a major etiologic driver of diffuse-type gastric cancer (DGC).However, improvements in hygiene have led to an increase in the prevalence of HP-na��ve DGC;that is, DGC that occurs independent of HP. Although multiple genomic cohort studies forgastric cancer have been conducted, including studies for DGC, distinctive genomic differencesbetween HP-exposed and HP-na��ve DGC remain largely unknown. Here, we employed exomeand RNA sequencing with immunohistochemical analyses to perform binary comparisonsbetween 36 HP-exposed and 27 HP-na��ve DGCs from sporadic, early-stage, and intramucosal orsubmucosal tumor samples. Among the samples, 33 HP-exposed and 17 HP-na��ve samples hadbeen preserved as fresh-frozen samples. HP infection status was determined using stringentcriteria. HP-exposed DGCs exhibited an increased single nucleotide variant burden (HP-exposed DGCs; 1.97 [0.48���7.19] and HP-na��ve DGCs; 1.09 [0.38���3.68] per megabase;p=0.0003) and a higher prevalence of chromosome arm-level aneuploidies (p<0.0001). CDH1was mutated at similar frequencies in both groups, whereas RHOA���ARHGAP pathwaymisregulation was exclusive to HP-exposed DGCs (p=0.0167). HP-exposed DGCs showedgains in chromosome arms 8p/8q (p<0.0001), 7p (p=0.0035) and 7q (p=0.0354), and losses in16q (p=0.0167). Immunohistochemical analyses revealed a higher expression of intestinalmarkers such as CD10 (p<0.0001) and CDX2 (p=0.0002) and a lower expression of the gastricmarker, MUC5AC (p=0.0305) among HP-exposed DGCs. HP-na��ve DGCs, on the other hand,had a purely gastric marker phenotype. This work reveals that HP-na��ve and HP-exposed DGCsdevelop along different molecular pathways, which provide a basis for early detection strategiesin high incidence settings.

  Study JGAS000575

• BLUEPRINT September 2016, ATAC-seq for osteoclast from venous blood, on Genome GRCh38

  ATAC-seq data for 2 sample(s) for osteoclast from venous blood, on Genome GRCh38. 2 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002907

• BLUEPRINT September 2016, ATAC-seq Mantle Cell Lymphoma from venous blood, on Genome GRCh38

  ATAC-seq data for 5 sample(s) Mantle Cell Lymphoma from venous blood, on Genome GRCh38. 5 run(s), 5 experiment(s), 5 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002918