15153 results for "cancer studies using rna-seq"

in 20.38 milliseconds.

• ChIP-Seq of human stimulated and cultured CD4+ Treg cells

  This dataset includes whole genome sequence data for ChIPmentation assays (18 H3K4me3, 20 H3K27ac and 3 input samples) of human stimulated and cultured CD4+ Treg cells.

  Dataset EGAD00001005816

• scRNA-seq dataset of A cycling, progenitor-like cell population at the root of atypical teratoid rhabdoid tumor subtype differentiation trajectories

  Study describing the differentiation trajectory...

  Dataset EGAD00001015545

• Colorectal cancer functional annotation - Micro-C

  Ultra high resolution Micro-C data from multiple colorectal cancer cell lines

  Study EGAS50000000206

• Pancreatic Cancer NGS WGS data

  Whole genome sequencing data for Pancreatic Cancer Samples exploring the tandem duplicator phenotype

  Study EGAS50000001078

• Division of Cancer Evolution National Cancer Center Research Institute Data Access Committee

  Data Access Committee for data from Division of Cancer Evolution, National Cancer Center Research Institute

  Dac EGAC50000000737

• Mutational anysis of breast cancer stem cells

  Exome sequences of breast cancer have been investigated for many patients. Recently it has been shown that there are intra-heterogeneity in tumor tissues. When the tumor cells were sequenced in bulk condition, only the major populations��� (clones���) mutations will be detected. Based on cancer stem theory, each populations��� cells are derived from each cancer stem cells, which their numbers are not so different among different clones. Here, we separated cancer cells into cancer stem cells and non-cancer stem cells exploiting cancer stem cell specific surface markers. By comping two groups��� mutation, we identified mutations, which were only detected in stem cell population. These mutations could be the mutations in cells of small size populations, and maybe the important mutations to understand the heterogeneity of tumor tissues, progression, and/or prediction for the outcome to therapies.

  Study JGAS000304

• WGS-Lung Cancer sample 30 pair

  This study includes 30 paired samples of Korean Lung Cancer paitients. 30 Lung Cancer samples are paired with each normal(Saliva derived for control) sequencing data.The results of this WGS study were analyzed by Mutect and GATK for ranking germline variants and cancer variants to make mutational profile matrix.

  Study EGAS00001001474

• Genomic analysis of Japanese gastric cancer (345 gastric cancers of NCC)

  As a contribution to the International Cancer Genome Consortium, whole exome sequencing of 345 Japanese gastric cancer (345 gastric cancers of NCC) with various histological subtypes have been conducted. This study aims to identify unique and common driver genes and molecular subtypes in Japanese gastric cancer.

  Study EGAS00001002884

• MCO colorectal cancer genomics at UNSW

  This dataset contains DNA sequencing data from 95 colorectal cancer and matched-normal samples. The dataset contains targeted deep sequencing of selected regulatory elements in 95 cancer and matched-normal samples, and data for one sample that was additionally whole-genome sequenced (cancer and matched-normal).

  Study EGAS00001003450

• BRCA Mutation Status Shapes the Microenvironment of Pancreatic Adenocarcinoma

  This study was established in order to address how the stromal landscape is influenced by BRCA-mutated and BRCA Wild-type (WT) pancreatic ductal adenocarcinoma (PDAC). A primary cohort of 12 PDAC patients (7 BRCA-WT and 5 germline BRCA-mut) was analyzed by laser-capture microdissection, RNA-sequencing and multiplexed immunofluorescence.

  Study phs002994

• T-cell receptor repertoire profiling (PBMC)

  This study assessed the TCR repertoire in peripheral blood from patients before, during and after neoadjuvant chemoimmunotherapy. TCR beta chain sequences in RNA from peripheral blood were amplified with the OncomineTM long read assay, templated and sequenced. TCR metrics such as clonality, evenness and diversity were assessed in relation with response metrics.

