9337 results for "cancer rna-seq"

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• Chromatin accessibility (ATAC-seq) and transcriptome (RNA-seq) data from immune cells for healthy young and healthy old subjects

  Dataset consisting of: (1) N=234 genome-wide chromatin accessibility (ATAC-seq) profiles for distinct N=21 healthy old and N=28 healthy young subjects. ATAC-seq biological samples provided for the following tissues: PBMC (N=24), CD14+ monocytes (N=18), CD8+ memory T cells (N=7), CD8+ naive T cells (N=7), CD4+ memory T cells (N=7), CD4+ naive T cells (N=7), and naive B cells (N=7). (2) N=39 genome-wide transcription (RNA-seq) data for distinct N=15 healthy old and N=24 healthy young subjects' PBMCs.

  Dataset EGAD00001003602

• RNA-Seq Pair End

  RNA analysis of two patients 11 and 15 with WGS done on Illumina HiSeq2000. For research purpose and authorised user only.

  Dataset EGAD00001003429

• Gene expression analysis for nasal polyps

  The aim of the study is to identify the gene expression profile and biomarkers related with chronic rhinosinusitis with nasal polyps (CRSwNP). RNA-sequencing was performed to identify differentially expressed genes between nasal polyps (NP) and inferior turbinate mucosa from 6 patients with CRSwNP. We validated the RNA-seq results by quantitative real-time PCR.

  Study JGAS000153

• Blood plasma and FFPE derived total RNA seq dataset from DLBCL and PMBCL patients

  Blood plasma samples (n=168) and matched diagnostic formalin-fixed paraffin-embedded (FFPE) tissue samples (n=69) of DLBCL patients, PMBCL patients and healthy controls were collected between 2016-2021. Plasma samples were collected at diagnosis, at interim evaluation, after treatment, and in case of refractory or relapsed disease. RNA was extracted from 200 µl plasma using the miRNeasy serum/plasma kit and from FFPE tissue using the miRNeasy FFPE kit. RNA was subsequently sequenced on a NovaSeq 6000 instrument using the SMARTer Stranded Total RNA-seq pico v3 library preparation kit.

  Dataset EGAD00001011679

• Breast Cancer - immune clusters - RNA-seq

  In this study we use expression data from breast cancer tumors to define immune clusters in breast cancer. Immune clusters have gradual levels of immune infiltration. In the intermediate immune infiltration cluster, we found a worse prognosis which is independent of known clinicopathological features. We also found the immune clusters associated with treatment response. Further using gene expression data and deconvolution algorithms to dissect the immune contexture of the clusters.

  Study EGAS00001003631

• Dexamethasone treatment in COVID-19, single-cell RNA-seq

  Study EGAS00001007460

• RNA-seq of PDAC patient-derived xenograft tumors

  Study EGAS00001007070

• Small RNA Sequencing across Diverse Biofluids Identifies Optimal Methods for exRNA Isolation

  We tested the efficiency and reproducibility of 10 RNA isolation methods on 5 different biofluids. Pooled human plasma and serum, bile and urine were used along with cell culture supernatants from human embryonic stem cells (hESC), primary neonatal rat ventricular myocytes (NRVM) and human cholangiocarcinoma cells (KMBC). 4 RNA isolation methods designed to isolate total RNA from bio fluids without enrichment of exRNA carriers were used. 6 methods that preferentially enriched for exRNA carriers were also compared. Small RNA libraries were constructed using the NEBNext small-RNA library prep. The efficiency and reproducibility of the different RNA isolation methods was compared using small-RNA seq.

  Study phs002143

• Case-control study with RNA-seq transcriptome between ASD patients and non ASD controls.

  Aim: To elucidate gene expression differences in the cerebellar tissues between ASD and normal control segmented by age. Object: The cerebellar tissues used in our study are from 16 autistic patients and 17 control patients. Method: We investigated the mRNA expression differences using RNA-seq between ASD and controls by age. We further investigated mRNA isoform expressions segmented by age.

  Study JGAS000668

• Heterogeneous metabolic signatures are linked to cancer cell differentiation in colorectal cancer

  Colorectal cancer (CRC) is characterized by functional intratumor heterogeneity that shares many similarites with the hierarchical organization of the normal intestinal epithelium. In order to relate transcriptional subtypes to functional tumor cell heterogeneity we applied scRNA-seq to 12 patient-derived CRC spheroid cultures. We identified shared expression programs that relate to intestinal lineages and revealed metabolic signatures that are linked to cancer cell differentiation. In addition, we validated and complemented sequencing results by quantitative microscopy using live-dyes and multiplexed RNA fluorescence in situ hybridization, thereby revealing metabolic compartmentalization and potential cell-cell interactions. Finally, we demonstrate functional differences between metabolically distinct lineage subtypes that might have strong implications for future treatment strategies of CRC.

  Dataset EGAD00001005524

• Chromatin landscape of medulloblastoma reveals context dependent driver

  In this study, we defined subgroup specific chromatin landscape (H3K27ac, H3K27me3, RNA-Seq, 27ac hichip, WGS) of medulloblastoma to identify pathogenic epigenetic alterations that regulate expression of a context dependent driver gene.