  Study EGAS50000001137

• T-cell receptor repertoire profiling (FFPE tissue)

  This study assessed the TCR repertoire in tumor tissue from NSCLC patients before, during and after neoadjuvant chemoimmunotherapy. TCR beta chain sequences in RNA from FFPE tissue were amplified with the OncomineTM short read assay, templated and sequenced. TCR metrics such as clonality, evenness and diversity were assessed in relation with response metrics.

  Study EGAS50000001138

• Transcriptomic analysis of hiPSC-derived vascular cells from CADASIL and isogenic control patient lines

  Bulk-RNA sequencing from hiPSC-derived cells (hiPSC; Endothelial Cells; Neural Crests Cells; Vascular Smooth Muscle Cells) from CADASIL patient lines (n=3) and respective isogenic-controls (n=3). CADASIL is a hereditary brain small vessel disease caused by pathogenic variants in the NOTCH3 gene, which lead to deposits of NOTCH3 protein in the walls of small arteries. This causes pathological vessel wall changes including degeneration of vascular smooth muscle cells. To investigate the impact of pathogenic NOTCH3 variants in hiPSC and differentiated cells we performed a bulk-RNA sequencing.

  Dataset EGAD50000002181

• Analysis_of_resistance_to_PLX4032

  We have collected material from a patient who had BrafV600E mutant melanoma that wastreated with PLX4032. We have germline DNA from the patient and DNA and RNA fromdistinct lesions before and after treatment with PLX4032. We would like to exome sequencethese samples to gain a snap shot of the mechanisms of resistance that are operative.

  Study EGAS00001000415

• Hypothalamic transcriptome in Prader-Willi syndrome

  Transcriptional analysis of brain tissue from people with molecularly defined causes of obesity may highlight novel disease mechanisms and therapeutic targets. Prader-Willi syndrome (PWS) is a genetic obesity syndrome characterised by severe hyperphagia. We performed RNA sequencing of the hypothalamus from 4 individuals with PWS and 4 age-matched controls.

  Study EGAS00001002901

• Oncogenic gene fusions in primary colon cancers

  This study represents RNA-sequencing data from 278 primary colon cancers obtained from fresh-frozen tumor sections. The project goal was to identify novel oncogenic gene fusions in these data. In addition, we studied the detected gene fusions at the molecular level and defined their effects on downstream pathways.

  Study EGAS00001002197

• The_Transcriptome_of_PLX4032_resistance

  We have collected material from a patient who had BrafV600E mutant melanoma that wastreated with PLX4032. We have germline DNA from the patient and DNA and RNA fromdistinct lesions before and after treatment with PLX4032. We have transcriptome sequenced these samples to obtain a snap shot of the mechanisms of resistance that are operative.

  Study EGAS00001000413

• Whole-genome and transcriptome sequencing of tumor-stage mycosis fungoides

  Mycosis fungoides (MF) is the most common cutaneous T-cell lymphoma (CTCL), a group of malignancies derived from skin-homing malignant T cells. We subjected tumor biopsies from MF patients to whole-genome sequencing and RNA-sequencing to investigate genomic alterations and deregulated gene expression in the disease.

  Study EGAS00001002860

• The genomic landscape of primary cutaneous anaplastic large cell lymphoma (pcALCL)

  Primary cutaneous anaplastic large cell lymphoma (pcALCL) is the second most common variant of cutaneous T-cell lymphoma. We subjected tumor biopsies from patients with pcALCL to whole-genome sequencing, whole-exome sequencing and RNA-sequencing to investigate genomic alterations and deregulated gene expression in the disease.

  Study EGAS00001004429

• Natural Killer Cell Plasticity During IL-15-driven Homeostatic Proliferation

  Here we performed single-cell RNA sequencing to address repertoire stability and subset plasticity during IL-15 driven homeostatic proliferation. Sorted NK cell subsets representing discrete stages of NK cell differentiation are compared with the corresponding subsets after proliferation and further sorted into two subsets depending on the rate of proliferation.

  Study EGAS00001003946