  Study EGAS00001006741

• Integrative multi-omic analyses of malignant pleural mesothelioma

  Multi-omic data (whole-genome sequencing, RNA-seq, EPIC 850K methylation arrays) for 123 samples from the MESOMICS project, the French project of molecular characterization of malignant pleural mesothelioma

  Study EGAS00001004812

• BLUEPRINT release August 2014, RNA-Seq for common myeloid progenitor

  RNA-Seq data for 3 common myeloid progenitor sample(s). 3 run(s), 3 experiment(s), 3 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001000907

• BLUEPRINT release August 2016, RNA-Seq for macrophage - T=6days B-glucan, on genome GRCh38

  RNA-Seq data for 4 macrophage - T=6days B-glucan sample(s). 4 run(s), 4 experiment(s), 4 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002522

• Long-read data (PacBio)

  The goal of this project was to perform long-read RNA sequencing (LR-seq, PacBio) in combination with short-read RNA-seq for systematic characterization of the isoform diversity in primary breast tumor samples. We sequenced the full-length transcriptomes of 26 breast tumors and 4 normal breast samples.

  Dataset EGAD00001006597

• Immunotesting cohort with RNA-seq data of melanoma samples

  This dataset contains RNA-seq raw data in fastq format from 9 melanoma samples. The samples are formalin-fixed paraffin-embedded (FFPE) treated. For target enrichment SureSelect XT Human All Exon V6 was used. The libraries were sequenced in paired-end mode (2 x 50 nt) on a NovaSeq6000 S2 flow cell.

  Dataset EGAD00001006783

• He et al. RNA-seq data

  This dataset are the bam files of RNA-seq data from the paper by He et al.

  Dataset EGAD00001007135

• RNA-seq on neuroblastoma PDX model COG-N-519 treated with control miR-1283 and test miR-99b-5p mimics

  RNA-sequencing on neuroblastoma PDX model COG-N-519 treated with control miR-1283 and test miR-99b-5p mimics. Three samples from each of the treatment condition were analysed. Next-Seq platform was used for sequencing.

  Dataset EGAD00001008035

• Illumina RNA-Seq paired of 10 different tumor samples from the Master program (H021)

  Fastq files of paired RNA-Seq of 10 different tumor samples, for which Nanopore and Illumina sequencing was compared. Illumina sequencing was carried out with HiSeq4000 or HiSeq X-Ten using the Illumina TruSeq stranded mRNA Kit.

  Dataset EGAD00001008971

• BLUEPRINT release January 2015, RNA-Seq for common myeloid progenitor

  RNA-Seq data for 3 common myeloid progenitor sample(s). 3 run(s), 3 experiment(s), 3 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001001169

• single-cell RNA-Seq samples of CRC patients

  The dataset contains samples of 11 CRC patients (2 samples for each patient, tumor and normal adjacent tissue site, 22 samples in total). Dataset is composed by fastq file (paired end) type from 10x single-cell RNA-Seq.

  Dataset EGAD00001009634

• GEP-NEN Bulk-RNA-seq dataset

  This dataset entails 40 Bulk-RNA sequenced patient-derived gastro-intestinal neuroendocrine (GEP-NEN) neoplasms.

  Dataset EGAD00001006657

• Evolution of Core Archetypal Phenotypes in High-Grade Serous Ovarian Cancer (HGSOC)

  The evolution of resistance in high-grade serous ovarian cancer (HGSOC) cells in response to chemotherapy is only partially understood. To uncover phenotypic changes associated with chemotherapy resistance, we performed single-cell RNA-sequencing (scRNA-seq) or whole-genome sequencing of 23 total patients, with longitudinal samples collected from 9, treatment-naïve samples from 8 patients, and post-treatment samples from 6 patients. Our study revealed that the HGSOC transcriptome could be described using three core archetypal phenotypes, defined as oncogenic tasks that describe majority of the transcriptional data. We implemented a multi-task learning approach to identify the biological tasks of each archetype and identified metabolism and proliferation, cellular defense response, and DNA repair signaling. The “metabolism and proliferation” archetype evolved during treatment and was enriched in cancer cells from patients that received multiple-lines of treatment and had elevated tumor burden indicated by CA-125 levels. The emergence of archetypes was not consistently linked to specific whole-genome driver mutations. However, archetypes were closely associated with sub-clonal clusters at the single-cell level, indicating that cancer cell sub-populations specialize in particular biological tasks. Our study reveals a defining principle of ovarian tumor evolution using temporal scRNA-seq profiles, identifies the key phenotypic features across patients and links metabolic shifts with a response to chemotherapy.

  Study phs002294

• RNA-sequencing of Non-muscle Invasive Bladder cancer (NMIBC)

  This RNA-sequencing cohort includes 78 Non-muscle Invasive Bladder cancer (NMIBC) samples and 7 Muscle Invasive Bladder cancer (MIBC) samples.

  Study EGAS00001004358

• CPTAC: Molecular Dissection of Chemotherapy Response in Triple Negative Breast Cancer

  Sporadic Triple Negative Breast Cancer (TNBC) represents 10-15% of breast cancers (BC) worldwide. Non-specific chemotherapy remains the standard of care as there are no targeted agents. In 50% of cases, pathological complete response (pCR) is not achieved, and these individuals experience poor survival. Predictive markers for chemotherapy have proved elusive, and patients can receive up to five different chemotherapy agents to optimize outcomes. Microscaled proteogenomics (PMID: 31988290) is a discovery technique that integrates DNA and RNA sequencing with mass spectrometry based proteomics. This approach was applied to snap-frozen biopsies obtained before TNBC treatment on a clinical trial of carboplatin and docetaxel. Proteogenomic profiling included whole exome sequencing (WES), RNA-seq, and tandem mass tag based proteomics and phosphoproteomics.The study was approved by the IRB at both participating sites: Washington University in St. Louis and Baylor College of Medicine (BCM), and followed the Declaration of Helsinki and Good Clinical Practice guidelines. The protocol and informed consent documents were approved by Washington University School of Medicine (WUSM) and BCM.

  Study phs002505